刘洋，1972年10月生，湖北松滋人，博士，教授，博士生导师。主要从事地震勘探方面的教学工作，地震正反演与偏移、多分量地震与VSP、地震资料人工智能处理与解释等方面的研究工作。发表期刊论文250余篇（其中SCI期刊论文130余篇）；获省部级和学会级科技奖一等、二等奖7项，国家级教育教学成果二等奖1项，省部级和学会级教育教学成果奖特等、一等、二等奖共4项；获中国地球物理学会傅承义青年科技奖、刘光鼎地球物理青年科技奖、国际勘探地球物理学家学会（SEG）特别表彰奖、北京市高等学校教学名师奖、SEG雷吉诺德・范信达奖；入选教育部新世纪优秀人才支持计划、新疆天山英才工程。目前任《Geophysics》高级助理主编、《石油地球物理勘探》常务编委、《石油物探》和《Earthquake Science》编委、SEG Global董事会董事、SEG中国指导委员会委员、中国地球物理学会勘探地球物理委员会副主任、中国石油学会石油物探专业委员会副秘书长、全国油标委石油物探专业标准化委员会委员、中国地球物理学会油气地球物理专业委员会和智能地球物理专业委员会及地震学专业委员会委员等。
1.主要研究方向
[1] 地震正反演与偏移；
[2] 多波多分量地震与VSP；
[3] 人工智能地震资料处理和解释。
2.联系方式
[1] 电子邮件：wliuyang@vip.sina.com；liuyang@cup.edu.cn；
[2] 电话：010-89733017。
3.教育与工作经历
[1] 1989年9月在江汉石油学院物探系学习，1993年6月获勘查地球物理专业工学学士学位；1993年9月在天天色天天(北京)地球科学系攻读硕士学位，1995年9月直攻博士，1998年6月获应用地球物理专业工学博士学位。
[2] 1998年9月留校任教，2000年12月晋升为副教授，2006年6月晋升为教授，2008年6月遴选为博士生导师。
[3] 2008年9月至2009年8月在美国德克萨斯大学奥斯汀分校做访问学者，2017年9月至2022年12月在中国天天色天天(北京)克拉玛依校区石油学院工作。
[4] 曾任系副主任(2004-2005)、系党支部书记(2005-2011)、学院副院长(2011-2016)、勘查专业负责人(2021-2022)、学院学术委员会主席(2021-2022)。
[5] 现为中国天天色天天(北京)地球物理学院教授、博士生导师。
4.学术兼职
[1] SEG(国际勘探地球物理学家学会)主办的《Geophysics》期刊副主编（Associate Editor，2015-2021）、助理主编（Assistant Editor，2021-2025）、高级助理主编（Senior Assistant Editor，2025-2026）。
[2] 中国地球物理学会主办的《Applied Geophysics》期刊编委（2006-）、副主编（2017-）。
[3] 《石油地球物理勘探》期刊编委（2003-2023）、常务编委（2023-）。
[4] 《石油物探》期刊编委（2007-）。
[5] 《Earthquake Science》期刊编委（2021-）。
[6] 中国地球物理学会年会（现为中国地球科学联合学术年会）“油气田与煤田地球物理勘探”专题召集人（2001-）。
[7] SEG Global董事会董事（Director of the Board of SEG Global Inc，2024-）。
[8] SEG大学与学生项目委员会委员（2014-2023）。
[9] SEG研究委员会委员（2015-2023）。
[10] SEG提名委员会委员（2020-2022）。
[11] SEG理事会成员及SEG第11区代表（2020-2022）。
[12] 中国地球物理学会勘探地球物理委员会副主任（2023-）。
[13] 中国地球物理学会油气地球物理专业委员会委员（2023-）。
[14] 中国地球物理学会智能地球物理专业委员会委员（2022-）。
[15] 中国地球物理学会地震学专业委员会委员（2023-）
[16] 中国石油学会石油物探专业委员会副秘书长（2022-）。
[17] 全国油标委石油物探专业标准化委员会委员（2018-）。
5.教学
[1] 在教学方面，先后为本科生讲授《C语言程序设计》、《地震勘探原理》、《地震资料数字处理》、《数字信号分析与处理》等课程，为研究生讲授《地球物理资料解释》、《地震资料数字处理》等课程，指导本科生开展地震资料采集、处理与解释等课程实践。1999年至今，累计授课/带实践课程88门次。
[2] 主持编写石油高等院校特色规划教材《地震资料处理与解释实习指导书》，参与编写高等院校石油天然气类规划教材《地震数据处理方法》、高等院校油气人工智能教育教学丛书《智能地球物理基础与应用场景探索》。
[3] 讲授的《地震勘探原理》课程，录制成视频，上传至优酷网、大学生自学网、B站，供免费学习。
[4] 讲授的《数字信号分析与处理》《地震资料数字处理》课程，录制成视频，上传至B站，供免费学习。
[5] 负责的本科课程《地震勘探原理》被评为北京高校“优质本科课程”和学校“金质优课”。
[6] 获国家级教育教学成果二等奖1项，获省部级、学会级教育教学成果奖特等奖1项、一等奖2项、二等奖1项，获北京市高等学校教学名师奖。
6.人才培养
[1] 指导全日制硕士研究生毕业92名、博士研究生毕业21名；硕士生主要在三大石油公司下属企业工作，部分在国内外继续攻读博士学位；毕业的21名博士中，13名在中国海洋大学、长安大学、中国地质大学（北京）、中国天天色天天（北京）克拉玛依校区、长江大学、东北天天色天天、东华理工大学、湖北经济学院、中国科学院地质与地球物理所等高校和科研院所工作，2名在大学做博士后，4名在三大石油公司下属研究院工作，2名留学生在中国石油集团东方地球物理公司工作。
[2] 2008年以来指导的研究生中，获全国百篇优秀博士学位论文提名奖1次，中国地球物理学会优秀博士论文奖1次，李四光优秀硕士研究生奖1次，中国地球物理学会学术年会“优秀学生论文奖”15人次，中国石油物探学术年会“优秀论文”特等奖1次、一等奖1次、二等奖1次，国际学术研讨会“优秀学生报告奖”1次、“最佳口头报告奖”1次、“最佳张贴报告奖”1次，“东方杯”全国大学生勘探地球物理大赛全国一等奖15人次。指导本科生团队获得“东方杯”全国大学生勘探地球物理大赛全国特等奖1次、一等奖1次。
[3] 担任SEG、EAGE学生分会指导教师期间，SEG学生分会于2014年、2016年两次获得全球“山峰学生分会”(从300多个中评选10余个)，EAGE学生分会2016年、2017年连续两年获得全球“最佳学生分会”(从70多个中评选3个)。
[4] 作为主要负责人之一，2013年创办“东方杯”全国大学生勘探地球物理大赛并成功举办六届大赛。
[5] 2015年，指导五名研究生组队参加EAGE的FIELD大赛并获全球第三名。
[6] 2021至2022年，指导六名研究生组队参加SEG的EVOLVE全球项目活动，学生团队获得“Hercules Award”，本人获得“Engaged Faculty Advisor Award”。
[7] 近年来，3名研究生荣获SEG奖学金，6名研究生由SEG资助到美国参加SEG全球学生领袖论坛（Student Leadership Symposium），12名研究生参加SEG的EVOLVE全球项目活动（其中2名研究生由SEG资助到美国汇报），52人次研究生出国参加SEG、EAGE年会。
7.科研
[1] 在科研及学术成果方面，长期从事地震勘探理论与方法研究工作，作为第一负责人完成教育部“新世纪优秀人才支持计划”项目、“油气资源与探测”国家重点实验室“杰出人才”培育课题、国家自然科学基金面上项目、国家863“探索导向类”项目、国家油气重大专项子课题、教育部回国留学启动基金、中国石油科技中青年创新基金等科研项目多项，在地震波动方程数值模拟、逆时偏移成像、全波形反演、多分量地震、提高地震资料分辨率、人工智能地震资料处理与解释等方面的研究中取得进展。
[2] 至2025年9月，共发表期刊论文250余篇，被SCI收录130余篇，SCI他引2100余次；以第一作者、通讯作者发表SCI期刊论文110余篇，其中国际SCI期刊论文80余篇。
[3] 2010年发表在美国《Geophysics》期刊上关于混合吸收边界条件的论文，被SEG主办的期刊《The Leading Edge》报道为地球物理亮点(Geophysics Bright Spots)。
[4] 1篇论文2014年获得国际SCI期刊《Journal of Geophysics and Engineering》最佳论文奖(Best Paper Award)。
[5] 1篇2020年发表的深度学习地震相识别论文图片，被作为国际SCI期刊《IEEE Geoscience and Remote Sensing Letters》的封面。
[6] 1篇2024年发表的人工智能扩散模型提高地震资料分辨率论文，被作为SCI期刊《Petroleum Science》的封面论文。
