Method for shallow water flow detection

• US 7,672,824 B2
• Filed: 12/10/2001
• Issued: 03/02/2010
• Est. Priority Date: 12/10/2001
• Status: Active Grant

• Current Assignee: WesternGeco LLC
• Original Assignee: WesternGeco LLC
• Inventors: Dutta, Nader, Mallick, Subhashis
• Primary Examiner(s): JONES, HUGH M
• Application Number:
  US10/016,437
• Publication Number:
  US 20030110018A1
• Time in Patent Office: 3,004 Days
• Field of Search: 703/6, 703/10, 703/9
• US Class Current: 703/10
• CPC Class Codes: G01V 1/282 Application of seismic models, synthetic seismograms
• CPC Class Codes: G01V 1/288 Event detection in seismic signals, e.g. microseismics G01V1/36 takes precedence
• CPC Class Codes: G01V 1/32 Transforming one recording into another or one representation into another
• CPC Class Codes: G01V 9/02 Determining existence or flow of underground water
• CPC Class Codes: Y02A 90/30 Assessment of water resources

Abstract

The present invention presents a method for determining shallow water flow risk using seismic data. The seismic data can be processed to enhance its stratigraphic resolution by sub-sampling the seismic data to less than a two-millisecond interval. Performing a stratigraphic analysis on the seismic data and evaluating the seismic attributes of the seismic data can be used to select a control location. A pre-stack waveform inversion is applied to seismic data at a selected control location to provide an elastic model, which includes pressure-wave velocity and shear-wave velocity. The shallow water flow risk is then determined using the elastic model by comparing the pressure-wave velocity to the shear-wave velocity. A post-stack inversion can be applied on the seismic data using the elastic model to model a 3D volume to determine the shallow water flow risk across the 3D volume.

Claims

1. A method for determining shallow water flow risk, comprising:

developing a geologic model of shallow water flow risk areas;

performing a stratigraphic analysis on reflected P-wave seismic data of the geologic model to determine a control location within the reflected P-wave seismic data;

applying a pre-stack full waveform inversion on the reflected P-wave seismic data at the control location to provide an elastic earth model of the shallow water flow risk areas based on the geologic model and the stratigraphic analysis, wherein the elastic earth model is determined by matching the reflected P-wave seismic data with synthetic seismic data of the geologic model and the elastic earth model comprises P-wave velocity and S-wave velocity;

computing a ratio between the P-wave velocity and the S-wave velocity; and

identifying multiple shallow water flow risk areas using the relationship of the P-wave velocity to the S-wave velocity ratio with respect to seismic travel time.

2. The method of claim 1, wherein the seismic data comprises seismic data selected from the list consisting of one-dimensional seismic data, two-dimensional seismic data, and three-dimensional seismic data.

3. The method of claim 1, wherein the elastic earth model further comprises attributes selected from the list consisting of density, Poisson'"'"'s ratio, and Lamé

elastic parameters.

4. The method of claim 1, further comprising processing the seismic data to enhance its stratigraphic resolution.

5. The method of claim 4, wherein the processing the seismic data comprises sub-sampling the seismic data to less than two millisecond intervals.

6. The method of claim 4, wherein the processing the seismic data comprises using an algorithm with an amplitude preserving flow.

7. The method of claim 4, wherein the processing the seismic data comprises using an algorithm selected from the list consisting of a pre-stack time migration, accurate velocity normal-moveout correction, and noise removal algorithms.

8. The method of claim 1, wherein the control location comprises a plurality of control locations.

9. The method of claim 1, wherein performing the stratigraphic analysis comprises identifying the control location by using the geologic model to identify a geologic feature selected from this list consisting of faults, blow-outs, bioherms, chaotic facies, cones, diapers, domes, gas vents, gas mounds, mud volcanoes, popckmarks, scarps, slumps, channels, slope fan deposition, and bottom simulator reflectors.

10. The method of claim 1, wherein selecting the control location within the seismic data further comprises evaluating the seismic attributes of the seismic data.

11. The method of claim 10, wherein evaluating the seismic attributes comprises using amplitude-variation-with-offset attributes, comprising intercept and gradient.

12. The method of claim 10, wherein evaluating the seismic attributes comprises evaluating polarity changes in reflection coefficient.

