GEO4270 – EXERCISE 2
PROSPECT EVALUATION
GEO4270GEO4270Integrated Basin Analysis and Prospect Evaluation
1. Integrated Seismic (reflection/refraction), Gravity and Magnetics and Basin Modelling
– Large Scale Structures of the BasinDeeper Parts of the Basin– Deeper Parts of the Basin
– Tectonic Development of the Basin– Maturation of Hydrocarbons
2. Prospect Evaluation
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GEO4270GEO4270Prospect Evaluation
Horda Platform:Tampen Spur:
Gullfaks; Snorre; Statfjord
Migration
Horda Platform:Troll, Oseberg
Gullfaks; Snorre; Statfjord,Visund, Tordis
Mature HC
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GEO4270GEO4270Prospect Evaluation
Prospect, n. An examination or test of the mineral richness of a locality or of the material from whichrichness of a locality or of the material from which
the ore, etc. is extractedOED IV 10 Mining bOED, IV. 10. Mining b.
Evaluation, The action of evaluating or determining the value of (a mathematical expression, a physical quantity, etc.), or of estimating the force of
(e.g. probabilities, evidence)OED, 2.
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GEO4270GEO4270Course Contents
• Introduction• PETREL™ Introduction Course• Exercise: Statfjord Field
D t l di– Data loading– Interpretation– Reservoir Modelling and Prospect Evaluation– Report
• Follow up meetings• Lecture on Geostatistical Reservoir Modeling• Lecture on Geostatistical Reservoir Modeling
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GEO4270GEO4270Prospect Evaluation – Exercise Data
• Offshore Norway – Northern North Sea• What will we be using during the project:
– Seismic data• 2D• 3D3D
– Well data• Formation Tops
G h i l ll l• Geophysical well logs
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WELL LOGGING / CORRELATION
ResistivityResistivityPorositySP
GEO4250
Short summary
GEO4270 – Well Logging / CorrelationGEO4270 Well Logging / CorrelationFormation Evaluation
Formation evaluation, the process of using borehole measurements to evaluate the characteristics of subsurface
formations.
H l d D P 1983 F d t l f F ti E l tiHelander, D.P., 1983. Fundamentals of Formation Evaluation
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GEO4270 – Well Logging / Correlation GEO4270 Well Logging / Correlation Formation Evaluation – Objectives
• Identification of the reservoir (primary)• Estimating hydrocarbons in place (primary)• Estimating hydrocarbons in place (primary)• Reservoir properties
– Shape– Thickness– Thickness– Porosity and permeability– Lithology
• Well-to-well correlation• Formation dip• Surface seismic well tie• A few more additional related to HC productionA few more additional related to HC production
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GEO4270 – Well Logging /CorrelationGEO4270 Well Logging /CorrelationHydrocarbons in Place
oiSAhN φ7758 N = initial oil in place (stb)A = drainage area (acres)
oi
oi
BN = h = productive interval thickness (ft)
φ = effective porosity (fraction)Soi = initial oil saturation (fraction)
oi
BSAhG φ560,43
=Boi = initial oil formation volume factor (reservoir bbl/stb)G = initial gas in place (scf)
giB Sgi = initial gas saturation (fraction)Bgi = initial gas formation volume factor (ft3/scf)
Oil formation volume factor: Oil and dissolved gas volume at reservoir conditions divided by oil volume at standard conditions.
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Gas formation volume factor: Gas volume at reservoir conditions divided by gas volume at standard conditions.
