Automatic focus identification method and system for Karst cave reservoir

Patent metadata

Field	Value
Publication number	US-10288752-B2
Application number	US-201715697745-A
Country	US
Kind code	B2
Filing date	Sep 7, 2017
Priority date	Sep 7, 2016
Publication date	May 14, 2019
Grant date	May 14, 2019

Abstract

Disclosed are an automatic focus identification method and a system for a Karst cave reservoir. According to the method, velocity replacement is performed based on a pre-stack time migration velocity model to obtain a plurality of replacement migration velocity volumes; pre-stack time migration is performed based on the plurality of replacement migration velocity volumes to obtain a plurality of post-stack seismic data volumes; a three dimensional cube window is selected based on a seismic response characteristic of the Karst cave reservoir; sparse statistical data of a seismic trace or sparse statistical data of a seismic trace attribute of each of the post-stack seismic data volumes in the three dimensional cube window are obtained respectively; and an optimized migration velocity and an optimized seismic trace are obtained through optimization determination.

First claim

The invention claimed is:

1. An automatic focus identification method for a Karst cave reservoir, comprising steps of:
performing velocity replacement based on a pre-stack time migration velocity model to obtain a plurality of replacement migration velocity volumes;
performing pre-stack time migration based on the plurality of replacement migration velocity volumes to obtain a plurality of post-stack seismic data volumes corresponding to the plurality of replacement migration velocity volumes one to one;
selecting a three dimensional cube window based on a seismic response characteristic of the Karst cave reservoir of seismic data;
obtaining sparse statistical data of a seismic trace, or sparse statistical data of a seismic trace attribute of each of the post-stack seismic data volumes respectively in the three dimensional cube window; and
obtaining an optimized migration velocity and an optimized seismic trace through optimization determination, based on the sparse statistical data of the seismic trace, or the sparse statistical data of the seismic trace attribute corresponding to all of the post-stack seismic data volumes.

2. The method according to claim 1 , wherein the sparse statistical data of the seismic trace corresponding to the post-stack seismic data volumes are obtained according to L1 norm criterion or Cauchy norm criterion.

3. The method according to claim 2 , further comprising evaluating a maximum value of the sparse statistical data of the seismic trace and a corresponding subscript based on the sparse statistical data of the seismic trace corresponding to all of the post-stack seismic data volumes so as to obtain the optimized migration velocity and the optimized seismic trace.

4. The method according to claim 1 , further comprising performing smoothness constraint on the optimized migration velocity and the optimized seismic trace obtained therein respectively.

5. The method according to claim 1 , wherein the seismic trace attribute is statistical instantaneous amplitude.

6. The method according to claim 5 , wherein a step of obtaining sparse statistical data of the statistical instantaneous amplitude corresponding to a post-stack seismic data volume comprises:
censusing instantaneous amplitudes of the post-stack seismic data volume in the three dimensional cube window according to L1 norm criterion so as to obtain the sparse statistical data of the statistical instantaneous amplitude corresponding to the post-stack seismic data volume.

7. The method according to claim 6 , wherein a step of obtaining an optimized migration velocity and an optimized seismic trace through optimization determination based on the sparse statistical data of the statistical instantaneous amplitude corresponding to all of the post-stack seismic data volumes comprises:
evaluating a maximum value of the sparse statistical data of the statistical instantaneous amplitude and a corresponding subscript based on the sparse statistical data of the statistical instantaneous amplitude corresponding to all of the post-stack seismic data volumes so as to obtain the optimized migration velocity and the optimized seismic trace.

8. The method according to claim 7 , further comprising fitting the sparse statistical data of the statistical instantaneous amplitude corresponding to all of the post-stack seismic data volumes through a least-squares extremum fit algorithm so as to obtain the maximum value of the sparse statistical data of the statistical instantaneous amplitude and the corresponding subscript.

9. The method according to claim 5 , wherein the seismic trace attribute is statistical time difference.

10. The method according to claim 9 , wherein a step of obtaining sparse statistical data of the statistical time difference corresponding to a post-stack seismic data volume comprises:
censusing time difference information of the post-stack seismic data volume in the three dimensional cube window according to L1 norm criterion so as to obtain the sparse statistical data of the statistical time difference corresponding to the post-stack seismic data volume.

11. The method according to claim 10 , wherein a step of censusing the time difference information comprises representing each sampling point of the post-stack seismic data volume in the three dimensional cube window by its surrounding multiple traces and multiple sampling points, performing slide scanning on the seismic data, selecting a center trace as a reference, cross-correlating other traces in the three dimensional cube window with the center trace, and obtaining the time difference information when a cross-correlation function has a maximum value.

12. The method according to claim 11 , wherein a step of obtaining an optimized migration velocity and an optimized seismic trace through optimization determination based on the sparse statistical data of the statistical time difference corresponding to all of the post-stack seismic data volumes comprises:
evaluating a minimum value of the sparse statistical data of the statistical time difference and a corresponding subscript based on the sparse statistical data of the statistical time difference corresponding to all of the post-stack seismic data volumes by fitting through a least-squares extremum fit algorithm so as to obtain the optimized migration velocity and the optimized seismic trace.

13. The method according to claim 1 , wherein a step of obtaining the plurality of replacement migration velocity volumes comprises:
defining a minimum replacement velocity, a maximum replacement velocity, and a replacement velocity change interval based on the pre-stack time migration velocity model, and performing velocity replacement on an existing migration velocity along a marker bed so as to obtain the plurality of replacement migration velocity volumes.

14. An automatic focus identification system for a Karst cave reservoir, comprising:
a replacement module, configured to perform velocity replacement based on a pre-stack time migration velocity model to obtain a plurality of replacement migration velocity volumes;
a migration module, configured to perform pre-stack time migration, based on the plurality of replacement migration velocity volumes, to obtain a plurality of post-stack seismic data volumes corresponding to the plurality of replacement migration velocity volumes one to one;
a selecting module, configured to select a three dimensional cube window based on a seismic response characteristic of the Karst cave reservoir;
a first obtaining module, configured to obtain sparse statistical data of a seismic trace or sparse statistical data of a seismic trace attribute of each of the post-stack seismic data volumes in the three dimensional cube window respectively; and
a second obtaining module, configured to obtain an optimized migration velocity and an optimized seismic trace through optimization determination based on the sparse statistical data of the seismic trace or the sparse statistical data of the seismic trace attribute corresponding to all of the post-stack seismic data volumes.

15. The system according to claim 14 , wherein the first obtaining module is specifically configured to obtain the sparse statistical data of the seismic trace corresponding to the post-stack seismic data volumes according to L1 norm criterion or Cauchy norm criterion.

16. The system according to claim 15 , wherein the second obtaining module is specifically configured to evaluate a maximum value of the sparse statistical data of the seismic trace and a corresponding subscript based on the sparse statistical data of the

Assignees

• China Petroleum & Chem Corp
• Sinopec Geophysical Res Inst

Inventors

• Xu Kai
• Tang Jinliang
• Wang Shixing

Classifications

• G01V1/302

  in 3D data cubes · CPC title

• G01V1/303 Primary

  for determining velocity profiles or travel times · CPC title

• G01V1/282

  Application of seismic models, synthetic seismograms · CPC title

• G01V1/307

  for determining seismic attributes, e.g. amplitude, instantaneous phase or frequency, reflection strength or polarity · CPC title