Granted Patent B2

US 12,360,271 · App. 17/728,718 · Granted Jul 15, 2025

Inventor: Maiza Bekara (Kingston Upon Thames, GB)

Assignee: PGS Geophysical AS

G01V1/301G01V1/32G01V1/34G01V1/3808G01V1/3843G01V20/00G01V2210/65G01V2210/74

Abstract

Claims (98)

1. In a computer-implemented process for generating an image of a subterranean formation from seismic data recorded in a seismic survey of the subterranean formation, the improvement comprising:

using an autoregressive model to reconstruct seismic data in a low frequency band of the seismic data from signals in the seismic data with relatively higher frequencies than the low frequency band to obtain low frequency reconstructed seismic data that is free of low frequency noise in the low frequency band;

constructing a velocity model of the subterranean formation based on the low frequency reconstructed seismic data; and

generating an image of the subterranean formation based on the velocity model and the low frequency reconstructed seismic data, the image revealing structures of the subterranean formation without contamination from the low frequency noise.

2. The process of claim 1 wherein using the autoregressive model to reconstruct seismic data in the low frequency band comprises:

for each location of a sliding space-time window of the seismic data,

transforming seismic data in the space-time window from a space-time domain to an intermediate domain, wherein the intermediate domain is one of a frequency-slowness domain, a frequency-velocity domain, and a frequency-wavenumber domain,

using the autoregressive model to reconstruct seismic data in the low frequency band of each trace in the intermediate domain, and

transforming the low frequency reconstructed traces to the space-time domain to obtain low frequency reconstructed seismic data in the space-time window.

3. The process of claim 1 wherein using the autoregressive model to reconstruct seismic data in the low frequency band comprises:

for each location of a sliding space-time window of the seismic data,

transforming seismic data in the space-time window from the space-time domain to an intermediate domain, wherein the intermediate domain is one of a frequency-slowness domain, a frequency-velocity domain, and a frequency-wavenumber domain, and

for each trace in the intermediate domain,

detecting amplitudes with frequencies in the low frequency band,

reconstructing the amplitudes in the low frequency band to obtain a low frequency reconstructed trace using the autoregressive model, and

replacing the trace with the low frequency reconstructed trace.

4. The process of claim 1 wherein using the autoregressive model to reconstruct seismic data in the low frequency band comprises:

transforming the seismic data from the time domain to obtain transformed seismic data in an intermediate domain, wherein the intermediate domain is one of a frequency-slowness domain, a frequency-velocity domain, and a frequency-wavenumber domain;

detecting amplitudes of the transformed seismic data with frequencies in a low frequency band;

reconstructing amplitudes of traces in the low frequency band of the intermediate domain using the autoregressive model to obtain low frequency reconstructed seismic data in the intermediate domain; and

inverse transforming the low frequency reconstructed seismic data in the space time domain.

5. The process of claim 1 wherein constructing the velocity model of the subterranean formation based on the low frequency reconstructed seismic data comprises performing full-waveform inversion with the low frequency reconstructed seismic data to obtain the velocity model free of contamination from the low frequency noise.

6. The process of claim 1 wherein the autoregressive model is one of a linear autoregressive model and a non-linear autoregressive model.

7. A computer system for generating an image of a subterranean formation from seismic data recorded in a seismic survey of the subterranean formation, the system comprising:

one or more processors;

one or more data-storage devices; and

machine-readable instructions stored in the one or more data-storage devices that when executed using the one or more processors controls the system to perform operations comprising:

using an autoregressive model to reconstruct seismic data in a low frequency band of the seismic data from signals in the seismic data with relatively higher frequencies than the low frequency band to obtain low frequency reconstructed seismic data that is free of low frequency noise in the low frequency band;

constructing a velocity model of the subterranean formation based on the low frequency reconstructed seismic data; and

generating an image of the subterranean formation based on using the velocity model and the low frequency reconstructed seismic data, thereby the image revealing structures of the subterranean formation without contamination from the low frequency noise.

