Krylov-space-based quasi-newton preconditioner for full-wavefield inversion

US10838093B2 · US · B2

Patent metadata
FieldValue
Publication numberUS-10838093-B2
Application numberUS-201615190222-A
CountryUS
Kind codeB2
Filing dateJun 23, 2016
Priority dateJul 2, 2015
Publication dateNov 17, 2020
Grant dateNov 17, 2020

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Abstract

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A method, including: storing, in a computer memory, seismic data acquired from a seismic survey of a subsurface region; and generating, with a computer, a final subsurface physical property model of the subsurface region by processing the seismic data with an iterative full wavefield inversion method, wherein the iterative full wavefield inversion method generates the final subsurface physical property model by iteratively applying a linear solver with a preconditioner that is generated from information from one or more previous iterations of the linear solver.

First claim

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The invention claimed is: 1. A method, comprising: storing, in a computer memory, seismic data acquired from a seismic survey of a subsurface region; generating, with a computer, a final subsurface physical property model of the subsurface region by processing the seismic data with an iterative full wavefield inversion method, wherein the iterative full wavefield inversion method includes a non-linear outer iteration process comprising a plurality of outer iterations, each of which updates physical property values m of the physical property model and a nested linear inner iteration process, wherein: (1) each iteration i of the plurality of non-linear outer iterations includes a nested linear inner iteration process for determining a search direction d i to be used in updating the physical property values m i of said non-linear outer iteration; and (2) each of the second and subsequent outer iterations of the plurality of non-linear outer iterations further includes applying a preconditioner to the nested linear inner iteration process of such respective second and subsequent non-linear outer iteration, wherein the preconditioner at such non-linear outer iteration i+1 is generated based at least in part upon the nested linear inner iteration process of the immediately previous outer iteration i and wherein the preconditioner is generated using vectors {γ l , H i γ l } solved for in the nested inner iteration process, where γ l is the search direction for the linear system and where H i γ l is the product of the vector γ l with a Hessian operator H i ; and creating, with a process, an image of the subsurface region from the final subsurface physical property model. 2. The method of claim 1 , comprising using a Krylov-space method as a linear solver for the nested inner iteration processes. 3. The method of claim 1 , comprising using a conjugate gradient method as a linear solver for the nested inner iteration processes. 4. The method of claim 2 , wherein each preconditioner is generated based on the nested inner iteration process of the immediately previous outer iteration using a limited-memory Broyden-Fletcher-Goldfarb-Shanno (BFGS) method. 5. The method of claim 2 , wherein each preconditioner is generated based on the nested inner iteration process of the immediately previous outer iteration using a quasi-Newton method. 6. The method of claim 1 , wherein the preconditioner of each of the second and subsequent outer iterations is a variable preconditioner such that the preconditioner can change when solving a linear system, and the preconditioner is generated based on the nested iteration process of the then-current outer iteration in addition to the nested inner iteration process of the immediately previous outer iteration. 7. The method of claim 1 , further comprising managing hydrocarbons based on the final subsurface physical property model of the subsurface region. 8. The method of claim 1 , further comprising: using the final subsurface physical property model in interpreting a subsurface region for hydrocarbon exploration or production. 9. The method of claim 1 , further comprising drilling for hydrocarbons at a location determined using the final subsurface physical property model of the subsurface region. 10. The method of claim 1 , wherein a generalized minimal residual method is used as a linear solver for the nested inner iteration processes.

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Inventors

Classifications

  • Processing seismic data, e.g. for interpretation or for event detection (G01V1/48 takes precedence) · CPC title

  • for determining physical properties of the subsurface, e.g. impedance, porosity or attenuation profiles · CPC title

  • G01V1/30Primary

    Analysis (G01V1/50 takes precedence) · CPC title

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What does patent US10838093B2 cover?
A method, including: storing, in a computer memory, seismic data acquired from a seismic survey of a subsurface region; and generating, with a computer, a final subsurface physical property model of the subsurface region by processing the seismic data with an iterative full wavefield inversion method, wherein the iterative full wavefield inversion method generates the final subsurface physical …
Who is the assignee on this patent?
Akcelik Volkan, Denli Huseyin, Exxonmobil Upstream Res Co
What technology area does this patent fall under?
Primary CPC classification G01V1/30. Mapped technology areas include Physics.
When was this patent published?
Publication date Tue Nov 17 2020 00:00:00 GMT+0000 (Coordinated Universal Time) (B2). Legal status and post-grant events are not shown on this page.
What related patents are in patentsdb?
We list 2 related publications on this page (citations in our corpus or others sharing the same primary CPC).