Reservoir Senior Project 2012

i

Port Said University

Faculty of Engineering

Natural Gas Engineering Program

A study on:-

Belayim Marine Field ( Zone II)

Submitted to:-

Natural Gas Engineering Program

ii

ACKNOWLEDGMENT

iii

ACKNOWLEDGMENT

Thanks and indebtedness is directed first and always to Allah for all his

graces, without the power he gave to us , the accomplishment of this

work would have been certainly impossible.

We would like to extend our deep gratitude and appreciation to our

family; for their love, help, understanding and continuous

encouragement.

We would like to express our deep gratitude, appreciation and sincerest

thanks to our professor for his supervision, advices, constructive

discussion and great help during the work Professor Doctor Attia M.

Attia, our thesis supervisor.

Finally, we would like to express our gratitude to our project assistant

Eng. Ahmed Rayan who helped us technically and mentally throughout

our work period.

Contents

iv

Contents

CHAPTER 1 ...................................................................................................................... 1

1.1 Introduction .......................................................................................................................................... 1

Belayim Marine Field (ZoneII) ........................................................................................................ 1

1.2 Objectives ................................................................................................................................................ 4

CHAPTER 2 ...................................................................................................................... 5

2 Literature Review................................................................................................................................... 5

2.1 Reserves Definition .................................................................................................................... 5

2.1.1 SEC Definitions ............................................................................................................... 6

2.1.2 SPE Definit ions ......................................................................................................... 9

2 . 2 R e s e r v e E s t i ma t i o n M e t h o d s .................................................................................... 12

2.2.1 Analogy:- ...................................................................................................................... 13

2.2.2 Volumetric Method ....................................................................................................... 15

2.2.2.1 Volumetric Uncertainty ....................................................................................... 17

2.2.3 Decline Curve Analysis (DCA): ............................................................................... 18

2.2.4 Material Balance Equation (MBE): .............................................................................. 24

2.2.4.1 MBE Assumptions:............................................................................................. 27

2.2.4.2 Primary Recovery Mechanism ............................................................................. 29

2.2.4.2 .1Rock And Liquid Expansion Drive: ....................................................... 30

2.2.4.2 .2 Depletion Drive: ......................................................................................... 31

2.2.4.2 .3 Gas-Cap Drive: .......................................................................................... 33

2.2.4.2.4 .Water Drive: ............................................................................................. 35

2.2.4.2.5 Gravity Drainage Drive : ............................................................................. 37

2.2.4.2.6 Combination: ............................................................................................. 39

2.2.4.3 Driving Indexes MBE: ........................................................................................ 40

2.2.4.3.1 Depletion Drive Index(Oil Zone Oil Expansion ),(DDI) ...................... 41

2.2.4.3.2Segregation Drive Index (Gas Zone Gas Expansion),(SDI) .................... 41

2.2.4.3.3Water Drive Index (W DI) .......................................................................... 41

2.2.4.3.4Expansion Drive Index (Rock And Liquid), (EDI) .............................. 41

2.2.4.4 MBE In Linear Form: .......................................................................................... 42

2.2.4.4.1 Volumetric Under saturated Reservoir ........................................................ 45

2.2.4.4 .2Volumetric Saturated Reservoirs ........................................................... 47

2.2.4.4 .3 Gas Cap Drive Reservoirs ...................................................................... 48

2.2.4.4 .4 Water Drive Reservoirs ............................................................................ 50

2.2.4.4 .5 Combination Drive Reservoir ............................................................... 57

2.2.4.5 Water Influx[5] .................................................................................................... 59

2.2.4.5 .1 Steady-state method .................................................................................... 59

2.2.4.5.2 VEH unsteady-state method ........................................................................ 61

2.2.4.5.3 Fetkovich Pseudo steady-state method ...................................................... 63

2.3 Enhanced Oil Recovery (EOR) [16,17] ................................................................................... 65

2.3 .1 Miscible EOR ................................................................................................................ 65

Contents

v

2.3 .2 Chemical EOR ............................................................................................................. 66

2.3.3 Other EOR Processes ................................................................................................... 66

2.3 .2.1 Polymer Flooding ................................................................................................ 69

2.3.2.2 Surfactant Flooding ............................................................................................. 74

2.3 .2.3 Alkaline Flooding ............................................................................................... 75

2.4 Reservoir Simulation ......................................................................................................... 80

2.4.1 MBAL [22] .................................................................................................................... 81

2.4.2 Monte Carlo Simulation .............................................................................................. 83

2.4.3 ECLIPSE Simulation[21] .............................................................................................. 84

2.5 Comparison Between Reserve Estimation Methods[23] .......................................................... 87

CHAPTER 3 .................................................................................................................... 89

3 Methodology ..............................................................................................................................................89

3.1 Available Data .......................................................................................................................... 89

3.2 Methodology............................................................................................................................. 92

3.2.1.1 The Material Balance Equation ............................................................................ 93

3.2.1.2 Water Influx ....................................................................................................... 101

3.2.1.2 .1Steady state Water Influx (SS) ................................................................... 101

3.2.1.2 .2 Semi-Steady State For Water Influx (SSS) ............................................... 105

3.2.1.2 .3 Unsteady state (USS) ................................................................................ 110

3.2.1.3 Prediction ........................................................................................................... 116

3.2.2 Reservoir Management Spread sheet ........................................................................... 125

3.2.3MBAL [24] ................................................................................................................... 129

3.2.3.1 Montecarlo Simulation Tool [24] : .................................................................... 129

3.2.3.2 MBE Tool [24] : ................................................................................................ 133

3.2.4 ECLIPSE [21] .............................................................................................................. 149

CHAPTER4 ................................................................................................................... 160

4 Result ..................................................................................................................................................160

4.1PVT Correlations [5] ............................................................................................................... 160

4.2 History Matching .................................................................................................................... 167

4.3 Prediction ................................................................................................................................ 172

4.4EOR ......................................................................................................................................... 175

4.5 MBAL .................................................................................................................................... 178

4.6 ECLIPSE Results .................................................................................................................... 179

Conclusion .................................................................................................................................... 189

REFERENCES ............................................................................................................................. 191

List of Figures

vi

List of Figures

Figure 1 Belayim Marine Oil Location Map . ........................................................................................................... 2

Figure 2 SEC Classification Of Oil And Gas Resources .[2] .................................................................................... 6

Figure 3 SPE Resource Classification System[1] ...................................................................................................... 9

Figure 4 Probabilistic Definition Of Reserves. ........................................................................................................ 10

Figure 5 Classification of production decline curves .[4] ........................................................................................ 19

Figure 6 Exponential, Hyperbolic And Harmonic Approaches . ............................................................................. 22

Figure 7 Decline Curve of an Oil well . [6] ............................................................................................................. 23

Figure 8 (Material Balance Tank Model) ................................................................................................................ 24

Figure 9 Solution Gas Drive Reservoir.[8] .............................................................................................................. 31

Figure 10 Production Data Of Depletion Drive Reservoir. [8] ............................................................................... 32

Figure 11 Gas-cap drive reservoir.[8] ..................................................................................................................... 33

Figure 12 Production Data For A Gas-Cap Drive Reservoir.[8] ............................................................................ 34

Figure 13 Reservoir With Water Drive .[8] ............................................................................................................. 35

Figure 14 Aquifer Geometries . [8] .......................................................................................................................... 36

Figure 15 Production Data For A Water Drive Reservoir. [8] ............................................................................... 36

Figure 16 Initial Fluid Distribution In An Oil Reservoir . [8] ................................................................................. 37

Figure 17 Combination Drive Mechanism . [8] ....................................................................................................... 39

Figure 18 Classification Of The Reservoir. [5] ....................................................................................................... 46

Figure 19 Determining N For Saturated Reservoirs . [5] ........................................................................................ 47

Figure 20 F versus Eo + m Eg . [5] ........................................................................................................................ 49

Figure 21(F/Eo) versus (Eg/Eo)............................................................................................................................... 49

Figure 22 (F/Eo) As A Function Of (∆P/Eo) .[5] ..................................................................................................... 52

Figure 23 Steady State Model Applied To MBE.[5] ................................................................................................. 53

Figure 24 Havlena And Odeh Straight Line Plot . [10.11] ....................................................................................... 56

Figure 25 VEH Cylindrical In Shape Reservoir. ...................................................................................................... 61

Figure 26 Dimensionless Time And Fluid Influx Chart.[5] ..................................................................................... 62

Figure 27 Pressure Steps Used To Approximate The Pressure-Time Curve . [5] .................................................... 63

Figure 28 EOR Injection Method.[17] ..................................................................................................................... 67

Figure 29 Chemical EOR Target In Selected Countries.[17] .................................................................................. 68

Figure 30 Chemical Floods History. [17]................................................................................................................ 68

Figure 31 Current Status World Wide Production World Wide.[17] ....................................................................... 68

Figure 32 Polymer Flood Field Performance .[17] ................................................................................................. 73

Figure 33 Surfactant Flood [17] .............................................................................................................................. 74

Figure 34 pH Values Of Alkaline Solutions .[16] .................................................................................................... 76

Figure 35 Alkaline Flood Field Performance. [17] ................................................................................................. 78

Figure 36 Isopach Contour Map For Net Pay Zone OF Marine Zone 2 . ............................................................... 89

Figure 37 Reservoir MBE . ...................................................................................................................................... 94

Figure 38 Chart Calculate N. ................................................................................................................................ 100

Figure 39 Plot Of Pressure And Pressure Drop Versus Time. [15] ....................................................................... 101

Figure 40 Semi Steady State Behavior . ................................................................................................................ 105

Figure 41 Un Steady State Behavior ..................................................................................................................... 110

Figure 42 Plotting ∑Qt.∆P/Eo Vs (F-Wi*Βw)/EO At Re/Rw =2. .......................................................................... 113

Figure 43 Plotting ∑Qt.∆P/Eo vs (F-Wi*βw)/EO at re/rw =4............................................................................... 113



Figure 46 ∑Qt.∆P/Eo At Re/Rw = Infinity. ............................................................................................................ 115

Figure 47 Chart between P with ( wepe& we uss)) ................................................................................................ 123

Figure 48 Chart Between P With ( Wepe& We Uss)By Using Mew Wi. ................................................................ 124

Figure 49 Predicted p . .......................................................................................................................................... 124

Figure 50 Reservoir Management Spread Sheet Wells Input. ................................................................................ 125

List of Figures

vii

Figure 51Reservoir Management Spread Sheet Pressure Input. ........................................................................... 126

Figure 52 Pressure Matching ................................................................................................................................ 126

Figure 53 Reservoir Management Spread Sheet PVT Input . ................................................................................ 126

Figure 54 Reservoir management spread sheet PVT Matching . ......................................................................... 127

Figure 55 Reservoir Management Spread Sheet Well Locations. .......................................................................... 127

Figure 56 Reservoir Management Spread Sheet Prediction .................................................................................. 128

Figure 57 Reservoir Management Spread Sheet Prediction by chemical effect ..................................................... 128

Figure 58 Choosing Monte Carlo Tool. ................................................................................................................. 129

Figure 59 System Option Window .......................................................................................................................... 130

Figure 60 PVT Menu ............................................................................................................................................. 130

Figure 61 Data Input ............................................................................................................................................. 130

Figure 62 Match PVT data .................................................................................................................................... 131

Figure 63 Selecting Distributions. ......................................................................................................................... 131

Figure 64 Distributions. ......................................................................................................................................... 132

Figure 65 General Option Widow. ........................................................................................................................ 134

Figure 66 PVT list . ............................................................................................................................................... 135

Figure 67 Black Oil ( Data Input). ......................................................................................................................... 135

Figure 68 PVT Matching. ...................................................................................................................................... 136

Figure 69 Matching. .............................................................................................................................................. 136

Figure 70 Oil FVF Curve. ..................................................................................................................................... 137

Figure 71 Oil Viscosity Curve............................................................................................................................... 137

Figure 72 GOR Curve. .......................................................................................................................................... 138

Figure 73 Input List. ............................................................................................................................................. 138

Figure 74 Tank Parameters. .................................................................................................................................. 139

Figure 75 Water Influx. ......................................................................................................................................... 139

Figure 76 Rock Compressibility. ............................................................................................................................ 140

Figure 77 Rock Compaction. ................................................................................................................................. 140

Figure 78 Relative Permeability. ........................................................................................................................... 141

Figure 79 Relative Permeability Curves. ............................................................................................................... 141

Figure 80 History Matching Table......................................................................................................................... 142

Figure 81 Import Window. .................................................................................................................................... 142

Figure 82 Import Setup. ........................................................................................................................................ 143

Figure 83 Import file. ............................................................................................................................................. 143

Figure 84 History Matching List. .......................................................................................................................... 144

Figure 85 Run History Matching. .......................................................................................................................... 144

Figure 86 Analytical Method. ............................................................................................................................... 145

Figure 87 Graphical method. ................................................................................................................................. 145

Figure 88 Energy Plot........................................................................................................................................... 146

Figure 89 WD Function Plot.................................................................................................................................. 146

Figure 90 Production Prediction List. ................................................................................................................... 147

Figure 91 Prediction Calculation Setup. ............................................................................................................... 147

Figure 92 Tank Prediction Data. ........................................................................................................................... 148

Figure 93 Run Simulation Window. ....................................................................................................................... 148

Figure 94 Data File Section. .................................................................................................................................. 149

Figure 95 Simulator Preface. ................................................................................................................................. 153

Figure 96 Run The Simulator. ................................................................................................................................ 153

Figure 97 Running The Simulator. ........................................................................................................................ 153

Figure 98 Print File Location. ............................................................................................................................... 154

Figure 99 Original Oil In Place (OOIP)................................................................................................................ 154

Figure 100 Start FLOVIZ ...................................................................................................................................... 154

Figure 101 Run The Model 1 . .............................................................................................................................. 155

Figure 102 Run The Model 3 . .............................................................................................................................. 155

Figure 103 Run The Model 2. ................................................................................................................................ 155

Figure 104 (FLOVIZ Parameters). ........................................................................................................................ 156

Figure 105 Reservoir Model . ............................................................................................................................... 156

Figure 106 RUN OFFICE. ..................................................................................................................................... 157

List of Figures

viii

Figure 107 Load All Vectors . ................................................................................................................................ 157

Figure 108 Input Variables . .................................................................................................................................. 158

Figure 109 Output OFFICE. ................................................................................................................................. 158

Figure 110 OFFICE Output table. ......................................................................................................................... 159

Figure 111 OFFICE Output Charts . .................................................................................................................... 159

Figure 112 Gas Solubility ...................................................................................................................................... 160

Figure 113 Correction. .................................................................................................................................... 161

Figure 114 FVF ..................................................................................................................................................... 162

Figure 115 Oil Compressibility ............................................................................................................................. 163

Figure 116 Oil Viscosity ........................................................................................................................................ 164

Figure 117 Crude Oil Denisty................................................................................................................................ 165

Figure 118 Bw ....................................................................................................................................................... 165

Figure 119 Water Compressibility ......................................................................................................................... 166

Figure 121 Gp Vs Years ......................................................................................................................................... 168

Figure 120 Wp,Wi,Np (bbl) Vs Years ..................................................................................................................... 168

Figure 122 Cw,Co,Rs ............................................................................................................................................. 170

Figure 123 Bo, Mo ................................................................................................................................................. 170

Figure 124 re/rw=infinty ....................................................................................................................................... 171

Figure 125 Past& Future ....................................................................................................................................... 174

Figure 126Purely Viscous ...................................................................................................................................... 175

Figure 127 Visco Elastic ........................................................................................................................................ 176

Figure 128 prediction by chemical effect ............................................................................................................... 177

Figure 129 Montecarlo Results 2 ........................................................................................................................... 178

Figure 130 Montecarlo Results 1 ........................................................................................................................... 178

Figure 131 Drive mechanism ................................................................................................................................. 179

Figure 132 Bottom drive aquifer ............................................................................................................................ 179

Figure 133 graphical method................................................................................................................................. 180

Figure 134 Analytical method ................................................................................................................................ 180

Figure 135 Gas and oil rate ................................................................................................................................... 181

Figure 136 Average water injected with cumulative oil produced ......................................................................... 181

Figure 137 cumulative gas and oil produced ......................................................................................................... 182

Figure 138 Cumulative oil produced with water injected ...................................................................................... 182

Figure 139 water injection And cumulative oil production with time .................................................................... 183

Figure 140 oil saturation with time........................................................................................................................ 183

Figure 141 recovery factor .................................................................................................................................... 184

Figure 142 Reservoir Model .................................................................................................................................. 185

Figure 143 Side view ............................................................................................................................................. 185

Figure 144 FOPT,FGPT, FWPT, FWIT Vs Date ................................................................................................... 186

Figure 145FGPR, FOPR, FWPR, FWIR Vs Date .................................................................................................. 186

Figure 146 In place calculation ............................................................................................................................. 187

Figure 147 New Well ............................................................................................................................................. 188

Figure 148 Comparison no. of wells ...................................................................................................................... 188

Figure 149 Comparison Inj. Wells ......................................................................................................................... 189

LIST OF TABLES

ix

List Of Tables Table 1 Classification Of Proved Reserves.[2] .......................................................................................................... 8

Table 2 Historical Development Of Reserves Definitions And Classifications. ........................................................ 11

Table 3 Recovery Factors For Oil And Gas Reservoirs .[2] .................................................................................... 16

