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Prosper
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PROSPER WELL MODELLING FUNDAMENTALS
PREPARED BY Ahmed mohamed Abdullah Refaat Galal Abol Fotoh Nader Ali Fahim Hesham Ahmed Abo-zaid Yahia Ali Shawky
CONTENTS
Introduction Well Modelling Fundamentals Setting up a well model PVT Modelling IPR modelling VLP modelling VLP / IPR matching and model validation Conclusions
PETEX (PETROLEUM EXPERTS)
Started business @ 1990 in the UK
Developing a set of petroleum engineering
software tools.
model oil reservoirs, production and injection
wells and surface pipeline networks as an
integrated production system.
SOFTWARE PACKAGES
IPM PACKAGE
The engineer is able to design complex field models.
The Reservoir, Wells and Complete Surface Systems model, having been matched for production history, will accurately optimize the entire network and run predictions.
IPM PACKAGE
IPM PACKAGE GAP enables the engineer to build
representative field models, that include the reservoirs, wells and surface pipeline production and injection system.
MBAL package contains the classical reservoir engineering tool, using analytical techniques to analyze the fluid dynamics in the reservoir.
IPM PACKAGE PVTP allows tuning of Equations of State
(EoS) to match laboratory data. The tuned EoS can then be used to simulate a range of reservoir and production processes, which impact equipment sizing and reservoir recovery.
REVEAL is a specialized reservoir simulator modeling near well bore effects including mobility and infectivity issues. Thermal and chemical effects are modeled rigorously.
PROSPER
PROSPER is designed to allow the building of reliable and consistent well models
Design and optimize well completion Tubing size Artificial lift method IPR model
CONTENTS
Introduction Well Modelling Fundamentals Setting up a well model IPR modelling VLP modelling VLP / IPR matching and model validation Conclusions
WELL MODELLING FUNDAMENTALS
Well modelling defines the pressure/rate relationship to facilitate: Well design Predicting well performance Identify well performance sensitivity to changes in operating
parameters or design Involves:
PVT Wellbore IPR Nodal Analysis
Well Modelling Fundamentals
Nodal Analysis It is the methodology used in well modelling to analyse
the performance of a multi-component system Objectives are to:
Quantify total pressure loss as a function of rate Quantify components within total pressure loss Identify bottlenecks to flow Optimise system design and operation given constraint Address specific well issues such as Artificial lift, well load
up, completion design optimisation and productivity improvement opportunities.
Important: Nodal analysis assumes a steady state and does not allow transient flow behaviour.
Well Modelling Fundamentals
Common Nodes used in Nodal Analysis
Well Modelling Fundamentals
Fundamental Concept
P P
P ? OUTFLOWINFLOW
Solution node
• Pressure defined at start and end nodes
• Solution node can be any intermediate position where pressure must be calculated
• Components upstream of solution node determine INFLOW performance
• Components downstream of solution node determine OUTFLOW performance
• For system continuity Qin = Qout and pressures must be equal
• From above, system can be solved to determine solution node pressure at a given rate
Qin Qout
Well Modelling Fundamentals
Top Node Bottom Node Solution Node Comments
Wellhead Reservoir Mid-perf Separates IPR from VLP
Wellhead Reservoir ESP, GL, etc To establish artifical lift reqirements
WH Choke Gauge Depth Wellhead To match given test data
Separator Reservoir Wellhead Separates well-reservoir from surface
Separator Reservoir Choke Combines choke effect with well-reservoir
Separator Wellhead ManifoldConcentrating on Network modelling with known contribution from well(s)
CONTENTS Introduction Well Modelling Fundamentals Setting up a well model PVT modelling IPR modelling VLP modelling VLP / IPR matching and model validation Conclusions
SETTING UP A WELL MODEL
What information do you need? Completion diagram / tally and directional survey
data, together with any recent work-over info/data Fluid data (PVT reports or existing PVT model) Complete production test data (recent as well
historical sets) comprising of rates, phase ratios, end pressures, etc.
Reservoir and available near-wellbore data (reservoir pressure & temperature, FBHP/downhole gage pressure, PI, skin, permeability and rel perm, etc).