[7] 发表在英国《Geophysical Journal International》、美国《Geophysics》期刊上的2篇论文入选2012年SEG出版的地球物理再版系列书(Geophysics Reprints Series book)《Numerical Modeling of Seismic Wave Propagation: Gridded Two-way Wave-equation Methods》，该书从20余种国际期刊、国际会议上发表的论文中遴选出78篇文献。
[8] 关于混合吸收边界条件的研究成果，被SEG出版的专著《3D Seismic Survey Design》(2012)和《Seismic Inversion》(2017)，以及Springer出版的百科词典《Encyclopedia of Solid Earth Geophysics (2nd edition)》(2021)介绍与推荐。
[9] 关于混合吸收边界条件、提高有限差分正演精度和效率的论文成果，得到来自美国、中国、日本、韩国、巴西、瑞士、希腊、印度、墨西哥、沙特等多个国家的学者的研究、应用或发展；15篇正演论文得到地学、数学、物理、计算机科学、工程等领域70余家国际SCI期刊论文他引。
[10] 完成10项国家软件著作权登记，获12项授权国家发明专利，获省部级、学会级科技奖励一等奖2项、二等奖5项。
[11] 1999年获中国地球物理学会傅承义青年科技奖，2010年入选教育部新世纪优秀人才支持计划，2011年获刘光鼎地球物理青年科技奖，2017年入选新疆天山英才工程，2020年被聘为新疆二级教授，2021年获SEG特别表彰奖(Special Commendation)，2025年获SEG雷吉诺德・范信达奖(Reginald Fessenden Award)。
8.波动方程正反演与偏移论文（代表性论文）
15篇波动方程正演代表性论文（本人第一作者且通讯作者论文）
[1] Yang Liu, Mrinal K. Sen, 2010, A hybrid scheme for absorbing edge reflections in numerical modeling of wave propagation, Geophysics, 75(2), A1–A6.
[2] Yang Liu, Mrinal K. Sen, 2012, A hybrid absorbing boundary condition for elastic staggered-grid modeling, Geophysical Prospecting, 60(6), 1114–1132.
[3] Yang Liu, Mrinal K. Sen, 2018, An improved hybrid absorbing boundary condition for wave equation modeling, Journal of Geophysics and Engineering, 15(6), 2602–2613.
[4] Yang Liu, Mrinal K. Sen, 2009, An implicit staggered-grid finite-difference method for seismic modeling, Geophysical Journal International, 179(1), 459–474
[5] Yang Liu, Mrinal K. Sen, 2009, A new time-space domain high-order finite-difference method for the acoustic wave equation, Journal of Computational Physics, 228(23), 8779–8806
[6] Yang Liu, Mrinal K. Sen, 2009, A practical implicit finite-difference method, examples from seismic modeling, Journal of Geophysics and Engineering, 6(3), 231–249.
[7] Yang Liu, Mrinal K. Sen, 2010, Acoustic VTI modeling with a time–space domain dispersion-relation-based finite-difference scheme, Geophysics, 75(3), A7–A13.
[8] Yang Liu, Mrinal K. Sen, 2011, Finite-difference modeling with adaptive variable length spatial operators, Geophysics, 76(4), T79–T89.
[9] Yang Liu, Mrinal K. Sen, 2011, Scalar wave equation modeling with time–space domain dispersion-relation-based staggered-grid finite-difference schemes, Bulletin of the Seismological Society of America, 101(1), 141–159.
[10] Yang Liu, Mrinal K. Sen, 2013, Time–space domain dispersion-relation-based finite-difference method with arbitrary even-order accuracy for the 2D acoustic wave equation, Journal of Computational Physics, 232(1), 327–345.
[11] Yang Liu, 2013, Globally optimal finite-difference schemes based on least squares, Geophysics, 78(4), T113–T132.
[12] Yang Liu, 2014, Optimal staggered-grid finite-difference schemes based on least squares for wave equation modeling, Geophysical Journal International, 197(2), 1033–1047.
[13] Yang Liu, 2020, Acoustic and elastic finite-difference modeling by optimal variable-length spatial operators, Geophysics, 85(2), T57–T70.
[14] Yang Liu, 2020, Maximizing the CFL number of stable time–space domain explicit finite-difference modeling, Journal of Computational Physics, 416, 109501.
[15] Yang Liu, 2022, Removing the stability limit of the time–space domain explicit finite difference schemes for acoustic modeling with stability condition-based spatial operators, Geophysics, 87(3), T205–T223.
部分波动方程正反演与偏移论文（学生第一作者、本人通讯作者论文）
[1] Wenbin Tian, Yang Liu, 2024, Extraction of ADCIGs in viscoelastic media based on fractional viscoelastic equations, Petroleum Science, 21(6), 4062–4066.
[2] Jingyi Xu, Yang Liu, 2024, A stable staggered-grid finite-difference scheme for acoustic modeling beyond conventional stability limit, Petroleum Science, 21(1), 182–194.
[3] Wenbin Tian, Yang Liu, Zilong Dong, 2024, Unbalanced optimal transport for full waveform inversion in visco-acoustic media, Journal of Geophysics and Engineering, 21(1), 184–199.
