周辉,教授,博士生导师,博士学位,江苏省启东市人。在长春地质学院应用地球物理系获应用地球物理专业学士、硕士和博士学位,研究方向为地震勘探。1997年6月于中国海洋大学博士后流动站出站并留校任教。2008年3月以引进人才身份到中国石油大学(北京)工作。2022年入选中国石油大学(北京)石大学者领军学者B岗。2016年5月至今,担任中石油物探重点实验室主任。2017年至今为中国地球物理学会油气地球物理专业委员会委员,2022年至今为《石油物探》编委。
主要从事地震资料的处理和正反演研究。负责以波动方程叠前偏移、吸收衰减补偿叠前偏移、波动方程非线性反演为研究主题的国家自然科学基金项目7项(其中1项为重点项目),国家重点基础研究发展规划973项目课题1项,国家重点研发计划项目课题1项,国家科技重大专项子课题3项,中石油“物探应用基础实验和前沿理论方法研究”项目1项,中石油创新基金1项,中石油“十二五” “十三五”新方法新技术研究项目子课题3项,横向课题多项。
发表期刊学术论文140篇,国际会议论文70多篇,授权发明专利6项,软件著作权登记6项。SCI 收录论文96篇、EI收录88篇(含SCI、EI双收录论文)。发表论文的SCI引用2373次(2023年11月ResearchGate查询结果),Geophysics Bright Spots论文1篇,1% ESI高被引论文3篇。
2000年入选“青岛市专业技术拔尖人才”, 2006年入选教育部“新世纪优秀人才支持计划”。获2015年度教育部科技进步二等奖1项(2/15),2023年获中国石油和化工自动化应用协会科技进步一等奖1项(1/15)。2018年被评为北京市师德先锋。
联系方式
电子邮件:huizhou@Xup.edu.Xn,其中大写字母X代表小写字母c。
电话:Y1Y-X9731YY5 (O.) ,其中X代表8,Y代表0。
Mobile:Z5XZZ25572X,其中X代表8,Z代表1。
工作经历
教授博导,中国石油大学(北京),2008/03-
博导,中国海洋大学,2002/03-2008/03
教授,中国海洋大学,2000/12-2008/03
访问学者,长崎大学,日本,2001/11-2006/12
访问学者,东北大学,日本,1997/07-2000/05
教师,中国海洋大学,1997/07-2008/03
博士后,中国海洋大学,1995/09-1997/06
教育经历
博士生,长春地质学院,地球物理系,1992/09-1995/07
硕士生,长春地质学院,地球物理系,1989/09-1992/07
本科生,长春地质学院,地球物理系,1985/09-1989/07
部分科研项目
[1] 2023-2025,起伏地表全波形反演技术研究,中国石油天然气股份有限公司勘探开发研究院
[2] 2023-2024,基于最优传输距离的反射波全波形反演算法研究,中海油田服务股份有限公司湛江分公司
[3] 2022-2025,物探应用基础实验和前沿理论方法研究,中国石油天然气集团有限公司
[4] 2020-2023,国家自然科学基金联合基金项目“海相深层油气富集机理与关键工程技术基础研究”课题“海相深层复杂构造成像与多类型储层预测方法”专题“深层复杂构造与储层地震波场传播机理研究”
[5] 2019-2020,粘弹介质波动方程正演与波场特征分析,中国石油勘探开发研究院
[6] 2019-2023,多信息相容约束高效全波形反演方法研究,国家重点研发计划变革性技术关键科学问题重点专项“高分辨率地震实时成像理论与技术”课题
[7] 2019-2022,弹簧网络模型和格子玻尔兹曼模型耦合的含流体孔隙介质波场模拟方法研究,国家自然科学基金面上项目
[8] 2019-2020,层致密砂砾岩和古中央隆起带特殊岩性储层岩石物理实验与声波响应规律研究,大庆油田勘探开发研究院
[9] 2019-2020,地震资料吸收衰减补偿处理技术,中石化江苏油田分公司物探研究院
[10] 2017-2021,变分数阶拉普拉斯算子粘滞声波方程正演、逆时偏移和全波形反演研究,国家自然科学基金重点项目
[11] 2019-2020,弹性波全波形反演适应性提升及精度优化研究,东方地球物理公司