GEO4270 – Well Logging / CorrelationGEO4270 Well Logging / CorrelationHydrocarbon Reserves
N = Oil Reserves (stb)
hArSN φ=Np = Oil Reserves (stb)φe = effective porosity (fraction)So = Oil saturation (fraction)hArSN oep φ= h = productive interval thickness (ft)A = drainage area (acres)r = Recovery Factorr Recovery Factor
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GEO4270 – Well Logging / CorrelationGEO4270 Well Logging / CorrelationImportant Parameters
Saturation (S), n. [Formation Evaluation]The relative amount of water, oil and gas in the pores of a rock, usually as a percentage of volume The pore space that does not contain as a percentage of volume. The pore space that does not contain formation water is assumed to contain hydrocarbons. Mathematically this can be expressed as:
Shc = 1 – Sw
Where Shc = hydrocarbon saturationSw = water saturation
If Sw is low, the formation is potentially productive
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GEO4270 – Well Logging / CorrelationGEO4270 Well Logging / CorrelationImportant Parameters
Porosity (φ), n. [Geology]The percentage of pore volume or void space, or that volume within rock that can contain fluids.
– Total Porosity (φt): The total pore volume per unit volume of rock
– Effective Porosity (φe): The interconnected pore volume or void space in a rock that contributes to fluid flow or permeability in a reservoirpermeability in a reservoir
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GEO4270 – Well Logging / CorrelationGEO4270 Well Logging / CorrelationImportant Parameters
Permeability (k), n. [Geology]The ability, or measurement of a rock's ability, to transmit fluids.
Permeability is required to calculate the flow rate at which hydrocarbons can be produced, following Darcy’ law:
dpkdxpu
μ−=
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Permeability will not be addressed in the course
How can we measure these parameters?
GEO4270 – Well Logging / CorrelationGEO4270 Well Logging / CorrelationWater Saturation
Water saturation can be measured with the help of:Resistivity (R), n. [Formation Evaluation]The ability of a material to resist electrical conduction. It is the inverse of conductivity and is measured in ohmm The inverse of conductivity and is measured in ohmm. The resistivity is a property of the material, whereas the resistance also depends on the volume measured. p
!! Hydrocarbons are resistive while formation water is conductive !!
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GEO4270 – Well Logging / CorrelationGEO4270 Well Logging / CorrelationWater Saturation
• The Resistivity of a formation is dependent on:– Presence of Formation water / Hydrocarbons– Salinity of Formation water– Temperature of Formation water– Volume of water-saturated pore spacep p– Geometry of the pore space– Morphology and species of clay mineralsp gy p y
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GEO4270 – Well Logging / CorrelationGEO4270 Well Logging / CorrelationWater Saturation
• Archie’s equation (Archie, G.E., 1942)
Relation between Water Saturation and Resistivity
q ( , , )• Sw = Water saturation• F = Formation Resistivity Factor (a/φm):
ow RFRS ==
y ( φ )• Porosity (φ)• Tortuosity factor (a)
ttw RR
S ==• Cementation factor (m)
• Rw = Resistivity of the formation water• Rt = Resistivity of a rock with HC, i.e.
true resistivity• R = Resistivity of the 100% water-
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Ro Resistivity of the 100% watersaturated rock
GEO4270 – Well Logging / CorrelationGEO4270 Well Logging / CorrelationPorosity
• Direct measurements– Conventional coring– Sidewall coring
• Indirect Measurements– Sonic Logg– Density Log– Neutron Logg
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GEO4270 – Well Logging / CorrelationGEO4270 Well Logging / CorrelationPorosity
