IP Library Granted Patent US 9,864,084
Granted Patent B2
US 9,864,084 · App. 14/295,639 · Granted Jan 9, 2018

Coherent noise attenuation method

Inventor: Gordon Poole (East Grinstead, GB)
Assignee: CGG SERVICES SAS
G01V1/36G01V2210/3246
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Quick Facts
Patent No.
US 9,864,084
App. No.
14/295,639
Granted
Jan 9, 2018
Kind
B2
Abstract

Computing device, computer instructions and method for denoising input seismic data d. The method includes receiving the input seismic data d recorded in a first domain by seismic receivers, wherein the input seismic data d includes pure seismic data ss relating to an exploration source and coherent noise data n generated by a man-made device; generating a model m in a second domain to describe the input seismic data d; and processing the model m to obtain an output seismic dataset d′ indicative of seismic data substantially free of the coherent noise data n generated by the man-made device.

Claims (44)

1. A method for denoising input seismic data d, the method comprising:

receiving the input seismic data d recorded in a first domain by seismic receivers, wherein the input seismic data d includes pure seismic data ss relating to an exploration source and coherent noise data n generated by a man-made device;

generating a vector model m as a vector in a second domain, which is different from the first domain, to describe the input seismic data d, wherein the vector model m includes a first sub-model for the pure seismic data ss and a second sub-model for the man-made device; and

processing the vector model m to obtain an output seismic dataset d′ indicative of seismic data substantially free of the coherent noise data n generated by the man-made device.

2. The method of claim 1 , wherein the vector model m further includes a third sub-model associated with another man-made device.

3. The method of claim 2 , wherein the step of generating includes jointly and simultaneously deriving the first sub-model associated with the pure seismic data and the second and third sub-models associated with the man-made device and the another man-made device.

4. The method of claim 1 , wherein the step of processing comprises:

computing the model m by solving an inverse problem based on an L transform; and

applying an L′ transform to the model m to obtain the output seismic dataset d′.

5. The method of claim 1 , wherein the step of processing comprises:

computing the model m by solving an inverse problem based on an L transform;

applying an L′ transform to the model m to obtain the noise data n; and

subtracting the noise data n from the input seismic data d to obtain the output seismic dataset d′.

6. The method of claim 1 , further comprising:

generating an image of a surveyed subsurface based on the output seismic dataset d′.

7. The method of claim 1 , wherein the first domain is a time-space domain.

8. The method of claim 1 , wherein the second domain is one of a radon domain, frequency-wave number domain, tau-p domain, parabolic domain, shifted hyperbola domain, singular value decomposition domain, rank reduction domain and curvelet domain.

9. The method of claim 1 , wherein the man-made device is one of a streamer bird, paravane, diverter, tail buoy or streamer steering device.

10. The method of claim 1 , wherein the noise data n is symmetric relative to a temporal axis.

11. The method of claim 1 , wherein the step of processing comprises:

computing the model m by solving an inverse problem based on an L transform,

wherein the L transform includes exponential terms.

12. The method of claim 11 , wherein exponential terms corresponding to the man-made device have an exponent that is proportional to a distance between the location of the man-made device and a receiver responsible for recording a corresponding trace.

13. The method of claim 1 , wherein the input seismic data d includes only pressure measurements, or only particle motion measurements, or a combination of pressure measurements and particle motion measurements.

14. A computing device for denoising input seismic data d, the computing device comprising:

an interface for receiving the input seismic data d recorded in a first domain by seismic receivers, wherein the input seismic data d includes pure seismic data ss relating to an exploration source and coherent noise data n generated by a man-made device; and

a processor connected to the interface and configured to,

generate a vector model m as a vector in a second domain, which is different from the first domain, to describe the input seismic data d, wherein the vector model m includes a first sub-model for the pure seismic data ss and a second sub-model for the man-made device, and

process the vector model m to obtain an output seismic dataset d′ indicative of seismic data substantially free of the coherent noise data n generated by the man-made device.

15. The computing device of claim 14 , wherein the vector model m further includes a third sub-model associated with another man-made device.

16. The computing device of claim 15 , wherein the processor is further configured to:

jointly and simultaneously derive the first sub-model associated with the pure seismic data and the second and third sub-models associated with the man-made device and the another man-made device.

17. The computing device of claim 14 , wherein the processor is further configured to:

compute the model m by solving an inverse problem based on an L transform; and

apply an L′ transform to the model m to obtain the output seismic dataset d′.

18. The computing device of claim 14 , wherein the processor is further configured to:

compute the model m by solving an inverse problem based on an L transform;

apply an L′ transform to the model m to obtain the noise data n; and

subtract the noise data n from the input seismic data d to obtain the output seismic dataset d′.

19. The computing device of claim 14 , wherein the first domain is a time-space domain and the second domain is one of a radon domain, frequency-wave number domain, tau-p domain, parabolic domain, shifted hyperbola domain, singular value decomposition domain, rank reduction domain and curvelet domain.

20. A non-transitory computer readable medium including computer executable instructions, wherein the instructions, when executed by a computer, implement a method for denoising input seismic data d, the method comprising:

receiving the input seismic data d recorded in a first domain by seismic receivers, wherein the input seismic data d includes pure seismic data ss relating to an exploration source and coherent noise data n generated by a man-made device;

generating a vector model m as a vector in a second domain, which is different from the first domain, to describe the input seismic data d, wherein the vector model m includes a first sub-model for the pure seismic data ss and a second sub-model for the man-made device; and

processing the vector model m to obtain an output seismic dataset d′ indicative of seismic data substantially free of the coherent noise data n generated by the man-made device.

Assignments (1)
ASSIGNMENT OF ASSIGNOR'S INTEREST Recorded Jun 4, 2014
From: POOLE, GORDON
To: CGG SERVICES SA
Reel/Frame 033027/0676 →
Continuity (3)
Provisional Application 61832504 · Jun 7, 2013
Provisional Application 61832456 · Jun 7, 2013
Related Publication 20140365135A1 · Dec 11, 2014