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Separation of diffracted waves via SVD filter

Petroleum Science 2020年第5期17卷 1259-1271页

作者： Hong-Yan Shen Qin Li Yue-Ying Yan Xin-Xin Li Jing Zhao School of Earth Sciences and Engineering Xi’an Shiyou UniversityXi’an 710065ShaanxiChina Key Laboratory of Shaanxi Province for Oil and Gas

Diffracted seismic waves may be used to help identify and track geologically heterogeneous bodies or ***,the energy of diffracted waves is weaker than that of ***,the extraction of diffracted waves is the basis for the effective utilization of diffracted *** on the difference in travel times between diffracted and reflected waves,we developed a method for separating the diffracted waves via singular value decomposition filters and presented an effective processing flowchart for diffracted wave separation and *** research results show that the horizontally coherent difference between the reflected and diffracted waves can be further improved using normal move-out(NMO) ***,a band-rank or high-rank approximation is used to suppress the reflected waves with better transverse ***,separation of reflected and diffracted waves is achieved after the filtered data are transformed into the original data domain by inverse *** and field examples show that our proposed method has the advantages of fewer constraints,fast processing speed and complete extraction of diffracted *** the diffracted wave imaging results can effectively improve the identification accuracy of geological heterogeneous bodies or zones.

关键词： Geological heterogeneity Reflected waves Diffracted waves SVD filter Seismic wave field separation migration imaging

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Prestack migration velocity analysis based on simplified two-parameter moveout equation

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Applied Geophysics 2016年第1期13卷 135-144,220,221页

作者：陈海峰李向阳钱忠平宋建军赵桂玲中国石油东方地球物理公司河北涿州072751 中国石油大学(北京)油气资源与探测国家重点实验室北京102249 中国石油大学(北京)CNPC物探重点实验室北京102249 英国地质调查局 Murchison HouseWest Mains RoadEdinburgh EH9 3LAU.K.

Stacking velocity V_（C2）,vertical velocity ratio γ_0,effective velocity ratio γ_（eff）,and anisotropic parameter x_（eff） are correlated in the PS-converted-wave（PS-wave） anisotropic prestack Kirchhoff time migration（PKTM） velocity model and are thus difficult to independently *** extended the simplified two-parameter（stacking velocity V_（C2） and anisotropic parameter k_（eff）） moveout equation from stacking velocity analysis to PKTM velocity model updating and formed a new four-parameter（stacking velocity V_（C2）,vertical velocity ratio γ_0,effective velocity ratio γ_（eff）,and anisotropic parameter k_（eff）） PS-wave anisotropic PKTM velocity model updating and process flow based on the simplified twoparameter moveout *** the proposed method,first,the PS-wave two-parameter stacking velocity is analyzed to obtain the anisotropic PKTM initial velocity and anisotropic parameters;then,the velocity and anisotropic parameters are corrected by analyzing the residual moveout on common imaging point gathers after prestack time *** vertical velocity ratio γ_0 of the prestack time migration velocity model is obtained with an appropriate method utilizing the P- and PS-wave stacked sections after level *** initial effective velocity ratio γ_（eff） is calculated using the Thomsen（1999） equation in combination with the P-wave velocity analysis;ultimately,the final velocity model of the effective velocity ratio γ_（eff） is obtained by percentage scanning *** method simplifies the PS-wave parameter estimation in high-quality imaging,reduces the uncertainty of multiparameter estimations,and obtains good imaging results in practice.

关键词： PS-converted-wave PKTM velocity updating two-parameter moveout equation migration imaging

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Study on Wave Field Characteristics and imaging of Collapse Column in Three-Dimensional Detection with Love Channel Wave Reflected outside the Working Face

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Open Journal of Geology 2020年第11期10卷 1027-1039页

作者： Huachao Sun Huide Zhang Jinyun Wang Xianzhuang Lv Xin Ding Shiyu Xing Heng Zhang China University of Mining and Technology School of Resources and Geophysics Xuzhou China Shang Dong Energy Linyi Group Luxi Coalmine Jining China Kaijia Group Yitang Changyuan Coalmine Jiexiu China China University of Mining and Technology School of Mechanics and Civil Engineering Xuzhou China

The safety accidents caused by collapse column water diversion occur frequently, which has great hidden danger to the safety production of coal mine. Limited by the space of underground, the detection of collapse column on the outside of working face has been a difficult problem. Based on this, numerical simulation and imaging research were carried out in this paper. The results indicate that when a seismic source near the roadway is excited, a part of seismic wave propagates along the roadway direction, namely direct P-wave, direct S-wave and direct Love channel wave. When the body waves and Love channel wave propagating to the outside of working face meet the interface of collapse column, the reflected Love channel wave and reflected body waves are generated. Reflection body waves and direct waves are mixed in time domain, which is difficult to identify in seismic records, while reflected Love channel wave whose amplitude is relatively strong. The reflected Love channel wave which has a large interval from other wave trains in the time domain is easily recognizable in seismic record, which makes it suitable for advanced detection of collapse column. The signal-to-noise ratio of X component is higher than that of Y component and Z component. According to the seismic records, polarization filtering was carried out to enhance the effective wave, which removed the interference waves, and the signal was migra

关键词： Reflected Love Channel Wave 3D Numerical Simulation Collapse Column Wave Field Characteristics migration imaging

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migration images guided high-resolution velocity modeling based on fully convolutional neural network

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Global Geology 2024年第3期27卷 145-153页

作者： DU Meng MAO Weijian YANG Maoxin ZHAO Jianzhi Research Center for Computational and Exploration Geophysics State Key Laboratory of Geodesy and Earth’s DynamicsInnovation Academy for Precision Measurement Science and TechnologyChinese Academy of SciencesWuhan 430077China College of Earth and Planetary Sciences University of Chinese Academy of SciencesBeijing 100049China Daqing Geophysical Research Institute BGP CNPC Daqing 163712HeilongjiangChina

Current data-driven deep learning(DL)methods typically reconstruct subsurface velocity models directly from pre-stack seismic ***,these purely data-driven methods are often less robust and produce results that are less physically ***,the authors propose a new method that uses migration images as input,combined with convolutional neural networks to construct high-resolution velocity *** to directly using pre-stack seismic records as input,the nonlinearity between migration images and velocity models is significantly ***,the advantage of using migration images lies in its ability to more comprehensively capture the reflective properties of the subsurface medium,including amplitude and phase information,thereby to provide richer physical information in guiding the reconstruction of the velocity *** approach not only improves the accuracy and resolution of the reconstructed velocity models,but also enhances the physical interpretability and *** experiments on synthetic data show that the proposed method has superior reconstruction performance and strong generalization capability when dealing with complex geological structures,and shows great potential in providing efficient solutions for the task of reconstructing high-wavenumber components.

关键词： deep learning seismic inversion migration imaging velocity modeling

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