4d noise suppression

Patent metadata

Field	Value
Publication number	US-2016209533-A1
Application number	US-201414914564-A
Country	US
Kind code	A1
Filing date	Aug 27, 2014
Priority date	Aug 27, 2013
Publication date	Jul 21, 2016
Grant date	—

Abstract

The present disclosure includes a method for suppressing 4D noise. The method includes calculating a first similarity map based on the similarity of one of one or more first 3D images and a second 3D image. The first and second 3D images are derived from first and second surveys, respectively. The method also includes calculating a second similarity map based on the similarity of one of the one or more first 3D images and a third 3D image, which is derived from the second survey. The method also includes calculating a third similarity map based on the similarity of first and second 4D images, which are based on differences between the 3D images. The method also includes generating a composite 4D image based at least on the first, second, and third similarity maps. The present disclosure may also include associated systems and apparatus.

First claim

What is claimed is:

1 . A method for suppressing 4D noise during seismic imaging, the method comprising:
calculating a first similarity map based at least on the similarity of one of one or more first 3D images and a second 3D image, wherein the one or more first 3D images are derived from a first survey recorded during a first time period, and the second 3D image is derived from a second survey recorded during a second time period; calculating a second similarity map based at least on the similarity of one of the one or more first 3D images and a third 3D image, wherein the third 3D image is derived from the second survey; calculating a third similarity map based at least on the similarity of first and second 4D images, wherein the first 4D image is based on a difference between one of the one or more first 3D images and the second 3D image, and the second 4D image is based on a difference between one of the one or more first 3D images and the third 3D image; and generating a composite 4D image based at least on the first, second, and third similarity maps.

2 . The method of claim 1 , wherein the composite 4D image is a weighted stack of at least the first and second 4D images.

3 . The method of claim 2 , wherein generating the composite 4D image comprises:
calculating a first weighting function based at least on the similarity of the first and third similarity maps; calculating the second weighting function based at least on the similarity of the second and third similarity maps; and generating the weighted stack by:
applying the first weighting function to the first 4D image and
applying the second weighting function to the second 4D image.

4 . The method of claim 1 , wherein calculating the third similarity map comprises applying one of the following functions to the first and second 4D images:
semblance; and cross-correlation.

5 . The method of claim 1 , further comprising modifying the first similarity map in response to determining that a portion of the similarity map is below threshold level of similarity.

6 . The method of claim 1 , wherein the second 3D image is derived from up-going wavefields, and the third 3D image is derived from down-going wavefields.

7 . The method of claim 1 , wherein:
the second 3D image is derived based on a first portion of the second seismic dataset; and the third 3D image is derived based on a second portion of the second seismic dataset.

8 . The method of claim 1 , wherein the first and second images are derived using different processing methods on the same portion of the second seismic dataset.

9 . The method of claim 1 , wherein the first seismic dataset is a baseline survey and the second seismic dataset is a monitor survey.

10 . A system for suppressing 4D noise comprising:
a plurality of receivers; and a computer system configured to:
calculate a first similarity map based at least on the similarity of one of one or more first 3D images and a second 3D image, wherein the one or more first 3D images are derived from a first survey recorded during a first time period from data acquired by the receivers, and the second 3D image is derived from a second survey recorded during a second time period from data acquired by the receivers;
calculate a second similarity map based at least on the similarity of one of the one or more first 3D images and a third 3D image, wherein the third 3D image is derived from the second survey;
calculate a third similarity map based at least on the similarity of first and second 4D images, wherein the first 4D image is based on a difference between one of the one or more first 3D images and the second 3D image, and the second 4D image is based on a difference between one of the one or more first 3D images and the third 3D image; and
generate a composite 4D image based at least on the first, second, and third similarity maps.

11 . The system of claim 10 , wherein the composite 4D image is a weighted stack of at least the first and second 4D images.

12 . The system of claim 11 , wherein the computer system is configured to generate the composite 4D image by:
calculating a first weighting function based at least on the similarity of the first and third similarity maps; calculating the second weighting function based at least on the similarity of the second and third similarity maps; and generating the weighted stack by:
applying the first weighting function to the first 4D image and
applying the second weighting function to the second 4D image.

13 . The system of claim 10 , wherein the computer system is configured to calculate the third similarity map by applying one of the following functions to the first and second 4D images:
semblance; and cross-correlation.

14 . The system of claim 10 , further comprising modifying the first similarity map in response to determining that a portion of the similarity map is below threshold level of similarity.

15 . The system of claim 10 , wherein the second 3D image is derived from up-going wavefields, and the third 3D image is derived from down-going wavefields.

16 . A non-transitory computer-readable medium containing instructions operable, when executed by a processor, to:
calculate a first similarity map based at least on the similarity of one of one or more first 3D images and a second 3D image, wherein the one or more first 3D images are derived from a first survey recorded during a first time period, and the second 3D image is derived from a second survey recorded during a second time period; calculate a second similarity map based at least on the similarity of one of the one or more first 3D images and a third 3D image, wherein the third 3D image is derived from the second survey; calculate a third similarity map based at least on the similarity of first and second 4D images, wherein the first 4D image is based on a difference between one of the one or more first 3D images and the second 3D image, and the second 4D image is based on a difference between one of the one or more first 3D images and the third 3D image; and generate a composite 4D image based at least on the first, second, and third similarity maps.

17 . The medium of claim 16 , wherein the composite 4D image is a weighted stack of at least the first and second 4D images.

18 . The medium of claim 17 , wherein the instructions are operable, when executed by the processor, to generate the composite 4D image by:
calculating a first weighting function based at least on the similarity of the first and third similarity maps; calculating the second weighting function based at least on the similarity of the second and third similarity maps; and generating the weighted stack by:
applying the first weighting function to the first 4D image and
applying the second weighting function to the second 4D image.

19 . The medium of claim 16 , wherein the instructions are operable, when executed by the processor, to calculate the third similarity map by applying one of the following functions to the first and second 4D images:
semblance; and cross-correlation.

20 . The medium of claim 16 , further comprising modifying the first similarity map in response to determining that a portion of the similarity map is below threshold level of similarity.

Assignees

• Cgg Services Sa

Inventors

• Haacke Ross
• Lim Chen Ning Ivan
• Hoeber Henning

Classifications

• G01V1/362

  Effecting static or dynamic corrections; Stacking · CPC title

• G01V2210/6124

  Subsidence, i.e. upwards or downwards · CPC title

• G01V2210/32

  Noise reduction · CPC title

• G01V1/308 Primary

  Time lapse or 4D effects, e.g. production related effects to the formation (fluid flow per se E21B47/00) · CPC title