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SEISMIC ATTRIBUTES FOR RESERVOIR CHARACTERIZATION

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Presentation on theme: "SEISMIC ATTRIBUTES FOR RESERVOIR CHARACTERIZATION"— Presentation transcript:

1 SEISMIC ATTRIBUTES FOR RESERVOIR CHARACTERIZATION

2 SEISMIC ATTRIBUTES FOR RESERVOIR CHARACTERIZATION
Elastic Rock Properties Seismic Velocity inversely correlated with Porosity Rock Property Predictions from Seismic Attributes Geometrical Attributes – Faults, Sedimentary Features, Channels Bright Spot vizualization

3 FOR FLOW SIMULATION MODEL THE RESERVOIR ENGINEER NEEDS
Porosity: amount and spatial distribution Permeability Nature of fluids and saturation Pressure Temperature Barriers to flow (faults, strat. barriers)

4 ELASTIC ROCK PROPERTIES
For isotropic media, (Sheriff, 1992) Compressional wave velocity Vp = [λ + 2μ /ρ] 0.5 where Lamé’s constant λ, an elastic parameter sensitive to fluid content, is related to μ and κ by λ = κ - 2μ/3. rigidity (shear modulus, μ), Incompressibility (bulk modulus, κ) density (ρ)

5 ELASTIC ROCK PROPERTIES
Shear wave velocity = Vs = (μ / ρ ) 0.5 where rigidity (shear modulus, μ), density (ρ)

6 ELASTIC ROCK PROPERTIES
where σ is the Poisson ratio.

7 SEISMIC VELOCITY AND POROSITY
where φ is the porosity, Vf is the velocity of the interstitial fluid, and Vm is the velocity of the rock matrix (Wyllie et al. 1956).

8 SEISMIC VELOCITY AND POROSITY
a high negative correlation between porosity and acoustic impedance has a physical basis

9 SEISMIC VELOCITY MAP AND WELL POROSITY

10 SEISMIC VELOCITY AND WELL POROSITY

11 Snap 3D Seismic to Grid Impedance (Stochastic Inversion)
3D Inversion Cube

12 Acoustic Impedance Model

13 PREDICTION METHODS Regression Geostatistics Neural networks

14 PREDICTION PROCESS Calibration Choice of seismic attribute(s)
Cross-validation Management decisions

15 SEISMIC VELOCITY MAP AND WELL POROSITY

16 RISK MAP based on 100 conditional simulations showing the probability that porosity is ≥ 9%.

17 FALSE CORRELATIONS Possiblity of false correlations increases with:
small number of well data many seismic attributes

18 GEOMETRICAL ATTRIBUTES
depict patterns related to: faults fracture swarms depositional patterns channels

19 GEOMETRICAL ATTRIBUTES
MULTIPLE-POINT STATISTICS allows geological patterns integration through pixel-based modeling (Journel, 1997, 2002; Caers, 2000; Strebelle, 2000). Training images depict the geological conceptual model then a sequential-based simulation algorithm is used to generate multiple realizations

20 GEOMETRICAL ATTRIBUTES
left - seismic amplitude data showing channel-like features center - conceptual model right - pixel-based realization

21 Data Integration Geology Geophysics
Structural Map on Top Reservoir using G&G

22 Example Well Average Porosities Seismic Amplitude Map
Average Porosity Maps Combined using Collocated Cokriging R = 0.75

23 Uncertainty Reduction
Average Porosities - Wells Only Realization 1 Realization 2 Realization 3 Average Porosities - Wells plus Seismic Realization 1 Realization 2 Realization 3

24 Example 3D sGs constrained by 2D seismic surface Cokriged Por. Map
Amplitude Map Cokriged Por. Map 3D Porosity Model Avg. of 3D Model

25

26 Reservoir Facies Using Seismic

27 A series of equally probable high resolution impedance models
Impedance Logs 3D Seismic Data Deterministic Inversion Stochastic Inversion A series of equally probable high resolution impedance models

28 Reservoir Geometry Using Seismic
Channel geometries are locally controlled by the use of Seismic facies.

29 Bright Spot Vizualization

30 Bright Spots

31

32 Seismic attributes can help in characterizing and modeling:
Reservoir Geometry Reservoir Facies Reservoir Property (Porosity) Bright spots


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