[4] Wenbin Tian, Yang Liu, Xi Di, 2024, Enhancing seismic waveform inversion using a three-step strategy with adversarial neural networks and seismic envelope, IEEE Geoscience and Remote Sensing Letters, 21, 7505105.
[5] Hongyu Zhou, Yang Liu, Jing Wang, 2023, Two exact first-order k-space formulations for low-rank viscoacoustic wave propagation on staggered grids, Petroleum Science, 20(3), 1521–1531.
[6] Hongyu Zhou, Yang Liu, Jing Wang, 2023, K-space dispersion error compensators for the fractional spatial derivatives based constant-Q viscoelastic wave equation modeling, Journal of Computational Physics, 487, 112161.
[7] Zhennan Yu, Yang Liu, 2022, Full-waveform inversion for reverse vertical seismic profiling data based on a variant of the optimal transport theory, Geophysical Prospecting, 70(7), 1163-1175.
[8] Hongyu Zhou, Yang Liu, Jing Wang, 2022, Elastic wave modeling with high-order temporal and spatial accuracy by selectively modified staggered-grid finite-difference and its linear optimization scheme, IEEE Transactions on Geoscience and Remote Sensing, 60, 3000122.
[9] Hongyu Zhou, Yang Liu, Jing Wang, 2022, Time–space domain scalar wave modeling by a new hybrid staggered-grid finite-difference method with high temporal and spatial accuracy, Journal of Computational Physics, 455, 111004.
[10] Hongyu Zhou, Yang Liu, Jing Wang, Yuanyuan Ma, 2022, Novel first order k-space formulations for wave propagation by asymmetrical factorization of space-wavenumber domain wave propagator, Geophysics, 87(6), T417-T433.
[11] Jing Wang, Yang Liu, Hongyu Zhou, 2022, High temporal accuracy elastic wave simulation with new time–space domain implicit staggered-grid finite-difference schemes, Geophysical Prospecting, 70(8), 1346-1366.
[12] Yabing Zhang, Yang Liu, Shigang Xu, 2021, Viscoelastic wave simulation with high temporal accuracy using time-domain complex-valued equations, Surveys in Geophysics, 42, 97-132.
[13] Yabing Zhang, Yang Liu, Shigang Xu, 2020, Arbitrary-order Taylor expansion based viscoacoustic wavefield simulation in 3D VTI media, Geophysical Prospecting, 68(8), 2379-2399.
[14] Shigang Xu, Yang Liu, 2019, Time-space-domain temporal high-order staggered-grid finite-difference schemes by combining orthogonality and pyramid stencils for 3D elastic-wave propagation, Geophysics, 84(4), T259-T282.
[15] Xin Liu, Yang Liu, Zhiming Ren, Bei Li, 2019, Perfectly matched layer boundary conditions for acoustic wave simulation in mesh-free discretization using frequency domain RBF-FD, Geophysical Prospecting, 67(7), 1732-1744.
[16] Zhiming Ren, Yang Liu, Mrinal K. Sen, 2017, Least-squares reverse time migration in elastic media, Geophysical Journal International, 208 (2), 1103-1125.
[17] Bei Li, Yang Liu, Mrinal K. Sen, Zhiming Ren, 2017, Time-space-domain mesh-free finite-difference based on least-squares for 2D acoustic wave modeling, Geophysics, 82(4), T143-T157.
[18] Enjiang Wang, Yang Liu, Mrinal K. Sen, 2016, Effective finite-difference modelling methods with 2-D acoustic wave equation using a combination of cross and rhombus stencils, Geophysical Journal International, 206(3), 1933-1958.
[19] Zhiming Ren, Yang Liu, 2016, A hierarchical elastic full-waveform inversion scheme based on wavefield separation and the multistep-length approach, Geophysics, 81(3), R99-R123.
[20] Zhiming Ren, Yang Liu, 2015, Acoustic and elastic modeling by optimal time–space domain staggered-grid finite-difference schemes, Geophysics, 80(1), T17-T40.
[21] Zhiming Ren, Yang Liu, 2015, Elastic full waveform inversion using the second generation wavelet and an adaptive operator length scheme, Geophysics, 80(4), R155-R174.
[22] Zhiming Ren, Yang Liu, Qunshan Zhang, 2014, Multiscale viscoacoustic waveform inversion with the second generation wavelet transform and adaptive time–space domain finite-difference method, Geophysical Journal International, 197 (2), 948-974.
[23] Hongyong Yan, Yang Liu, 2013, Visco-acoustic prestack reverse-time migration based on time–space domain adaptive high-order finite-difference method, Geophysical Prospecting, 61(5), 941-954.
9.人工智能地震资料处理与解释论文（所有期刊论文）
[1] 刘洋, 孙宇航, 张浩然, 田文彬, 陈桂, 马江涛, 2025, 人工智能地震资料处理与解释方法研究进展, 石油地球物理勘探, 60(4): 1067-1087.
[2] Gui Chen, Yang Liu, Mi Zhang, Yuhang Sun, Haoran Zhang, 2025, Unsupervised seismic reconstruction via deep learning with one-dimensional signal representation, Computers and Geosciences, 200, 105916.
[3] Dingding Deng, Yang Liu, Gui Chen, Jiangtao Ma, Yujiao Wang, 2025, A wavefield decomposition-guided deep-learning framework for removing smearing artifacts from VSP RTM, Journal of Geophysics and Engineering, 22 (4), 1085–1095.
[4] Wenbin Tian, Yang Liu, Yibo Zhang, 2025, Enhancing learning to solve multicomponent fractional viscoelastic equations with U-net Fourier neural operators, Journal of Geophysics and Engineering, 22(1), 16–35.
[5] Tengyu Wang, Dingding Deng, Duoming Zheng, Zhen Zhang, Wenjun Luo, Yang Liu, 2025, Joint P- and S-wave VSP Traveltime Tomography via Well Log-Guided Physics-Informed Neural Networks, IEEE Access, 13, 133280–13292.
[6] Mi Zhang, Kai Jiao, Yang Liu, Gui Chen, Haoran Zhang, 2025, Resolution-enhanced BM3D for post-stack weak signal recovery, Journal of Geophysics and Engineering, 22 (4), 1115–1131.
[7] 李钦昭, 刘洋, 席念旭, 张浩然, 邸希, 2025, 基于互相关约束和CNN-GRU网络的井震自动标定, 石油地球物理勘探, 60(3), 564-575.
[8] 邸希, 刘洋, 2025, 深度学习在地震断层解释中的研究进展, 地球物理学进展, 40(4), 1688–1716.
[9] 赵军才, 马江涛, 刘洋, 王宁, 胡亚东, 谭勇, 2025,基于多数据融合和自适应加权混合损失函数约束的地震波初至智能拾取方法, 石油物探, 64(4): 691–700.