Table 4 Decline Curve Equations'. ......................................................................................................................... 21

Table 5 Dimensionless Time And Fluid Influx Table .[5] ........................................................................................ 62

Table 6 Polymer Structures And Their Characteristics.[16] ................................................................................... 70

Table 7 Properties Of Several Common Alkalis .[16].............................................................................................. 77

Table 8 Reserve Estimation Methods Comparison .[23] ......................................................................................... 87

Table 9 Summary Of Reserve Estimation Methods.[23] .......................................................................................... 88

Table 10 Belayim Marine Field (Zone 2) Data. ....................................................................................................... 90

Table 11 Belayim Marine Field (Zone 2) Pvt Data . ............................................................................................... 91

Table 12 Calculate Oil Compressibility. .................................................................................................................. 96

Table 13 Calculate Water Compressibility . ............................................................................................................ 97

Table 14 Calculate Effective Compressibility. ........................................................................................................ 98

Table 15 Calculate Wi ,Wp,βw . ............................................................................................................................... 98

Table 16 Calculate (Eo)&(F-Wi βw). ...................................................................................................................... 99

Table 17 Marine zone II Data ................................................................................................................................ 103

Table 18 Calculated k' values ................................................................................................................................ 104

Table 19 Determining Semi Steady State Equations’ Parameters ......................................................................... 108

Table 20 Comparing Values Of (Δwe SSS)/ΔT And (Δwe MBE)/ΔT. .................................................................. 109

Table 21 Td vs pressure and Ce. ............................................................................................................................ 112

Table 22 Calculation of ∑Qt.∆P/Eo at re/rw = 2 and 4. ....................................................................................... 113

Table 23 Calculation Of ∑Qt.∆P/Eo At Re/Rw = 6 And 8. .................................................................................... 114

Table 24 Calculating ∑Qt.∆P/Eo At Re/Rw = Infinity. .......................................................................................... 115

Table 25 Prediction Table ..................................................................................................................................... 116

Table 26 3 Pressures Assumption .......................................................................................................................... 116

Table 27 Cw,Co,Ce, βo, βw for P.=1400 ............................................................................................................... 116



Table 30 Input Cw,Co,Ce, βo, βw for the 3 P. ....................................................................................................... 117

Table 31Calculate Delta P ..................................................................................................................................... 118

Table 32 Calculate TD ........................................................................................................................................... 118

Table 33 Calculate TD at re/rw >10 [5]................................................................................................................ 119

Table 34 Calculate (QT) ........................................................................................................................................ 119

Table 35 Calculate ∑Qt.∆P ................................................................................................................................... 120

Table 36 Input QT ,∑Qt.∆P. .................................................................................................................................. 120

Table 37 Calculate We uss ..................................................................................................................................... 121

Table 38 Input Wp ,NP........................................................................................................................................... 121

Table 39 Calculate Wi ........................................................................................................................................... 122

Table 40 Calculate NP*βo ,WP*βw, WI*βw ,∆P ................................................................................................... 122

Table 41 Calculate N*βoi*Ce*∆P ......................................................................................................................... 122

Table 42 Calculate We MBE .................................................................................................................................. 123

Table 43 crude oil denisty used correletion. .......................................................................................................... 164

Table 44 Oil Denisty suitable Correlation ............................................................................................................. 164

Table 45 PVT Conculosion .................................................................................................................................... 166

Table 46 History Matching. ................................................................................................................................... 167

Table 47 PVT Matching. ........................................................................................................................................ 169

Table 48 Wi/Np & dWi/Np ..................................................................................................................................... 172

Table 49 Prediction Calculation ............................................................................................................................ 173

Table 50 Conclusion .............................................................................................................................................. 190

LIST OF TABLES

x

CHAPTER 1

1

CHAPTER 1

1.1 Introduction

Belayim Marine Field (ZoneII)

Zone II is one of the oil reservoirs composing Belayim Marine field;

from the stratigraphic point of view, it belongs to the upper

portion of Belayim formation. Zone II was discovered by 113M-1 in

1962 and production started in 1963 through wells 113M-1 & BM-

2, by Dec. 1996, Zone II had produced a cum. of 6.75*106

STD m3

of oil and the production rate was 526 STD m3/d.

The geological structure of Zone II that was reconstructed based

composed of sand bodies mainly deposited in the west-southwest

flank of an anticline with a north-west southeast trend. The sand

thickness reduces along the crest of the structure and is interrupted

by a fault along the west flank.

Two aquifers have been identified based on the different original

OWC depths. The OWC of the main aquifer is identified based on

the log analysis of well 113M-25, the secondary aquifer is present

only in an isolated area and well 113M-31 identified it.

The oil characteristics were determined based on the analysis of the

surface sample collected at well 113M-26; it points out a medium-

high density oil of 20.7 API.

CHAPTER 1

2

Balayim Marine Oil Field – Location map

Figure 1 Belayim Marine Oil Location Map .

CHAPTER 1

CHAPTER 1

3

This book starts with showing the project objectives to be a good

reservoir engineer and whats the purpose of reservoir engineering and

what is reservoir engineer concerns.

Then talking about literature review about reservoir engineering which

used to build knowledge about types of reservoirs, driving mechanisms

and different types of reserve calculation.

Then starts to show the available data that will be used in calculations and

starts it in methodology that shows the procedures followed in calculation

to get final results

Finally the book shows the final results and conclusion of different

calculations type and compare between results to get the best one and

build recommendations to increasing the recovery factor and productivity

CHAPTER 1

4

1.2 Objectives

From Reservoir Engineering Concepts Starting The Main Project

Objectives:-

1- Selecting the most suitable correlations to calculate fluid

properties of (Belayim Marine Field (ZoneII)) with lowest

average absolute error(AAE) to helping and decrease money

paid in core analysis and PVT Lab.

2- Knowing the reservoir type and its driving mechanism.

3- Calculating the original oil in place (OOIP) by using different

methods e.g.(MBE, Montecarlo , Decline curve, MBAL

,Eclipse) , compare between those methods and choose the

most accurate result.

4- Predicting of the reservoir life and production rate with highest

recovery factor.

5- Enhancing oil recovery method to increase oil production and

decrease water cut percentage.

5

CHAPTER 2

2 Literature Review

2.1 Reserves Definition

Unfortunately, there are some disagreements in the world related to reserve

definition. While some countries base their reserves on maximum recoverable,

others rely on minimum recoverable. Many countries tend to maximize their

reserves for political and economic reasons and keep their reserves confidential. So

it is very difficult to estimate the world reserves, not only for the disagreements in

definitions but also for the lack of data and incorrect aggregation. The problem

of definitions is being solved over the years by applying standard definitions.

The most common definitions used globally are those set by SPE and The US

Securities and Exchange Commission (SEC).

6

2.1.1 SEC Definitions

According to the US Securities and Exchange Commission (SEC), Oil and Gas

resources are classified according to the flow chart shown in Figure

The total oil and gas resources are the total quantities expected to be present

underground, this can be divided into discovered resources and undiscovered

resources.

Undiscovered resources are those quantities not yet discovered.

Discovered resources are those resources already discovered using existing

technology. They can be classified into recoverable and unrecoverable resources.

Unrecoverable resources are those quantities that cannot be recovered due to

lack of technology or economic reasons.

Recoverable resources are those quantities that can be recovered using

existing technology and current economic conditions. They can be further classified

into reserves and cumulative production.

Cumulative production is the quantities already produced from known

accumulation s using the existing technology and under current economic

conditions.

Figure 2 SEC Classification Of Oil And Gas Resources .[2]

7

Reserves are estimated volumes of crude oil, condensate, natural gas, natural

gas liquids, and associated substances anticipated to be commercially

recoverable from known accumulations from a given date forward, under

existing economic conditions, by established operating practices, and under current

government regulations. Reserve estimates are based on geologic and/or engineering

data available at the time of estimate. The relative degree of an estimated

uncertainty is reflected by the categorization of reserves as either "proved" or

"unproved"

Proved Reserves can be estimated with reasonable certainty to be

recoverable under current economic conditions. Current economic conditions

include prices and costs prevailing at the time of the estimate. Reserves are

considered proved if the commercial productivity of the reservoir is supported by

actual engineering tests. By using probabilistic approach, if the probability that

the real production will have a chance of 90% to exceed or be equal to the

calculated value, we consider the estimated value as proved reserves. Proved

reserves can be further classified as shown in Figure 2.

Unproved Reserves are based on geological and/or engineering data similar to

those used in the estimates of proved reserves, but when technical, contractual,

economic or regulatory uncertainties preclude such reserves being classified as

proved. They may be estimated assuming future economic conditions different

from those prevailing at the time of the estimate.. Unproved reserves may

further be classified as probable and possible.

8

Probable Reserves (P50) are less certain than proved reserves and can be

estimated with a degree of certainty sufficient to indicate they are more likely to be

recovered than not. By using probabilistic approach, the chance of the real

production figure to be equal to or exceed the calculated value is 50%, we

usually refer to it as proved plus probable reserves and are given by (P50).

Possible Reserves are less certain than proved reserves and can be estimated

with a low degree of certainty, insufficient to indicate whether they are more likely

to be recovered than not

PDP are those quantities expected to be recovered from locations where a

proper field development plan was introduced, wells were drilled, and

production is on-going.

PDNP are those quantities expected to be recovere3d from locations where a

proper field development plan was introduced, wells were drilled, but

production has not yet started.

PUD are those quantities that in order to be recovered, the accumulation sin

which they exist need a proper development plan to take place in order to decide the

number of wells needed And other requirement for these quantities to be

produced and the field to be productive.

Table 1 Classification Of Proved Reserves.[2]

9

2.1.2 SPE Definitions

Figure 4 presents the petroleum resource classification according to Society

of Petroleum Engineers (SPE) and its similarity to the SEC resource classification

.

Discovered Petroleum-initially-in-place is that quantity of petroleum which is

estimated, on a given date, to be contained in known accumulations, plus those

quantities already produced therefrom. This may be may be subdivided into

Commercial and Sub-commercial categories, with the estimated potentially

recoverable portion being classified as Reserves and Contingent Resources

respectively.

Reserves are defined as those quantities of petroleum which are anticipated to

be commercially recovered from known accumulations from a given date

forward. The uncertainty in reserve estimation can be reflected in proved. Probable,

and possible reserves.

Proved, probable and possible reserves have the same definitions of the SEC

classification. The probabilistic approach is best explained in figure 4.

Figure 3 SPE Resource Classification System[1]

10

.

Contingent Resources are those quantities of petroleum which are estimated,

on a given date, to be potentially recoverable from known accumulations, but which

are not currently considered to be commercially recoverable.

Undiscovered Petroleum-initially-in-place is that quantity of petroleum

which is estimated, on a given date, to be contained in accumulations yet to be

discovered.

Prospective Resources are those quantities of petroleum which are estimated,

on a given date, to be potentially recoverable from undiscovered accumulations

Many governments, organisations and companies have made their own reserves

definitions and classifications. The complete historical development of reserves

definitions and classifications is shown in table 2.

Figure 4 Probabilistic Definition Of Reserves.

11

Table 2 Historical Development Of Reserves Definitions And Classifications.

Society of Petroleum Engineers (SPE) Other Organizations

Date Definition Organization Name Date

1964 SPE Reserves Definitions [20] American Petroleum

Institute Reserves

Definition (API) [27]

1936

1981 SPE, WPC, AAPG [21] ARPS Reserve

Classification [28]

1962

October, 1988 SPE Reserves Definitions [22] McKelvey Resource

Classification System

[29]

1972

March, 1997 SPE/ WPC [23] SEC Reserve

Classification [30]

1975

February,

2000

SPE/WPC/AAPG [24] Norwegian Petroleum

Directorate (NPD)

[31]

2001

2001 Guidelines for the Evaluation

of Petroleum Reserves and

Resources, 2001 [25]

The UNFC

Classification System

[32]

November 2003

2005 Glossary of Terms Used in

Petroleum

Reserves/Resources

Definitions [26]

Chinese Classification

System [33]

2005

12

2 . 2 Reserve Estimation Methods

Reserves can be calculated using the following techniques[2] :-

Analogy

Volumetric

Decline curve analysis

Material Balance

Reservoir simulation

Two calculation approaches can be applied. These are deterministic and

probabilistic approaches.

The deterministic approach involves using a single value from each input

parameter of the equation used in the estimation process. This generates a single

value for the IOIP. This approach is used when uncertainty is low or when the

degree of confidence in the data available is very high.

The probabilistic approach involves making a probability distribution function for

each input parameter using the range of uncertainty in each parameter

(minimum, maximum, average). This distribution function allows the calculation of

all the possible outcomes of the IOIP value and covers all the ranges of

uncertainty. This approach I used when the uncertainty is very high and can be also

used as a risk analysis method.

13

2.2.1 Analogy:-

Reserves are estimated by analogy to reservoir in the same geographic area or

field with similar properties. The SEC institute that only offset wells in the same

field can be used to estimate proved reserves by analogy. Nevertheless, analogy is

most used to determine probable and possible reserves in the same geographic

area. The similarities between the target reservoir and the analogy model should

include :-

• Lithology and depositional environment of the reservoir rock

• Petrophysical parameters of the rock and fluid saturations

• Initial bottom hole pressure (BHP) and temperature (BHT)

• BHP at the start-up of a project

• Reservoir fluid properties (PVT)

• Structural configuration

• Reservoir heterogeneity and continuity

• Recovery mechanism, natural or induced

• Well spacing and spacing pattern

Reservoir maturity and the stage of development of both the analogy and the target

reservoir should be taken into account. When the proper analogy has been

established, it can be used to estimate[2]:

• Ultimate recovery per well

• Drainage area and appropriate well spacing

• Initial reservoir parameters

• Initial productivity per well

• Typical decline type and decline characteristics

• Expected abandonment pressure

• Expected drive mechanism

14

• Enhanced recovery factor for pressure maintenance

• Recovery for a given drive mechanism:

− Per well

− Per acre-foot (RF)

The analogy method is applied by comparing the following factors for the

analogous and current fields or wells:

1. Recovery Factor (RF),

2. Barrels per Acre-Foot (BAF).

3. Estimated Ultimate Recovery (EUR).

The RF of a close-to-abandonment analogous field is taken as an approximate

value for another field. Similarly, the BAF is assumed to be the same for the

analogous and

current field or well, which is calculated by the following equation

15

2.2.2 Volumetric Method

The volumetric technique is the most widely used approach to estimate reserves

during the exploration stage of a field. Often used as first step, it is compared with

other techniques as more data become available and the uncertainty decrease. The

estimate ultimate recovery (EUR) for an oil reservoir is given by:

Where:-

N = oil in place (STB)

RF = Recovery factor

Vb = Bulk reservoir volume (acre ft)

Ø = Average reservoir porosity

Sw = Average reservoir water saturation

Bo = Oil formation volume factor (RB/STB)

From a contour map: where

Vb = contour interval

Ao = area of the contour

Using reservoir drainage area and thickness:-

Where:

A = reservoir area (acres)

h = thickness (ft)

16

Table 3 (gives the typical primary recovery factors for oil and gas reservoirs by

drive mechanism. The primary oil driving mechanisms will be discussed in the

Material balance equation section .

Table 3 Recovery Factors For Oil And Gas Reservoirs .[2]

17

2.2.2.1 Volumetric Uncertainty

A volumetric estimate provides a static measure of oil or gas in place. The

accuracy of the estimate depends on the amount of data available, which is very

limited in the early stages of exploration and increases as wells are drilled and the

pool is developed.

Monte Carlo simulation provides a methodology to quantify the uncertainty in the

volumetric estimate based on assessing the uncertainty in input parameters such as:

• Gross rock volume, reservoir geometry and trapping

• Pore volume and permeability distribution

• Fluid contacts

The accuracy of the reserve or resource estimates also increases once production data

is obtained and performance type methods such as material balance and decline

analysis can be utilized. Finally, integrating all the techniques provides more

reliable answers than relying solely on any one method

18

2.2.3 Decline Curve Analysis (DCA):

Production decline analysis is a basic tool for forecasting production from a well

or a group of wells once there is sufficient production to establish a decline trend as

a function of time or cumulative production. The technique is more accurate than

volumetric methods when sufficient data is available to establish a reliable trend

and is applicable to both oil and gas wells.

It is most often used to estimate remaining recoverable reserves, but it is also useful

for water flood and enhanced oil recovery (EOR) performance assessments and in

identifying production issues/mechanical problems.

Production decline analysis of an analogous producing pool provides a basis for

forecasting production and ultimate recovery from an exploration prospect or step-

out drilling location. A well‘s production capability declines as production

proceeds. This happens mainly due to combination of pressure depletion,

displacement of another fluid (gas and/or water) and changes in relative fluid

permeability. Plots of production rate versus production history (time or cumulative

production) illustrate declining production rates as cumulative production increases.

In theory, production decline analysis is only applicable to individual wells but in

practice extrapolations of group production trends often provide acceptable

approximations for group performance. The estimated ultimate recovery (EUR) for

a producing unit is obtained by extrapolating the trend to an economic production

limit.

The extrapolation is valid provided that [3]:

• Past trends were developed with the well producing at capacity.

• Volumetric expansion was the primary drive mechanism. The technique is

not valid when there is significant pressure support from an underlying

aquifer.

