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FWS 06 L 13 - Seismic AttributesCourtesy of ExxonMobil Lecture 13 Horizon A Horizon B Good Seal Good Reservoir W1 W2 W3 W5 W4 W6 W7 W8 W9.

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Presentation on theme: "FWS 06 L 13 - Seismic AttributesCourtesy of ExxonMobil Lecture 13 Horizon A Horizon B Good Seal Good Reservoir W1 W2 W3 W5 W4 W6 W7 W8 W9."— Presentation transcript:

1 FWS 06 L 13 - Seismic AttributesCourtesy of ExxonMobil Lecture 13 Horizon A Horizon B Good Seal Good Reservoir W1 W2 W3 W5 W4 W6 W7 W8 W9

2 FWS 06 L 13 - Seismic AttributesCourtesy of ExxonMobil Review causes of seismic response Modeling the seismic response What are seismic attributes? Overview of seismic attribute applications - Qualitative analyses Exercise: Mapping depositional environments - Quantitative analyses Exercise: Predicting average porosity Outline

3 FWS 06 L 13 - Seismic AttributesCourtesy of ExxonMobil Limestone Shale Seismic Response What causes a seismic response? 1.Changes in bulk-rock velocity or density Lithology (e.g., sandstone, shale, limestone, salt)

4 FWS 06 L 13 - Seismic AttributesCourtesy of ExxonMobil FastSlow Seismic Response What causes a seismic response? 1.Changes in bulk-rock velocity or density Porosity (e.g., intrinsic, compaction, diagenesis) Lithology (e.g., sandstone, shale, limestone, salt)

5 FWS 06 L 13 - Seismic AttributesCourtesy of ExxonMobil Seismic Response Mineralogy (e.g., calcite vs. dolomite, carbonaceous shales) What causes a seismic response? 1.Changes in bulk-rock velocity or density Porosity (e.g., intrinsic, compaction, diagenesis) Lithology (e.g., sandstone, shale, limestone, salt)

6 FWS 06 L 13 - Seismic AttributesCourtesy of ExxonMobil Fluid type and saturation (water, oil, gas) Pore FluidDensity Salt Water Fresh Water Oil Gas Pore FluidDensity Salt Water Fresh Water Oil Gas Sandstone with 30% Porosity: Seismic Response Mineralogy (e.g., calcite vs. dolomite, carbonaceous shales) What causes a seismic response? 1.Changes in bulk-rock velocity or density Porosity (e.g., intrinsic, compaction, diagenesis) Lithology (e.g., sandstone, shale, limestone, salt)

7 FWS 06 L 13 - Seismic AttributesCourtesy of ExxonMobil Modeling the seismic response: Determine bulk-rock velocity and density Calculate impedance (Recall: I = ρ x v) Represent impedance changes as reflection coefficient Convolve seismic wavelet to reflection coefficients I 2 - I 1 I 2 + I 1 RC= Seismic Modeling

8 FWS 06 L 13 - Seismic AttributesCourtesy of ExxonMobil The Convolution Method VelocityDensityImpedance Reflection Coefficients Wavelet Model Lithology = x * Shale Sand Shale Sand Shale

9 FWS 06 L 13 - Seismic AttributesCourtesy of ExxonMobil A wedge model is used to display the interactions of reflection coefficients as the thickness changesA wedge model is used to display the interactions of reflection coefficients as the thickness changes Note how themiddle peak changes amplitude, shape, and duration as the sand thins to the eastNote how themiddle peak changes amplitude, shape, and duration as the sand thins to the east WE Wedge Modeling Seismic Modeling

10 FWS 06 L 13 - Seismic AttributesCourtesy of ExxonMobil What are seismic attributes? Seismic attributes are mathematical descriptions of the shape or other characteristic of a seismic trace over specific time intervals. Definition

11 FWS 06 L 13 - Seismic AttributesCourtesy of ExxonMobil Why are seismic attributes important? Our increasing reliance on seismic data requires that we extract the most information available from the seismic response Seismic attributes enable interpreters to extract more information from the seismic data Applications include hydrocarbon play evaluation, prospect identification and risking, reservoir characterization, and well planning and field development Importance / Benefits

12 FWS 06 L 13 - Seismic AttributesCourtesy of ExxonMobil Classes of seismic attributes? Horizon (loop) Horizon A Peak amplitude Duration Symmetry Sample (volume, instantaneous) Amplitude Time Frequency Interval Average amplitude Maximum (Minimum) Duration Isochron Horizon B Single-Trace Types