[10] Yu-Hang Sun, Hong-Li Dong, Gui Chen, Xue-Gui Li, Yang Liu, Xiao-Hong Yu, Jun Wu, 2025, Intelligent seismic AVO inversion method for brittleness index of shale oil reservoirs, Petroleum Science, 22(2), 627-640
[11] Gui Chen, Yang Liu, Yuhang Sun, 2024, Unsupervised 3D seismic data reconstruction using a weighted-attentive deep learning framework, Geophysics, 89(6), V635–V652.
[12] Haoran Zhang, Yang Liu, 2024, SeisResoDiff: Seismic resolution enhancement based on a diffusion model, Petroleum Science, 21(5), 3166–3188.
[13] Gui Chen, Yang Liu, Xi Di, Haoran Zhang, 2024, CO2Seg: Automatic CO2 segmentation from 4-D seismic image using convolutional vision transformer, IEEE Transactions on Geoscience and Remote Sensing, 62, 4505014.
[14] Gui Chen, Yang Liu, 2024, FUDLInter: Frequency-space-dependent unsupervised deep learning framework for 3D and 5D seismic data interpolation, IEEE Transactions on Geoscience and Remote Sensing, 62, 5922018.
[15] Gui Chen, Yang Liu, 2024, Combining unsupervised deep learning and Monte Carlo dropout for seismic data reconstruction and its uncertainty quantification, Geophysics, 89(1), WA53–WA65.
[16] Wenbin Tian, Yang Liu, Xi Di, 2024, Enhancing seismic waveform inversion using a three-step strategy with adversarial neural networks and seismic envelope, IEEE Geoscience and Remote Sensing Letters, 21, 7505105.
[17] 杨菲, 刘洋, 常锁亮, 陈桂, 2024, 基于双向GRU和注意力机制的叠前地震孔隙度预测方法, 石油物探, 63(3), 598–609.
[18] Yuhang Sun, Yang Liu, Hongli Dong, Gui Chen, Xuegui Li, 2024, Seismic AVO inversion method for viscoelastic media based on a tandem invertible neural network model, IEEE Transactions on Geoscience and Remote Sensing, 62, 5903418.
[19] Yuhang Sun, Hongli Dong, Gui Chen, Yamin Shang, Liyan Zhang, Yang Liu, 2024, Seismic PP-Wave AVO inversion method for VTI media based on double discriminator conditional generative adversarial networks, IEEE Transactions on Geoscience and Remote Sensing, 62, 5928021.
[20] Haoran Zhang, Tariq Alkhalifah, Yang Liu, Claire Birnie, Xi Di, 2023, Improving the generalization of deep neural networks in seismic resolution enhancement, IEEE Geoscience and Remote Sensing Letters, 20, 7500105.
[21] Carlos Honorio Bastidas Pérez, Yang Liu, 2023, Three-dimensional initial salt body building for full-waveform inversion assisted by deep learning, IEEE Geoscience and Remote Sensing Letters, 20, 3002105.
[22] David Cova, Yang Liu, 2023, Shear wave velocity prediction using bidirectional recurrent gated graph convolutional network with total information embeddings, Frontiers in Earth Science, 11, 1101601.
[23] 李键, 陈桂, David Cova, 孙永壮, 孙宇航, 刘洋, 2023, 一种基于ConvLSTM神经网络的TOC含量地震预测方法, 地球物理学进展, 38(3), 1143–1151.
[24] Yuhang Sun, Yang Liu, 2022, Model-data-driven P-wave impedance inversion using U-Net convolutional neural networks and normalized zero-lag cross-correlation objective function, Petroleum Science, 19(6), 2711–2719.
[25] Jinshui Liu, Yuhang Sun, Yang Liu, 2022, Model-data-driven seismic inversion method based on small sample data, Petroleum Exploration and Development, 49(5), 1046–1055.
[26] Yuhang Sun, Yang Liu, Mi Zhang, Haoran Zhang, 2022, Inversion of low–medium frequency velocities and density from AVO data using invertible neural network, Geophysics, 87(3), A37-A42.
[27] Mi Zhang, Yang Liu, 2022, 3D Seismic Data Recovery via Neural Network Based Matrix Completion, IEEE Geoscience and Remote Sensing Letters, 19, 8026305.
[28] Haoran Zhang, Ping Yang, Yang Liu, Yaneng Luo, Jingyi Xu, 2022, Deep learning-based low-frequency extrapolation and impedance inversion of seismic data, IEEE Geoscience and Remote Sensing Letters, 19, 7505905.
[29] Gui Chen, Yang Liu, Mi Zhang, and Haoran Zhang, 2022, Dropout-based robust self-supervised deep learning for seismic data denoising, IEEE Geoscience and Remote Sensing Letters, 19, 8027205..
[30] 马江涛, 刘洋, 张浩然, 2022, 地震相智能识别研究进展, 石油物探, 61(2), 262-275.
[31] Yuhang Sun, Yang Liu, 2021, Model-data-driven AVO inversion method based on multiple objective functions, Applied Geophysics, 18(4), 525-536.
[32] Haoran Zhang, Tiansheng Chen, Yang Liu, Yuxi Zhang, Jiong Liu, 2021, Automatic seismic facies interpretation based on supervised deep learning, Geophysics, 86(1), IM15-IM33.
[33] David Cova, 刘洋, 丁成震, 魏程霖, 胡飞, 李韵竹 2021, 人工智能和视速度约束的地震波初至拾取方法, 石油地球物理勘探, 56(3), 419–435.
[34] 孙宇航, 刘洋, 2021, 基于无监督深度学习的多波AVO反演及储层流体识别, 石油物探, 60 (3), 385–394.
[35] 陈桂, 刘洋, 2021, 基于人工智能的断层自动识别研究进展, 地球物理学进展, 36(1), 119–131.
[36] Yuxi Zhang, Yang Liu, Haoran Zhang, Hao Xue, 2020, Seismic facies analysis based on deep learning, IEEE Geoscience and Remote Sensing Letters, 17(7): 1119–1123.
[37] 张玉玺, 刘洋, 张浩然, 吕文杰, 薛浩, 2020, 基于深度学习的多属性盐丘自动识别方法, 石油地球物理勘探, 55(3):475–483.
[38] 孙宇航, 刘洋, 2020, 基于GRU神经网络的横波速度预测方法, 石油地球物理勘探, 55(3):484–492, 503.
[39] Mi Zhang, Yang Liu, Min Bai, and Yangkang Chen, 2019, Seismic noise attenuation using unsupervised sparse feature learning, IEEE Transactions on Geoscience and Remote Sensing, 57(12).
[40] Mi Zhang, Yang Liu and Yangkang Chen, 2019, Unsupervised seismic random noise attenuation based on deep convolutional neural network, IEEE Access, 7: 179810–179822.
10.期刊论文（分年度）
2025年
[1] 刘洋, 孙宇航, 张浩然, 田文彬, 陈桂, 马江涛, 2025, 人工智能地震资料处理与解释方法研究进展, 石油地球物理勘探, 60(4): 1067-1087.
[2] Gui Chen, Yang Liu, Mi Zhang, Yuhang Sun, Haoran Zhang, 2025, Unsupervised seismic reconstruction via deep learning with one-dimensional signal representation, Computers & Geosciences, 200, 105916.
