Generalized free surface multiple suppression technique based on model optimization and its application to the deep water of the Indian Ocean

WANG Xiaojie; YAN Zhonghui; LIU Jun; LIU Xinxin; YANG Jiajia

doi:10.16562/j.cnki.0256-1492.2020101202

2021 Vol. 41, No. 5

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Article navigation > Marine Geology & Quaternary Geology > 2021 > 41(5): 221-230

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WANG Xiaojie, YAN Zhonghui, LIU Jun, LIU Xinxin, YANG Jiajia. Generalized free surface multiple suppression technique based on model optimization and its application to the deep water of the Indian Ocean[J]. Marine Geology & Quaternary Geology, 2021, 41(5): 221-230. doi: 10.16562/j.cnki.0256-1492.2020101202

Citation:

WANG Xiaojie, YAN Zhonghui, LIU Jun, LIU Xinxin, YANG Jiajia. Generalized free surface multiple suppression technique based on model optimization and its application to the deep water of the Indian Ocean[J]. Marine Geology & Quaternary Geology, 2021, 41(5): 221-230. doi: 10.16562/j.cnki.0256-1492.2020101202

Generalized free surface multiple suppression technique based on model optimization and its application to the deep water of the Indian Ocean

1.
Qingdao Institute of Marine Geology, China Geological Survey,Qingdao 266237, China
2.
Laboratory for Marine Mineral Resources, Qingdao National Laboratory for Marine Science and Technology, Qingdao 266237, China

More Information

Corresponding author: YAN Zhonghui, zhonghui4564573@163.com

Received Date: 12 October 2020

Revised Date: 07 December 2020

Publish Date: 28 October 2021

Abstract

Abstract

The bottom of the deep water area of the Indian Ocean is rather flat, and the main multiples are usually related to the multiples created by strong energy and wide frequency wave band, which are difficult to be removed by the conventional generalized free surface multiples prediction technique. In order to solve the problem, the multi-wave model is improved with the generalized free surface multi-wave prediction technique, and thus the original data are separated into two parts, i.e. low frequency data and high frequency data. The low-frequency data may be converted into curvelet domain to optimize the multi-wave model. Reducing the multi-wave model directly from the original data, multiples are suppressed. The technique has been successfully applied in the deep waters of the Indian Ocean, as the correlation multiples of the seabed are suppressed, the effective signals highlighted, and the signal-to-noise ratio and quality of the profile obviously improved.
- multiwave /
- GSMP technique /
- curvelet transform /
- multiwave model /
- signal to noise ratio

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References

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