Method of generating and combining multiple horizons to determine a seismic horizon and its uncertainty

• US 9,239,398 B2
• Filed: 10/12/2012
• Issued: 01/19/2016
• Est. Priority Date: 11/11/2011
• Status: Active Grant

• Current Assignee: Exxonmobil Upstream Research Company (Exxon Mobil Corporation)
• Original Assignee: Exxonmobil Upstream Research Company (Exxon Mobil Corporation)
• Inventors: Kim, Chul-Sung, Dobin, Mark W.
• Primary Examiner(s): HULKA, JAMES R
• Application Number:
  US13/651,204
• Publication Number:
  US 20130121111A1
• Time in Patent Office: 1,194 Days
• Field of Search: 367/73
• US Class Current: 1/1
• CPC Class Codes: G01V 1/301 for determining seismic cross-sections or geostructures
• CPC Class Codes: G01V 2210/643 Horizon tracking

Abstract

There is provided a system and method for creating model of a subsurface region based on multiple depth values. The method includes selecting seeds that represent a starting location within a desired horizon surfaces and generating a plurality of candidate horizons from the selected seeds. A number of depth values from the candidate horizons may be combined into a representative depth value and an uncertainty may be computed based on discrepancies among the depth values. A model of the subsurface region may be created using the depth values and the uncertainty.

Claims

1. A method of generating a horizon surface based on multiple candidate horizon surfaces, the method comprising:

selecting seeds that represent different starting locations within a desired horizon surface;

generating a plurality of candidate horizons from the selected seeds;

generating the horizon surface by combining, for each point on the horizon surface, depth values from corresponding points on the plurality of candidate horizons into a single representative depth value;

computing an uncertainty for each point on the horizon surface based on a difference between two or more depth values from the plurality of candidate horizons that create the single representative depth value, respectively; and

creating a model of the subsurface region using the horizon surface.

2. The method recited in claim 1, wherein the seeds include interpretation line segments with differing lengths, interpretation line segments that are not in-line or cross-line segments, or points.

3. The method recited in claim 1, wherein the model of the subsurface region includes a consistency map and an uncertainty map.

4. The method recited in claim 1, comprising:

combining, for each point on the horizon surface, the depth values into the single representative depth value using an average of the depth values, respectively; and

computing the uncertainty as a standard deviation of the depth values used to generate the single representative depth value, respectively.

5. The method recited in claim 1, comprising:

combining, for each point on the horizon surface, the depth values into the single representative depth value using a weighted average of the depth values, respectively, with a weight computed using a distance calculation and an error calculation; and

computing the uncertainty as a standard deviation of the depth values used to generate the single representative depth value, respectively.

6. The method recited in claim 1, comprising:

combining, for each point on the horizon surface, depth values into the single representative depth value using an average of a matching set of depth values at each location, respectively;

computing the uncertainty as a standard deviation of the depth values used to generate the single representative depth value, respectively.

7. The method recited in claim 1, comprising iteratively creating an uncertainty map or a consistency map, using additional interpretation lines on the uncertainty map or the consistency map in each iteration to refine the depth values.

8. A computer system that is configured to generate a horizon surface based on multiple candidate surfaces, the computer system comprising:

a processor; and

a non-transitory, machine-readable storage medium that stores machine-readable instructions for execution by the processor, the machine-readable instructions comprising;

code that is configured to cause the processor to select seeds that represent different starting locations within a desired horizon surface;

code that is configured to cause the processor to generate a plurality of candidate horizons from the selected seeds;

code that is configured to cause the processor to generate the horizon surface by combining, for each point on the horizon surface, depth values from corresponding points on the plurality of candidate horizons into a single representative depth value;

code that is configured to cause the processor to compute an uncertainty for each point on the horizon surface based on a difference between two or more depth values from the plurality of candidate horizons that create the single representative depth value, respectively; and

code that is configured to cause the processor to render a model of the subsurface region using the horizon surface.

9. The system recited in claim 8, wherein the seeds include interpretation line segments with differing lengths, interpretation line segments that are not in-line seismic sections or cross-line seismic sections, or points.

10. The system recited in claim 8, comprising code that is configured to cause the processor to render the model of the subsurface region by rendering a consistency map and an uncertainty map.

11. The system recited in claim 8, comprising code that, when executed by the processor, is configured to cause the processor to combine, for each point on the horizon surface, the depth values into the single representative depth value using an average of the depth values, respectively, and compute the uncertainty as a standard deviation of the depth values used to generate the single representative depth value, respectively.

12. The system recited in claim 8, comprising code that is configured to cause the processor to combine, for each point on the horizon surface, the depth values into the single representative depth value using a weighted average of the depth values, respectively, with a weight computed using a distance calculation and an error calculation, and compute the uncertainty as a standard deviation of the depth values used to generate the single representative depth value, respectively.

13. The system recited in claim 8, comprising code that is configured to cause the processor to combine the depth values into the representative depth value using an average of a matching set of depth values at each location and compute the uncertainty as a standard deviation of the depth values at used to generate the single representative depth value, respectively.

14. The system recited in claim 8, comprising code that, when executed by the processor, is configured to cause the processor to render a model of the subsurface region using the uncertainty by iteratively creating an uncertainty map or a consistency map, using additional interpretation lines on the uncertainty map or the consistency map in each iteration to refine the depth values.

15. A non-transitory, computer readable medium comprising code, which when executed by a processor causes the processor to execute a method of generating a horizon surface based on multiple candidate horizon surfaces, the method comprising:

selecting seeds that represent different starting locations within a desired horizon surface;

generating a plurality of candidate horizons from the selected seeds;

generating the horizon surface by combining, for each point on the horizon surface, depth values from corresponding points on the plurality of candidate horizons into a representative depth value;

computing an uncertainty for each point on the horizon surface based on a difference between two or more depth values from the plurality of candidate horizons that create the single representative depth value, respectively; and

creating a model of the subsurface region using the horizon surface.

16. The non-transitory, computer readable medium recited in claim 15, wherein the seeds include interpretation line segments with differing lengths, interpretation line segments that are not in-line seismic sections, cross-line seismic sections, or points.

17. The non-transitory, computer readable medium recited in claim 15, comprising code configured to direct a processor to combine, for each point on the horizon surface, the depth values into the single representative depth value using an average of the depth values, respectively, and compute the uncertainty as a standard deviation of the depth values used to generate the single representative depth value, respectively.

18. The non-transitory, computer readable medium recited in claim 15, comprising code configured to direct a processor to combine, for each point on the horizon surface, the depth values into the single representative depth value using a weighted average of the depth values, respectively, with a weight computed using a distance calculation and an error calculation, and compute the uncertainty as a standard deviation of the depth values used to generate the single representative depth value, respectively.

19. The non-transitory, computer readable medium recited in claim 15, comprising code configured to direct a processor to combine, for each point on the horizon surface, the depth values into the single representative depth value using an average of a matching set of depth values at each location, respectively and compute the uncertainty as a standard deviation of the depth values used to generate the single representative depth value, respectively.

20. The non-transitory, computer readable medium recited in claim 15, comprising code configured to direct a processor to create a model of the subsurface region using the uncertainty by iteratively creating an uncertainty map or a consistency map, using additional interpretation lines on the uncertainty map or the consistency map in each iteration to refine the depth values.