YU Jie. Application of pre-stack denoising technique in full digital high density 3D seismic technique in coal mining districts[J]. COAL GEOLOGY & EXPLORATION, 2020, 48(6): 48-54. DOI: 10.3969/j.issn.1001-1986.2020.06.007
Citation: YU Jie. Application of pre-stack denoising technique in full digital high density 3D seismic technique in coal mining districts[J]. COAL GEOLOGY & EXPLORATION, 2020, 48(6): 48-54. DOI: 10.3969/j.issn.1001-1986.2020.06.007

Application of pre-stack denoising technique in full digital high density 3D seismic technique in coal mining districts

Funds: 

National Key R&D Program of China(2018YFC0807803);Independent Innovation Project of Double First Class Construction of China University of Mining and Technology(2018ZZCX05)

More Information
  • Received Date: October 24, 2020
  • Revised Date: November 17, 2020
  • Published Date: December 24, 2020
  • High density 3D seismic technique uses digital detectors to receive data. The high sensitivity of digital detectors makes weaker background noises and the effective signals are recorded by adopting broadband acceptance. Therefore, in the full digital high density seismic exploration, the data collected by digital detectors have higher noise level and lower SNR. Taking the full digital high density 3D seismic data of Huaibei mining area as an example, the paper explains the characteristics of the three main noises in the high density 3D seismic data, including surface wave, abnormal amplitude and multiple wave, and combines the characteristics of the high density 3D seismic data including wide azimuth, high density and multi-offset to makes cross-alignment analysis of surface wave in the direction of in-line and off-line, and designs conical filter according to the characteristics of surface wave to filter it, sets a threshold to identify abnormal amplitude and performs single channel suppression after calculating the envelope of multiple seismic channels, and applies the Radon transform to eliminate multiple waves from the CMP channel set into the domain. After processing the original data, the effective signals are preserved and the SNR is greatly improved.
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