Computing a calibration term based on combining divergence data and seismic data
IPC분류정보
국가/구분
United States(US) Patent
등록
국제특허분류(IPC7판)
G01V-001/00
G01V-001/28
출원번호
US-0939331
(2010-11-04)
등록번호
US-9091783
(2015-07-28)
발명자
/ 주소
Edme, Pascal
Muyzert, Everhard
출원인 / 주소
WESTERNGECO L.L.C.
인용정보
피인용 횟수 :
0인용 특허 :
30
초록▼
Divergence data is received from a divergence sensor and seismic data is received from seismic sensors, where the divergence sensor and seismic sensors are part of a sensor assembly. A calibration term is computed based on combining the divergence data and the seismic data, where the calibration ter
Divergence data is received from a divergence sensor and seismic data is received from seismic sensors, where the divergence sensor and seismic sensors are part of a sensor assembly. A calibration term is computed based on combining the divergence data and the seismic data, where the calibration term includes a first parameter that is related to a characteristic of the sensor assembly, and a second parameter that is related to a characteristic of a near-surface subterranean medium.
대표청구항▼
1. A method comprising: receiving divergence data from a divergence sensor and seismic data from seismic sensors, wherein the divergence sensor and seismic sensors are part of a sensor assembly, and wherein the seismic data includes an inline propagating wavefield and a crossline propagating wavefie
1. A method comprising: receiving divergence data from a divergence sensor and seismic data from seismic sensors, wherein the divergence sensor and seismic sensors are part of a sensor assembly, and wherein the seismic data includes an inline propagating wavefield and a crossline propagating wavefield;determining a first product of inline horizontal slowness and the inline propagating wavefield using forward and inverse tau-p transform or F-K transform in an inline direction;determining a second product of crossline horizontal slowness and the crossline wavefield using forward and inverse tau-p transform or F-K transform in the crossline direction; andcomputing, by one or more processors, a calibration term by taking a ratio of the divergence data to a sum of the first and the second products, wherein the calibration term includes a first parameter that is related to a characteristic of the sensor assembly, and a second parameter that is related to a characteristic of a near-surface subterranean medium. 2. The method of claim 1, further comprising disregarding one of the first and second products to simplify computing the calibration term, wherein the second product is set to zero for pure inline events, and wherein the first product is set to zero for pure crossline events. 3. An article comprising at least one non-transitory computer-readable storage medium storing instructions that upon execution by a computer system cause the computer system to: receive divergence data from a divergence sensor and seismic data from seismic sensors, wherein the divergence sensor and seismic sensors are part of a sensor assembly, and wherein the seismic data includes an inline propagating wavefield and a crossline propagating wavefield; andcompute a KDKS term by taking a ratio of the divergence data to one or a combination of a first product of the inline propagating wavefield and a first slowness, and a second product of the crossline propagating wavefield and a second slowness, wherein the KDKS term includes a first parameter KD that is related to a characteristic of the sensor assembly, and a second parameter KS that is related to a characteristic of a near-surface subterranean medium. 4. A computer system comprising: a storage media to store divergence data received from a divergence sensor and seismic data received from seismic sensors, wherein the divergence sensor and seismic sensors are part of a sensor assembly, and wherein the seismic data includes an inline propagating wavefield and a crossline propagating wavefield; andone or more processors configured to: determine a first slowness in an inline direction;determine a second slowness in a crossline direction; andcompute a calibration term by taking a ratio of the divergence data to a sum of a first product of the first slowness and the inline propagating wavefield, and a second product of the second slowness and the crossline propagating wavefield, wherein the calibration term includes a first parameter that is related to a characteristic of the sensor assembly, and a second parameter that is related to a characteristic of a near-surface subterranean medium. 5. The computer system of claim 4, wherein the one or more processors are configured to further disregard one of the first and second products to simplify computing the calibration term, wherein the second product is set to zero for pure inline events, and wherein the first product is set to zero for pure crossline events. 6. A method comprising: receiving divergence data from a divergence sensor and seismic data from seismic sensors, wherein the divergence sensor and seismic sensors are part of a sensor assembly, wherein the divergence sensor comprises a container filled with a material, and a pressure sensor immersed in the material, and wherein the seismic data comprises velocity or acceleration;computing, by one or more processors, a spatial derivative of the seismic data;computing, by the one or more processors, a ratio of a value derived from the divergence data to a value derived from the spatial derivative of the seismic data; andcomputing, by the one or more processors, a calibration term using the ratio, wherein the calibration term includes a first parameter that is related to a characteristic of the sensor assembly, and a second parameter that is related to a characteristic of a near-surface subterranean medium. 