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Preconditioning point-source/point-receiver high-density 3D seismic data for lacustrine shale characterization in a loess mountain area

Wang Wei, Wang Xiangzeng, Hongliu Zeng and Liang Quansheng
Preconditioning point-source/point-receiver high-density 3D seismic data for lacustrine shale characterization in a loess mountain area
Interpretation (Tulsa) (May 2017) 5 (2): SF177-SF188

Abstract

In the study area, southeast of Ordos Basin in China, thick lacustrine shale/mudstone strata have been developed in the Triassic Yanchang Formation. Aiming to study these source/reservoir rocks, a 3D full-azimuth, high-density seismic survey was acquired. However, the surface in this region is covered by a thick loess layer, leading to seismic challenges such as complicated interferences and serious absorption of high frequencies. Despite a specially targeted seismic processing workflow, the prestack Kirchhoff time-migrated seismic data were still contaminated by severe noise, hindering seismic inversion and geologic interpretation. By taking account of the particular data quality and noise characteristics, we have developed a cascade workflow including three major methods to condition the poststack 3D seismic data. First, we removed the sticky coherent noise by a local pseudo f-x-y Cadzow filtering. Then, we diminished the random noise by a structure-oriented filtering. Finally, we extended the frequency bandwidth with a spectral-balancing method based on the continuous wavelet transform. The data quality was improved after each of these steps through the proposed workflow. Compared with the original data, the conditioned final data show improved interpretability of the shale targets through geometric attribute analysis and depositional interpretation.


ISSN: 2324-8858
EISSN: 2324-8866
Serial Title: Interpretation (Tulsa)
Serial Volume: 5
Serial Issue: 2
Title: Preconditioning point-source/point-receiver high-density 3D seismic data for lacustrine shale characterization in a loess mountain area
Affiliation: Shaanxi Yanchang Petroleum Company, Research Institute, Xi'an, China
Pages: SF177-SF188
Published: 201705
Text Language: English
Publisher: Society of Exploration Geophysicists, Tulsa, OK, United States
References: 37
Accession Number: 2017-050334
Categories: Economic geology, geology of energy sourcesApplied geophysics
Document Type: Serial
Bibliographic Level: Analytic
Illustration Description: illus. incl. sects., sketch maps
Secondary Affiliation: University of Texas at Austin, USA, United States
Country of Publication: United States
Secondary Affiliation: GeoRef, Copyright 2017, American Geosciences Institute. Reference includes data from GeoScienceWorld, Alexandria, VA, United States. Reference includes data supplied by Society of Exploration Geophysicists, Tulsa, OK, United States
Update Code: 201727
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