• The drive mechanism and operating practices continue into the future.

19

Curves that can be used for production forecasting include:

1. Production rate versus time.

2. Production rate versus cumulative production.

3. Water cut percentage versus cumulative production

4. Water level versus cumulative production

5. Cumulative gas versus cumulative oil

6. Pressure versus cumulative production.

Figure 5 shows the classification of production decline curves and how each of them

can be applied by using exponential, hyperbolic and harmonic approaches.[4]

Figure 5 Classification of production decline curves .[4]

20

The first two types are the most common types of decline curves, because the

trend for wells producing from conventional reservoirs under primary production

will be ―exponential‖ ,which means that the data will present a straight line trend

when production rate vs. time is plotted on a semi-logarithmic scale. The

data will also present a straight line trend when production rate versus

cumulative production is plotted on regular Cartesian coordinates. The well‘s

ultimate production volume can be read directly from the plot by extrapolating

the straight line trend to the production rate economic limit.

Arps (1945, 1956) developed the initial series of decline curve equations to

model well performance [3]. The equations were initially considered as

empirical and were classified into (Exponential, Hyperbolic, Harmonic), based

on the value of the exponent ―b‖ that characterizes the change in production

decline rate with the rate of production.

For exponential decline ‗b‘=0, for hyperbolic ‗b‘ is generally between 0 and 1.

Harmonic decline is a special case of hyperbolic decline where ‗b‘=1. Table 4

summarizes ARPS‘ equation used in DCA.

21

Figure 6 shows the difference between the exponential, hyperbolic, and harmonic

approaches used in DCA (rate versus time). [5]

Table 4 Decline Curve Equations'.

22

Figure 6 Exponential, Hyperbolic And Harmonic Approaches .

Chapter 2

23

Figure7 is an example of a typical oil well showing the difference between

Exponential and Harmonic Extrapolations (rate versus cumulative production)

and also shows the economic limit at which data are extrapolated. [6]

Figure 7 Decline Curve of an Oil well . [6]

In Figure 7, the Exponential extrapolation yields a straight line, while the

Harmonic extrapolation yielded a concave upward shape (curve). This is due to

the difference in the exponent ‗b‘ values for both methods. The economic limit

line is the line showing the economic production limit at which the data are

extrapolated in order to predict future production.

Chapter 2

24

2.2.4 Material Balance Equation (MBE):

Material balance is the technique that uses the law of conservation of matter.

The material balance method is a tank model equation. It is written from start of

production to any time (t) as the expansion of oil in the oil zone plus the

expansion of gas in the gas zone plus the expansion of connate water in the oil

and gas zones plus the contraction of pore volume in the oil and gas zones plus

the water influx plus the water injected plus the gas injected equal to the oil

produced plus the gas produced plus the water produced.[5]

Figure 8 shows the tank model on which MBE was built.

A general material balance equation that can be applied to all reservoir types

was first developed by Schilthuis in 1936 [7]. Although it is a tank model

equation, it can provide great insight for the practicing reservoir Engineer.

Figure 8 (Material Balance Tank Model)

Chapter 2

25

It is written from start of production to any time (t) as follows:

Expansion of oil in the oil zone

+ Expansion of gas in the gas zone

+ Expansion of connate water in the oil and gas zones

+ Water influx + Water injected + Gas injected

= Oil produced + Gas produced + Water produced

The Generalized MBE can be written mathematically as:

Where:

N = initial oil in place, STB

Np = cumulative oil produced, STB

G = initial gas in place, SCF

Gi = cumulative gas injected into reservoir, SCF

Gp = cumulative gas produced, SCF

We = water influx into reservoir, bbl

Wi = cumulative water injected into reservoir, STB

Wp = cumulative water produced, STB

Bti = initial two-phase formation volume factor, bbl/STB = Boi

Boi = initial oil formation volume factor, bbl/STB

Chapter 2

26

Bgi = initial gas formation volume factor, bbl/SCF

Bt = two-phase formation volume factor, bbl/STB = Bo + (Rsoi - Rso)Bg

Bo = oil formation volume factor, bbl/STB

Bg = gas formation volume factor, bbl/SCF

Bw = water formation volume factor, bbl/STB

Big = injected gas formation volume factor, bbl/SCF

Biw = injected water formation volume factor, bbl/STB Rsoi = initial solution

gas-oil ratio, SCF/STB

Rso = solution gas-oil ratio, SCF/STB

Rp = cumulative produced gas-oil ratio, SCF/STB

Cf = formation compressibility, psia-1

Cw = water isothermal compressibility, psia-1, Swi = initial water saturation,

Δpt = reservoir pressure drop, psia = pi - p(t)

p(t) = current reservoir pressure, psia

Chapter 2

27

2.2.4.1 MBE Assumptions:

The MBE keeps an inventory on all material entering, leaving, or accumulating

within a region over discrete periods of time during the production history.

The calculation is most vulnerable to many of its underlying assumptions early

in the depletion sequence when fluid movements are limited and pressure

changes are small. Uneven depletion and partial reservoir development

compound the accuracy problem.

The basic assumptions in the MBE are as follows [5]:-

Constant temperature: Pressure–volume changes in the reservoir are

assumed to occur without any temperature changes. If any temperature

changes occur, they are usually sufficiently small to be ignored without

significant error.

Reservoir characteristics: The reservoir has uniform porosity,

permeability, and thickness characteristics. In addition, the shifting in the

gas–oil contact or oil–water contact is uniform throughout the reservoir.

Fluid recovery: The fluid recovery is considered independent of the

rate, number of wells, or location of the wells. The time element is not

explicitly expressed in the material balance when applied to predict future

reservoir performance.

Pressure equilibrium: A uniform pressure is assumed to apply across

the pool.

The model is considered as a tank with infinite permeability.

Constant reservoir volume: Reservoir volume is assumed to be constant

except for those conditions of rock and water expansion or water influx that

are specifically considered in the equation.

Reliable production data: There are essentially three types of production

data that must be recorded in order to use the MBE in performing reliable

reservoir calculations. These are:

1. Oil production data, even for properties not of interest, can usually be

obtained from various sources and is usually fairly reliable.

2. Gas production data is becoming more available and reliable as the

market value of this commodity increases; unfortunately, this data will often

be more questionable where gas is flared.

Chapter 2

28

3. The water production term need represent only the net withdrawals of

water; therefore, where subsurface disposal of produced brine is to the

same source formation, most of the error due to poor data will be

eliminated.

Chapter 2

29

2.2.4.2 Primary Recovery Mechanism

The overall performance of oil reservoirs is greatly affected by the nature of

energy (driving mechanism), responsible for moving the oil to the well bore.

There are basically six driving mechanisms which are [5] :-

1. Rock and Liquid expansion drive.

2. Depletion drive.

3. Gas-cap drive.

4. Water drive.

5. Gravity drainage drive.

6. Combination drive.

Chapter 2

30

2.2.4.2 .1Rock And Liquid Expansion Drive:

An under-saturated reservoir is a reservoir that initially exists at a pressure

higher than its bubble point pressure. At pressures above the bubble point

pressure, crude oil, connate water and rock are the only materials present. As the

reservoir pressure declines (with production), the rock and fluids expand due

to their compressibilities.

This compressibility is due to the expansion of individual rock grains and

formation compaction. As a result of this expansion, the pore volume will be

reduced as a result of a decrease in fluid pressure. This reduction in pore volume

will force the crude oil and water out of the pore volume to the wellbore which

explains this driving mechanism. The reservoirs under this driving mechanism,

usually has a constant gas oil ratio. This driving mechanism is considered the

least efficient driving force and has the lowest oil recovery rates.

Chapter 2

31

2.2.4.2 .2 Depletion Drive:

This mechanism is also referred to as:

Solution gas drive

Dissolved gas drive

Internal gas drive

In this type of reservoir, the major source of energy us a result of gas liberation

from the crude oil and the subsequent expansion of the solution gas as the

reservoir pressure is reduced. As pressure falls below bubble point pressure, gas

bubbles are liberated; these bubbles expand and force the crude oil out of the

pore space as shown in figure 9.

Cole (1969), suggested that a depletion drive reservoir can be identified

by the following characteristics:[9]

1) Reservoir pressure declines rapidly and continuously

2) Gas Oil ratio increases to maximum ad then declines

3) Water production is absent or negligible

4) Well behavior: requires pumping at early stage

5) Oil recovery ranges from 8% to 25%

Figure 9 Solution Gas Drive Reservoir.[8]

Chapter 2

32

The above characteristic trends occurring during the production life of

depletion drive reservoirs is shown in figure 10.

Figure 10 Production Data Of Depletion Drive Reservoir. [8]

Chapter 2

33

2.2.4.2 .3 Gas-Cap Drive:

Gas-cap drive reservoirs can be identified by the presence of a gas cap with

little or no water drive as shown in figure 11.

The natural energy available to produce the crude oil comes from:

The expansion of the gas cap

The expansion of solution gas as it is liberated

Cole and Clark (1969), suggested that gas-cap drive reservoirs have the

following characteristics [9]:

1) Reservoir pressure falls slowly and continuously

2) Gas Oil ratio rises continuously

3) Water production is absent or negligible

4) Well behavior: gas-cap drive reservoirs tend to flow longer than

depletion drive reservoirs


Figure 11 Gas-cap drive reservoir.[8]

Chapter 2

34

The above characteristic trends occurring during the production life of gas-

cap drive reservoirs is shown in figure 12 .

Figure 12 Production Data For A Gas-Cap Drive Reservoir.[8]

Chapter 2

35

2.2.4.2.4 .Water Drive:

any reservoirs are bounded on a portion or all of their edges by water bearing

rocks called aquifers. The aquifers may be so large compared to the reservoir

where they act infinitely. They may also range down to small (almost negligible),

in their effects on the reservoir performance.

The aquifer may be entirely bounded by impermeable rock so that the

reservoir and aquifer together form a volumetric (closed unit). On the other

hand, the reservoir may be outcropped at one or more places where it may be

replenished by surface water as shown in figure 13.

Figure 13 Reservoir With Water Drive .[8]

When talking about water influx, it is common to speak about edge water and

bottom water drive. Bottom water occurs directly beneath the oil and edge water

occurs in the flanks at the edge of the oil as shown in figure 14 .

Regardless of the source of water, the water drive mechanism is the result of

water moving into the pore spaces originally occupied by oil, replacing the oil

and displacing it to the producing wells.

Chapter 2

36

Figure 14 Aquifer Geometries . [8]

Cole (1969), suggested that water drive reservoirs have the following

characteristics

[11]:

1) Reservoir pressure remains high

2) Gas Oil ratio remains low

3) Water production starts early and increase to appreciable amounts

4) Well behavior: flow until water production gets excessive


Figure 15 shows the production data for a water drive

reservoir.

Figure 15 Production Data For A Water Drive Reservoir. [8]

Chapter 2

37

2.2.4.2.5 Gravity Drainage Drive :

The mechanism of gravity drainage occurs in petroleum reservoirs as a result of

differences in densities of the reservoir fluids. The effects of gravitational forces

can be simply illustrated by placing a quantity of crude oil and a quantity of

water in a jar and agitating the contents. After agitation, the jar is placed at rest,

and the denser fluid (normally water) will settle to the bottom of the jar, while

the less dense fluid (normally oil) will rest on top of the denser fluid. The fluids

have separated as a result of the gravitational forces acting on them.

The fluids in petroleum reservoirs have all been subjected to the forces of

gravity, as evidenced by the relative positions of the fluids, i.e., gas on top, oil

underlying the gas, and water underlying oil. The relative positions of the

reservoir fluids are shown in Figure 16 .

Figure 16 Initial Fluid Distribution In An Oil Reservoir . [8]

Gravity segregation of fluids is probably present to some degree in all petroleum

reservoirs, but it may contribute substantially to oil production in some

reservoirs.

Chapter 2

38

Cole (1969), stated that reservoirs under gravity drainage drive have the

following characteristics [9] :-

1) Reservoir pressure has variable rates of pressure decline depending

on the amount of gas. In most cases, there is a rapid pressure decline.

2) Gas Oil ratio remains low.

3) Water production starts is absent or negligible.

4) Oil recovery ranges from 30% to 70%.

Chapter 2

39

2.2.4.2.6 Combination:

In real cases, a reservoir usually includes at least two main drive mechanisms.

For instance, in the case shown in the figure below, the management of the

reservoir for different drive mechanisms can be diametrically opposed (e.g.

low perforation for gas cap reservoirs compared with high perforation for water

drive reservoirs). If both occur as in Figure, a compromise must be required,

and this compromise must take into account the strength of each drive present,

the size of the gas cap, and the size/permeability of the aquifer. It is the job of

the reservoir manager to identify the strengths of the drives as early as

possible in the life of the reservoir to optimize the reservoir performance.

Figure 17 Combination Drive Mechanism . [8]

Chapter 2

40

2.2.4.3 Driving Indexes MBE:

As discussed earlier, oil can be primarily recovered by five driving

mechanisms, to determine the relative magnitude of each of these driving

mechanisms, the compressibility term in the general material balance equation

is neglected and the equation is rearranged as follows:

Dividing by the right hand side of the equation gives:

The terms on the left hand side of equation above represent the depletion drive

index (DDI), the segregation drive (gas cap drive) index (SDI), and the water

drive index (WDI) respectively. The expansion drive index (EDI), has a minor

effect on the oil recovery and can be neglected (not included in the equation).

Prison‘s abbreviation can be used to give the following equation [7] :

DDI + SDI+ WDI+ EDI + 1

Where EDI can be neglected as mentioned earlier.

The driving index for each mechanism can be calculated for a reservoir in

order to calculate the efficiency of each driving mechanism.

Chapter 2

41

2.2.4.3.1 Depletion Drive Index(Oil Zone Oil Expansion ),(DDI)

Depletion drive is the oil recovery mechanism wherein the production of the oil

from its reservoir rock is achieved by the expansion of the original oil volume with

all its original dissolved gas.

2.2.4.3.2 Segregation Drive Index (Gas Zone Gas Expansion),(SDI)

Segregation drive (gas cap drive) is the mechanism wherein the displacement of

oil from the formation is accomplished by the expansion of the original free gas cap.

2.2.4.3.3 Water Drive Index (W DI)

Water drive is the mechanism wherein the displacement of the oil is

accomplished by the net encroachment of water into the oil zone.

2.2.4.3.4 Expansion Drive Index (Rock And Liquid), (EDI)

For under saturated oil reservoirs with no water influx, the principle source of

energy is a result of the rock and fluid expansion. Where all the other three driving

mechanisms are contributing to the production of oil and gas from the reservoir, the

contribution of the rock and fluid expansion to the oil recovery is too small and

essentially negligible and can be ignored.

Chapter 2

42

2.2.4.4 MBE In Linear Form:

Normally, when using the material balance equation, each pressure and the

corresponding production data is considered as being a separate point from other

pressure values. From each separate point, a calculation is made and the results

of these calculations are averaged. However, a method is required to make use of

all data points with the requirement that these points must yield solutions to the

material balance equation that behave linearly to obtain values of the

independent variable. The straight- line method was developed by Havlena and

Odeh (1963) by starting with[10,11] :

Defining the ratio of the initial gas cap volume to the initial oil volume as:

Putting m in the equation gives:

Chapter 2

43

Let:

Where:

F = Underground withdrawal

Eo = Oil and Dissolved gas expansion terms

Eg = Gas cap expansion term

Ef,w = rock and water compression/expansion terms

So we obtain:

The above equation was developed in order to determine the following three

unknowns [10,11]

1. The Original Oil in Place N

2. The cumulative water influx We

3. The original gas cap size compared to the oil zone size m.

(E1)

Chapter 2

44

The straight line relationship developed by Havlena and Odeh can be used

in the following six applications:

Case 1: Determination of N in volumetric undersaturated reservoirs

Case 2: Determination of N in volumetric saturated reservoirs

Case 3: Determination of N and m in gas cap drive reservoirs

Case 4: Determination of N and We‖ in water drive reservoirs

Case 5: Determination of N, m, and We in combination drive reservoirs

Case 6: Determination of average reservoir pressure, p

In this study, the main aim is to calculate the IOIP (N), and so the first five

cases will be considered for calculating N only.

Chapter 2

45

2.2.4.4.1 Volumetric Under saturated Reservoir

For a volumetric under-saturated reservoir, the conditions associated with a

driving mechanism are [5]:

• We = 0, since the reservoir is volumetric

• m = 0, since the reservoir is undersaturated

• Rs = Rsi = Rp, since all produced gas is dissolved in the oil

Applying the above condition to Equation (E1) gives:

Or

To calculate N, a plot of (F/ Eo+ Ef ,w) versus cumulative production Np is

plotted. Figure shows an example of this plot.

Dake (1994) suggest that this plot can take two shapes [12]. As shown in figure

9, Line A implies that the reservoir is a volumetric reservoir. This defines a

purely depletion drive reservoir whose energy drives solely form the expansion

of rock, connate water and oil. Lines B and C, implies the existence of a water

drive in which the reservoir was energized by water influx, Line B represents a

moderate aquifer whose degree of energizing decreases with time. While, Line c

represents a strong aquifer who is acting infinitely. In all cases, IOIP (N) is the

ordinate value of the plateau as shown in figure 18.

