Joint full wavefield inversion of P-wave velocity and attenuation using an efficient first order optimization

Patent metadata

Field	Value
Publication number	US-10459096-B2
Application number	US-201715614960-A
Country	US
Kind code	B2
Filing date	Jun 6, 2017
Priority date	Jul 13, 2016
Publication date	Oct 29, 2019
Grant date	Oct 29, 2019

Abstract

A method for iteratively inverting seismic data to jointly infer a model for at least P-wave velocity and attenuation parameters of the subsurface, the method including: jointly inverting the P-wave velocity and attenuation parameters with an iterative visco-acoustic full wavefield inversion process, wherein the iterative visco-acoustic full wavefield inversion process includes computing a gradient of an objective function, the objective function measuring a misfit between all or part of the seismic data and corresponding model-simulated seismic data; for each of the P-wave velocity and attenuation parameters, computing a search direction in model space from the gradient; determining line search step sizes α and β for the search directions for the P-wave velocity and attenuation parameters, respectively, wherein a ratio of the step sizes is a function of the P-wave velocity parameter; and using the step sizes α and β and the search directions for each of the P-wave velocity and attenuation parameters, computing a new search direction in model space, then performing a line search along the new search direction to arrive at a new step size, and using the new step size and the new search direction to generate an updated model for a current iteration of the iterative visco-acoustic full wavefield inversion process.

First claim

What is claimed:

1. A method for iteratively inverting seismic data to jointly infer a model for at least P-wave velocity and attenuation parameters of the subsurface, said method comprising:
jointly inverting the P-wave velocity and attenuation parameters with an iterative visco-acoustic full wavefield inversion process, wherein the iterative visco-acoustic full wavefield inversion process includes computing a gradient of an objective function, the objective function measuring a misfit between all or part of the seismic data and corresponding model-simulated seismic data;
for each of the P-wave velocity and attenuation parameters, computing a search direction in model space from the gradient;
determining line search step sizes α and β for the search directions for the P-wave velocity and attenuation parameters, respectively, wherein a ratio of the step sizes is a function of the P-wave velocity parameter; and
using the step sizes α and β and the search directions for each of the P-wave velocity and attenuation parameters, computing a new search direction in model space, then performing a line search along the new search direction to arrive at a new step size, and using the new step size and the new search direction to generate an updated model for a current iteration of the iterative visco-acoustic full wavefield inversion process;
wherein the step sizes satisfy

β
α

≈

-

π

V
p

⁢

log
⁡

(

ω

ω
0

)

,

V p is the P-wave velocity parameter, ω is frequency and ω o is a reference frequency.

2. The method of claim 1 , wherein the obtaining the starting P-wave velocity model includes determining, with a computer, the starting P-wave velocity model from an iterative acoustic full wavefield inversion process, wherein the iterative acoustic full wavefield inversion process includes using a cross-correlation objective function to minimize a misfit between all or part of the seismic data and corresponding model-simulated seismic data.

3. The method of claim 1 , wherein the objective function is an L2 objective function.

4. The method of claim 1 , wherein the objective function is a cross-correlation objective function.

5. The method of claim 1 , further comprising:
generating a subsurface image from the updated model; and
using the subsurface image to prospect for hydrocarbons.

Assignees

• Tan Sirui
• Tang Yaxun
• Baumstein Anatoly I
• Ayeni Gboyega
• Vdovina Tetyana
• Dickens Thomas A
• Exxonmobil Upstream Res Co

Inventors

• Tan Sirui
• Tang Yaxun
• Baumstein Anatoly I
• Ayeni Gboyega
• Vdovina Tetyana
• Dickens Thomas A

Classifications

• G06F17/11

  for solving equations {, e.g. nonlinear equations, general mathematical optimization problems (optimization specially adapted for a specific administrative, business or logistic context G06Q10/04)} · CPC title

• G01V1/303

  for determining velocity profiles or travel times · CPC title

• G01V1/282 Primary

  Application of seismic models, synthetic seismograms · CPC title

• G01V1/368

  Inverse filtering · CPC title