[12] 2016-2020,油藏地球物理地震反演新技术与软件研制,“十三五”国家科技重大专项
[13] 2016-2018,弹性波全波形反演方法研究,东方地球物理公司
[14] 2013-2017,深层波动方程反演综合建模与偏移成像,国家重点基础研究发展规划973项目课题
奖励、荣誉、学术兼职
2023,高成熟区复杂油气藏地震资料高精度成像与高分辨率储层识别技术及应用,中国石油和化工自动化应用协会,科技进步一等奖(1/15)
2022,中国石油大学(北京)首届石大学者领军学者B岗
2018,评为北京市师德先锋
2017,中国地球物理学会油气地球物理专业委员会委员
2016,中国石油天然气集团公司物探重点实验室主任
2015,中国石化地球物理重点实验室第二届学术委员会委员
2015,薄互层油气藏高分辨率地震成像与结构表征关键技术及其工业化应用,教育部,科技进步二等奖(2/15)
2006,教育部“新世纪优秀人才支持计划”
讲授课程
2008-今,地震资料解释基础,本科生
2017-2018,计算方法,本科生
2008-今,计算地球物理,研究生
指导研究生所获荣誉
2023,王玲谦,中国地球物理学会杰出博士学位论文奖
2022,唐瑾璇,北京市优秀毕业生
2021,姜春涛,国家奖学金(博士生)
2021,唐瑾璇,国家奖学金(硕士生)
2021,王泽禹,中国石油大学(北京),优秀硕士学位论文
2020,谷子骞,北京市优秀毕业生
2019,赵学彬,北京市优秀毕业生
2019,赵学彬,中国石油大学(北京),优秀硕士学位论文
2018,于 波,北京市优秀毕业生
2017,赵学彬,第五届“东方杯”全国大学生勘探地球物理大赛全国三等奖
2017,王玲谦,第五届“东方杯”全国大学生勘探地球物理大赛全国二等奖
2016,夏木明,第四届“东方杯”全国大学生勘探地球物理大赛全国二等奖
2016,祖绍环,中国石油大学(北京),优秀硕士学位论文
2015,杨雅慧,第三届“东方杯”全国大学生勘探地球物理大赛全国二等奖
2015,曲 杉,中国石油大学(北京),优秀硕士学位论文
2014,张庆臣,北京市优秀毕业生
2014,夏木明,第二届“东方杯”全国大学生勘探地球物理大赛全国一等奖
2014,袁 江,第二届“东方杯”全国大学生勘探地球物理大赛全国一等奖
2014,杨雅慧,第二届“东方杯”全国大学生勘探地球物理大赛全国二等奖
2013,陈汉明,中国第四届李四光优秀硕士研究生奖
2013,陈汉明,中国石油大学(北京),优秀硕士学位论文
2013,陈汉明,北京市优秀毕业生
指导的10名博士生分别到美国德克萨斯大学奥斯汀分校、加州大学圣克鲁兹分校、哈佛大学、斯坦福大学、宾夕法尼亚州立大学、新加坡国立大学、苏黎世联邦理工学院、英国爱丁堡大学、法国艾克斯-马赛大学进行联合培养。
2017年以来发表的期刊论文
[1] Tang J.X., Xia M.M., Zhou H., et al., 2023, Lattice spring model for irregular interface based on an adaptive location strategy, IEEE Transactions on Geoscience and Remote Sensing, 61, 5921711.
[2] 王玲谦,周辉,陈汉明,李红辉,2023,去噪算法驱动的地震反演正则化方法,地球物理学报,66(11): 4664-4676.
[3] 蒋书琦,周辉,陈汉明,等,2023,稳定Q补偿梯度的黏滞声波全波形反演,石油地球物理勘探,58(6).
[4] Zheng J.X., Zhou H., Tang J.X., et al., 2023, Finite difference method for first-order velocity-stress equation in body-fitted coordinate system. IEEE Transactions on Geoscience and Remote Sensing, 61, 5910711, 1-11.