(E2)

0

(E2)

0

Chapter 2

46

Figure 18 Classification Of The Reservoir. [5]

Chapter 2

47

2.2.4.4 .2Volumetric Saturated Reservoirs

A saturated oil reservoir is an oil reservoir that originally exists at its bubble

point pressure (Pb). The main driving mechanism in saturated reservoirs results

from the liberation and expansion of the solution gas as the pressure drops

below bubble point pressure. Havlena and Odeh equation (Equation (E1)) can be

written as [10, 11]:

(E3)

Assuming that the water and rock expansion term Ef,w is negligible in

comparison with the expansion of solution gas.

This relationship can be used to determine N for saturated reservoirs by plotting

F versus Eo. This should result in a straight line going through the origin with a

slope of N as shown in figure 19.

Figure 19 Determining N For Saturated Reservoirs . [5]

Chapter 2

48

2.2.4.4 .3 Gas Cap Drive Reservoirs

In gas cap reservoirs, the expansion of the gas-cap gas is the dominant driving

mechanism and assuming that natural water influx is negligible (We=0), the

Havlena and Odeh MBE (Equation (E1)) can be written as:

(E4)

The way in which equation (E4) is applied depends on the number of

unknowns in the equation, there are three possible unknowns in equation

(E4).

N is unknown, m is known.

M is unknown, N is known.

N and m are unknown.

The first and last case will be considered, because in the second case, N is

known ,and as mentioned earlier; only methods to determine N will be

discussed.

Unknown N, Known m:

Equation 3 indicates that when m is known, a plot of F versus (Eo + m Eg) on

a Cartesian scale would produce a straight line through the origin with a slope

of N as shown in figure 20.

Chapter 2

49

N and m are unknown:

If both N and m are unknown, equation (E4) can be re-expressed as:

(E5)

A plot of F/Eo versus Eg/Eo should be linear with intercept N and slope mN as

shown in figure 21.

Figure 20 F versus Eo + m Eg . [5]

Figure 21(F/Eo) versus (Eg/Eo).

Chapter 2

50

2.2.4.4 .4 Water Drive Reservoirs

Dake (1978) points out that the term Ef,w can be neglected in water drive

reservoirs. And so equation (E1) can be written as [13]:

(E6)

If, the reservoir has no initial gas cap, equation (E6) can be re-written as:

(E7)

Dake (1978) points out that in attempting to use the above two equations to

match the production and pressure history of a reservoir, the greatest

uncertainty is always the determination of the water influx (We) [13]. In fact, in

order to calculate the influx the engineer is confronted with what is inherently

the greatest uncertainty in the whole subject of reservoir engineering. The

reason is that the calculation of (We) requires a mathematical model which

itself relies on the knowledge of aquifer properties. Three water influx models

will be discussed. These models are:

Pot aquifer model

Schilthuis steady-state model.

Van Everdingen- Hurst unsteady state model.

The assumed reservoir for these models will be a water drive reservoir with no

gas cap which is represented by the following equation:

(E8)

Chapter 2

51

Pot-Aquifer model:

The pot aquifer model is used to represent water influx and is summarised

by the following equation (E8)

(E9)

The aquifer properties cw, cf, h, ra, and θ are rarely available and they can be

combined as one unknown (K) and so equation (E9) can be written as:

(E10)

Combining equations (E8) and (E10) gives:

(E11)

Equation (E11) implies that a plot of (F/Eo) as a function of (∆P/Eo) would

yield a straight line with an intercept of N and slope of K as shown in figure 22.

Chapter 2

52

Figure 22 (F/Eo) As A Function Of (∆P/Eo) .[5]

Schilthuis steady-state model:

The steady state aquifer model was proposed by Schilthuis (1936) is given by [11]:

(E12)

Chapter 2

53

Combining equation (E8) with equation (E12) gives:

(E13)

Plotting F/Eo versus results in a straight line with an intercept N and

a slope (C) that describes the water influx as shown in figure 23.

Figure 23 Steady State Model Applied To MBE.[5]

Chapter 2

54

Van Everdingen - Hurst unsteady state model:

The Van Everdingen-Hurst unsteady state model is given by [14]:

With:

(E14)

Van Everdingen and Hurst presented the dimensionless water influx WeD as a

function of the dimensionless time tD and dimensionless radius rD that are given

by:

Combining equation (E8) with (E14) gives:

(E14)

Chapter 2

55

The proper methodology of solving the above linear relationship is summarized

in the following steps.

Step 1. From the field past production and pressure history, calculate the

underground withdrawal F and oil expansion Eo.

Step 2. Assume an aquifer configuration, i.e., linear or radial.

Step 3. Assume the aquifer radius ra and calculate the dimensionless radius rD.

Step 4. Plot (F/Eo) versus (Σ Δp WeD)/Eo on a Cartesian scale. If the assumed

aquifer parameters are correct, the plot will be a straight line with N being the

intercept and the water influx constant B being the slope. It should be noted that

four other different plots might result. These are:

• Complete random scatter of the individual points, which indicates

that the calculation and/or the basic data are in error.

• A systematically upward curved line, which suggests that the assumed

aquifer radius (or dimensionless radius) is too small.

• A systematically downward curved line, indicating that the selected

aquifer radius (or dimensionless radius) is too large.

• An s-shaped curve indicates that a better fit could be obtained if a linear

water influx is assumed.

Figure 24 shows a schematic illustration of Havlena-Odeh (1963) methodology

in determining the aquifer fitting parameters [10,11].

Chapter 2

56

Figure 24 Havlena And Odeh Straight Line Plot . [10.11]

Chapter 2

57

2.2.4.4 .5 Combination Drive Reservoir

The general straight line MBE equation is illustrated in equation E1 and is given

by:

(E1)

Where:

Havlena and Odeh differentiated equation (E1) with respect to pressure and

rearranged the equation to eliminate m to give [10, 11]:

(E15)

Where:

Chapter 2

58

A plot of the left-hand side of equation (E15) versus the second term on the

right for a selected aquifer model should, if the choice is correct, provide a

straight line with unit slope whose intercept on the ordinate gives the initial oil

in place, N. After determining N and We, equation (E1) can be used to solve

directly for m.

The derivatives used in equation (E15) can be evaluated numerically by any

finite difference technique including forward , backward and central techniques.

Chapter 2

59

2.2.4.5 Water Influx[5]

Many reservoirs are bounded on a portion or all their perimeters by water

bearing rocks – aquifers.

As reservoir fluids are produced, a pressure differential develops between

the surrounding aquifer and the reservoir. The aquifer reacts by encroaching

across the original hydrocarbon-water contact.

Aquifers retard pressure decline in reservoirs by providing a sourceof water

influx We.

We is a function of time (production).

We is dependent on the size of aquifer and the pressure drop from the

aquifer to the reservoir.

2.2.4.5 .1 Steady-state method

Schilthuis Steady-state method is the simplest model for water influx.

Water influx is proportional to the pressure drawdown (pi – p):

Integrating Eq gives

Where: k′= water flux constant, bbl/day-psi

P = pressure at the original oil-water contact

pi= initial pressure at the external boundary of the aquifer.

Calculation of k′and Wefrom production data: In a reasonably long period, if the production rate and reservoir pressure remain

substantially constant, there is:

Chapter 2

60

The equation can be rearranged to:

If the pressure stabilizes and the withdraw rates are not reasonably constant, water

influx in the pressure stabilized period Δt can be calculated from the total

productions of oil, gas and water within Δt:

Then k′can be found from the following equation:

For an under-saturated oil reservoir and at pressures higher than the bubble point

pressure, Equation can be simplified to:

Chapter 2

61

2.2.4.5.2 VEH unsteady-state method

Van Everdingen and Hurst solutions to the single-phase unsteady state flow

equation are used to calculate water influx.

The hydrocarbon reservoir is the inner boundary condition and is analogous

to the well and the aquifer is the flow medium analogous to the reservoir.

Properties of aquifer are assumed homogeneous and constant.

Reservoir and aquifer are assumed cylindrical in shape.

Water flux is calculated by the following equations:

In Where WeD is given as a function of dimensionless time D t and dimensionless

radius D r (see Tables 5and Figures 26):

The dimensionless time and dimensionless radius are defined as

Figure 25 VEH Cylindrical In Shape Reservoir.

Chapter 2

62

Figure 26 Dimensionless Time And Fluid Influx Chart.[5]

Table 5 Dimensionless Time And Fluid Influx Table .[5]

Chapter 2

63

Values for Δpj are determined from measure pressures. The pressure changes are

calculated as follows to approximate the pressure-time curve:

2.2.4.5.3 Fetkovich Pseudo steady-state method

The size of the aquifer is known-finite aquifer.

Any water influx from the aquifer depletes the pressure accordingto the

material balance equation.

Steps of calculation of water influx by using Fetkovich Pseudo steady state

method:

1. Calculate the initial encroachable water, Wei(in bbls), in the aquifer

Figure 27 Pressure Steps Used To Approximate The Pressure-Time Curve . [5]

Chapter 2

64

2. Calculate the productivity index, J, for flow from the aquifer to the

reservoir

a) For finite aquifer with no flow at the outer boundary:

b) For finite aquifer with constant pressure the outer boundary:

3. Calculate the average reservoir pressure during a time step:

4. Calculate the water influx during a time step

5. Calculate the total cumulative water influx at the current time

6. Calculate the average aquifer pressure at the end of the current timestamp

7. Repeat Steps 3 to 6 for next time step.

Chapter 2

65

2.3 Enhanced Oil Recovery (EOR) [16,17]

The life of an oil well goes through three distinct phases where various techniques

are employed to maintain crude oil production at maximum levels. The primary

importance of these techniques is to force oil into the wellhead where it can be

pumped to the surface. Techniques employed at the third phase, commonly known

as Enhanced Oil Recovery (EOR), can substantially improve extraction efficiency.

Laboratory development of these techniques involves setups that duplicate well

and reservoir conditions. Core Flooding Pumps or Core Analysis Pumps, such as

Teledyne Isco Syringe Pumps, are used in laboratory testing of these Enhanced

Oil Recovery (EOR) techniques.

The Three Stages of Oil Field Development

Primary Recovery : In Primary Recovery, oil is forced out by pressure generated

from gas present in the oil.

Secondary Recovery : In Secondary Recovery, the reservoir is subjected to water

flooding or gas injection to maintain a pressure that continues to move oil to the

surface.

Tertiary Recovery : Tertiary Recovery, also known as Enhanced Oil Recovery

(EOR), introduces fluids that reduce viscosity and improve flow. These fluids

could consist of gases that are miscible with oil (typically carbon dioxide), steam,

air or oxygen, polymer solutions, gels, surfactant-polymer formulations, alkaline-

surfactant-polymer formulations, or microorganism formulations.

2.3 .1 Miscible EOR

Commonly applied in West Texas, this method usually employs supercritical CO2

to displace oil from a depleted oil reservoir with suitable characteristics (typically

containing ―light‖ oils). Through changes in pressure and temperature, carbon

dioxide can form a gas, liquid, solid, or supercritical fluid. When at or above the

critical point of pressure and temperature, supercritical CO2 can maintain the

properties of a gas while having the density of a liquid. Injected miscible CO2

will mix thoroughly with the oil within the reservoir such that the interfacial

tension between these two substances effectively disappears. CO2 can also

improve oil recovery by dissolving in, swelling, and reducing the viscosity of oil.

Chapter 2

66

In deep, high-pressure reservoirs, compressed nitrogen has been used instead of

CO2. Hydrocarbon gases have also been used for miscible oil displacement in

some large reservoirs.

CO2, nitrogen, hydrocarbon gases, and flue gases have also been injected to

immiscibly displace oil. At one extreme of conditions, these displacements may

simply amount to ―pressure maintenance‖ in the reservoir (a secondary recovery

process). Depending on oil character, gas composition and pressure, and

temperature, the displacements could have a range of efficiencies up to and

approaching a miscible displacement. CO2 has also been injected in a ―huff ‗n

puff‖ or cyclic injection mode, like cyclic steam injection.

2.3 .2 Chemical EOR

Three chemical flooding processes include polymer flooding, surfactant-polymer

flooding, and alkaline-surfactant-polymer (ASP) flooding. In the polymer

flooding method, water-soluble polymers increase the viscosity of the injected

water, leading to a more efficient displacement of moderately viscous oils.

Addition of surfactant to the polymer formulation may, under very specific

circumstances, reduce oil-water interfacial tension to almost zero—displacing

trapped residual oil.

Although no large-scale surfactant-polymer floods have been implemented, the

process has considerable potential to recover oil.

A variation of this process involves addition of alkaline to the surfactant-polymer

formulation. For some oils, alkaline may convert some acids within the oil to

surfactants that aid oil recovery. The alkaline may also play a beneficial role in

reducing surfactant retention in the rock. For all chemical flooding processes,

inclusion of a viscosifier (usually a water-soluble polymer) is required to provide

an efficient sweep of the expensive chemicals through the reservoir.

Gels are also often used to strategically plug fractures (or other extremely

permeable channels) before injecting the relatively expensive chemical solutions,

miscible gases, or steam.

2.3.3 Other EOR Processes

Over the years, a number of other innovative EOR processes have been

conceived, including injection of carbonated water, microorganisms, foams,

alkaline (without surfactant), and other formulations. These methods have shown

varying degrees of promise, but require additional development before such

applications will become common.

Chapter 2

67

Figure 28 EOR Injection Method.[17]

In our case we will focus in chemical EOR

Why we use chemical EOR?

Conventional oil RF <33%, worldwide

―Unrecoverable‖ oil = 2x1012

bbls

Much of it is recoverable by chemical methods

Chemical methods are attractive:

Burgeoning energy demand and high oil prices, most likely for long-

term

Diminishing reserves

Advancements in technologies

Better understanding of failed projects

Chapter 2

68

Chemical Method:

Chemical EOR target in selected countries

Chemical floods history

Current status world wide production world wide

Figure 29 Chemical EOR Target In Selected Countries.[17]

Figure 30 Chemical Floods History. [17]

Figure 31 Current

Status World Wide

Production World

Wide.[17]

Chapter 2

69

Objectives of

chemical flooding:

1) Increase the Capillary Number Nc to mobilize residual oil

2) Decrease the Mobility Ratio M for better sweep

3) Emulsification of oil to facilitate production

Chemical Flooding General Limitations

1) Cost of chemicals

2) Excessive chemical loss: adsorption, reactions with clay and

brines, dilution

3) Gravity segregation

4) Lack of control in large well spacing

5) Geology is unforgiving!

6) Great variation in the process mechanism, both areal and cross-

sectional

2.3 .2.1 Polymer Flooding

the mobility control requirement is closely related to the ratio of displacing fluid

mobility to displaced fluid mobility .Because changing displaced oil mobility

(relative permeability and/or viscosity)often is not feasible without the injection of

heat, most often we inject chemicals to change displacing fluid mobility.

Primarily, the injected chemicals are polymers whose obvious function is to

increase the displacing polymer solution viscosity, although other mechanisms are

involved.

Type of polymers and polymer related systems

The two main types of polymers are synthetic polymers such as hydrolyzed

polyacrylamide (HPAM) and biopolymers such as xan than gum. Less commonly

used are natural polymers and their derivatives, such as guar gum ,sodium

carboxymethyl cellulose, and hydroxyl ethyl cellulose (HEC). Table6 summarizes

the characteristics of different polymer structures.

Chapter 2

70

properties:

o No –O– in the backbone (carbon chain) for thermal stability

o Negative ionic hydrophilic group to reduce adsorption on rock surfaces

o Good viscosifying powder

o Nonionic hydrophilic group for chemical stability

Based on these criteria, HPAM is a good polymer.

Table 6 Polymer Structures And Their Characteristics.[16]

Chapter 2

71

1) Hydrolyzed Polyacrylamide

The most widely used polymer in EOR applications is HPAM (Manriqueet

al.2007). For either a given polymer concentration or viscosity level, HPAM

solutions have provided significantly greater oil recovery under Daqing

conditions. The reason is that HPAM solutions exhibit significantly greater

viscoelasticity than xanthan solutions (Wang et al., 2006a). Polyacrylamide

adsorbs strongly on mineral surfaces. Thus, the polymer is partially hydrolyzed to

reduce adsorption by reacting polyacrylamide with a base, such as sodium or

potassium hydroxide or sodium carbonate. Hydrolysis converts some of the amide

groups (CONH2) to carboxyl groups (COO−), as shown in the following

structure:

2) Xanthan Gum

Another widely used polymer, a biopolymer, is xanthan gum (corn sugar gum),or

xanthan for short. The structure of a xanthan biopolymer is shown in the

following figure. The polymer acts like a semirigid rod and is quite resistant to

mechanical degradation. Average reported molecular weights of xanthan

biopolymerused in EOR processes range from 1 million to 15 million.

Xanthanbiopolymers are supplied as a dry powder or as a concentrated broth

(Greenand Willhite, 1998). Generally, polyacrylamide copolymers are much more

viscous than polysaccharide biopolymer at equivalent concentrations in

freshwater, but these copolymers are much more sensitive to saline water than

thebiopolymers. The viscosity of copolymers is lower than that of biopolymers in

the saline water (10,000 ppm TDS). Some permanent shear loss of viscosity could

occur for polyacrylamide, but not for polysaccharide at the wellbore .However,

the residual permeability reduction factor of polysaccharide polymersis low (Luo

et al., 2006). In EOR processes, HPAM is much more widelyused. Other potential

EOR biopolymers are scleroglucan, simusan, AGBP, and so on (Luo et al., 2006).