Well Modelling Fundamentals
Surface choke
Sales LineGas
SeparatorLiquid
StockTank
To Sales
Bottom holerestriction
Psep
P5 = (Pwh - PDSC)
PDSC
P6 = (PDSC - Psep)
P8 = (Pwh - Psep)
Pwh
PDSV
PUSV
PDR
PUR
Pwf Pwfs Pr Pe
P3 =(PUR - PDR)
P7 = (Pwf - Pwh)
P4 = (PUSV - PDSV)
P2 = (Pwfs - Pwf) P1 = (Pr - Pwfs)
P9 = (Pr - Pwf)
P8 = Pwh - Psep
P6 = PDSC - Psep
P5 = Pwh - PDSV
P4 = PUSV - PDSV
P7 = Pwf - Pwh
P3 = PUR - PDR
P2 = Pwfs - Pwf
P9 = Pr - Pwf
P1 = Pr - Pwfs = Loss in porous medium= Loss across completion= Loss across restriction= Loss across safety valve= Loss across surface choke= Loss in flowline= Total loss in tubing= Total loss in flowline= Total loss in reservoir / completion
Surface choke
Sales LineGas
SeparatorLiquid
StockTank
To Sales
Bottom holerestriction
Psep
P5 = (Pwh - PDSC)
PDSC
P6 = (PDSC - Psep)
P8 = (Pwh - Psep)
Pwh
PDSV
PUSV
PDR
PUR
Pwf Pwfs Pr Pe
P3 =(PUR - PDR)
P7 = (Pwf - Pwh)
P4 = (PUSV - PDSV)
P2 = (Pwfs - Pwf) P1 = (Pr - Pwfs)
P9 = (Pr - Pwf)
P8 = Pwh - Psep
P6 = PDSC - Psep
P5 = Pwh - PDSV
P4 = PUSV - PDSV
P7 = Pwf - Pwh
P3 = PUR - PDR
P2 = Pwfs - Pwf
P9 = Pr - Pwf
P1 = Pr - Pwfs = Loss in porous medium= Loss across completion= Loss across restriction= Loss across safety valve= Loss across surface choke= Loss in flowline= Total loss in tubing= Total loss in flowline= Total loss in reservoir / completion
P8 = Pwh - Psep
P6 = PDSC - Psep
P5 = Pwh - PDSV
P4 = PUSV - PDSV
P7 = Pwf - Pwh
P3 = PUR - PDR
P2 = Pwfs - Pwf
P9 = Pr - Pwf P9 = Pr - Pwf
P1 = Pr - Pwfs = Loss in porous medium= Loss across completion= Loss across restriction= Loss across safety valve= Loss across surface choke= Loss in flowline= Total loss in tubing= Total loss in flowline= Total loss in reservoir / completion
Sources of pressure loss in a production system
SETTING UP A WELL MODEL
Pre-processing data Completion data consistent with directional
survey and other work-over info. Fluid data/PVT model consistent with other wells
and formation info. Production test data complete and consistent
with current well performance. Reservoir data dates consistent with the
production test dates.
