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《Chinese Journal of Geophysics》 2013-06
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Seismic imaging studies of complex high and steep structures in Kuqa depression

FU Li-Yun1, XIAO You-Jun2, SUN Wei-Jia1, WU Chao2, GUAN Xi-Zhu1, ZHANG Jing-Zhou2 1 Institute of Geology and Geophysics, Chinese Academy of Sciences, Beijing 100029,China 2 Tarim Oilfield Company, PetroChina Company Limited, Korla Xinjiang 841000,China  
Seismic imaging generally depends on data quality, velocity reliability, and migrator performance. Complex near-surface geological conditions in Kuqa depression cause extremely low signal-to-noise (S/N) ratios of seismic data. Salts penetrated into overthrust structures are widely distributed, vary in thickness and shape of complex geometries, and distort the imaging of subsalt faults, leading to complicated imaging problems. This article studies three key aspects. In the preprocessing of prestack data, some innovative techniques combined with commercial techniques are employed by three levels to improve data quality and reconstruct the reflections from depths. Three-stage migration velocity analyses, subtle DMO velocity analysis, prestack time-migration, and prestack depth-migration velocity analyses are implemented to build a topology-preservation prestack-migration velocity model. The time-depth conversion of the prestack time-migration velocity model is performed based on the Kuqa-depression modeling theory of salt-related overthrust complex structures combined with the velocity-varying mapping technique. The well-constrained seismic inversion for low-frequency velocities is conducted to handle the syncretization of the well-building and migration-building velocity fields. Finally, prestack time and depth migrations are performed by a semi-analytic degenerate Fourier migrator that improves the imaging of high-wavenumber components. Applications to the Dabei, Bozi, Quele, Xiqiu10, and Xiqiu4 structures result in well-positioned images for salt-related overthrust complex structures.
【Fund】: 国家自然科学基金项目(41130418 40925013);; 国家重点基础研究计划(973计划)项目(2006CB202306)课题资助
【CateGory Index】: P631.4
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