Chapter 2

72

3) Salinity-Tolerant Polyacrylamide—KYPAM

KYPAM is the commercial name of a new Chinese product; its meaning in

English is salinity-tolerant polyacrylamide, and its English translation is

combshapepolyacrylamide. There are several sample products of this type in the

laboratory. RSP1 is used mainly in treating drilling fluids; RSP2 is used main lyin

EOR; and RSP3 is used mainly in water shut-off or profile control. The

commercial product RSP2, which is known as KYPAM in EOR, is produced by

Beijing Hengju (Luo et al., 2002). This new copolymer incorporates a small

fraction of functional monomers with acrylamide to form comb-like

copolymers. The structure of a functional monomer, aromatic hydrocarbon with

ethylene(AHPE), is

and the structure of KYPAM is

4) Hydrophobically Associating Polymer

The polymer is hydrophobically associating water soluble, meaning it contains

one or more water-soluble monomers (acrylamides) and a small fraction (0.5to

4%) of water-insoluble (hydrophobic) monomers. A typical hydrophobically

associating polymer (HAP) structure is

Chapter 2

73

5) 2-Acrylamide-2-Methyl Propane-Sulfonate Copolymer

The structure of the AM and Na-AMPS copolymer is

AMPS, or 2-Acrylamide-2-Methyl Propane-Sulfonate, has water-soluble anionic

sulfonate, shielding acrylamide, and unsaturated double bond. Sulfonate makes it

have good ionic exchange capability, electric conductivity, andgood resistance to

divalence and salinity in general. Acrylamide gives it good thermal stability and

good resistance to hydrolysis, acid, and alkaline. Plus, the double bond leads to

easy synthesis and polymerization. The rigid side chains, large chains, or chains

of ring structure also give it good thermal stability. AMPS are combined with

other monomers to produce copolymers that are used in many industries (Lu and

Chen, 1996). In the oil industry, the main application is in drilling (Hou et al.,

2003).

And other types like: Movable Gels,pH-Sensitive Polymers ,Bright Water , Micro

ball ,Inverse Polymer Emulsion and Preformed Particle Gel.

Polymer flood field performance

Figure 32 Polymer Flood Field Performance .[17]

Chapter 2

74

2.3.2.2 Surfactant Flooding

Types of Surfactants

The term surfactant is a blend of surface acting agents. Surfactants are usually

organic compounds that are amphiphilic, meaning they are composed of a

hydrocarbon chain (hydrophobic group, the ―tail‖) and a polar hydrophilic group

(the ―head‖). Therefore, they are soluble in both organic solvents and water. They

adsorb on or concentrate at a surface or fluid/fluid interface to alterthe surface

properties significantly; in particular, they reduce surface tensionor interfacial

tension (IFT).

Surfactants may be classified according to the ionic nature of the head group as

anionic, cationic, nonionic, and zwitter ionic (Ottewill, 1984). Anionic surfactants

are most widely used in chemical EOR processes because they exhibit relatively

low adsorption on sandstone rocks whose surface charge is negative. Nonionic

surfactants primarily serve as co-surfactants to improve system phase behavior.

Although they are more tolerant of high salinity, their function to reduce IFT is

not as good as anionic surfactants. Quite often, a mixture of anionic and nonionic

is used to increase the tolerance to salinity. Cationic surfactants can strongly

adsorb in sandstone rocks; therefore, they are generally not used in sandstone

reservoirs, but they can be used in carbonate rocks to change wettability from oil-

wet to water-wet. Zwitterionic surfactants contain two active groups. The types of

zwitterionic surfactants can be non ionic-anionic ,nonionic-cationic, or anionic-

cationic. Such surfactants are temperature-and salinity-tolerant, but they are

expensive. A term amphoteric is also used elsewhere for such surfactants (Lake,

1989). Sometimes surfactants are grouped into low-molecular and high-molecular

according to their weight. Within any class, there is a huge variety of possible

surfactants. For more surfactants used in oil recovery, see Akstinat (1981). For

more details on the effect of structure on surfactant properties, see Graciaa et al.

(1982) and Barakatet al. (1983).

Surfactant flood field performance

Figure 33

Surfactant Flood Field

Performance .[17]

Chapter 2

75

2.3 .2.3 Alkaline Flooding

The alkaline flooding method relies on a chemical reaction between chemicals

such as sodium carbonate and sodium hydroxide (most common alkali agents)and

organic acids (saponifiable components) in crude oil to produce in situ surfactants

(soaps) that can lower interfacial tension. Another very important mechanism is

emulsification. The addition of the alkali increases pH and lowers the surfactant

adsorption so that very low surfactant concentrations can be used to reduce cost.

Comparison of alkalis used in alkaline flooding

1) General Comparison and pH

Alkaline flooding is also called caustic flooding. Alkalis used for in situ formation

of surfactants include sodium hydroxide, sodium carbonate, sodium orthosilicate,

sodium tri-polyphosphate, sodium metaborate, ammonium hydroxide, and

ammonium carbonate. In the past, the first two were used most often. However,

owing to the emulsion and scaling problems observed in Chinese field

applications, the tendency now is not to use sodium hydroxide. The dissociation

of an alkali results in high pH. For example, NaOH dissociates to yield OH:-

Sodium carbonate dissociates as:

followed by the hydrolysis reaction:

The dissociation of sodium silicate is complex and cannot be described by a single

reaction equation. The pH values of several commonly used alkaline agents are

presented in Figure 10.1. Of course, the pH of the solutions varies with salt

content. For instance, the pH of caustic solutions decreases from 13.2to 12.5 when

the salinity increases from 0 to 1% NaCl. By comparison, the pH of sodium

carbonate solutions is less dependent on salinity (Labrid, 1991). In terms of

effectiveness to reduce interfacial tension (IFT), it has been observed that there is

little difference among the commonly used alkalis (Campbell,1982; Burk, 1987).

Chapter 2

76

Figure 34 pH Values Of Alkaline Solutions .[16]

Figure 34 shows a comparison of some of the properties of several common

alkalis. Potassium-based alkalis, the price of which is higher than sodium-based

alkalis, are not included. They are considered when clay swelling and injectivity

problems are expected. Some alkalis are further discussed and compared in the

following sections.

2) Polyphosphate

Chang (1976) showed that use of a polyphosphate, which is a buffer, improved

recovery. Sodium tri-polyphosphate (STPP) was used in laboratory tests for

Cretaceous Upper Edwards reservoir (Central Texas). STPP was proposed to

minimize divalent precipitation, for wettability alteration and

emulsification(Olsen et al., 1990). Generally, it is not used as a primary alkali to

generate soap for purposes of IFT reduction. Instead, it is used together with other

alkalis such as sodium carbonate when divalent could be a problem (Harry Chang

, Chemor Tech International, Plano, Texas, personal communication on June

16,2009).

Chapter 2

77

Silicate versus Carbonate

Campbell (1981) compared sodium or thosilicate and sodium hydroxide in

recovering residual oil. The test results showed that the former was more effective

than the latter under the conditions studied, both for continuous flood in gand 0.5

PV slug. The mechanisms through which sodium or thosilicate produced higher

recovery than sodium hydroxide in those tests were not concluded. Reduction in

interfacial tension is similar for both chemicals. Other factors must play a more

important role .Radke and Somerton (1978) investigated the use of a sodium meta

silicate(Na2SiO3) buffer in core floods. A meta silicate buffer at a pH of 11.2

showed break through at 2.5 PV injection, whereas sodium hydroxide of the same

pH did not appear until a 12 PV injection (Mayer et al., 1983). This result means

that sodium meta silicate reaction with rock is much weaker than sodium

hydroxide. Chang and Wasan (1980) indicated that there were differences in

coalescence behavior and emulsion stability that favor sodium or thosilicate over

sodium hydroxide .Silicate precipitates, however, are generally hydrated,

flocculent, and highly plugging even at low concentrations. Carbonate precipitates

are relatively granularand less adhering on solid surfaces (Cheng, 1986). Thus,

under equivalent experimental conditions of porosity and flow rate, sodium

carbonate shows less degree of permeability damage in the presence of hard water

.

Table 7 Properties Of Several Common Alkalis .[16]

Chapter 2

78

Alkaline flood field performance

And other types of chemical methods like Surfactant-Polymer Flooding, Alkaline-

Polymer Flooding, Alkaline-Surfactant Flooding, and Alkaline-Surfactant-

Polymer Flooding.

How to plan a flood

a) Choose a process likely to succeed in a candidate reservoir

b) Determine the reasons for success or failure of past projects of the

process

c) Research to ―fill in the blanks‖

i. Determine process mechanisms

ii. Derive necessary scaling criteria

iii. Carry out lab studies

d) Field based research

e) Establish chemical supply

f) Financial incentives essential

Figure 35 Alkaline Flood Field Performance. [17]

Chapter 2

79

Process evaluation

a) Compare field results with lab (numerical) predictions

b) Relative permeability changes?

c) Oil bank formation? If so, what size?

d) Mobility control?

e) Fluid injectivity?

f) Extent of areal and vertical sweep?

g) Oil saturations from post-flood cores?

The case for chemical flooding

a) Escalating energy demand, declining reserves

b) Two trillion bbl oil remaining, mostly in depleted reservoirs or those

nearing depletion

c) Infill drilling often meets the well spacing required

d) Fewer candidate reservoirs for CO2 and miscible

e) Opportunities exist under current economic conditions

f) Improved technical knowledge, better risk assessment and

implementation techniques

Conclusions:

a) Valuable insight has been gained through chemical floods in the past –

failures as well as successes

b) Chemical flooding processes must be re-evaluated under the current

technical and economic conditions

c) Chemical floods offer the only chance of commercial success in many

depleted and water flooded reservoirs

d) Chemical flooding is here to stay because it holds the key to maximizing

the reserves in our known reservoirs

Chapter 2

80

2.4 Reservoir Simulation

Reservoir simulation is the technique that applies mathematical modeling to the

analysis of reservoir performance. It generally uses the finite difference method

to solve the partial differential equations that govern the flow behavior of all

fluid phases in the porous medium (reservoir). Generally the outputs from the

simulator are the reserves estimate, the depletion, the production forecast, and

the field development strategy that optimize the recovery factor. The reservoir

simulation process encompasses five fundamentals phases:

1. Data collection

2. Model grid design

3. Sensitivity tests

4. History matching

5. Performance prediction

Reserves determination carries a lot of uncertainty even when calculated by

the most skilled estimators and the most sophisticated means.

Chapter 2

81

2.4.1 MBAL [22]

Efficient reservoir development requires a good understanding of

reservoir and production systems. MBAL helps the engineer better define

reservoir drive mechanisms and hydrocarbon volumes. This is a

prerequisite for reliable simulation studies. MBAL is commonly used for

modeling the dynamic reservoir effects prior to building a numerical

simulator model.

MBAL contains the classical reservoir engineering tool and has redefined

the use of Material Balance in modern reservoir engineering.

For existing reservoirs, MBAL provides extensive matching facilities.

Realistic production profiles can be run for reservoirs with or without

history matching.

MBAL is an intuitive program with a logical structure that enables the

reservoir engineer to develop reliable reservoir models quickly.

Reservoir Engineering Tool

Material Balance

Monte Carlo Simulator

Decline Curve Analysis

1D model

Multi-Layer

Tight Gas

Material Balance

This incorporates the classical use of Material Balance calculations for

history matching through graphical methods (like Havlena-Odeh,

Campbell, Cole etc.). Detailed PVT models can be constructed (both

black oil and compositional) for oils, gases and condensates.

Furthermore, predictions can be made with or without well models and

using relative permeabilities to predict the amount of associated phase

productions.

Multi Tank Variable PVT with Depth

Determine Components of Reservoir Energy

Visualize the Parameters that Impact Performance

Chapter 2

82

Forecast Well and Reservoir Performance

Forecast Using Rate Schedule or Well and manifold pressure

schedule

Set well and global constraints:

At well and field level

Determine when wells will water out

Forecast pressure decline, producing GOR

The long term effects of completion decisions on compression,

gas/water injection, gas recycling

PVT

Black oil

Fully Compositional

Compositional Tracking

Chapter 2

83

2.4.2 Monte Carlo Simulation

The probabilistic method is less commonly used than the deterministic

method because it is not accepted by many governments for reserves

estimation. However, many companies use the probabilistic methods to

evaluate potential reserves when the uncertainty is very high,

especially in the early stage of field development and areas where

new technology is applied.

There are several different probabilistic methods used to estimate

reserves such as the scenario approach, the decision tree, and the Monte

Carlo method. Due to huge improvements in computer technology, the

Monte Carlo method became easier to use with no expensive

commercial software.

Monte Carlo simulation, named for the famous gambling capital of

Monaco [18] , is a very potent methodology. For the practitioner,

simulation opens the door for solving difficult and complex but

practical problems with great ease. Perhaps the most famous early use

of Monte Carlo simulation was by the Nobel physicist Enrico

Fermi (sometimes referred to as the father of the atomic bomb) in 1930,

when he used a random method to calculate the properties of the

newly discovered neutron. Monte Carlo methods were central to the

simulations required for the Manhattan Project, where in the 1950s

Monte Carlo simulation was used at Los Alamos for early work relating

to the development of the hydrogen bomb, and became popularized in

the fields of physics and operations research [19]. By the early 1970‘s

petroleum engineers were beginning to use this technique to model

reserve estimates[20].

The Monte Carlo method depends on making a probability distribution

function for each input parameter, this PDF is used to get all the

possible variations of this parameters. This leads to the calculation of

multiple values for the IOIP along with their probability of occurrence.

A plot between the IOIP and the frequency can then be used to

determine the proved reserves (P90), proved plus probable reserves

(P50) , and proved plus probable plus possible reserves (P10). This

method is used when the data is very limited, when production and

pressure history are not available and we cannot confirm the IOIP

value. Also, this technique is used in risk analysis. This can be done

by many computer software such as EXCEL and MBAL.

Chapter 2

84

2.4.3 ECLIPSE Simulation[21]

ECLIPSE from the most advanced software in reservoir engineering, Its

developed by many great companies in Petroleum Engineering

e.g.(Schumberger)

ECLIPSE software based on Governing Physic (Darcy‘s Law (without

gravity term)& Mass Balance Equation)

Darcy‘s Law (without gravity term)

Mass Balance Equation

The ECLIPSE simulator consists of two separate simulators:

ECLIPSE 100 specializing in black oil modeling, and ECLIPSE 300

specializing in compositional modeling.

ECLIPSE 100 (Black oil Simulation) With fully implicit, three-phase,

3D simulations, ECLIPSE Black oil reservoir simulation software

models extensive well controls and supports efficient field operations

planning, including water and miscible-solvent gas injection. The black

oil model assumes that the reservoir fluids consist of three phases—oil,

water, and gas, with gas dissolving in oil and oil vaporizing in gas.

Pq

k

Chapter 2

85

The Benefits of using Simulator:-

• Accurate determination of reserves.

• Prediction of production performance.

• Determination of number of wells needed.

• Determination of the best well pattern.

• Determination of the best perforation interval.

• Determination of the best completion size.

• Assessment of the early gas or water breakthrough and investigate

how to minimize it.

• Determination of the best injection rates and the best time for

injection.

• Confirm understanding of reservoir flow barriers to assess whether

undrained regions exist.

• Estimate the optimum time for a new phases.

Reservoir Simulation Basics

• The reservoir is divided into a number of cells

• Basic data is provided for each cell

• Wells are positioned within the cells

• The required well production rates are specified as a function of

time

• The equations are solved to give the pressure and saturations for

each block as well as the production of each phase from each well

Chapter 2

86

Required data to enabling use Simulator

– Reservoir structure

Depth

Faults

– Gross thickness

– Lithology

– NTG

– Porosity

– Permeability

– Fluids contacts

– Initial saturation

– Rock/fluid functions

PVT analysis

Special core analysis

Rock compressibility

Capillary pressure

Relative permeability

– Pressure

RFT and well test data

– Production data

Well surveys, completion

data

Historical production and

pressure data

Chapter 2

87

2.5 Comparison Between Reserve Estimation Methods[23]

Table 8 shows when each method is best used

Table 8 Reserve Estimation Methods Comparison .[23]

Method Best used when

Volumetric • you don‘t have production trends

• you have a good estimate of recovery factor

• a representative reservoir model exists

DCA and MBAL • reliable production trends exist

• history of reservoir pressure available

• detailed reservoir model/data is not

available Simulation • reliable production trends exist

• you have an accurate reservoir model

• you have complete & accurate reservoir

properties

Analogy • you have no other choice

• geographic location, formation

characteristics,

etc. render analogy appropriate

Chapter 2

88

Table 9 shows the data needed, the advantages, the disadvantages, and the

results of using different estimation methods.

Table 9 Summary Of Reserve Estimation Methods.[23]

CHAPTER 3

89

CHAPTER 3

3 Methodology

3.1 Available Data

Isopach Contour Map for NetPay Zone

Figure 36 Isopach Contour Map For Net Pay Zone OF Marine Zone 2 .

CHAPTER 3

90

Belayim Marine Field(Zone 2) Case Study

Reservoir Data Table 10 Belayim Marine Field (Zone 2) Data.