[3] Wenbin Tian, Yang Liu, Yibo Zhang, 2025, Enhancing learning to solve multicomponent fractional viscoelastic equations with U-net Fourier neural operators, Journal of Geophysics and Engineering, 22(1), 16–35.
[4] Dingding Deng, Yang Liu, Gui Chen, Jiangtao Ma, Yujiao Wang, 2025, A wavefield decomposition-guided deep-learning framework for removing smearing artifacts from VSP RTM, Journal of Geophysics and Engineering, 22 (4), 1085–1095.
[5] 李钦昭, 刘洋, 席念旭, 张浩然, 邸希, 2025, 基于互相关约束和CNN-GRU网络的井震自动标定, 石油地球物理勘探, 60(3), 564-575.
[6] 董子龙, 刘洋, 孙宇航, 田文彬, 邸希, 2024, 应用互相关目标函数和贝叶斯理论的纵波和转换波联合AVO反演方法, 石油地球物理勘探, 60(3), 761-774.
[7] Tengyu Wang, Dingding Deng, Duoming Zheng, Zhen Zhang, Wenjun Luo, Yang Liu, 2025, Joint P- and S-wave VSP Traveltime Tomography via Well Log-Guided Physics-Informed Neural Networks, IEEE Access, 13, 133280–13292.
[8] 赵军才, 马江涛, 刘洋, 王宁, 胡亚东, 谭勇, 2025, 基于多数据融合和自适应加权混合损失函数约束的地震波初至智能拾取方法, 石油物探, 64(4): 691–700.
[9] Yu-Hang Sun, Hong-Li Dong, Gui Chen, Xue-Gui Li, Yang Liu, Xiao-Hong Yu, Jun Wu, 2025, Intelligent seismic AVO inversion method for brittleness index of shale oil reservoirs, Petroleum Science, 22(2), 627-640.
[10] Mi Zhang, Kai Jiao, Yang Liu, Gui Chen, 2025, Haoran Zhang, Resolution-enhanced BM3D for post-stack weak signal recovery, Journal of Geophysics and Engineering, 22 (4), 1115–1131.
2024年
[11] Jingyi Xu, Yang Liu, 2024, A stable staggered-grid finite-difference scheme for acoustic modeling beyond conventional stability limit, Petroleum Science, 21(1), 182–194.
[12] Haoran Zhang, Yang Liu, 2024, SeisResoDiff: Seismic resolution enhancement based on a diffusion model, Petroleum Science, 21(5), 3166–3188.
[13] Wenbin Tian, Yang Liu, 2025, Extraction of ADCIGs in viscoelastic media based on fractional viscoelastic equations, Petroleum Science, 21(6), 4062–4066.
[14] Gui Chen, Yang Liu, Xi Di, Haoran Zhang, 2024, CO2Seg: Automatic CO2 segmentation from 4-D seismic image using convolutional vision transformer, IEEE Transactions on Geoscience and Remote Sensing, 62, 4505014.
[15] Gui Chen, Yang Liu, 2024, FUDLInter: Frequency-space-dependent unsupervised deep learning framework for 3D and 5D seismic data interpolation, IEEE Transactions on Geoscience and Remote Sensing, 62, 5922018.
[16] Gui Chen, Yang Liu, 2024, Combining unsupervised deep learning and Monte Carlo dropout for seismic data reconstruction and its uncertainty quantification, Geophysics, 89(1), WA53–WA65.
[17] Gui Chen, Yang Liu, Yuhang Sun, 2024, Unsupervised 3D seismic data reconstruction using a weighted-attentive deep learning framework, Geophysics, 89(6), V635–V652.
[18] Gui Chen, Yang Liu, Mi Zhang, Yuhang Sun, Haoran Zhang, 2024, Low-rank approximation reconstruction of five-dimensional seismic data, Surveys in Geophysics, 45, 1459–1492.
[19] Wenbin Tian, Yang Liu, Zilong Dong, 2024, Unbalanced optimal transport for full waveform inversion in visco-acoustic media, Journal of Geophysics and Engineering, 21(1), 184–199.
[20] Wenbin Tian, Yang Liu, Xi Di, 2024, Enhancing seismic waveform inversion using a three-step strategy with adversarial neural networks and seismic envelope, IEEE Geoscience and Remote Sensing Letters, 21, 7505105.
[21] 杨菲, 刘洋, 常锁亮, 陈桂, 2024, 基于双向GRU和注意力机制的叠前地震孔隙度预测方法, 石油物探, 63(3), 598–609.
[22] 许静怡, 王瑞贞, 张亚兵, 刘洋, 2024, 地震衰减模型的研究进展, 地球物理学进展, 39(2): 525–541.
[23] 张亚兵, 刘洋, 陈同俊, 2024, 基于分数阶Zener模型的VTI黏弹性介质频变Q效应数值模拟, 地球物理学报, 67(9): 3510–3526.
[24] Yabing Zhang, Tongjun Chen, Hejun Zhu, Yang Liu, 2024, A stable Q-compensated reverse-time migration method using a modified fractional viscoacoustic wave equation, Geophysics, 89(1), S15–S29.
[25] Yabing Zhang, Hejun Zhu, Yang Liu, Tongjun Chen, 2024, Frequency-dependent Q simulation and viscoacoustic reverse time migration based on the fractional Zener model, Geophysics, 89(1), S47–S59.
[26] Yabing Zhang, Hejun Zhu, Yang Liu, Tongjun Chen, 2024, Power-law frequency-dependent Q simulations in viscoacoustic media using decoupled fractional Laplacians, Geophysics, 89(4), T183–T194.
[27] Yuhang Sun, Yang Liu, Hongli Dong, Gui Chen, Xuegui Li, 2024, Seismic AVO inversion method for viscoelastic media based on a tandem invertible neural network model, IEEE Transactions on Geoscience and Remote Sensing, 62, 5903418.
[28] Yuhang Sun, Hongli Dong, Gui Chen, Yamin Shang, Liyan Zhang, Yang Liu, 2024, Seismic PP-Wave AVO inversion method for VTI media based on double discriminator conditional generative adversarial networks, IEEE Transactions on Geoscience and Remote Sensing, 62, 5928021.
2023年
[29] Hongyu Zhou, Yang Liu, Jing Wang, 2023, K-space dispersion error compensators for the fractional spatial derivatives based constant-Q viscoelastic wave equation modeling, Journal of Computational Physics, 487, 112161.
[30] Carlos Honorio Bastidas Pérez, Yang Liu, 2023, Three-dimensional initial salt body building for full-waveform inversion assisted by deep learning, IEEE Geoscience and Remote Sensing Letters, 20, 3002105.
[31] Hongyu Zhou, Yang Liu, Jing Wang, 2023, Two exact first-order k-space formulations for low-rank viscoacoustic wave propagation on staggered grids, Petroleum Science, 20(3), 1521-1531.
[32] David Cova, Yang Liu, 2023, Shear wave velocity prediction using bidirectional recurrent gated graph convolutional network with total information embeddings, Frontiers in Earth Science, 11, 1101601.