Sonic Log, n. [Geophysics]A type of acoustic log that displays traveltime of P-waves versus depth (recorded in interval transit time (Δt), μs/ft, which is the reciprocal of velocity) Sonic logs are typically recorded by pulling a tool on a wireline up velocity). Sonic logs are typically recorded by pulling a tool on a wireline up the wellbore. The tool emits a sound wave that travels from the source to the formation and back to a receiver.L b l DTLog symbol: DT
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GEO4270 – Well Logging / CorrelationGEO4270 Well Logging / CorrelationPorosity
• Dependent on lithology and porosity• Sonic porosity derived by:
T tt 1l ⎟⎞
⎜⎛ Δ−Δ
φsonic = sonic derived porosity
TCptt
tt
matrixf
matrixsonic
1log ×⎟⎟⎠
⎞⎜⎜⎝
⎛
Δ−Δ
ΔΔ=φ
Δtmatrix = interval transit time of the matrix (table)Δtlog = interval transit time of the formationΔtf = interval transit time of the fluid in the wellbore (fresh mud = 189; salt mud = 185)Cp = compaction factor =
R1 p p
with:
R2 100Ctsh ×Δ
with:– Δtsh = interval transit time for adjacent shale– C = a constant, normally 1.0
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GEO4270 – Well Logging / CorrelationGEO4270 Well Logging / CorrelationPorosity
Density Log, n. [Formation Evaluation]A well log that records formation density. The logging tool consists of a gamma-ray source (e.g., Cs137) and a detector shielded from the source so that it records backscattered gamma rays from the formation (Compton
i ) Th b k i d d h l d i f h scattering). The backscattering depends on the electron density of the formation, which is roughly proportional to the bulk density.Log symbol: RHOB, DEN
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GEO4270 – Well Logging / CorrelationGEO4270 Well Logging / CorrelationPorosity
Density Log1. Identify evaporite minerals2. Detect gas-bearing zones3. Determine hydrocarbon
density4. Evaluate shaly sand reservoirs
and complex lithologies
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GEO4270 – Well Logging / CorrelationGEO4270 Well Logging / CorrelationPorosity
• DRHO is a correction curve, if DRHO > 0.20 gm/cc the RHOB curve is invalid
• RHOB (formation bulk density) is a function of matrix density, porosity and density of the fluids in the pores, th ftherefore:
bmatrix ρρφ −=
fmatrixden ρρφ
−=
with:φden = density derived porosityρmatrix = matrix density (table)
f ti b lk d itρb = formation bulk densityρf = fluid density
L b l DPHI
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DRHO = 0.20 Log symbol: DPHI
GEO4270 – Well Logging / CorrelationGEO4270 Well Logging / CorrelationPorosity
Neutron Porosity, adj. [Formation Evaluation]Referring to a log of porosity based on the effect of the formation on fast neutrons emittedby a source Hydrogen has by far the biggest effect in slowing down and capturingby a source. Hydrogen has by far the biggest effect in slowing down and capturingneutrons. Since hydrogen is found mainly in the pore fluids, the neutron porosity logresponds principally to porosity. However, the matrix and the type of fluid also have aneffect.S l d i i l t li t it it i l NPHI l t li tScaled in equivalent limestone porosity units, i.e. low NPHI values represent limestoneLog symbol: NPHI, CN
H d i t h d b d h l NOT i t f ld d Hydrogen in pore water, hydrocarbons and shales NOT in quartz, feldspars and carbonates
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GEO4270 – Well Logging / CorrelationGEO4270 Well Logging / CorrelationCorrelation Logs
Gamma Ray Log• A well log of the natural
formation radioactivity level• The log mainly reflects clay
content because clay t i th di ti contains the radioactive
isotopes of K, U and Th• Often used in association • Often used in association
with the SP-log
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GEO4270 – Well Logging / CorrelationGEO4270 Well Logging / CorrelationCorrelation Logs
Spontaneous Potential Log• A record of Direct Current (DC)
voltage (or Potential) that develops naturally (spontaneous) between a naturally (spontaneous) between a moveable electrode in the well and a fixed electrode located at the surfacesurface
• Used to– Correlation– Detect permeable beds– Detect permeable beds– Detect boundaries of permeable beds– Determine formation-water resistivity (Rw)– Determine the volume of shale in permeable