Initial Reservoir Pressure (psi) 3558

Reservoir Temperature (oF) 205

Water Salinity (PPM) 150000

API 21

Saturation Pressure (psi) 1050

Porosity 0.2

Permeability (md) 500

rw (m) 2460

Connate water saturation 0.3098

Water viscosity (cp) 0.5

Cf (psi-1

) 3.75*10-6

Initial Formation Volume Factor 1.1563

Reservoir History This reservoir belongs to Belayim Petroleum Company PETROPEL)

in Belayim Field zone ΙΙ.

The production started on October 1963 from zone II , In May 1973

all the wells were shut off and the reservoir has produced

4595000.00stb of oil.

In Jan/1978 all the wells were put on stream The water injection was

started at Jan/1985, then a program of water injection has started to

compensate the sharp decrease in the reservoir pressure.

In October 2007 the reservoir has produced 6.42E+07 stb of oil with

Production rate =932.5 bbl/day

CHAPTER 3

91

Table 11 Belayim Marine Field (Zone 2) Pvt Data .

CHAPTER 3

92

3.2 Methodology

1 • Calculation MBE (Excel)

2 • Prediction (Excel)

3 • Montecarlo Simulation

4 • Reservoir Management Spread Sheet

5 • MBAL

6 • Eclipse

CHAPTER 3

93

3.2.1.1 The Material Balance Equation

The material balance equation (MBE) has long been recognized as one

of the basic tools of reservoir engineers for interpreting and predicting

reservoir performance. The MBE, when properly applied, can be used

to:

1- Estimate initial hydrocarbon volumes in place

2- Predict future reservoir performance

3- Predict ultimate hydrocarbon recovery under various types of primary

driving mechanisms

The equation is structured to simply keep inventory of all materials

entering, leaving, and accumulating in the reservoir. In its simplest form,

the equation can be written on volumetric basis as:

Initial volume = volume remaining + volume removed Since oil, gas,

and water are present in petroleum reservoirs, the material balance

equation can be expressed for the total fluids or for any one of the fluids

present. Before deriving the material balance, it is convenient to denote

certain terms by symbols for brevity. The symbols used conform where

possible to the standard nomenclature adopted by the Society of

Petroleum Engineers.

Reservoir type:- This reservoir is oil reservoir

According to production history

There‘s no gas cap in the reservoir

GP : produced during production from tubing

Also that‘s small value

CHAPTER 3

94

The saturation of reservoir according to PVT data:-

From reservoir pressure records and PVT data

Pb= 1050 Psi

And the current reservoir pressure =1390 Psi

This reservoir is under saturated reservoir

Type of under saturated reservoir

From MBE

The driving mechanism in this case depends on

Cw: that‘s water compressibility from (correlation)

CF: formation compressibility from (chart)

Assume that this reservoir is without bottom water drive

Figure 37 Reservoir MBE .

CHAPTER 3

95

From 1, 2

CHAPTER 3

96

1-Co : That’s Oil Compressibility

2-CF: Formation Compressibility From (Chart Between

Porosity Vs Cf )[5]

Cf=0.0000037

Table 12 Calculate Oil Compressibility.

CHAPTER 3

97

3- Solubility Of Oil From (Data)

So= 0.6962

Solubility of water from (Data)

Sw=0.3038

4- Cw: That’s Water Compressibility From (Correlation)

Table 13 Calculate Water Compressibility .

CHAPTER 3

98

5- Ce: Effective Compressibility

6- From History Data Get

Table 14 Calculate Effective Compressibility.

Table 15 Calculate Wi ,Wp,βw .

CHAPTER 3

99

7- Final Equation Will Be Applied.

Table 16 Calculate (Eo)&(F-Wi βw).

CHAPTER 3

100

From this chart (N) is not constant

So This reservoir is with bottom water drive

-5

0

5

10

15

20

25

30

35

40

0 0.01 0.02 0.03 0.04 0.05

F-w

iBw

10E

6

Eo

N

N

Figure 38 Chart Calculate N.

CHAPTER 3

101

3.2.1.2 Water Influx

3.2.1.2 .1Steady state Water Influx (SS)

In this type of influx , the rate of water influx ,

is directly

proportional to , where the pressure (P) , is measured at the

original oil-water contact .

This type assumes that the pressure at the external boundary of the

aquifer is maintained at the initial value (Pi) , and that flow to the

reservoir is , by Darcy’s Law , proportional to the pressure differential ,

assuming the water viscosity ,average permeability ,and aquifer

geometry remain constant.

Figure 39 Plot Of Pressure And Pressure Drop Versus Time. [15]

CHAPTER 3

102

Where

o k’ is the water influx constant in barrels per day per pounds per

square inch .

o (Pi-P) is the boundary pressure drop in pounds per square inch.

From MBE Equation:

Since We cant be determined due to inability to calculate N , by

differentiation previous equation with time:

If the reservoir is under steady state water influx condition , then k’ must

be constant.

CHAPTER 3

103

How to Calculate k’?

y using the Microsoft excel software , K can be easily determined by

following the following steps :

1. A table is made with Date , Pressure , Δ P , Np , Wp , Wi , Δ NP

, ΔWP , ΔWi , βo and βw values as shown in table:

Table 17 Marine zone II Data

CHAPTER 3

104

2. By substituting the equation’s parameters , k’ can be easily

calculated as follow :

Since k‘ values aren‘t constant , then the reservoir isn‘t under steady

state conditions and other states has to be tested.

Table 18 Calculated k' values

CHAPTER 3

105

Pi1

i

Pw1

www

Pw2

Pw3

Pi2

i

Pi3

3i

3.2.1.2 .2 Semi-Steady State For Water Influx (SSS)

In the semi-steady state, ∆P remains constant but there's a change in the

initial pressure (Pi) with time that depends on time interval.

re : increases with time

Characteristics :

-has strong We (water Influx).

-Has external boundary.

-Initial Pressure declines with time.

-(re) increases with time.

Figure 40 Semi Steady State Behavior .

CHAPTER 3

106

For number of periods of time:

Log(a) . ∑Ki + Log(ti) . ∑Ki = n.C (1)

By Multiplying time (t) in each period of time:

t . K.Log (a) + t . K.Log (t) = t.C

Total:

Log(a) . ∑ti.Ki + Log(t) . ∑ti.Ki = C.∑ti (2)

Where:

a : constant.

C: a constant refers to the reservoir‘s characteristics.

t : time in days.

n : number of periods of time included in the calculations.

From equations (1) & (2) the values of " a & c "can be determined as

Shown Below :-

CHAPTER 3

107

CHAPTER 3

108

Using This Table we determine the parameters of the equations (1) and

(2) using the Microsoft excel software :-

Table 19 Determining Semi Steady State Equations’ Parameters

CHAPTER 3

109

By using this Table :

It is found that

Then this reservoir doesn‘t follow the semi steady state behavior.

Table 20 Comparing Values Of (Δwe SSS)/ΔT And (Δwe MBE)/ΔT.

CHAPTER 3

110

3.2.1.2 .3 Unsteady state (USS)

Unsteady state models for both edge water and bottom water drives are

presented.

An edge water drive is defined as water influxing the reservoir from its

flanks with negligible flow in the vertical direction . in contrast , a bottom

water drive has significant vertical flow.

The van Everdingen and Hurst Edge-Water Drive Model:

Consider a circular reservoir of radius Rw , as shown , in a horizontal

circular aquifer of radius Re which is uniform in thickness , permeability

and porosity and in rock and water compressibilities.

The radial diffusivity equation expresses the relation ship between

pressure , radius and time for a radial system as shown in fig . where the

driving potential of the system is the water expandibility and the rock

compressibility.

The diffusivity equation is applied to the aquifer where the inner

boundary is defined as the interface between the reservoir and the aquifer

With the interface as the inner boundary , it would be more useful to

require he pressure at the inner boundary o remain constant and observe

Re

Rw

Figure 41 Un Steady State Behavior

CHAPTER 3

111

the flow rate as it crosses he boundary or as it enters the reservoir from

the auifer.

Mathmaically , this condistion is stated as

P = constant = Pi – ΔP at R=Rw

Where Rw is constant and is equal to the outer radius of the reservoir

(the original oil-watter contact).

The pressure P must be determined at this original oil-water conact . van

Everdingen and Hurst solved the diffusivity equation for his condition ,

which is referred to as the constan terminal pressure case , and the

following initial and outter boundary conditions:

Initial condition:

P= Pi for all values of R

Outer boundary condition:

For an infinite aquifer : P = Pi at R =

For a finite aquifer:

= 0 at R =Re

At this point , the diffusivity equation is rewritten in terms of the

following dimensionless parameters:

Dimensionless Time :

Dimensionless Radius :

Dimensionless Pressure :

With these dimensionless parameters , the diffusivity equation becomes:

Van Everdingen and Hurst converted their solutions to dimensionless

cummulative water influx values and made he results available in a

CHAPTER 3

112

convenient form given in tables for various ratios of aquifer to reservoir

size by he ration of their radii

.

The data are given in terms of dimensionless time tD , and dimensionless

water influx Qt so that one set of values suffices for all aquifers whose

behavior can be represented by the radial form of the diffusivity equation

The water influx is then found by using this equation :

Where B‘ is the water influx constant in barrels per pounds per square

inch.

Each radii ratio is tested and plotted to determine the type of the aquifer

as follows:

Table 21 Td vs pressure and Ce.

CHAPTER 3

113

Figure 42 Plotting ∑Qt.∆P/Eo Vs (F-

Wi*Βw)/EO At Re/Rw =2. Figure 43 Plotting ∑Qt.∆P/Eo vs (F-

Wi*βw)/EO at re/rw =4.

Table 22 Calculation of ∑Qt.∆P/Eo at re/rw = 2 and 4.

-1

0

1

2

3

4

5

6

7

0 50 100

[F-(

Wi*

Bw

)]/E

o

Mil

lio

ns

∑Qt*∆P/Eo

Thousands

re/rw=2

re/rw=2

Linear (re/rw=2)

-1

0

1

2

3

4

5

6

7

0 0.2 0.4 0.6

[F-(

Wi*

Bw

)]/E

o

Mil

lio

ns

∑Qt*∆P/Eo

Millions

re/rw=4

re/rw=4

Linear

(re/rw=4)

CHAPTER 3

114

Figure 45 Plotting ∑Qt.∆P/Eo vs (F-Wi*βw)/EO

at re/rw =6. Figure 44 Plotting ∑Qt.∆P/Eo vs (F-Wi*βw)/EO

at re/rw =8.

Table 23 Calculation Of ∑Qt.∆P/Eo At Re/Rw = 6 And 8.

0

50

100

150

200

250

300

350

400

450

500

0 0.5 1 1.5 2

Mil

lio

ns

Millions

re/rw=8

0

50

100

150

200

250

300

350

400

450

500

0 0.5 1

(F-W

i*β

w)/

EO

M

illi

on

s

∑Qt.∆P/Eo Millions

re/rw=6

re/rw=6

CHAPTER 3

115

From the results , the reservoir is clearly not under finite outer boundary

conditions so , infinite outer boundary calculations are applied as follows

Table 24 Calculating ∑Qt.∆P/Eo At Re/Rw = Infinity.

The result shows that the outer boundary is infinite.

0

50

100

150

200

250

300

0 10 20 30 40

(F-W

i.B

w)/

Eo

Mil

lio

ns

∑Qt.∆P/Eo

Millions

re/rw=infinty

re/rw=infinty

Linear (re/rw=infinty)

Figure 46 ∑Qt.∆P/Eo At Re/Rw = Infinity.

CHAPTER 3

116

3.2.1.3 Prediction

1) Assume 3 pressures :

1400 ,1410 , 1420

2) From Reservoir Management Spread sheet , Interpolating Cw,

Co, Ce, Cf, βo, βw with actual data

Table 25 Prediction Table

Table 26 3 Pressures Assumption

Table 27 Cw,Co,Ce, βo, βw for P.=1400

CHAPTER 3

117

3) Put the data in the prediction table :

where C = Cf + Cw



Table 30 Input Cw,Co,Ce, βo, βw for the 3 P.

CHAPTER 3

118

4) Calculate ∆P :

5) Then Calculate Td :

Table 31Calculate Delta P

Table 32 Calculate TD

CHAPTER 3

119

6) Calculate (QT) From Unsteady State (re/rw >10) :By using

Interpolation:

7) Then Calculate ∑Qt.∆P :

Table 33 Calculate TD at re/rw >10 [5]

Table 34 Calculate (QT)

CHAPTER 3

120

Then put the final result

Table 35 Calculate ∑Qt.∆P

Table 36 Input QT ,∑Qt.∆P.

CHAPTER 3

121

8) Calculate We uss

9) Calculate NP :

Enter Wp Values :

10) Calculate Wi :

―Assume this const. Until We USS curve intercepts with We MBE

curve‖

― ‖

Table 37 Calculate We uss

Table 38 Input Wp ,NP

CHAPTER 3

122

First assume it = 1

11) Calculate NP*βo ,WP*βw, WI*βw ,∆P( )

12) Calculate : N*βoi*Ce*∆P

Table 39 Calculate Wi

Table 40 Calculate NP*βo ,WP*βw, WI*βw ,∆P

Table 41 Calculate N*βoi*Ce*∆P

CHAPTER 3

123

13) Calculate We MBE :

14) Draw a Chart Between P with ( WE MBE& WE USS) :

15) Change the value of the const. Until We uss intercepts with We

mbe

Const. Should be less than 2.5

At const. = 1.2992 the 2 curves are intercepted

Figure 47 Chart between P with ( wepe& we uss))

Table 42 Calculate We MBE

CHAPTER 3

124

Figure 48 Chart Between P With ( Wepe& We Uss)By Using Mew Wi.

16) Get the P. at the intercept P. = 1416

17) Repeat these steps for every 2 years until : NP/Wi = 2.5

Then the prediction stops .

3.86

3.87

3.88

3.89

3.9

3.91

3.92

3.93

1395 1400 1405 1410 1415 1420 1425

We M

illi

on

s

P

uss

me

3.86

3.87

3.88

3.89

3.9

3.91

3.92

3.93

1395 1400 1405 1410 1415 1420 1425

Mil

lio

ns

uss

mbe

Figure 49 Predicted p .

CHAPTER 3

125

3.2.2 Reservoir Management Spread sheet

It‘s an Excel sheet depends on mathematical calculation by using

Microsoft Macros to calculate reservoir engineering purpose.

The benefits of using Reservoir Management Spread sheet

Interpolate the PVT data to match data with reservoir pressure.

Draw Production History Matching Curve.

Reservoir Production Prediction.

Comparing the production will be with changing water viscosity by

(Polymer Flooding).

The Required Data

Start of Production date .

Initial pressure .

Reservoir Area and hight.

Number and names of wells , wells types (production or injection),

wells location and initial flow rate per day

PVT data from lab or by correlations at different pressures.

Reservoir pressure for each well along production history.

Injection water viscosity.

Steps:-

1- Insert wells information.

Insert well

name, Type

and initial

flow rate in

bbl/day

Insert initial pressure and

starting of production date

Figure 50 Reservoir Management Spread Sheet Wells Input.

CHAPTER 3

126

2- Press (Pressure Matcher) to insert wells pressures along

production history.

3- Press (MATCH) to history matching the pressure with time.

4- From Fig.53 press (PVT LAB MATCHER) to insert pvt lab

data and start to match the data with different reservoir

pressure.

Figure 51Reservoir Management Spread Sheet Pressure Input.

Figure 53 Reservoir Management Spread Sheet PVT Input .

Figure 52 Pressure Matching

CHAPTER 3

127

5- Press (GO TO LAB) to start matching the PVT data with wells

pressure.

Figure 54 Reservoir management spread sheet PVT Matching .

6- From Fig. 55 press (PREDICTION) , Insert (Wells locations,

Reservoir area, Height , Initial injection water viscosity and

injection water with polymers viscosity) then press (Predict).

Figure 55 Reservoir Management Spread Sheet Well Locations.

CHAPTER 3

128

7- The following fig shows the prediction of the production of the

reservoir.

8- The following fig showing prediction of reservoir production

behavior at initial injection water viscosity and changing in

water viscosity.

Figure 56 Reservoir Management Spread Sheet Prediction

Figure 57 Reservoir Management Spread Sheet Prediction by chemical effect

CHAPTER 3

129

3.2.3MBAL [24]

3.2.3.1 Montecarlo Simulation Tool [24] :

The tool enable the user to perform statistical evaluation of reservoir

.distribution can be assigned to variable like porosity or thickness of

reservoir and the program will generate the range of probability

associated with reserve range.

Decline Curve Analysis :

Production data can be fitted to Hyperbolic , exponential or Hermic

decline . these is can be the extrapolation in future for generation

forecasts.

Software steps:

1-Choose Mote Carlo Tool From Tool Manu As Shown:

Figure 58 Choosing Monte Carlo Tool.

CHAPTER 3

130

2- Defining the general option :

3- enter the PVT fluid properties data form PVT menu :

4- then enter the data required in the new window as shown :

Figure 59 System Option Window

Figure 60 PVT Menu

Figure 61 Data Input

CHAPTER 3

131

5-Match PVT data :

6- Then choose Distribution from Input menu:

Figure 63 Selecting Distributions.

Figure 62 Match PVT data

CHAPTER 3

132

7- Entre the required data in the window where the bulk volume is

calculated from reservoir geology information :

8- Then press ― Calc ― , to watch the results .