7. The method of claim 6, wherein the divergence sensor and the seismic sensors are contained within a housing of the sensor assembly. 8. The method of claim 6, wherein the first parameter is dependent on an impulse response and a coupling of the sensor assembly with the near-surface subterranean medium. 9. The method of claim 6, wherein the calibration term is derived from a product of the first and second parameters. 10. The method of claim 6, wherein the seismic data includes horizontal seismic data. 11. The method of claim 6, wherein the sensor assembly is part of a distribution of sensor assemblies, and wherein each of the sensor assemblies in the distribution includes a divergence sensor and seismic sensors, the method further comprising: receiving divergence data and seismic data from each of the sensor assemblies as part of a common shot gather, wherein the calibration term over the distribution of sensor assemblies is computable from a single shot. 12. The method of claim 6, wherein the seismic data comprises inline seismic data and crossline seismic data, wherein the value derived from the spatial derivative of the seismic data is a sum of a spatial derivative of the inline seismic data and a spatial derivative of the crossline seismic data. 13. The method of claim 12, wherein computing the calibration term is based on the seismic data obtained for a three-dimensional varying subterranean medium. 14. The method of claim 6, wherein the divergence data and the seismic data are part of one or more common receiver gathers in which the divergence data and seismic data are responsive to multiple activations of corresponding seismic sources, and wherein computing the calibration term comprises computing the calibration term based on data of the one or more common receiver gathers. 15. The method of claim 14, further comprising reordering the divergence data and seismic data that are part of a common shot gather to provide the one or more common receiver gathers. 16. The method of claim 6, wherein the seismic data comprises inline seismic data and crossline seismic data, wherein the value derived from the spatial derivative of the seismic data is a spatial derivative of the inline seismic data in an x direction, wherein the inline seismic data has been processed to remove events scattered off an xz plane, wherein the xz plane is a plane including the x direction and a z direction that is generally vertical. 17. The method of claim 16, wherein computing the calibration term is based on the seismic data obtained for a three-dimensional varying subterranean medium or a two- dimensional varying subterranean medium. 18. The method of claim 6, wherein the seismic data comprises inline seismic data and crossline seismic data, wherein the value derived from the spatial derivative of the seismic data is a derivative of the crossline seismic data in a y direction, wherein the crossline seismic data has been processed to remove events scattered off an yz plane, wherein the yz plane is a plane including the y direction and a z direction that is generally vertical. 19. The method of claim 18, wherein computing the calibration term is based on the seismic data obtained for a three-dimensional varying subterranean medium or a two- dimensional varying subterranean medium. 20. The method of claim 6, further comprising removing aliased portions of the divergence data and the seismic data prior to performing the computing of the spatial derivative, the computing of the ratio, and the computing of the calibration term. 21. The method of claim 6, further comprising: responsive to one of the first parameter and second parameter being known, computing the other of the first parameter and the second parameter based on the known first or second parameter and the computed calibration term. 22. The method of claim 21, wherein computing the second parameter based on the known first parameter and the computed calibration term comprises computing the second parameter as a function of frequency. 23. A computer system comprising: at least one processor to: receive divergence data from a divergence sensor and seismic data from seismic sensors, wherein the divergence sensor and seismic sensors are part of a sensor assembly, wherein the divergence sensor comprises a container filled with a material, and a pressure sensor immersed in the material, and wherein the seismic data comprises velocity or acceleration;compute a spatial derivative of the seismic data;compute a ratio of a value derived from the divergence data to a value derived from the spatial derivative of the seismic data; andcompute a calibration term using the ratio, wherein the calibration term includes a first parameter that is related to a characteristic of the sensor assembly, and a second parameter that is related to a characteristic of a near-surface subterranean medium. 24. The computer system of claim 23, wherein the first parameter is dependent on an impulse response and a coupling of the sensor assembly with the near-surface subterranean medium, and wherein the calibration term is derived from a product of the first and second parameters. 25. The computer system of claim 24, wherein the seismic data comprises inline seismic data and crossline seismic data, wherein the value derived from the spatial derivative of the seismic data is a sum of a spatial derivative of the inline seismic data and a spatial derivative of the crossline seismic data.
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