Artifact Reduction In Iterative Inversion Of Geophysical Data

• US 20110276320A1
• Filed: 03/10/2011
• Published: 11/10/2011
• Est. Priority Date: 05/07/2010
• Status: Active Grant

• Current Assignee: Jerome R. Krebs, Sunwoong Lee, Young H.O. Cha
• Original Assignee: Jerome R. Krebs, Sunwoong Lee, Young H.O. Cha
• Inventors: Cha, Young Ho, Krebs, Jerome R., Lee, Sunwoong
• Granted Patent: US 8,694,299 B2
• Time in Patent Office: Days
• US Class Current: 703/6
• CPC Class Codes: G01V 1/00 Seismology; Seismic or acoustic prospecting or detecting
• CPC Class Codes: G01V 11/00 Prospecting or detecting by methods combining techniques covered by two or more of main groups G01V1/00 - G01V9/00
• CPC Class Codes: G01V 20/00 Geomodelling in general
• CPC Class Codes: G06F 30/20 Design optimisation, verification or simulation optimisation, verification or simulation of circuit designs G06F30/30
• CPC Class Codes: G06T 11/006 Inverse problem, transformation from projection-space into object-space, e.g. transform methods, back-projection, algebraic methods

Abstract

Method for reducing artifacts in a subsurface physical properties model (120) inferred by iterative inversion (140) of geophysical data (130), wherein the artifacts are associated with some approximation (110) made during the iterative inversion. In the method, some aspect of the approximation is changed (160) as the inversion is iterated such that the artifacts do not increase by coherent addition.

Claims

1. A method for reducing artifacts in a subsurface physical property model caused by an approximation, other than source encoding, in an iterative, computerized geophysical data inversion process, said method comprising varying the approximation as the iterations progress.

2. The method of claim 1, wherein said method comprises:

(a) assuming a physical properties model of a subsurface region, said model providing values of at least one physical property at locations throughout the subsurface region;

(b) selecting an iterative data inversion process having a step wherein a calculation is made of an update to the physical properties model that makes it more consistent with measured geophysical data acquired from the subsurface region;

(c) making in said calculation an approximation that either speeds up the selected iterative inversion process other than by source encoding, or that works an accuracy tradeoff;

(d) executing, using a computer, one cycle of the selected iterative inversion process with said approximation and using the physical properties model;

(e) executing, using the computer, a next iterative inversion cycle, wherein a selection is made to either change some aspect of the approximation or not to change it;

(f) repeating (e) as necessary, changing the approximation in some or all of the iteration cycles, until a final iteration wherein a selected convergence criterion is met or another stopping condition is reached; and

(g) downloading the updated physical properties model from the final iteration or saving it to computer storage.

3. The method of claim 2, wherein one or more artifact types are identified in an updated subsurface physical property model as being caused by the approximation.

4. The method of claim 3, wherein the aspect of the approximation that is changed in some or all iteration cycles is selected for having an effect on artifacts of the one or more identified artifact types.

5. The method of claim 4, wherein said effect is such that artifacts from one approximation do not add constructively with artifacts from another iteration cycle that uses an approximation with a changed aspect.

6. The method of claim 2, wherein the approximation is to select a subset of the measured geophysical data for inputting to the iterative inversion process, and the changed aspect is a different selected subset.

7. The method of claim 6, wherein each different subset is selected randomly.

8. The method of claim 1, wherein the approximation is imperfect absorbing boundaries in simulation of synthetic data in the iterative inversion process.

9. The method of claim 1, wherein the approximation is reflecting boundaries in simulation of synthetic data in the iterative inversion process.

10. The method of claim 1, wherein the approximation is random boundary conditions in simulation of synthetic data in the iterative inversion process.

11. The method of claim 1, wherein the approximation is spatial variation of grid cell size in a finite difference simulator in the iterative inversion process.

12. The method of claim 1, wherein the approximation is spatial variation in a simulation operator'"'"'s accuracy in the iterative inversion process.

13. The method of claim 1, wherein the approximation is use of a grid cell size in simulation of synthetic data in the iterative inversion process, wherein the grid cell size is too coarse to accurately represent variations in the model.

14. The method of claim 1, wherein the approximation is use of a large time step in a time domain simulator in the iterative inversion process, where “

large”

is determined relative to other time steps used.

15. The method of claim 1, wherein the iterative, computerized, geophysical data inversion process includes computing gradients of a cost function, and the approximation involves using less accurate absorbing boundary conditions in order to make the gradient computations more accurate.