8. The computer system of claim 7 wherein using the autoregressive model to reconstruct seismic data in the low frequency band comprises:

for each location of a sliding space-time window of the seismic data,

transforming seismic data in the space-time window from the space-time domain to an intermediate domain, wherein the intermediate domain is one of a frequency-slowness domain, a frequency-velocity domain, and a frequency-wavenumber domain,

using the autoregressive model to reconstruct seismic data in the low frequency band of each trace in the intermediate domain, and

transforming the low frequency reconstructed traces to the space-time domain to obtain low frequency reconstructed seismic data in the space-time window.

9. The computer system of claim 7 wherein using the autoregressive model to reconstruct seismic data in the low frequency band comprises:

for each location of a sliding space-time window of the seismic data,

transforming seismic data in the space-time window from the space-time domain to an intermediate domain, wherein the intermediate domain is one of a frequency-slowness domain, a frequency-velocity domain, and a frequency-wavenumber domain, and

for each trace in the intermediate domain,

detecting amplitudes with frequencies in the low frequency band,

reconstructing the amplitudes in the low frequency band to obtain a low frequency reconstructed trace using the autoregressive model, and

replacing the trace with the low frequency reconstructed trace.

10. The computer system of claim 7 wherein using the autoregressive model to reconstruct seismic data in the low frequency band comprises:

transforming the seismic data from the time domain to obtain transformed seismic data an intermediate domain, wherein the intermediate domain is one of an intercept time-slowness domain, a frequency-slowness domain, a frequency-velocity domain, and a frequency-wavenumber domain;

detecting amplitudes of the transformed seismic data with frequencies in a low frequency band;

reconstructing amplitudes of traces in the low frequency band of the intermediate domain using the autoregressive model to obtain low frequency reconstructed seismic data in the intermediate domain; and

inverse transforming the low frequency reconstructed seismic data in the space time domain.

11. The computer system of claim 7 wherein constructing the velocity model of the subterranean formation based on the low frequency reconstructed seismic data comprises performing full-waveform inversion with the low frequency reconstructed seismic data to obtain the velocity model free of contamination from the low frequency noise.

12. The computer system of claim 7 wherein the autoregressive model is one of a linear autoregressive model and a non-linear autoregressive model.

13. A non-transitory computer-readable medium having machine-readable instructions encoded thereon for enabling one or more processors of a computer system to perform operations comprising:

reconstructing seismic data in a low frequency band of the seismic data from signals in the seismic data with relatively higher frequencies than the low frequency band to obtain low frequency reconstructed seismic data that is free of low frequency noise in the low frequency band;

constructing a velocity model of a subterranean formation based on the low frequency reconstructed seismic data; and

generating an image of the subterranean formation based on the velocity model and the low frequency reconstructed seismic data.

14. The medium of claim 13 wherein reconstructing seismic data in the low frequency band comprises:

for each location of a sliding space-time window of the seismic data,

transforming seismic data in the space-time window from the space-time domain to an intermediate domain, wherein the intermediate domain is one of a frequency-slowness domain, a frequency-velocity domain, and a frequency-wavenumber domain,

using an autoregressive model to reconstruct seismic data in the low frequency band of each trace in the intermediate domain, and

transforming the low frequency reconstructed traces to the space-time domain to obtain low frequency reconstructed seismic data in the space-time window.

15. The medium of claim 13 wherein reconstructing seismic data in the low frequency band comprises:

for each location of a sliding space-time window of the seismic data,

transforming seismic data in the space-time window from the space-time domain to an intermediate domain, wherein the intermediate domain is one of a frequency-slowness domain, a frequency-velocity domain, and a frequency-wavenumber domain, and

for each trace in the intermediate domain,

detecting amplitudes with frequencies in the low frequency band,

reconstructing the amplitudes in the low frequency band to obtain a low frequency reconstructed trace using an autoregressive model, and

replacing the trace with the low frequency reconstructed trace.