[33] Haoran Zhang, Tariq Alkhalifah, Yang Liu, Claire Birnie, Xi Di, 2023, Improving the generalization of deep neural networks in seismic resolution enhancement, IEEE Geoscience and Remote Sensing Letters, 20, 7500105.
[34] 王静, 刘洋, 周泓宇, 2023, 时间-空间高阶精度矩形交错网格隐式有限差分声波正演模拟, 地球物理学报, 66(1), 368-382.
[35] Yabing Zhang, Tongjun Chen, Hejun Zhu, Yang Liu, Tao Xing, Xin Zhang, 2023, Approximating constant-Q seismic wave propagations in acoustic and elastic media using a Cole-Cole model, Bulletin of the Seismological Society of America, 113(1), 312-332.
[36] 李键, 陈桂, David Cova, 孙永壮, 孙宇航, 刘洋, 2023, 一种基于ConvLSTM神经网络的TOC含量地震预测方法, 地球物理学进展, 38(3), 1143-1151.
[37] Yabing Zhang, Tongjun Chen, Yang Liu, Hejun Zhu, 2023, High temporal accuracy viscoacoustic wave propagation based on k-space compensation and the fractional-Zener model, Surveys in Geophysics, 44, 821-845.
2022年
[38] Yang Liu, 2022, Removing the stability limit of the time–space domain explicit finite difference schemes for acoustic modeling with stability condition-based spatial operators, Geophysics, 87(3), T205-T223.
[39] Yuhang Sun, Yang Liu, Mi Zhang, Haoran Zhang, 2022, Inversion of low–medium frequency velocities and density from AVO data using invertible neural network, Geophysics, 87(3), A37-A42.
[40] Hongyu Zhou, Yang Liu, Jing Wang, Yuanyuan Ma, 2022, Novel first order k-space formulations for wave propagation by asymmetrical factorization of space-wavenumber domain wave propagator, Geophysics, 87(6), T417-T433.
[41] Hongyu Zhou, Yang Liu, Jing Wang, 2022, Elastic wave modeling with high-order temporal and spatial accuracy by selectively modified staggered-grid finite-difference and its linear optimization scheme, IEEE Transactions on Geoscience and Remote Sensing, 60, 3000122.
[42] Hongyu Zhou, Yang Liu, Jing Wang, 2022, Time–space domain scalar wave modeling by a new hybrid staggered-grid finite-difference method with high temporal and spatial accuracy, Journal of Computational Physics, 455, 111004.
[43] Haoran Zhang, Ping Yang, Yang Liu, Yaneng Luo, Jingyi Xu, 2022, Deep learning-based low-frequency extrapolation and impedance inversion of seismic data, IEEE Geoscience and Remote Sensing Letters, 19, 7505905.
[44] Mi Zhang, Yang Liu, 2022, 3D seismic data recovery via neural network based matrix completion, IEEE Geoscience and Remote Sensing Letters, 19, 8026305.
[45] Gui Chen, Yang Liu, Mi Zhang, Haoran Zhang, 2022, Dropout-based robust self-supervised deep learning for seismic data denoising, IEEE Geoscience and Remote Sensing Letters, 19, 8027205.
[46] Yuhang Sun, Yang Liu, 2022, Model-data-driven P-wave impedance inversion using U-Net convolutional neural networks and normalized zero-lag cross-correlation objective function, Petroleum Science, 19(6), 2711-2719.
[47] Jing Wang, Yang Liu, Hongyu Zhou, 2022, A new linear optimized time–space domain spatial implicit and temporal high-order finite-difference scheme for scalar wave modeling, Journal of Applied Geophysics, 201, 104637.
[48] Zhennan Yu, Yang Liu, 2022, Full-waveform inversion for reverse vertical seismic profiling data based on a variant of the optimal transport theory, Geophysical Prospecting, 70(7), 1163-1175.
[49] Jing Wang, Yang Liu, Hongyu Zhou, 2022, High temporal accuracy elastic wave simulation with new time–space domain implicit staggered-grid finite-difference schemes, Geophysical Prospecting, 70(8), 1346-1366.
[50] Yabing Zhang, Yang Liu, Hejun Zhu, Tongjun Chen, Juanjuan Li, 2022, Modified viscoelastic wavefield simulations in the time domain using the new fractional Laplacians, Journal of Geophysics and Engineering, 19(3), 346-361.
[51] Jing Wang, Yang Liu, Hongyu Zhou, 2022, A novel equivalent staggered-grid finite-difference scheme and its optimization strategy for variable-density acoustic wave modelling, Exploration Geophysics, 53(6), 669-682.
[52] 张梦柯, 赵前华, 罗斌, 刘洋, 2022, 钻头随钻地震技术综述, 地球物理学进展, 37(4), 1677-1688.
[53] 马江涛, 刘洋, 张浩然, 2022, 地震相智能识别研究进展, 石油物探, 61(2), 262-275.
[54] Zhennan Yu, Yang Liu, 2022, A robust migration velocity analysis method based on adaptive differential semblance optimization, Journal of Applied Geophysics, 207, 104851.
[55] Jinshui Liu, Yuhang Sun, Yang Liu, 2022, Model-data-driven seismic inversion method based on small sample data, Petroleum Exploration and Development, 49(5), 1046-1055.
[56] Yabing Zhang, Tongjun Chen, Yang Liu, Hejun Zhu, Guanghui Zhu, Yunfei Niu, 2022, Viscoelastic wave propagation in transversely isotropic media based on constant-order fractional polynomial approximations, Geophysics, 87(5), T363-T379.
[57] 徐世刚, 包乾宗, 任志明, 刘洋, 2022, 基于时间高精度空间隐式矩形交错网格有限差分的弹性波数值模拟, 地球物理学报, 65(4), 1389-1401.
[58] 徐世刚, 包乾宗, 任志明, 刘洋, 2022, 结合泊松算法和改进波场分解的各向异性纯声波逆时偏移成像, 石油地球物理勘探, 57(3), 613-623.
2021年
[59] Yabing Zhang, Yang Liu, Shigang Xu, 2021, Viscoelastic wave simulation with high temporal accuracy using time-domain complex-valued equations, Surveys in Geophysics, 42, 97-132.
[60] Haoran Zhang, Tiansheng Chen, Yang Liu, Yuxi Zhang, Jiong Liu, 2021, Automatic seismic facies interpretation using supervised deep learning, Geophysics, 86(1), IM15-IM33.
[61] Zhennan Yu, Yang Liu, 2021, Differential semblance optimization based on the adaptive quadratic Wasserstein distance, Journal of Geophysics and Engineering, 18(5), 605-617.
[62] Jing Wang, Yang Liu, Hongyu Zhou, 2021, Acoustic wave propagation with new spatial implicit and temporal high-order staggered-grid finite-difference schemes, Journal of Geophysics and Engineering, 18(5), 808-823.