13. The method of claim 1, wherein the pre-stack full waveform inversion comprises applying a genetic algorithm.

14. The method of claim 13, wherein the genetic algorithm comprises:

generating a plurality of elastic earth models;

generating pre-stack synthetic seismograms for the elastic earth models;

matching the generated seismograms with the seismic data;

generating a fitness for the elastic earth models;

genetically reproducing the elastic earth models using the fitness for the elastic earth models; and

determining convergence of the reproduced elastic earth models to select the elastic earth model.

15. The method of claim 14, wherein the plurality of elastic earth models comprises a random population of the elastic earth models.

16. The method of claim 14, wherein matching the generated seismograms with the seismic data further comprises matching normal moveout of the generated seismograms and the seismic data, and matching reflection amplitudes of the generated seismograms and the seismic data.

17. The method of claim 14, wherein genetically reproducing the elastic earth models using the fitness for the elastic earth models comprises:

reproducing the elastic earth models in proportion to the elastic earth models fitness;

randomly crossing over the reproduced elastic earth models; and

mutating the reproduced elastic earth models.

18. The method of claim 1, wherein applying the pre-stack full waveform inversion comprises using an exact wave equation having mode conversions and interbed multiple reflections.

19. The method of claim 1, further comprising applying a post-stack inversion on the seismic data using the elastic earth model to determine the shallow water flow risk over a 3D volume.

20. The method of claim 19, wherein the post-stack inversion is performed using an AVO intercept and a pseudo shear-wave data volume.

21. The method of claim 1, wherein shallow water flow risk is identified when the P-wave velocity compared to the S-wave velocity is between approximately 3.5 and approximately 7.

22. The method of claim 1, wherein the P-wave seismic data are a single component P-wave seismic data.

23. The method of claim 1, wherein the S-wave velocity is obtained indirectly from an amplitude variation with offset (AVO) analysis of the P-wave seismic data.

24. The method of claim 1, wherein the stratigraphic analysis excludes S-wave seismic data that would have been acquired in a marine environment.

25. The method of claim 1, wherein applying the pre-stack full waveform invention comprises deriving the S-wave velocity.

26. A computerized method for determining shallow water flow risk using seismic data comprising:

processing reflected P-wave seismic data to enhance its stratigraphic resolution, wherein the reflected P-wave seismic data are obtained from marine towed streamers;

selecting a control location comprising;

performing a stratigraphic analysis on the reflected P-wave seismic data; and

evaluating the seismic attributes of the reflected P-wave seismic data;

applying a pre-stack full waveform inversion on the reflected P-wave seismic data at the control location to provide an elastic earth model of shallow water flow risk areas, wherein the elastic earth model is determined by matching the reflected P-wave seismic data with synthetic seismic data of the geologic model and the elastic earth model comprises P-wave velocity and S-wave velocity;

applying a post-stack inversion on the reflected P-wave seismic data using the elastic earth model to map a ratio between the P-wave velocity and the S-wave velocity in a three dimensional (3D) volume; and

determining multiple shallow water flow risk areas using the relationship of the ratio between the P-wave velocity and the S-wave velocity with respect to seismic travel time.

27. The method of claim 26, wherein the pre-stack waveform inversion comprises using a genetic algorithm comprising:

generating a plurality of elastic earth models;

generating pre-stack synthetic seismograms for the elastic earth models;

matching the generated seismograms with the seismic data;

generating a fitness for the elastic earth models;

genetically reproducing the elastic earth models using the fitness for the elastic earth models; and

determining convergence of the reproduced elastic earth models to select the elastic earth model.

28. A method for determining a shallow water flow risk area, comprising:

developing a geologic model of the shallow water flow risk area;

performing a stratigraphic analysis on reflected P-wave seismic data of the geologic model to determine a control location within the reflected P-wave seismic data;

applying a pre-stack full waveform inversion on the reflected P-wave seismic data at the control location to provide P-wave velocity (Vp) and Poisson'"'"'s ratio;

computing for S-wave velocity (Vs) using the P-wave velocity (Vp) and the Poisson'"'"'s ratio;

computing for a ratio (Vp/Vs) between the P-wave velocity (Vp) and the S-wave velocity (Vs); and

identifying multiple shallow water flow risk areas using the relationship of the ratio (Vp/Vs) with respect to seismic travel time.

29. The method of claim 28, wherein the S-wave velocity (Vs) is computed using

$v=\frac{1-2}{}$

( V S V P ) 2 2 ⁡

[ 1 - ( V S V P ) 2 ] ,

where ν

is the Poisson'"'"'s ratio, Vp is the P-wave velocity and Vs is the S-wave velocity.