SETTING UP A WELL MODELSystem Summary Screen
Can model up to5 stages for compmodelling
Select 1. tubing or 2. annular or 3. tubing AND annular
Information only
Useful repository for well test and model information
Reservoir connection options –
influence later inflow options
Specify whether a single well or
multilateral
Specify type of temperature modelling
Define fluid type and PVT method (i.e. black oil or equation of state model)
PVT Property
(Pb) Bubble-point
Pressure (psia)
(Bo) Bubble-Point
Oil FVF (rb/stb)
(GOR or Rs) Gas/Oil
Ratio (scf/stb)
Reservoir
Temperature (ºF)
Stock Tank Oil
Gravity (ºAPI)
Gas Specific Gravity
(air = 1)
Separator Pressure
(psia)
Separator
Temperature (ºF)
PVT Property
(Pb) Bubble-point
Pressure (psia)
(Bo) Bubble-Point
Oil FVF (rb/stb)
(GOR or Rs) Gas/Oil
Ratio (scf/stb)
Reservoir
Temperature (ºF)
Stock Tank Oil
Gravity (ºAPI)
Gas Specific Gravity
(air = 1)
Separator Pressure
(psia)
Separator
Temperature (ºF)
Standing
130 – 7000
1.024 – 2.15
20 – 1425
100 – 258
16.5 – 63.8
0.59 – 0.95
265 – 465
100
Standing
130 – 7000
1.024 – 2.15
20 – 1425
100 – 258
16.5 – 63.8
0.59 – 0.95
265 – 465
100
Lasater
48 – 5780
N/A
3 – 2905
82 – 272
17.9 – 51.1
0.574 – 1.22
15 – 605
36 - 106
Lasater
48 – 5780
N/A
3 – 2905
82 – 272
17.9 – 51.1
0.574 – 1.22
15 – 605
36 - 106
Vazquez-
Beggs
15 – 6055
1.028 – 2.226
0.0 – 2199
75 – 294
15.3 – 59.5
0.511 – 1.351
60 – 565
76 – 150
Vazquez-
Beggs
15 – 6055
1.028 – 2.226
0.0 – 2199
75 – 294
15.3 – 59.5
0.511 – 1.351
60 – 565
76 – 150
GlasØ
165 – 7142
1.087 – 2.588
90 – 2637
80 – 280
22.3 – 48.1
0.65 – 1.276
415
125
GlasØ
165 – 7142
1.087 – 2.588
90 – 2637
80 – 280
22.3 – 48.1
0.65 – 1.276
415
125
Petrosky-
Farshad
1574 – 6523
1.1178 – 1.622
217 – 1406
114 – 288
16.3 – 45.0
0.5781 – 0.85
N/A
N/A
Petrosky-
Farshad
1574 – 6523
1.1178 – 1.622
217 – 1406
114 – 288
16.3 – 45.0
0.5781 – 0.85
N/A
N/A
Macary
1200 – 4600
1.2 – 2.0
200 – 1200
180 – 290
25 – 40
0.7 – 1.0
N/A
N/A
Macary
1200 – 4600
1.2 – 2.0
200 – 1200
180 – 290
25 – 40
0.7 – 1.0
N/A
N/A
Black Oil Correlations can be selected based on the applicability of the test range of the data in question:
Setting up a well model
CONTENTS Introduction PVT Fundamentals Well Modelling Fundamentals Setting up a well model PVT Modelling IPR modelling VLP modelling VLP / IPR matching and model validation Conclusions
SETTING UP A WELL MODEL
PVT Model Tuning
Select PVT correlations relevant to the given fluids.
If PVT matching data absent or sparse use correlation which has proved appropriate in offset wells / fields
Use corrected PVT data to tune the selected PVT correlations
SETTING UP A WELL MODELPVT Summary
• PVT modelling involves:
– Gathering quality test data
– Convert Diff Lib data to flash conditions if required (correction)
– Selecting appropriate correlation/EoS.
– Tuning selected correlation/EoS.
– Generating PVT properties at all pressure-temperature combinations encountered in flow stream.
• There is no substitute for quality test data.
• Incorrect PVT model has detrimental effect on IAM modelling, which is quite often incorrectly accounted for by adjusting flow correlations.
• Note that in gas condensate wells, inaccurate temperature modelling can have a profound effect on PVT – often neglected
STEP 1: BASIC PVT DATA INPUT
Basic Data Input from PVT report, DST testing (may sometimes be all that is available)
Setting up a well model
SETTING UP A WELL MODEL
Match Data input from PVT report – use only flash corrected data. Normally enter as much data as possible to optimise correlation matching
Step 2: PVT Match Data Input
STEP 3: MATCHING PVT CORRELATIONS TO REAL PVT DATA
PVT correlations are empirically derived mathematical fits of real experimental data Correlations approximate real fluid behaviour – some more suitable than other for
certain fluid systems Matching is a regression process which reduces the error between correlation and PVT
data User can specify which gas properties it is critical to match (to reflect possible
uncertainty in input data accuracy Parameter 1 and 2 statistics provide match quality and correlation predictive reliability –
Parameter 1 is the “multiplier” which has to be applied to correlation (should be within 10% of unity)
Parameter 2 is the shift
Setting up a well model
SETTING UP A WELL MODELEntering a physical description of the well and its subsurface environment
Enter up to 18 depth pairs (measured & TVD)
Include effect of any pipework from wellhead to manifold (incl choke)
ID / OD and roughness of all tubing and casing, restrictions etc down to the reservoir. Mid-perf depth is bottom depth entered.