Figure 64 Distributions.

CHAPTER 3

133

3.2.3.2 MBE Tool [24] :

Field development planning using MBE will be applied using MBAL

software, the workflow can be divided into:

1. Data loading:

This step is the initial step of the development process. In this stage, the

available data of the reservoir is loaded into the software, and the general

options of the model are determined. These data include:

i. Fluid properties

ii. PVT properties

iii. Estimation of the IOIP from the results of Eclipse simulation results.

iv. Production start date.

v. Petro-physical data

vi. Relative permeability data.

vii. Historical data (production and pressure)

After loading the data, matching process should be applied for the fluid

properties and PVT data as discussed earlier in the volumetric method.

The main output of this step is the relative permeability plot and the

cumulative oil production and pressure plot.

Data loading

History matching

Prediction

CHAPTER 3

134

2. History matching:

History matching process involves matching the historical data with the

data predicted by the model.

3. Model validation:

Before using the model for any future prediction, the model‘s ability to

predict the past performance in agreement with the input data must be

checked. In order to check the model, the model is run on prediction from

the start till the end data of the input data. A plot of the cumulative

production and historical pressure can be constructed to compare the

input data with the prediction data, if the values match; then the model is

ready for the prediction process.

4. Prediction:

After making sure that the model is valid for prediction, we have to

define the target and constraints for the prediction and then check the

reservoir behavior under different scenarios.

Software step:

1. Data loading

Defining model general options

Figure 65 General Option Widow.

CHAPTER 3

135

Fluid properties From PVT list , choosing fluid properties

Then data would be entered

Figure 66 PVT list .

Figure 67 Black Oil ( Data Input).

CHAPTER 3

136

Then match the data by using Match button and input the data in the table

Then click Match and choose data which will match on such as (Bubble

point , Gas oil ratio , Oil FVF and Oil Viscosity ) as shown and press

Calc button

Figure 69 Matching.

Figure 68 PVT Matching.

CHAPTER 3

137

Then click Plot button to plot the matched data graphs as shown in the

figure :

1-Oil FVF

2-oil viscosity

Figure 70 Oil FVF Curve.

Figure 71 Oil Viscosity Curve.

CHAPTER 3

138

3- Gas Oil Ratio

Reservoir parameters

The next step is to define the tank (reservoir parameters which include the

estimation of the IOIP , average petro-physical data (porosity, water

saturation), the relative permeability data, and production history.

Figure 73 shows the determination of tank parameters From Input choose

Tank Data

Figure 72 GOR Curve.

Figure 73 Input List.

CHAPTER 3

139

1-Input tank parameters as shown :

2-the water influx of the aquifer was defined using Van Everdingen-

Hurst model discussed earlier in the literature review section as shown:

Figure 74 Tank Parameters.

Figure 75 Water Influx.

CHAPTER 3

140

3-Then enter the rock compressibility by correlation as shown

4-Enter the rock compaction reversible as shown :

Figure 76 Rock Compressibility.

Figure 77 Rock Compaction.

CHAPTER 3

141

5- Relative permeability from tables

The plots of permeability

Figure 78 Relative Permeability.

Figure 79 Relative Permeability Curves.

CHAPTER 3

142

6- production History

input the production history by using Import a new window

will appear

Figure 81 Import Window.

Figure 80 History Matching Table.

CHAPTER 3

143

Choose ―Browse‖ and identify the file location then choose " done "

in the new window choose ― Tab Delimited ― then choose "done "

choose data shown with given field names

Figure 82 Import Setup.

Figure 83 Import file.

CHAPTER 3

144

2- History matching

Click on the History Matching button then choose Run Simulation

to run the simulation

In the new window click Clac button to start calculation

\

Figure 84 History Matching List.

Figure 85 Run History Matching.

CHAPTER 3

145

Then choose :

1- Analytical method :

2-Graphical method :

Figure 86 Analytical Method.

Figure 87 Graphical method.

CHAPTER 3

146

3- energy plot :

4-WD function plot :

Figure 88 Energy Plot.

Figure 89 WD Function Plot.

CHAPTER 3

147

4-prediction :

The main objective of this study is the identification and evaluation

of the remaining potential in existing producing zones.

Prediction steps :

1-choose production prediction from prediction set up :

2-entire the data required as shown

Figure 90 Production Prediction List.

Figure 91 Prediction Calculation Setup.

CHAPTER 3

148

3- then choose prediction and constrains and enter the required data

4-Then run the simulation and click Calc

Figure 92 Tank Prediction Data.

Figure 93 Run Simulation Window.

CHAPTER 3

149

3.2.4 ECLIPSE [21]

As shown in the literature review before the importance of using

software or especially simulators, Here starts to know the steps of using

the Reservoir Simulation (ECLIPSE).

ECLIPSE Data File

Its consist of eight sections each section specialized in a specific data to

input in it as shown:

Figure 94 Data File Section.

Start the Data Input

Open New Text pad file and start input data sections

1- RUNSPEC

The RUNSPEC section is the first section of an ECLIPSE data input file.

It contains the run title, start date, units, various problem dimensions

(numbers of blocks, wells, tables etc.), The RUNSPEC section must

always be present.

CHAPTER 3

150

The used data code :-

( TITLE, START, DIMENS, OIL, GAS, WATER, DISGAS,

FIELD,EQLDIMS ,TABDIMS, WELLDIMS, AQUDIMS) each of this

data code require a specific data, ECLIPSE Manual must had used for

helping what this codes needs.

2- GRID

The GRID section determines the basic geometry of the simulation grid

and various rock properties (porosity, absolute permeability, net-to-gross

ratios) in each grid cell. From this information, the program calculates

the grid block pore volumes, mid-point depths and inter-block

transmissibilities. The actual keywords used depend upon the use of the

radial or cartesian geometry options. The program accepts the radial form

in a cartesian run and vice versa, but issues a warning.


(TOPS,DX, DY, DZ, PERMX, PERMY, PERMZ, PORO, NTG,

GRIDFILE, INIT, NOECHO, PINCH).

3- EDIT

The EDIT section contains instructions for modifying the pore volumes,

block center depths, transmissibilities, diffusivities, and nonneighbor

connections (NNCs) computed by the program from the data entered in

the GRID section. It is entirely optional.

CHAPTER 3

151

4- PROPS

Tables of properties of reservoir rock and fluids as functions of fluid

pressures, saturations and compositions (density, viscosity, relative

permeability, capillary pressure, etc.). Contains the equation of state

description in compositional runs.


(SWFN, SGFN, SOF3, ROCK, DENISITY, PVDG, PVTO, PVTW,

AQUATAB)

5- REGIONS

` Empty, because this section used for divide the reservoir in different

regions and different properties.

6- SOLUTION

The SOLUTION section contains sufficient data to define the initial state

(pressure, saturations, compositions) of every grid block in the reservoir

.


(EQUIL, RSVD, RPTRST, RPTSOL)

7- SUMMARY

Specification of data to be written to the Summary file after each time

step. Necessary if certain types of graphical output (for example watercut

as a function of time) are to be generated after the run has finished. If this

section is omitted no Summary files are created.

CHAPTER 3

152


(RPTONLY, DATE, EXCEL, SEPARATE, ELAPSED, FOIP, FOPR,

FOPRH,FOPT,FOPTH,FLPR,FLPRH,FLPT,FLPTH,GOPR,GOPRH,

GOPT,GOPTH,GWPR,GGPR,WOPR,WOPRH,WOPT,WOPTH,

WWPR,WWPRH,WGPR,WGPRH,FWPR,FWPRH,FWCT,FWCTH,

FWPT,FWPTH,GWPR,GWPRH,GWCT,GWCTH,GWPT,GWPTH,

WWPRH,WWCTH,WWPT,WWPTH,FGIP,FGPR,FGPRH,FGOR,

FGORH,FGPT,FGPTH,RGIP,GGPR,GGPRH,GGOR,GGORH,GGPT,

GGPTH,WGPR,WGPRH,WGOR,HWGPT,WGPTH,FPR,RPR,WBHP,

WBP5,WBP9,WBHPH,WPI,WPIH,FAQR,FOEW,ROEW,TCPU,

WMCTL,WLPR,WLPRH,WPR,AAQR,FAQR,FAQT,

AAQP,FOPV,FWPV, WLPT, WLPTH, WWIR,WWIT,

FWIR, FWIT,WPI, WBP9)

8- SCHEDULE

Specifies the operations to be simulated (production and injection

controls and constraints) and the times at which output reports are

required. Vertical flow performance curves and simulator tuning

parameters may also be specified in the SCHEDULE section.


(WELSPECS, COMPDAT, WCONHIST, WCONINJE, DATES,

WCONPROD)

After Input the reservoir Data in the Data File, Starting the next step

that‘s running the simulation

CHAPTER 3

153

Figure 97 Running The Simulator.

Running the Simulator:-

1- From the Program Launcher ballet press ECLIPSE

2- Browsing computer drivers to select input data file and press RUN

3- Running the Simulator till end and having confirmation that there is no

warning massages or errors

Figure 96 Run The Simulator.

Figure 95 Simulator Preface.

CHAPTER 3

154

4- After running to show the calculation of OOIP, open the file (.PRT)

from input folder and search for OOIP

5- Showing the Model, From Program Launcher select (FLOVIZ)

Figure 98 Print File Location.

Figure 99 Original Oil In Place (OOIP).

Figure 100 Start FLOVIZ

CHAPTER 3

155

6- After pressing (RUN), FILEOPENECLIPS

Figure 101 Run The Model 1 .

Figure 103 Run The Model 2.

Figure 102 Run The Model 3 .

CHAPTER 3

156

7- (GRID PROPERTEY ) Button enable to show the different properties

required and response of model with TIME factor, that can be

selected from (PLAY,PAUSE, …ETC. ) Buttons which at the top bar

of the software.

Figure 105 Reservoir Model .

Figure 104 (FLOVIZ Parameters).

CHAPTER 3

157

To get the last report and drawing the curves of different requirements

from production rates (Gas, Oil & Water) along reservoir life from the

beginning till the predicted depletion, Select from program Launcher

(OFFICE).

8- Select REPORTFILEOPEN SUMMERY LOAD ALL

VECTORS.

Figure 106 RUN OFFICE.

Figure 107 Load All Vectors .

CHAPTER 3

158

9- At (INPUT), select the vectors required to plot or shown in the output

file then press (GENERATE REPORT) .

10- To see the report Press (OUTPUT) then select showing it as table

or Plot as required.

Figure 108 Input Variables .

Figure 109 Output OFFICE.

CHAPTER 3

159

11- Finally, may have more than one plot and different vectors as

required.

Figure 110 OFFICE Output table.

Figure 111 OFFICE Output Charts .

CHAPTER 4

160

CHAPTER4

4 Result

4.1 PVT Correlations [5]

Gas Solubility (Rs)

The used correlations :-

Standing‘s

Glaso‘s

The Best and suitable correlation was (Standing correlation) with

Average Absolute Error (AAE%) = 50.98 %

x= 0.0125 API - 0.00091(T - 460)

the modified correlation

0

20

40

60

80

100

120

140

160

180

200

0 2000 4000 6000

Rs

Pressure

Gas Solubility

Actual

Modified Rs

Glaso

Standin

Figure 112 Gas Solubility

CHAPTER 4

161

Gas Specific gravity

From knowing the gas specific gravity in the separator enabling to

calculate the gas specific gravity in different reservoir conditions by

adding the factor Delta (∆) from the followed chart.

Figure 113 Correction.

At known pressure

∆= (-6×10-15

P5)+(10

-11 P

4)-(9×10

-9 P

3)+(10

-6 P

2)+(.001P)-.255

= ± ( ∆ )

Formation Volume Factor (Bo)

The used correlatins:-

Above Bubble Point Pressure

(Calhoun's correlation)

∆= -6E-15 P5 + 1E-11 P4 - 9E-09P3 + 1E-06P2 + 0.001P - 0.255

R² = 1

-0.3

-0.2

-0.1

0

0.1

0.2

0 100 200 300 400 500 600 700 800 ∆

p

p,delta Poly. (p,delta)

Calhoun's correlation

CHAPTER 4

162

1.02

1.04

1.06

1.08

1.1

1.12

1.14

1.16

1.18

1.2

0 1000 2000 3000 4000 5000

Bo

Pressure

Bo

Actual

Standing

Bo calhoun's correlation

Modified

Glaso’s Correlation

The Vasquez-Beggs

Correlation

Below Bubble Point Pressure

Standing's correlation

Glaso‘s Correlation

The Vasquez-Beggs Correlation

The Suitable Correlation where

P<Pb was (Standing's correlation) with AAE%= 1.282454 %

P>Pb was (Calhoun's correlation) with AAE%= 1.033 %

Glaso’s Correlation

Standing's correlation

The Vasquez-Beggs Correlation

Figure 114 FVF

CHAPTER 4

163

0

5

10

15

20

25

30

35

40

0 1000 2000 3000 4000 5000

Co *10^-6 The

Petrosky-Farshad

Correlation Co real * 10^-6

Co *10^-6 The

Vasquez-Beggs

Correlation Modified Petrosky-

Farshed *10^6

Oil Compressibility (Co)

The used correlations:-

The Petrosky-Farshad Correlation (P>Pb)

The Vasquez-Beggs Correlation (P>Pb)

Best correlation was Petrosky-Farshad Correlation with AAE %=

19.11%

Oil Viscosity

The used correlation:-

The Chew-Connally Correlation (P<Pb).

(where Mob is the oil viscosity and Mod is

the oil viscosity at P=14.7psia)

The Beggs-Robinson Correlation

(P<Pb).

(where Mob is the oil viscosity

and Mod is the oil viscosity at

P=14.7psia)

Mob = (10)^a (Mod)^b

a = Rs [2.2(10^-7) Rs - 7.4(10^-4)]

b=(0.68/10^c)+(0.25/10^d)+(0.062/10^e)

c = 8.62(10^-5)Rs

d = 1.1(10^-3)Rs

e = 3.74(10^-3)Rs

Figure 115 Oil Compressibility

CHAPTER 4

164

The Best Correlation Chew-Connally Correlation with AAE%=2.972%

Crude Oil Density

The used correlation:- Table 43 crude oil denisty used correletion.

Below Bubble Point Pressure Above Bubble Point Pressure

1. Material Balance Equation 1. Vasquez-Beggs

2. Standing 2. Petrosky-Farshad

The most suitable correlation:- Table 44 Oil Denisty suitable Correlation

Below Bubble Point Pressure Above Bubble Point Pressure

Standing

Vasquez-Beggs

AAE % = 8.28% AAE %= 0.946866842

0

1

2

3

4

5

6

7

8

9

10

0 500 1000 1500

Mo

Pressure

Oil viscosity

Mo Actual

Mo chew

Mo Beggs-Robinson

Modified Chew

Figure 116 Oil Viscosity

CHAPTER 4

165

40

45

50

55

60

65

70

75

80

0 500 1000 1500 2000 2500 3000 3500 4000 4500 5000

Actual

MBE

Standing

Vasques-Beggs

Petrosky-Farshad

Modified

1.04

1.0405

1.041

1.0415

1.042

0 1000 2000 3000 4000 5000

Bw

Pressure

Bw

Bw

Water formation volume factor (Bw)

The used correlation

βw = βwp(1+A*y*10^-4)

Where βwp = C1+C2*P+C3*P^2

A=5.1*10^-8*P+ (T-60)*(5.47*10^-6-1.95*10^-10*P) + (T-60) ^2 * (-

3.23*10^-8+8.5*10^-13*P)

C1=0.9911+6.35*10^-5*T+8.5*10^-7*T^2

C2=1.093*10^-6-3.497*10^-9*T+4.57*10^-12*T2

C3=-5*10^-11+6.429*10^-13*T-1.43*10^-15*T^2

Where

βwp= water formation volume factor at (p=14.7, T), bbl/Stb

T = Reservoir Temperature

(oF)

Y =water salinity (PPM)

P =reservoir pressure (psia)

y= 150000 ppm

T= 205 F

C1= 1.039839

C2= 3.77E-07

C3= 2.17E-11

Figure 117 Crude Oil Denisty.

Figure 118 Bw

CHAPTER 4

166

0.000003

3.05E-06

0.0000031

3.15E-06

0.0000032

3.25E-06

0.0000033

0 2000 4000 6000

Water Comprisibliity

Water

Comprisibliity

Water Compressibility (Cw)

Cw =Cwp * (1+X*Y*10^-4)

Where

X =5.1*10^-8*P+(T-60)*(5.47*10^-6+1.95*10^-10*P)+(T-60)^2*(-

3.23*10^-8+8.5*10^-13*P)

Cwp =(C1+C2*T+C3*T^2)*10^-6

C1=3.8546-0.000134*P

C2=-0.01052+4.77*10^-7*P

C3=3.9267*10^-5-(8.8*10^-10*P)

Where

Cwp =water compressibility at

p=14.7,T,cp

T = Reservoir Temperature (oF)

Y =water salinity (PPM)

P =reservoir pressure (Psi)

Table 45 PVT Conculosion

Property Suitable Correlation AAE%

Gas Solubility (Rs) Standing correlation

50.98

Gas Specific gravity = ± ( ∆ )

----

Formation Volume Factor(Bo)

P<Pb

Standing's correlation 1.282454

P>Pb

Calhoun's correlation

1.033

Oil Compressibility (Co)

Petrosky-Farshad Correlation 19.11

Oil Viscosity

Chew-Connally

2.972

Crude Oil Density

P<Pb

Standing 0.946866842

P>Pb

Vasquez-Beggs

8.28

Figure 119 Water Compressibility

Pressure

Wc

CHAPTER 4

167

4.2 History Matching

Table 46 History Matching.