b dbeds– Detection of hydrocarbons by the suppression of
the SP curve• Often used in association with the
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Often used in association with the GR-log
SEISMIC INTERPRETATION
Reservoir IdentificationSeismic Attributes
GEO4240
Sh t Short summary
GEO4270 – Seismic InterpretationGEO4270 Seismic InterpretationReservoir Identification
• Phase• Polarity• Amplitude
Seismic characteristics• Spatial Extent• Frequency
V l it
Seismic characteristicshelping to identify HC
• Velocity• AVO• Shear wave• Shear wave
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GEO4270 – Seismic InterpretationGEO4270 Seismic InterpretationReservoir Identification
Identify Phase and PolarityMinimum Phase
Identify Phase and Polarity
RC+ RC-
Normal Polarity Reverse PolarityZero Phase
Normal Polarity Reverse Polarity
RC+ RC-
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GEO4270 – Seismic InterpretationGEO4270 Seismic InterpretationReservoir Identification
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GEO4270 – Seismic InterpretationGEO4270 Seismic InterpretationSeismic Attributes
• An attribute is a derivative of a basic seismic measurementAll th h i d f ti tt ib t il bl ( Fi 8• All the horizon and formation attributes available (see Fig. 8-1) are not independent of each other but simply different ways of presenting and studying a limited amount of basic
finformation• That basic information is time, amplitude, frequency and
attenuation and these form the basis of our attribute attenuation and these form the basis of our attribute classification
• Seismic attributes may be defined as “all the information obtained from seismic data either by direct measurements obtained from seismic data, either by direct measurements or by logical or experience based reasoning.” (Taner, 1998)
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GEO4270 – Seismic InterpretationGEO4270 Seismic InterpretationSeismic Attributes
• Time-derived attributes provide structural information• Amplitude derived attributes provide stratigraphic and reservoir • Amplitude-derived attributes provide stratigraphic and reservoir
information• Frequency-derived attributes are not yet well understood but there is
wide-spread optimism that they will provide additional useful wide spread optimism that they will provide additional useful stratigraphic and reservoir information
• Attenuation is not used today, but there is a possibility that in the future it will yield information on permeabilityy p y
• Most attributes are derived from the normal stacked and migrated data volume but variations of basic measurements as a function of angle of gincidence (and hence source to receiver offset) provides a further source of information. The principal examples of these pre-stack attributes is AVO
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GEO4270 – Seismic InterpretationGEO4270 Seismic InterpretationSeismic Attributes
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GEO4270 – Seismic InterpretationGEO4270 Seismic InterpretationSeismic Attributes
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GEO4270 – Seismic InterpretationGEO4270 Seismic InterpretationSeismic Attributes
• Time Slice!
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Property Modeling (or Reservoir Modeling)
”It is better to have a model of uncertainty th ill i f lit ”than an illusion of reality”
Andre Journel
GEO4270 – Property ModelingGEO4270 Property ModelingIntroduction
• Goal of Property modeling:– Capture geology and build realistic property models
• Goal of Reservoir modeling:– Predicting rock properties at unsampled locations and forecasting the future
flow behaviour of complex geological and engineering systems (Deutsch, flow behaviour of complex geological and engineering systems (Deutsch, 12002)
b f G t ti tiby use of Geostatistics
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GEO4270 – Property ModelingGEO4270 Property ModelingWhy create a realistic reservoir property model?