Input formation temperatures versus depth, and overall Heat Transfer coefficient (“U” value)
Enter specific heats for oil, water and gas – use default Values In this example
SETTING UP A WELL MODEL
Only enter minimum number of points required to describe basic shape of wellpath
Tip: normally use survey points giving >5% change in inclination
Entering Deviation Survey Data
SETTING UP A WELL MODEL
Manifold (or other constant pressure
node in system)
Surface equipment
NB:
• Enter UPSTREAM end TVDs for each section of pipe (i.e. nearest the tree for producers)
• Use “Plot” to visualise pipework layout and check for errors
• Can use an “X-Y” coordinate system if required to enter more detailed pipework desciption (applicable to subsea)
Entering the Surface Equipment Description
SETTING UP A WELL MODEL
Notes:
• Typically use drilling depth references i.e. relative to rotary table - e.g. in a subsea well Xmas tree depth may be +400 ft• Enter bottom depth of each section of same diameter tubing, associated ID and roughness• Enter SSSV’s and restrictions• Casing depth where you wish pressure loss calculations to begin (typically mid perf).
• In a long perforated interval may be better to use more complex inflow model
Downhole Equipment DescriptionRoughness Guidelines
Plastic .0002 inCr Steel .0006 inSS .0006 inC Steel New .0018 in to Old .0060 in
SETTING UP A WELL MODEL
Notes:
• Enter a temperatures survey obtained from STATIC logging, or best offset data• Ensure a survey point for the bottom node in the equipment data is included.
Geothermal Gradient calculations enable Prosper to predict flowing wellbore temperatures from reservoir to wellhead under various scenarios, based upon an Overall Heat Transfer Coefficient or U value.
Typical Values are: Oil wells 8 BTU/h/ft2/FGas wells 3 BTU/h/ft2/FGas Cond wells 3.7 BTU/h/ft2/F
Geothermal Gradient
CONTENTS Introduction PVT Fundamentals Well Modelling Fundamentals Setting up a well model IPR modelling VLP modelling VLP / IPR matching and model validation Conclusions
IPR MODELLING Fundamental Input information:
Reservoir Pressure & temperature At least one stable flowing BHP and rate (ensure
reservoir pressure consistent in time with FBHP if varying)
GOR (oil well) / CGR (gas well) Watercut (oil well) / WGR (gas well)
Theoretical vs empirical IPR models Reservoir / Completion parameters:
Rock permeability & anisotropy Producing interval, perforations, deviation &
drainage area Gravel Pack properties & dimensions
IPR MODELLING
The Inflow Performance Relationship (IPR) defines the pressure drawdown in a well as a function of production rate
Drawdown is a complex function of PVT, permeability (absolute & relative), effective overburder etc
Several IPR model available – optimum choice depends on data available and calculations required including:-
Gas Well PI Models
• Jones ~ includes a linear (Darcy) pressure drop and a rate-squared (non-Darcy) term. Uses pseudopressure, better for high reservoir pressures (>2000 psi)
• Backpressure,
• Forcheimer,
• C and N ~ use various “backpressure” equations to describe the Darcy and non-Darcy inflow behaviour
• Petroleum Experts ~ uses a multi-phase pseudo pressure function to allow for changing gas and condensate saturations with pressure – applicable to gas condensate modelling or dry gas
IPR Fundamentals
IPR MODELLING
Oil Well PI Models
• PI entry ~ simplest, useful where no where no reservoir perm or skin data available, and where the PI is already known
• Vogel ~ uses an empirical correlation to account for deviation from straight line PI below bubble point
• Composite ~ interpolates a Vogel IPR for oil and straight line IPR for oil as a function of watercut – useful for sensitivities on increasing watercut
• Darcy ~ classic radial flow equation useful for estimating productivity from petrophysical data
• Fetkovich ~ adapted from isochronal theory – gives similar results to Vogel