[5] Wang L.Q. Zhou H., Chen H.M., 2023, Adaptive feature map-guided well-log interpolation, Remote Sensing, 2023, 15, 459.
[6] Jiang S.Q., Zhou H., et al., 2023, Source-independent full-waveform inversion based on convolutional Wasserstein distance objective function, IEEE Transactions on Geoscience and Remote Sensing, 61, 5910014.
[7] Cao Y.M., Zhou H., Yu B., 2023, Decorrelated linearized seismic-petrophysics inversion, Computers and Geosciences, 176, 105374.
[8] Jiang C.T., Zhou H. Xia M.M., et al., 2023, A joint absorbing boundary for the multiple-relaxation-time lattice Boltzmann method in seismic acoustic wavefield modeling, Petroleum Science. https://doi.org/10.1016/j.petsci.2023.02.019.
[9] Zhang Y.P., Zhou H., Zhang M.Z., et al., 2023, Structurally constrained initial impedance modeling for poststack seismic inversion, IEEE Transactions on Geoscience and Remote Sensing, 61, 5906310, 1-10.
[10] Xia M.M., Zhou H., et al., 2022, Viscoacoustic wave simulation with the lattice Boltzmann method, Geophysics, 87(6), T403-T416.
[11] Jiang C.T., Zhou H., Xia M.M., et al., 2022, Stability conditions of multiple-relaxation-time lattice Boltzmann model for seismic wavefield modeling, Journal of Applied Geophysics, 204, 104742.
[12] Zhang M.K., Zhou H.*, Chen H.M., et al., 2022, Reverse-time migration using local Nyquist cross-correlation imaging condition, IEEE Transactions on Geoscience and Remote Sensing, 60, 5913914.
[13] Zhang Y.P., Zhou H.*, Wang Y.F., et al., 2022, A novel multichannel seismic deconvolution method via structure-oriented regularization, IEEE Transactions on Geoscience and Remote Sensing, 60, 5910410, 1-10.
[14] Tang J.X., Zhou H.*, et al., 2022, A perfectly matched layer technique applied to lattice spring model in seismic wavefield forward modeling for Possion's solids, Bulletin of the Seismological Society of America, 112(2): 608–621.
[15] Zhang Y.P., Zhou H.*, et al., 2022, Poststack impedance inversion with geological structure-guided total variation constraint, IEEE Geoscience and Remote Sensing Letters, 19, 8023605, 1-5.
[16] Wang N., Xing G.C., Zhu T.Y., Zhou H., Shi Y., 2022, Propagating seismic waves in VTI attenuating media using fractional viscoelastic wave equation, Journal of Geophysical Research: Solid Earth, 127, e2021JB023280.
[17] 闫海洋,周辉,刘海波,等,2022,FK和Shearlet域联合压缩感知数据重构技术,石油地球物理勘探,57(3,557-569.
[18] Chen H., Zhou H., Rao Y., 2021. Source wavefield reconstruction in fractional Laplacian viscoacoustic wave equation-based full waveform inversion, IEEE Transactions on Geoscience and Remote Sensing, 59(8), 6496-6509.
[19] Wang L.Q. Zhou H.*, et al., 2021, Poststack seismic inversion using a patch-based Gaussian mixture model, Geophysics, 86(5), R685–R699.
[20] Wang L.Q., Zhou H.*, Liu W. L., Yu B., Zhang S., 2021, High-resolution seismic acoustic impedance inversion with sparsity-based statistical model, Geophysics, 86(4), 86(4), R509–R527.
[21] Chen H., Zhou H., Rao Y., 2021, Constant-Q wave propagation and compensation by pseudo-spectral time-domain methods, Computers & Geosciences, 2021: 104861.
[22] 姜春涛,周辉,夏木明,等,2021,多松弛时间格子Boltzmann方法的黏滞吸收边界,石油地球物理勘探,56(5): 1030-1038.
[23] Yu B., Zhou H., Liu W.L. Chen H.M., 2021, Interpolation method based on pattern-feature correlation, Geophysics, 86(3): R253-R264.