13 FWS 06 L 13 - Seismic AttributesCourtesy of ExxonMobil Classes of seismic attributes? Multi-Trace - Dip / azimuth - Coherency Correlation Window Trace A Trace B Amplitude A Amplitude B R 2 = 0.92 Multi-Trace Types

14 FWS 06 L 13 - Seismic AttributesCourtesy of ExxonMobil Faults Stratigrahic features Dip map Multi-Trace Types

15 FWS 06 L 13 - Seismic AttributesCourtesy of ExxonMobil Seismic attribute applications: Qualitative Quantitative - Data quality; seismic artifact identification - Seismic facies; depositional environment - Equations relating rock property changes to changes in seismic attributes Reservoir thickness Lithology Porosity Type of fluid fill Applications

16 FWS 06 L 13 - Seismic AttributesCourtesy of ExxonMobil Data Quality Analysis (Artifact detection): Identify zones where seismic data quality is adversely affected by acquisition or processing methods or by geologic interference. - Acquisition gaps, Inline-parallel striping - Multiples, migration errors, incorrect velocities - Improper amplitude and phase balancing - Frequency attenuation - Overlying geology (e.g., shallow gas, channel) Qualitative Analyses

17 FWS 06 L 13 - Seismic AttributesCourtesy of ExxonMobil Data Quality Analysis (Artifact detection): Inline-parallel acquisition striping at water bottom (~ 40 ms) Data Quality Inline Direction

18 FWS 06 L 13 - Seismic AttributesCourtesy of ExxonMobil Data Quality Data Quality Analysis (Artifact detection): Inline-parallel acquisition striping at 1000ms Inline Direction

19 FWS 06 L 13 - Seismic AttributesCourtesy of ExxonMobil Seismic facies mapping: Facies are packages of rocks that exhibit similar characteristics (e.g., lithofacies, petrophysical facies, depositional facies) Seismic facies are packages of seismically-defined bodies that exhibit similar seismic characteristics (e.g., reflection geometry, amplitude, continuity, frequency). Environment of Deposition (EoD) can be interpreted from patterns of seismic facies (i.e., similar seismic attributes) Qualitative Analyses

20 FWS 06 L 13 - Seismic AttributesCourtesy of ExxonMobil Orange Datum Qualitative Analyses

21 FWS 06 L 13 - Seismic AttributesCourtesy of ExxonMobil Conceptual Depositional Model: Stacked, prograding fluvial to nearshore to offshore siliciclastic parasequences Orange Magenta Seismic Facies Mapping Exercise Fluvial shales - sands Offshore shales Nearshore sands

22 FWS 06 L 13 - Seismic AttributesCourtesy of ExxonMobil Marine Shale (seal) Porous Sand (reservoir) Marine Shale (seal) Porous Sand (reservoir) Fluvial (reservoir) Orange Magenta Prograding sands increase in porosity upwards before being capped by variable quality marine shale. Seismic Facies Mapping Exercise Conceptual Depositional Model:

23 FWS 06 L 13 - Seismic AttributesCourtesy of ExxonMobil Modern Analog: Fluvial to nearshore progression resulting in wave dominated, barrier island complex (Texas Gulf Coast) Seismic Facies Mapping Exercise

24 FWS 06 L 13 - Seismic AttributesCourtesy of ExxonMobil Modeled Seismic Response Seismic modeling indicates the following response to changes in reservoir and seal quality: Good Seal Good Reservoir Good Seal Poor Reservoir Poor Seal Good Reservoir Poor Seal Poor Reservoir Strong Peak Strong Trough Strong Peak Strong Trough Strong Peak Moderate Trough Strong Peak Moderate Trough Moderate Peak Strong Trough Moderate Peak Strong Trough Moderate Peak Moderate Trough Moderate Peak Moderate Trough Seismic Facies Mapping Exercise

25 FWS 06 L 13 - Seismic AttributesCourtesy of ExxonMobil Objective: Identify areas where good-quality seal rocks overlay good-quality reservoir rocks Available data / tools: Seismic attribute maps Orange time structure map Depositional model and seismic response Tracing paper and pencils Seismic Facies Mapping Exercise

26 FWS 06 L 13 - Seismic AttributesCourtesy of ExxonMobil Seismic Facies Mapping Exercise Good Seal Poor Reservoir Poor Seal Good Reservoir Poor Seal Poor Reservoir Good Seal Good Reservoir Strong Peak Strong Trough Strong Peak Strong Trough Strong Peak Moderate Trough Strong Peak Moderate Trough Moderate Peak Strong Trough Moderate Peak Strong Trough Moderate Peak Moderate Trough Moderate Peak Moderate Trough