IPR MODELLING
Options will dependon fluid type selectedin System Summary
Skin model definition
Select the “Jones” model (modified form of Darcy Equation)
Defining IPR model to be used:
IPR MODELLING
Enter data in all sheets with highlighted tabs (working left to right)
Entering IPR data
IPR MODELLING
When data entry complete, click on “Calculate” button to generate IPR plot
Entering IPR data
IPR MODELLING
AOF: Absolute Open Hole Flow Potential(theoretical flow potential assuming zeroBackpressure)
Static reservoir pressure
Flowing bottom hole pressure (FBHP)
IPR curve – gas well
CONTENTS Introduction PVT Fundamentals Well Modelling Fundamentals Setting up a well model IPR modelling VLP modelling VLP / IPR matching and model validation Conclusions
VLP MODELLINGFlow Patterns/Regimes in Vertical Upward Flow
BUBBLYFLOW
SLUGFLOW
CHURNFLOW
ANNULARFLOW
BUBBLYFLOW
SLUGFLOW
CHURNFLOW
ANNULARFLOW
COMMON FLOW REGIME IN GAS / GAS CONDENSATE WELLS
ROLE OF MULTI-PHASE FLOW CORRELATIONS
• VLP correlations predict the pressure loss in pipe, allowing for the gravity, friction and acceleration effects
• Correlations handle Slip, holdup and multiphase flow pattern in different ways e.g. slip, flow regime accounted for / not accounted for
• Correlations using flow maps may give discontinuous results – modern mechanistic correlations overcome this.
• No single correlation is “best”, and comparison of the correlations is recommended to select the the optimum one for a given application
VLP Modelling
VLP MODELLING
Author Year Data Source Nominal ID Fluids & Rates CommentDuns & Ros Original 1961 185' high experimental loop+field
data1.26" to 5.6" with 2 annulus config.
Air, water & liquid hydrocarbon
Good over a wide range, more so for mist flows, tend to overpredict VLP in oil wells
Duns & Ros Modified
Francher & Brown 1963 Field data from plastic coated tubing 1.995 ID Gas and water at < 400stb/d & GOR
>5000
Being no-slip always predicts lowest pressure drops therefore good for data QC
Hagedorn & Brown 1965 475 test data sets from 1500' deep vertical experimental well
1" to 2.5" Air, water & crude oils of 10, 30 & 110cp
Most widely used VLP correlation - good over a wider range particularly for slug flows
Petroleum Experts ? Uses the Gould et al flow map, Hagedorn & Brown for slug, Duns
and Ros for mist
Generally obsolete
Petroleum Experts 2 ? Improved version of PE1, better for preditcing low rate VLP
Petroleum Experts 3 ? Include PE2 featues with additional features for viscous, volatile and
foamy oils
Preferred for gassy, foamy heavy oils
Petroleum Experts 4 ? Advanced mechanistic model suitable for any fluid (including
condensates)
Good all round correlation, avoids discontinuities which apply to empirical correlations, runs slower than empirical
Orkiszewiski 1967 Huge set of field data various! various! 'Hybrid' model of different 'best' correlations. Hence found discontinuous! Use not
encouraged!Beggs & Brill 1973 90' long acrylic pipe with ±90
inclination changes. 584 measure tests with flow pattern observations.
1" to 1.5" Air & water Better for all angles. Mukherjee & Brill attempted to improve it in 1985
GRE BP Mechanistic Correlation Developed to model slug flow in pipelines but also found to be applicable to tubing
Gray 1978 108 well test data with 88 producing free liquids
3.5" Condensate up to 50b/MM & water up to 5b/MM with velocities
up to 50ft/s
Excellent for gas and gas-condensate wells but should be used with caution for higher
WGR/CGR
Multiphase Flow Correlations available in Prosper
Correlations suitable for gas wells
CONTENTS
Introduction PVT Fundamentals Well Modelling Fundamentals Setting up a well model IPR modelling VLP modelling VLP / IPR matching and model validation Conclusions
CONTENTS
Introduction PVT Fundamentals Well Modelling Fundamentals Setting up a well model IPR modelling VLP modelling VLP / IPR matching and model validation Conclusions
THANK YOU