Date T

year press,psi

∆t

days

t

days

NP

(bbl) GP(MMSCF) WP(bbl) WI(bbl)

Oct-63 1963 3550 0

Dec-63 1963 3500 60.8 60.8 131161.4 36833.19739 69.18792 0

Dec-65 1965 3110 730 790.8 1594203 457607.4514 1012.66 0

Dec-67 1967 2860 730 1521 2258608 690542.993 1320.86 0

Dec-69 1969 2695 730 2251 2874789 906562.8094 1346.02 0

Dec-71 1971 2555 730 2981 3360180 1057850.842 3943.711 0

Dec-73 1973 2415 730 3711 4553037 1338178.666 6660.91 0

Dec-75 1975 2275 730 4441 4595367 1347607.682 6660.91 0

Dec-77 1977 2165 730 5171 4595367 1347607.682 6660.91 0

Dec-79 1979 2055 730 5901 5856330 1793137.517 9315.21 0

Dec-81 1981 1970 730 6631 7480535 2408742.788 97529.81 0

Dec-83 1983 1860 730 7361 11147941 3251562.624 124991.1 0

Dec-85 1985 1805 730 8091 17339241 4279254.74 593802.2 912552.4

Dec-87 1987 1695 730 8821 21990877 5659457.859 1791955 5727963

Dec-89 1989 1665 730 9551 27760281 7581882.371 3303377 9440997

Dec-91 1991 1600 730 10281 32935028 8540004.594 5576024 11020377

Dec-93 1993 1525 730 11011 37532647 9438303.772 7078767 18805440

Dec-95 1995 1470 730 11741 41055155 10393282.99 8506195 27964291

Dec-97 1997 1390 730 12471 43656149 10987734.77 9514156 33643078

Dec-99 1999 1335 730 13201 45965899 11659207.85 10828708 38510358

Dec-01 2001 1335 730 13931 51218395 12879859.3 12529240 47821449

Dec-03 2003 1350 730 14661 56173602 14039769.53 14640220 65198390

Dec-05 2005 1360 730 15391 60766000 15604244.58 17798347 78063401

Oct-07 2007 1390 669.2 16060 64211703 16789192.91 21056041 91329803

CHAPTER 4

168

Figure 121 Gp Vs Years

0

500

1000

1500

2000

2500

3000

3500

4000

0

2

4

6

8

10

12

14

16

18

1960 1970 1980 1990 2000 2010

Pre

ssu

re(P

SIA

)

Gp

(MS

CF

)

Mil

lio

ns

Time(years)

GP(MMSCF)

press,psi

0

500

1000

1500

2000

2500

3000

3500

4000

-20

0

20

40

60

80

100

1960 1965 1970 1975 1980 1985 1990 1995 2000 2005 2010

Pre

ssu

re

Wp

,Wi,

Np

(b

bl)

Mil

lio

ns

time (YEARS)

NP WP WI Pressure

Figure 120 Wp,Wi,Np (bbl) Vs Years

CHAPTER 4

169

PVT Matching

Table 47 PVT Matching.

CHAPTER 4

170

Figure 122 Cw,Co,Rs

0

0.000002

0.000004

0.000006

0.000008

0.00001

0.000012

0.000014

0

20

40

60

80

100

120

140

160

180

200

0 500 1000 1500 2000 2500 3000 3500 4000

Cw, Co, Rs

Rs Co Cw

4.1

4.2

4.3

4.4

4.5

4.6

4.7

4.8

4.9

5

1.15

1.155

1.16

1.165

1.17

1.175

1.18

0 500 1000 1500 2000 2500 3000 3500 4000

Bo

P

Bo

Mo

Pb

Pb

Figure 123 Bo, Mo

CHAPTER 4

171

Reservoir type: under saturated reservoir with active water drive

Aquifer type: Unsteady state with infinite Aquifer boundary

OOIP=205749458 STB

Figure 124 re/rw=infinty

Res

erv

oir

Ty

pe

Under- saturated

Oil Reservoir

Dri

vin

g M

ech

anis

m

Active Bottom water Drive A

qu

ifer

Sta

te

Unsteady state with infinity Aquifer Boundary

0

50

100

150

200

250

300

0 10 20 30 40

(F-W

i.B

w)/

Eo

Mil

lio

ns

∑Qt.∆P/Eo

Millions

re/rw=infinty

re/rw=infint

y

Linear

(re/rw=infin

ty)

CHAPTER 4

172

4.3 Prediction

The project gets the prediction from ends of available data

times :

2009, 2011, 2013, 2015, 2017, 2019

get Wi/Np and then ΔWi/Np as shown :

Table 48 Wi/Np & dWi/Np

Time WI/NP ΔWI/NP

2009 1.2992

2011 1.326 0.0268

2013 1.3524 0.0264

2015 1.3775 0.0251

2017 1.4021 0.0246

2019 1.4265 0.0244

CHAPTER 4

173

Then get (avg: ΔWI/NP) which equals = 0.0253625

Table 49 Prediction Calculation

T NP NP/N WP WI WI/NP WI/VP

2009 68000000 0.330497555 22157428 88345600 1.2992 0.223612

2011 72000000 0.349938587 24905428 95472000 1.326 0.241649

2013 76000000 0.36937962 27813428 102782400 1.3524 0.260153

2015 80000000 0.388820652 30881428 110200000 1.3775 0.278927

2017 84000000 0.408261685 34109428 117776400 1.4021 0.298104

2019 88000000 0.427702718 37497428 125532000 1.4265 0.317734

2021 92000000 0.44714375 41045428 133571350 1.451863 0.338082

2023 96000000 0.466584783 44753428 141813600 1.477225 0.358944

2025 100000000 0.486025816 48621428 150258750 1.502588 0.38032

2027 104000000 0.505466848 52649428 158906800 1.52795 0.402209

2029 108000000 0.524907881 56837428 167757750 1.553313 0.424612

2031 112000000 0.544348913 61185428 176811600 1.578675 0.447528

2033 116000000 0.563789946 65693428 186068350 1.604038 0.470958

2035 120000000 0.583230979 70361428 195528000 1.6294 0.494901

2037 124000000 0.602672011 75189428 205190550 1.654763 0.519358

2039 128000000 0.622113044 80177428 215056000 1.680125 0.544328

2041 132000000 0.641554076 85325428 225124350 1.705488 0.569812

2043 136000000 0.660995109 90633428 235395600 1.73085 0.59581

2045 140000000 0.680436142 96101428 245869750 1.756213 0.622321

2047 144000000 0.699877174 1.02E+08 256546800 1.781575 0.649346

2049 148000000 0.719318207 1.08E+08 267426750 1.806938 0.676884

2051 152000000 0.73875924 1.13E+08 278509600 1.8323 0.704936

2053 156000000 0.758200272 1.2E+08 289795350 1.857663 0.733501

2055 160000000 0.777641305 1.26E+08 301284000 1.883025 0.76258

2057 164000000 0.797082337 1.32E+08 312975550 1.908388 0.792172

2059 168000000 0.81652337 1.39E+08 324870000 1.93375 0.822278

2061 172000000 0.835964403 1.46E+08 336967350 1.959113 0.852898

2063 176000000 0.855405435 1.53E+08 349267600 1.984475 0.884031

2065 180000000 0.874846468 1.6E+08 361770750 2.009838 0.915678

2067 184000000 0.894287501 1.67E+08 374476800 2.0352 0.947838

2069 188000000 0.913728533 1.74E+08 387385750 2.060563 0.980512

CHAPTER 4

174

Then predict that :

The reservoir Abundant time is 2069 as : NP/N =0.913728533 and

WI/VP=0.980512 and this is the maximum acceptable values for each

of them !!

Now draw a chart between :Time on (x-axis) and (P, Np, Wi, Wp) on

(y-axis) :

Figure 125 Past& Future

1320

1340

1360

1380

1400

1420

1440

1460

1480

1500

0

20000000

40000000

60000000

80000000

100000000

120000000

140000000

1999 2004 2009 2014 2019

Pressure

Np,

Wp,

Wi

Time

Np

Wp

Wi

P

CHAPTER 4

175

4.4EOR

From last study in literature review about types of recovery the best one

and most suitable one is the(Polymer Flooding) that will be

environmentally and economically good for the reservoir.

Using polymers to increase viscosity of water in small bores and making

the displacement of oil by water with same rate to not to trap oil

So must use special type of polymers:

1. Purely Viscous

This type at small diameter Ɣ1 increase water has low viscosity (high

speed) so in small pores oil will be trapped that‘s make this type not

suitable for use.

Ex: a) Poly Socharide (PS).

b) Hydroxy Ethyle Celelouse (HEC)

Figure 126Purely Viscous

CHAPTER 4

176

2. Visco Elastic

This type is suitable as in small diamter Ɣ1 has high water viscosity

(low speed) and In large diamters Ɣ2 has low viscosity (high speed) .

Ex: a) Poly Acylamide (PA)

b) Poly Ethylene Oxyde (PEO)

so by adding visco elastic polymer with optimum concentration make

water in large and small diameter move at same velocity.

The Viscosity selection

The selection of water viscosity that will flood its defends on the

condition of the reservoir at moment of flooding and the target required

By using (Reservoir management spread sheet) its able to show the

behavior of reservoir with different water viscosity and comparing

between them.

Figure 127 Visco Elastic

CHAPTER 4

177

0

2E+10

4E+10

6E+10

8E+10

1E+11

1.2E+11

0 2E+09 4E+09 6E+09 8E+09

time (days)

prediction by chemical effect

visc. 1 visc. 2 visc. 3

As shown in the following chart

Where Visc.1= 0.5 CP, Visc.2= 1 CP & Visc.3= 10 CP

From this chart notice that the effect of changing viscosity on production

where with increasing water viscosity the result is increasing in

cumulative oil produced and retardant of water production

Figure 128 prediction by chemical effect

CHAPTER 4

178

4.5 MBAL

1- Montecarlo Tool

Figure 130 Montecarlo Results 1

Figure 129 Montecarlo Results 2

CHAPTER 4

179

2-MBAL MBE

1- History Matching results :

A-Drive mechanism is shown in the figure

The figure shows the drive mechanism of the reservoir where it start with

fluid expansion with

Fluid expansion Pore volume compressibility and water influx with the

percentage shown in the figure was the dominated driving mechanism .

and at 1985 the water injection was started .

B-Bottom drive aquifer

Figure 132 Bottom drive aquifer

Figure 131 Drive mechanism

CHAPTER 4

180

C-Graphical method graph

The Graphical method shows the relationship between (F/Et ) and

(We/ Et ) where the intercept is the original oil in place (OOIP ) as

shown in the figure = 205.79 MMSTB

D-Analytical method graph :

Figure 133 graphical method

Figure 134 Analytical method

CHAPTER 4

181

Prediction results:

1-average gas and oil rate with time

2-Average water injected with cumulative oil produced

Figure 135 Gas and oil rate

Figure 136 Average water injected with cumulative oil produced

CHAPTER 4

182

3-cumulative gas and oil produced with time

4 - Cumulative oil produced with water injected

Figure 137 cumulative gas and oil produced

Figure 138 Cumulative oil produced with water injected

CHAPTER 4

183

5-water injection And cumulative oil production with time

6-oil saturation with time

Figure 139 water injection And cumulative oil production with time

Figure 140 oil saturation with time

CHAPTER 4

184

7- Oil recovery factor

Recovery factor is 47 % at 1-1-2035

Figure 141 recovery factor

CHAPTER 4

185

4.6 ECLIPSE Results

1- Model

Eclipse model the reservoir with its wells in present time and in

future till reservoir depletion with different properties.

Side view of reservoir with different saturations.

Figure 142 Reservoir Model

Figure 143 Side view

CHAPTER 4

186

2- GRAPHES

a. Total production (Oil, Gas & Water) , total water injection

verses Years

Total oil production (FOPT)

Total gas production (FGPT)

Total water Production (FWPT)

Total water injection (FWIT)

b. Production and injection rates verses date

Field Gas Production Rate (FGPR)

Field Oil Production Rate (FOPR)

Field Water Production Rate (FWPR)

Field Water Injection Rate (FWIR)

Figure 144 FOPT,FGPT, FWPT, FWIT Vs Date

Figure 145FGPR, FOPR, FWPR, FWIR Vs Date

CHAPTER 4

187

3- Originally In Place Calculations

Eclipse provide report for each year till depletion in the previous report

show that:-

Original Oil In Place 204.653154 MMSTB

Original Water In Place 215.737127 MMSTB

Original Gas In Place 43664.797 MMSCF

Prediction

Figure 146 In place calculation

CHAPTER 4

188

Recommendation

Final Recovery factor can be increase by increasing number of

produced wells or increase the injection rate .

New produced well in marine zone at cell (9,2)

Result recovery factor = .68

Increasing number of produced wells in highly oil saturation cells

and thick formation will be economically and increasing the

recovery factor and have the optimum production

Cell(9,2) New produced well

3

0.63

4

.68

0 1 2 3 4 5

no. of wells

RF

Series2

Series1

Figure 147 New Well

Figure 148 Comparison no. of wells

CHAPTER 4

189

RF With and Without Injection

The following chart shows the importsance of the water injection in

the reservoir to increase the recovery factor.

So By increasing the injection wells the production increase

0

10

20

30

40

50

60

70

1

RF

%

Wiyhout inj.

With inj.

Figure 149 Comparison Inj. Wells

CHAPTER 4

190

Conclusion

Based on the case study and the previous explanation, the following can

be concluded:

MBE by Excel calculations must be used to know the reservoir type and

primary reserve estimate.

Monte Carlo simulation (probabilistic approach) proved to be more

successful in estimating IOIP as it gives all the possible values based on

the data available (P10, P50, P90).

MBAL Material Balance Tool can be used to confirm the IOIP from

Monte Carlo and can also be used to determine the reservoir driving

mechanism.

ECLIPSE Simulation very useful for model the reservoir , shows the

whole parameters of the reservoir with time changing , predict the

reservoir behavior with changing conditions .

The summary of IOIP and RF results of the case study can be

summarized as follows.

Table 50 Conclusion

MBE

Calculation Montecalo

MBE MBAL

ECLIPSE

OOIP 205.6 209 205.3 204 RF% @ 2035

.69 Not applicaple

.47 .65

REFERENCES

191

REFERENCES

1- The Petroleum Society of CIM, Determination of Oil and Gas Reserves,

Canada,1994.

2- Repsol YPF, Reserves Reporting System, Louisiana, 2005.

3- Arps,J.J, 1945, Analysis of Decline Curves, Trans. AIME

4- Arps,J.J, 1956, Estimation of primary oil reserves, Trans. AIME

5- Ahmed, Tarek. Reservoir Engineering Handbook. Amsterdam , Elsevier,

GPP, 2006.Print.

6- Reservoir Issue 1, part of Reservoir Engineering for Geologists, Fekete,

February 2008

7- Schilthius,R., Solution-Gas-Drive Reservoirs, Trans. AIME, 1936, Vol.118.

8- Clark, N., Elements of Petroleum Reservoirs. Dallas, TX:SPE, 1969.

9- Cole, F., Reservoir Engineering Manual, Houston, TX: Gulf Publishing Co.,

1969.

10- Havlena, D., and Odeh, A. S., “The Material Balance as an Equation of a

Straight.

Line,” JPT, August 1963,

11- Havlena, D., and Odeh, A. S., “The Material Balance as an Equation of a

Straight Line, Part II—Field Cases,” JPT, July 1963.

12- Dake, L., The Practice of Reservoir Engineering, Amsterdam: Elsevier. 1994.

13- Dake, L. P., Fundamentals of Reservoir Engineering. Amsterdam: Elsevier.

1978.

14- Van Everdingen, A., and Hurst, W., “The Application of the Laplace

Transformation to Flow Problems in Reservoirs,” Trans. AIME, 1949.

15- B.C.Craft, Applied Petroleum Reservoir Engineering,2nd

edition ,1991.

16- James J. Sheng,Ph.D.,Modern Chemical Enhanced Oil Recovery Theory

and Practices, Elsevier, GPP,2010, Print

17- Sara Thomas , Chemical EOR-The Past, Does It Have A Future , SPE

Distinguished Lecturer Series ,2005.

18- George S. Monte Carlo: Concepts, Algorithms, and Applications. New

York, Springer, 2008. Print

19- Metropolis, N. and Ulam, S., “The Monte Carlo Method” J. Amer. Stat.

Assoc., 1949.

20- “Petroleum Reserves Definitions” published by SPE, 1964.

REFERENCES

192

21- Schlumberger ,Simulation Software Manuals , Eclipse , 2005.

22- Petroleum Expert, MBAL Explanation, www.petex.com/products/?ssi=4

23- Islam Amged Nassar , Reservoir Project , BUE, 2010

24- Petroleum Experts, Reservoir Analytical Simulation , MBAL, version 7 ,

2003.

http://www.petex.com/products/?ssi=4

Documents

Reservoir Senior Project 2012