27 FWS 06 L 13 - Seismic AttributesCourtesy of ExxonMobil Seismic attribute applications: Qualitative Quantitative - Data quality; seismic artifact identification - Seismic facies; depositional environment - Equations relating rock property changes to changes in seismic attributes. Reservoir thickness Lithology Porosity Applications

28 FWS 06 L 13 - Seismic AttributesCourtesy of ExxonMobil Quantitative Seismic Attribute Analysis Requirements: - Controlled Amplitude, Controlled Phase processing - Data quality reconnaissance - Good well-seismic ties - Sufficient well control (additional seismic modeling is usually necessary) Quantitative Analyses

29 FWS 06 L 13 - Seismic AttributesCourtesy of ExxonMobil Goal: Build a correlation between seismic attributes and sand thickness to predict areas of high reservoir producibility. Tools: Seismic - well log (i.e., rock property) models Quantitative Analyses

30 FWS 06 L 13 - Seismic AttributesCourtesy of ExxonMobil Backstepping, unconfined sheet-sands comprising two multicycle reservoirs separated by a marine shale Geologic Description

31 FWS 06 L 13 - Seismic AttributesCourtesy of ExxonMobil Well 9 Well 2 Well 6 Sand Shale Which seismic attributes differentiate average sand thickness? Attribute Response

32 FWS 06 L 13 - Seismic AttributesCourtesy of ExxonMobil Maximum Average Minimum Calibration

33 FWS 06 L 13 - Seismic AttributesCourtesy of ExxonMobil Seismic Attribute Calibration Average Positive Amplitude Measured Average Sand Thickness (ft) Thickness = APA R 2 = Seismic Attribute Calibration

34 FWS 06 L 13 - Seismic AttributesCourtesy of ExxonMobil LowHigh Average Amplitude W1 W2 W3 W5 W4 W6 W7 W8 W9 Input Seismic Attribute

35 FWS 06 L 13 - Seismic AttributesCourtesy of ExxonMobil RESULT ThinThick Average Sand Thickness W1 W2 W3 W5 W4 W6 W7 W8 W9 160 feet

36 FWS 06 L 13 - Seismic AttributesCourtesy of ExxonMobil Quantitative Analysis: A Brief Example Porosity in the Upper Smackover Porous Zone Impedanc e Smackover Norphlet Haynesville No Porosity in the Upper Smackover Tight Smackover Norphlet Haynesville Impedanc e An Oil Field, Onshore Alabama

37 FWS 06 L 13 - Seismic AttributesCourtesy of ExxonMobil Change Porosity -> Change Seismic Response Representative In-Line Porosity in the Smackover No Porosity in the Smackover The trough is lower in amplitude and loop duration is longer The trough is higher in amplitude and loop duration is shorter Mapped Horizon (white)

38 FWS 06 L 13 - Seismic AttributesCourtesy of ExxonMobil 1-D Seismic Modeling Changing the porosity in the Upper Smackover in 1-D models confirms there is a seismic signature related to porosity Smackover Haynesville Norphlet 16 ft Porous Zone 3 ft Porous Zone 10 ft Porous Zone

39 FWS 06 L 13 - Seismic AttributesCourtesy of ExxonMobil Attribute Calibration & Evaluation Porosity for the Smackover –Predicted based on 4 attributes –Calibration based on 8 wells Actual Average Smackover Porosity Predicted Average Smackover Porosity Best Fit 95% C.I.

40 FWS 06 L 13 - Seismic AttributesCourtesy of ExxonMobil A Predicted Porosity Map Applying the derived attribute equation to the 3D seismic survey resulted in a Smackover porosity map 18% 0 porosity Possible New Well Location

41 FWS 06 L 13 - Seismic AttributesCourtesy of ExxonMobil Inadequate well control: Wells don t represent all variability within reservoir Use seismic modeling to infill gaps Redundant attributes Different attributes highly correlated to one another Remove redundant attributes; keep one that correlates best with rock property Linear correlation Nonlinear correlation may be better representation Test other nonlinear correlation schemes but be aware of extrapolation problems Potential Pitfalls / Solutions

42 FWS 06 L 13 - Seismic AttributesCourtesy of ExxonMobil Seismic attributes describe shape or other characteristics of a seismic trace over specific intervals or at specific times Seismic attributes are important because they enable interpreters to extract more information from seismic data Seismic attributes can be derived from a single-trace or by comparison of multiple traces Three common types of single-trace attributes are horizon-, interval-, and sample-based Seismic attributes are used for qualitative analysis (e.g., data quality, seismic facies mapping) and quantitative analysis (e.g., net sand, porosity prediction) Summary


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