• We are making big decisions based on limited data• Maximize the usage of all information – optimise production• Correct upscaling of logs and a proper facies interpretation
is important• Reservoir properties are critical factors affecting production
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GEO4270 – Property ModelingGEO4270 Property ModelingGeostatistics
• Geostatistics is a branch of applied statistics that places h i emphasis on:
– The geological context of the data– The spatial relationship between the datap p– Data measured with different volumetric support and precision
B i N d k th b t ibl d i i i th f f Business Need: make the best possible decision in the face of uncertainty. Uncertainty exists because of our incomplete knowledge of a dataset (always incomplete data). One of g ( y p )the biggest uncertainties is the numerical description of the subsurface
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GEO4270 – Property ModelingGEO4270 Property ModelingExamples of Geostatistics
• Analysis of variables in space• Samples located close to each other are probably more
similar than samples located far from each other• The spatial coordinates of the observed samples are built
into the statistic formulas• Examples:
– Gold content in ore (ppm)– Reservoir sandstone porosity (%)– Reservoir sandstone porosity (%)– Reservoir sandstone bed thickness (meter/feet)
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GEO4270 – Property ModelingGEO4270 Property ModelingIncorporate the Maximum Amount of Data
Well data Seismic data Production Outcrops Other geological studies
Integrated study• Structure (horizon, fault)
Deterministicinformation
( , )• Stratigraphic correlation• Facies images• Framework
information
Sedimentological model HistogramStatistical
informationConceptualinformation
• Sedimentological model• Facies description• Connectivity
• Histogram• Variogram• Correlation• Trend• Variation
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GEO4270 – Property ModelingGEO4270 Property ModelingSequential Approach to Property Modeling
1. Defining the geometry and stratigraphic layering of the reservoir interval to be modeled– Involves the development of a conceptual model for the major architecture and continuity of
facies, porosity and permeability witihin each layer2. The facies rock types are modeled by either (1) cell-based or (2) object-based
techniques within each stratigraphic layertechniques within each stratigraphic layer3. The porosity is modeled on a by-facies basis before permeability because there
are more reliable porosity data available4. The 3-D models of permeability are constrained to the porosity, facies and
l i i l t bli h dlayering previously established5. Multiple equally likely realizations are created by repeating the entire process
― Each realization is ”equally likely to be drawn”; however, some realizations are more similar to others, hence their class has higher probability
6. These models are input to a simulator or visualized and used to aid in decision making
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Tampen Spur
Introduction
Tampen Spur
F
Tampen SpurLocation
B
H
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Statfjord FieldStatfjord FieldFacts
• Discovery well: 33/12-1• Discovery Year: 1974• Gullfaks producing since 24 11 1979• Gullfaks producing since 24.11.1979
– Total production of saleable products 04.2007: 633.786214 mill. Sm3 o.e.– Recoverable reserves:
• Oil: 13.60 mill Sm3Statfjord ProductionOil: 13.60 mill Sm
• Gas: 25.70 bill Sm3
• NGL: 11.40 mill tonne• Total number of wells: 282
Statfjord Production
35
40
45
50
Total number of wells: 282
10
15
20
25
30
Sm3
0
5
2006
2005
2004
2003
2002
2001
2000
1999
1998
1997
1996
1995
1994
1993
1992
1991
1990
1989
1988
1987
1986
1985
1984
1983
1982
1981
1980
1979
Year
Oil [mill Sm3] Gas [bill Sm3] Sm3o.e. [mill] Water [mill Sm3]
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NGL: Natural Gas Liquids, incl. propane, butane, pentane, hexane and heptane, but not methane and ethane1 tonne NGL: 1.9 Sm3 o.e.
Tampen SpurTampen SpurStratigraphy
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Tampen SpurTampen SpurCross Section
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GEO42 0 P E l iGEO4270 – Prospect Evaluation
• IMPORTANT!– PETREL™ is ”just” a tool which helps you with your interpretation and
modeling– This exercise is meant for leaning reservoir identification, reservoir s e e c se s ea o ea g ese o de ca o , ese o
evaluation and reservoir modeling
– The results depend completely on your own interpretationd th f th il bl d tand the accuracy of the available data
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I li kImportant links
• http://www.npd.no/English/Produkter+og+tjenester/Fakta+og+statistikk/fakta-start.htm (Norway Wells)
• http://www.og.dti.gov.uk/information/wells.htm (UK Wells)
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R fReferences
• Asquith, G. and Krygowski, D. (2004). Basic Well Log Analysis
• Brown, A. (2004). Interpretation of Three-Dimensional SSeismic Data
• Deutsch, C. (2002). Geostatistical Reservoir Modeling• Evans, D. et al. (2003). Millenium Atlas• Schlumberger (2006). Petrel Seismic to Simulation Software
P t M d li C 2005– Property Modeling Course, v.2005
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