[63] Lele Zhang, Yang Liu, Wanli Jia, 2021, Suppressing residual low-frequency noise in VSP reverse time migration by combining wavefield decomposition imaging condition with Poynting vector filtering, Exploration Geophysics, 52(2), 235-244.
[64] Hongyu Zhou, Yang Liu, Jing Wang, 2021, Optimizing orthogonal-octahedron finite-difference scheme for 3D acoustic wave modeling by combination of Taylor-series expansion and Remez exchange method, Exploration Geophysics, 52(3), 335-355.
[65] Zhennan Yu, Yang Liu, 2021, A robust migration velocity analysis through an asymptotic inverse via generalized Radon transform, Exploration Geophysics, 52(6), 643-658.
[66] Yuhang Sun, Yang Liu, 2021, Model-data-driven AVO inversion method based on multiple objective functions, Applied Geophysics, 18(4), 525-536.
[67] David Cova, 刘洋, 丁成震, 魏程霖, 胡飞, 李韵竹 2021, 人工智能和视速度约束的地震波初至拾取方法, 石油地球物理勘探, 56(3), 419-435.
[68] 孙宇航, 刘洋, 2021, 基于无监督深度学习的多波AVO反演及储层流体识别, 石油物探, 60 (3), 385-394.
[69] 陈桂, 刘洋, 2021, 基于人工智能的断层自动识别研究进展, 地球物理学进展, 36(1), 119-131.
[70] Hongyu Zhou, Yang Liu, Jing Wang, 2021, Acoustic finite-difference modeling beyond conventional Courant–Friedrichs–Lewy stability limit: an approach by variable-length temporal and spatial operators, Earthquake Science, 34(2), 123-136.
[71] Mengyao Jiao, Tianyue Hu, Yang Liu, Shaohuan Zu, Weikang Kuang, 2021, Deblending method of multisource seismic data based on a periodically varying cosine code, IEEE Geoscience and Remote Sensing Letters, 18(9), 1675-1670.
[72] Shigang Xu, Qianzong Bao, Yang Liu, 2021, Applying an advanced temporal and spatial high-order finite-difference stencil to 3D seismic wave modeling, Journal of Computational Physics, 436, 110133.
[73] Mengyao Jiao, Tianyue Hu, Yang Liu, Zhenzhen Yu, Shanglin Liang, Lichao Liu, Jiwei Liu, 2021, Effects of periodically varying codes on separation of multisource blended data, Applied Geophysics, 18(3), 331-344.
2020年
[74] Yang Liu, 2020, Acoustic and elastic finite-difference modeling by optimal variable-length spatial operators, Geophysics, 85(2), T57-T70.
[75] Yang Liu, 2020, Maximizing the CFL number of stable time–space domain explicit finite-difference modeling, Journal of Computational Physics, 416, 109501.
[76] Mi Zhang, Yang Liu, Haoran Zhang, Yangkang Chen, 2020, Incoherent noise suppression of seismic data based on robust low-rank approximation, IEEE Transactions on Geoscience and Remote Sensing, 58(12), 9709-9723.
[77] Yuxi Zhang, Yang Liu, Haoran Zhang, Hao Xue, 2020, Seismic facies analysis based on deep learning, IEEE Geoscience and Remote Sensing Letters, 17(7), 1119-1123.
[78] Yabing Zhang, Yang Liu, Shigang Xu, 2020, Arbitrary-order Taylor expansion based viscoacoustic wavefield simulation in 3D VTI media, Geophysical Prospecting, 68(8), 2379-2399.
[79] Yabing Zhang, Yang Liu, Shigang Xu, 2020, Anisotropic viscoacoustic wavemodelling in VTI media using frequency-dependent complex velocity, Journal of Geophysics and Engineering, 17(4), 700-714.
[80] 张玉玺, 刘洋, 张浩然, 吕文杰, 薛浩, 2020, 基于深度学习的多属性盐丘自动识别方法, 石油地球物理勘探, 55(3), 475-483.
[81] 孙宇航, 刘洋, 2020, 基于GRU神经网络的横波速度预测方法, 石油地球物理勘探, 55(3):484-492, 503.
[82] Enjiang Wang, Jing Ba, José M. Carcione, Yang Liu, 2020, Reflection and transmission of plane elastic waves at an interface between two double-porosity media: effect of local fluid flow, Surveys in Geophysics, 41, 283-322.
[83] Enjiang Wang, Jing Ba, José M. Carcione, Yang Liu, Hongchao Dong, 2020, Effect of local fluid flow on the reflection and transmission of elastic waves at an interface between an elastic solid and a double-porosity medium, Geophysics, 85(4), T237-T256.
[84] Shigang Xu, Yang Liu, 2020, Modeling 3D acoustic-wave propagation using modified cuboid-based staggered-grid finite-difference methods with temporal and spatial high-order accuracy, Studia Geophysica Et Geodaetica, 64(4), 465-482.
[85] Lei Shi, Yuhang Sun, Yang Liu, David Cova, Junzhou Liu, 2020, High-order AVO inversion for effective pore-fluid bulk modulus based on series reversion and Bayesian theory, Energies, 13, 1313.
2019年
[86] Mi Zhang, Yang Liu, Min Bai, Yangkang Chen, 2019, Seismic noise attenuation using unsupervised sparse feature learning, IEEE Transactions on Geoscience and Remote Sensing, 57(12), 9709-9723.
[87] Mi Zhang, Yang Liu, Yangkang Chen, 2019, Unsupervised seismic random noise attenuation based on deep convolutional neural network, IEEE Access, 7, 179810-179822.
[88] Shigang Xu, Yang Liu, 2019, Time-space-domain temporal high-order staggered-grid finite-difference schemes by combining orthogonality and pyramid stencils for 3D elastic-wave propagation, Geophysics, 84(4), T259-T282.
[89] Xin Liu, Yang Liu, Zhiming Ren, Bei Li, 2019, Perfectly matched layer boundary conditions for frequency-domain acoustic wave simulation in the mesh-free discretization, Geophysical Prospecting, 67(7), 1732-1744.
[90] Shigang Xu, Yang Liu, 2019, A rectangular staggered-grid finite-difference scheme with fourth-order temporal accuracy for pseudo-acoustic VTI modelling, Exploration Geophysics, 50(1), 94-110.
[91] Yabing Zhang, Yang Liu, Shigang Xu, 2019, Efficient modelling of optimised pure acoustic wave equation in 3D transversely isotropic and orthorhombic anisotropic media, Exploration geophysics, 50(5), 561-574.
[92] Shigang Xu, Yang Liu, 2019, Modelling 3D elastic VTI wave propagation using an optimal k-space operator-based temporal high-accuracy staggered-grid finite-difference scheme, Journal of Applied Geophysics, 170, 103847 (11 pages).
[93] Xiao Wu, Yang Liu, Yong Wang, Shigang Xu, Wanli Jia, 2019, An improved fast converted-wave imaging method, Applied Geophysics, 17(2), 171-184.
[94] Enjiang Wang, Yang Liu, Yuxin Ji, Tiansheng Chen, Tao Liu, 2019, Q full-waveform inversion based on the viscoacoustic equation, Applied Geophysics, 17(1), 77-91.
