Full waveform inversion using time delayed seismic data

Patent metadata

Field	Value
Publication number	US-11448784-B2
Application number	US-201916731437-A
Country	US
Kind code	B2
Filing date	Dec 31, 2019
Priority date	Dec 31, 2019
Publication date	Sep 20, 2022
Grant date	Sep 20, 2022

Abstract

Systems, methods, and apparatuses directed to determining a long wavelength velocity model using acquired seismic data lacking low-frequency data is disclosed. Determination of the long wavelength velocity model may include generating a time-delayed signal from the acquired seismic data to produce low-frequency information and reducing a residual energy between the time-delayed signal from the acquired seismic data and a time-delayed signal of modeled data using an objective function to produce an optimized initial velocity model using full waveform inversion. Moreover, a full waveform inversion on the optimized initial velocity model using acquired data can be used to produce a velocity model more accurately representing subterranean formations.

First claim

What is claimed is:

1. A computer program product encoded on a non-transitory medium, the product comprising computer readable instructions for causing one or more processors to perform operations comprising:
receiving a set of observed seismic data;
receiving an initial velocity model and an initial source wavelet, the initial velocity model being a user-selected velocity model and the initial source wavelet being a user-selected wavelet;
performing a wavefield simulation using the initial source wavelet and the initial velocity model to generate modeled seismic data;
converting the received set of observed seismic data into a first time-delayed signal;
converting the modeled seismic data into a second time-delayed signal;
optimizing the initial velocity model containing long wavelength subterranean formations using a full waveform inversion utilizing the first time-delayed signal and the second time-delayed signal; and
performing a full waveform inversion utilizing observed data and modeled data on the optimized initial velocity model to produce a detailed velocity model that more accurately represents subterranean formations;
wherein optimizing the initial velocity model containing long wavelength subterranean formations using a full waveform inversion utilizing the first time-delayed signal and the second time-delayed signal comprises reducing a residual energy between the first time-delayed signal and the second time-delayed signal; and
wherein reducing a residual energy between the first time-delayed signal and the second time-delayed signal comprises:
applying an objective function to the first time-delayed signal and the second time-delayed signal to determine the residual energy;
determining whether the residual energy satisfies a predetermined condition; and
if the residual energy does not meet the predetermined condition, repeating an iterative loop until an occurrence of the predetermined condition or until a selected number of iterative loops is completed, the iterative loop comprising:
taking a partial derivative of the objective function with respect to velocity to determine a directional change of the velocity;
updating the initial velocity model according to the determined directional change of velocity to form a new velocity model;
updating the initial source wavelet via a source estimation algorithm by minimizing a difference between a modeled green-function and the received set of observed seismic data forming a new source wavelet;
performing a wavefield simulation with the new source wavelet and the new velocity model to generate new modeled seismic data;
converting the received set of observed seismic data into a new first time-delayed signal;
converting the new modeled seismic data into a new second time-delayed signal;
applying the objective function to the new first time-delayed signal and the new second time-delayed signal to determine a new residual energy; and
determining whether the new residual energy satisfies the predetermined condition.

2. The computer program product of claim 1 , wherein performing a full waveform inversion utilizing modified data using time delayed signal on the initial velocity model to produce an optimized initial model contains long wavelength subterranean formations and performing a full waveform inversion utilizing acquired data on the optimized initial velocity model to produce detailed velocity model that more accurately represents subterranean formations.

3. The computer program product of claim 1 , wherein the predetermined condition comprises:
a condition in which the residual energy is decreased to or less than a selected value;
a condition in which the residual energy is no longer decreasing; or
a condition in which a rate of decrease of the residual energy is at or less than a selected rate.

4. The computer program product of claim 1 , wherein the source wavelet is a Gaussian wavelet, a Ricker wavelet, or a first derivative of a Gaussian wavelet.

5. The computer program product of claim 1 , wherein performing a full waveform inversion to produce an optimized initial velocity model containing long wavelength subterranean formations using modified acquired data and performing a full waveform inversion on the optimized initial velocity model using acquired data to produce a velocity model more accurately representing subterranean formations.

6. A computer implemented method performed by one or more processors for automatically generating a long wavelength velocity model that more accurately represents subterranean formations, the method comprising:
receiving a set of observed seismic data;
receiving an initial velocity model and an initial source wavelet, the initial velocity model being a user-selected velocity model and the initial source being a user-selected wavelet;
performing a wavefield simulation using the initial source wavelet and the initial velocity model to generate modeled seismic data;
converting the received set of observed seismic data into a first time-delayed signal;
converting the modeled seismic data into a second time-delayed signal;
optimizing the initial velocity model containing long wavelength subterranean formations using full waveform inversion utilizing the first time-delayed signal and the second time-delayed signal; and
performing a full waveform inversion utilizing observed data and modeled data on the optimized initial velocity model to produce a detailed velocity model that more accurately represents subterranean formations;
wherein optimizing the initial velocity model utilizing the first time-delayed signal and the second time-delayed signal comprises reducing a residual energy between the first time-delayed signal and the second time-delayed signal; and
wherein reducing a residual energy between the first time-delayed signal and the second time-delayed signal comprises:
applying an objective function to the first time-delayed signal and the second time-delayed signal to determine the residual energy;
determining whether the residual energy satisfies a predetermined condition; and
if the residual energy does not meet the predetermined condition, repeating an iterative loop until an occurrence of the predetermined condition or until a selected number of iterative loops is completed, the iterative loop comprising:
taking a partial derivative of the objective function with respect to velocity to determine a directional change of the velocity;
updating the initial velocity model according to the determined directional change of velocity to form a new velocity model;
updating the initial source wavelet via a source estimation algorithm by minimizing a difference between a modeled green-function and the received set of observed seismic data forming a new source wavelet;
performing a wavefield simulation with the new source wavelet and the new velocity model to generate new modeled seismic data;
converting the received set of observed seismic data into a new first time-delayed signal;
converting the new modeled seismic data into a new second time-delayed signal;
applying the objective function to the new first time-delayed signal and the new second time-delayed signal to determine a new residual energy; and

determining whether the new residual energy satisfies the predetermined condition.

7. The computer implemented method of claim 6 , wherein the predetermined condition comprises:
a condition in which the residual energy is decreased to or less than a selected value;
a condition in which the residual energy is no longer decreasing; or
a condition in which a rate of decrease of the residual energy is at or less than a selected rate.

8. The computer implemented method of claim 6 , wherein the source wavel

Assignees

• Saudi Arabian Oil Co

Inventors

• Yoo Jewoo
• Van Borselen Roald

Classifications

• G01V1/303 Primary

  for determining velocity profiles or travel times · CPC title

• G01V2210/675

  Wave equation; Green's functions · CPC title

• G01V2210/614

  Synthetically generated data · CPC title

• G01V1/282 Primary

  Application of seismic models, synthetic seismograms · CPC title