16. The medium of claim 13 wherein reconstructing seismic data in the low frequency band comprises:

transforming the seismic data from the time domain to obtain transformed seismic data an intermediate domain, wherein the intermediate domain is one of a frequency-slowness domain, a frequency-velocity domain, and a frequency-wavenumber domain;

detecting amplitudes of the transformed seismic data with frequencies in a low frequency band;

reconstructing amplitudes of traces in the low frequency band of the intermediate domain using an autoregressive model to obtain low frequency reconstructed seismic data in the intermediate domain; and

inverse transforming the low frequency reconstructed seismic data in the space time domain.

17. The medium of claim 13 wherein constructing the velocity model of the subterranean formation based on the low frequency reconstructed seismic data comprises performing full-waveform inversion with the low frequency reconstructed seismic data to obtain the velocity model free of contamination from the low frequency noise.

18. Apparatus for generating an image of a subterranean formation from seismic data recorded in a seismic survey of the subterranean formation, the apparatus comprising:

means for reconstructing seismic data in a low frequency band of the seismic data from signals in the seismic data with relatively higher frequencies than the low frequency band to obtain low frequency reconstructed seismic data that is free of low frequency noise in the low frequency band;

means for constructing a velocity model of the subterranean formation based on the low frequency reconstructed seismic data; and

means for generating the image of the subterranean formation based on the velocity model and the low frequency reconstructed seismic data.

19. The apparatus of claim 18 wherein means for reconstructing seismic data in the low frequency band comprises:

for each location of a sliding space-time window of the seismic data,

transforms seismic data in the space-time window from the space-time domain to an intermediate domain, wherein the intermediate domain is one of a frequency-slowness domain, a frequency-velocity domain, and a frequency-wavenumber domain,

uses an autoregressive model to reconstruct seismic data in the low frequency band of each trace in the intermediate domain, and

transforms the low frequency reconstructed traces to the space-time domain to obtain low frequency reconstructed seismic data in the space-time window.

20. The apparatus of claim 18 wherein means for reconstructing seismic data in the low frequency band comprises:

for each location of a sliding space-time window of the seismic data,

transforms seismic data in the space-time window from the space-time domain to an intermediate domain, wherein the intermediate domain is one of a frequency-slowness domain, a frequency-velocity domain, and a frequency-wavenumber domain, and

for each trace in the intermediate domain,

detects amplitudes with frequencies in the low frequency band,

reconstructs the amplitudes in the low frequency band to obtain a low frequency reconstructed trace using an autoregressive model, and

replaces the trace with the low frequency reconstructed trace.

21. The apparatus of claim 18 wherein means for reconstructing seismic data in the low frequency band comprises:

transforms the seismic data from the time domain to obtain transformed seismic data an intermediate domain, wherein the intermediate domain is one of a frequency-slowness domain, a frequency-velocity domain, and a frequency-wavenumber domain;

detects amplitudes of the transformed seismic data with frequencies in a low frequency band;

reconstructs amplitudes of traces in the low frequency band of the intermediate domain using an autoregressive model to obtain low frequency reconstructed seismic data in the intermediate domain; and

inverse transforms the low frequency reconstructed seismic data in the space time domain.

22. The apparatus of claim 18 wherein constructing the velocity model of the subterranean formation based on the low frequency reconstructed seismic data comprises performing full-waveform inversion with the low frequency reconstructed seismic data to obtain the velocity model free of contamination from the low frequency noise.

23. A method for manufacturing a geophysical data product, the method comprising:

reconstructing seismic data in a low frequency band of the seismic data from signals in the seismic data with relatively higher frequencies than the low frequency band using an autoregression model to obtain low frequency reconstructed seismic data that is free of low frequency noise in the low frequency band;

constructing a velocity model of a subterranean formation based on the low frequency reconstructed seismic data;

generating an image of the subterranean formation based on the velocity model and the low frequency reconstructed seismic data; and

storing the velocity model and the image in a computer-readable medium.

Assignments (1)

Continuity (2)

References Cited (19)