[95] Enjiang Wang, Jing Ba, Yang Liu, 2019, Temporal high-order time–space domain finite-difference methods for modelling 3D acoustic wave equation on general cuboid grids, Pure and Applied Geophysics, 176, 5391-5414.
[96] 薛浩, 刘洋, 蔡晓慧, 2019, 基于复数波场分解的VSP逆时偏移方法研究, 地球物理学进展, 34(2), 649-657.
2018年
[97] Yang Liu, Mrinal K. Sen, 2018, An improved hybrid absorbing boundary condition for wave equation modeling, Journal of Geophysics and Engineering, 15(6), 2602-2613.
[98] Enjiang Wang, Yang Liu, 2018, An implicit spatial and high-order temporal finite difference scheme for 2D acoustic modelling, Exploration Geophysics, 49(2), 187-201.
[99] Bei Li, Yang Liu, Xin Liu, 2018, Hybrid absorbing boundary condition for piecewise smooth curved boundary in 2D acoustic finite-difference modeling, Exploration Geophysics, 49(4), 469-483.
[100] Shigang Xu, Yang Liu, 2018, Effective modeling and reverse-time migration for novel pure acoustic wave in arbitrary orthorhombic anisotropic media, Journal of Applied Geophysics, 150, 126-143.
[101] Xiaohui Cai, Yang Liu, Zhiming Ren, Acoustic reverse-time migration using GPU card and POSIX thread based on the optimal finite-difference scheme and hybrid absorbing boundary condition, Computers & Geosciences, 115, 42-55.
[102] Shigang Xu, Yang Liu, 2018, Pseudoacoustic tilted transversely isotropic modeling with optimal k-space operator-based implicit finite-difference schemes, Geophysics, 83(3), T139-T157.
[103] Shigang Xu, Yang Liu, 2018, 3D acoustic wave modeling with a time-space-domain temporal high-order finite-difference scheme, Journal of Geophysics and Engineering, 15(5), 1963-1976.
[104] Enjiang Wang, Jing Ba, Yang Liu, 2018, Time-space-domain implicit finite-difference methods for 2D acoustic wave equation modeling, Geophysics, 83(4), T175-T193.
[105] Enjiang Wang, Jing Ba, Yang Liu, 2018, Cross-rhombus stencil-based finite-difference methods for 2D acoustic modeling and reverse-time migration on rectangular grids, Journal of Geophysics and Engineering, 15(6), 2674-2685.
[106] 徐世刚, 刘洋, 2018, 基于优化有限差分和混合吸收边界条件的三维VTI介质声波和弹性波数值模拟, 地球物理学报, 61(7), 2950-2968.
[107] Hao Xue, Yang Liu, 2018, Reverse-time migration using multidirectional decomposition method, Applied Geophysics, 15(2), 222-233.
[108] 吴潇, 刘洋, 蔡晓慧, 2018, 弹性波波场分离方法对比及其在逆时偏移成像中的应用, 石油地球物理勘探, 53(4), 710-721.
[109] 薛浩, 刘洋, 2018, 基于优化时空域频散关系的声波方程有限差分最小二乘逆时偏移, 石油地球物理勘探, 53(4), 745-753.
[110] Shigang Xu, Yang Liu, 2018, Modeling and RTM for arbitrary-order pure acoustic wave equation in VTI media using normalized pseudo-analytical method, Earthquake Science, 31(2), 83-91.
2017年
[111] Zhiming Ren, Yang Liu, Mrinal K. Sen, 2017, Least-squares reverse time migration in elastic media, Geophysical Journal International, 208(2), 1103-1125.
[112] Bei Li, Yang Liu, Mrinal K. Sen, Zhiming Ren, 2017, Time-space-domain mesh-free finite-difference based on least-squares for 2D acoustic wave modeling, Geophysics, 82(4), T143-T157.
[113] Enjiang Wang, Yang Liu, 2017, The hybrid absorbing boundary condition for one-step extrapolation and its application in wavefield decomposition-based reverse time migration, Journal of Geophysics and Engineering, 14(5), 1177-1188.
[114] Zhiming Ren, Zhenchun Li, Yang Liu, Mrinal K. Sen, 2017, Modeling of the Acoustic Wave Equation by Staggered-Grid Finite-Difference Schemes with High-Order Temporal and Spatial Accuracy, Bulletin of the Seismological Society of America, 107(9), 2160-2182.
[115] Xin Liu, Yang Liu, Zhiming Ren, Bei Li, Shigang Xu, Lekai Zhou, 2017, Hybrid absorbing boundary condition for three-dimensional elastic wave modeling, Applied Geophysics, 14(2), 270-278.
[116] 钟晗, 刘洋, 2017, 频变AVO影响因素研究, 石油地球物理勘探, 52(4), 783-796.
2016年
[117] Zhiming Ren, Yang Liu, 2016, A hierarchical elastic full-waveform inversion scheme based on wavefield separation and the multistep-length approach, Geophysics, 81(3), R99-R123.
[118] Enjiang Wang, Yang Liu, Mrinal K. Sen, 2016, Effective finite-difference modelling methods with 2-D acoustic wave equation using a combination of cross and rhombus stencils, Geophysical Journal International, 206(3), 1933-1958.
[119] Wei Liu, Siyuan Cao, Yang Liu, Yangkang Chen, 2016, Synchrosqueezing transform and its applications in seismic data analysis, Journal of Seismic Exploration, 25(3), 27-44.
2015年
[120] Zhiming Ren, Yang Liu, 2015, Acoustic and elastic modeling by optimal time-space domain staggered-grid finite-difference schemes, Geophysics, 80(1), T17-T40.
[121] Zhiming Ren, Yang Liu, 2015, Elastic full waveform inversion using the second generation wavelet and an adaptive operator length scheme, Geophysics, 80(4), R155-R174.
[122] Li Guofa, Yang Liu, Hao Zheng, Wei Huang, 2015, Absorption decomposition and compensation via a two-step scheme Geophysics, 80(6), V145-V155.
[123] Yang Liu, Guangyi Hu, Ting’en Fan, 2015, Suppression of strong scattered tube waves using the transverse component, Journal of Applied Geophysics, 112, 226-235.
[124] Xi Zhang, Yang Liu, Xiaohui Cai, Zhiming Ren, 2015, The AWWE-based hybrid absorbing boundary condition for finite-difference modeling and its application in reverse-time migration, Journal of Applied Geophysics, 123, 93-101.
[125] 蔡晓慧，刘洋，王建民，王维红，任志明, 2015, 基于自适应优化有限差分方法的全波VSP逆时偏移, 地球物理学报, 58(9), 3317-3334.
[126] Xiaohui Cai, Yang Liu, Zhiming Ren, Jianmin Wang, Zhide Chen, Keyang Chen, Cheng Wang, 2015, 3D acoustic wave equation modeling based on an optimal finite-difference scheme, Applied Geophysics, 12(3), 409-420.