[24] Zhao X.B., Zhou H., Chen H.M., Wang Y.F., 2021, Domain decomposition for large-scale viscoacoustic wave simulation using localized pseudo-spectral method, IEEE Transactions on Geoscience and Remote Sensing, 59(3): 2666-2679.
[25] Wang L, Zhou H, Liu W, et al., 2021, Data-driven multichannel poststack seismic impedance inversion via patch-ordering regularization. Geophysics, 86(2): R197-R210.
[26] Fang J.W., Zhou H., et al., 2020, Data-driven low-frequency signal recovery using deep learning predictions in full-waveform inversion, Geophysics, 85(6), 1-4.
[27] Zhao X.B., Zhou H., Chen H.M., Wang Y.F., 2020, Fractional Laplacian viscoacoustic wave simulation using localized pseudo-spectral method, IEEE Transactions on Geoscience and Remote Sensing, 58(4).
[28] Yu B., Zhou H., et al., 2020, Prestack Bayesian statistical inversion constrained by reflection features, Geophysics, 85(4), R349-R363.
[29] Chen H.M., Zhou H., Yao Y., 2020, An implicit stabilization strategy for Q-compensated reverse time migration, Geophysics, 85(3), S169–S183.
[30] Fang J.W., Chen H.M., Zhou H., et al., 2020, Elastic full-waveform inversion based on GPU accelerated temporal fourth-order finite-difference approximation, Computers & Geoscience, 135, 104381, 1-10.
[31] Yu B., Zhou H., et al., 2020, A modified shear-wave velocity estimation method based on well-log data, Journal of Applied Geophysics, 173, 103932.
[32] 陈汉明,汪燚林,周辉,2020,一阶速度—压力常分数阶黏滞声波方程及其数值模拟,石油地球物理勘探,55(2),302-310.
[33] 陈汉明,周辉,田玉昆,2020,分数阶拉普拉斯算子黏滞声波方程的最小二乘逆时偏移,石油地球物理勘探,55(3),616-625.
[34] Wang N., Zhou H., et al., 2020, Fractional Laplacians viscoacoustic wavefield modeling with k-space based time-stepping error compensating scheme, Geophysics, 85(1), T1–T13.
[35] Wang L.Q., Zhou H., et al., 2020, Adaptive seismic single channel deconvolution via convolutional sparse coding model, IEEE Geoscience and Remote Sensing Letters, 17(8), 1415-1419. (SCI, 二区) 69
[36] Wang L.Q., Zhou H., Yu B., et al., 2019, Inversion for geofluid discrimination based on poroelasticity and AVO inversion, Geofluid, 2656747, 1-17.
[37] Chen H.M., Zhou H., Jiang S. Q., Rao Y., 2019, Fractional Laplacian wave equation low-rank temporal extrapolation, IEEE Access, 7, 93187-93197.
[38] Chen H.M., Zhou H., Rao Y., et al., 2019, A matrix-transform numerical solver for fractional Laplacian viscoacoustic wave equation, Geophysics, 84(4), T283-T297.
[39] Wang N., Zhou H., Chen H.M., et al., 2019, An optimized parallelized SGFD modeling scheme for 3D seismic wave propagation, Computers and Geosciences, 131, 102-111.
[40] Wang L.Q., Zhou H., Wang Y.F., et al., 2019, Three parameters prestack seismic inversion based on L1-2 minimization, Geophysics, 84(5), R753-R766.
[41] Zu S.H., Zhou H., Wu R.S., et al., 2019, Dictionary learning based on dip patch selection training for random noise attenuation, Geophysics, 84(3), V169–V183.
[42] Fang, J., Zhou, H., Chen, H., et al., 2019, Source-independent elastic least-squares reverse time migration. Geophysics, 84(1), S1-S16.
[43] Zu S.H., Zhou H., Wu R.S., et al., 2019, Hybrid-sparsity constrained dictionary learning for iterative deblending of extremely noisy simultaneous-source data, IEEE Transactions on Geoscience and Remote Sensing, 57(4), 2249-2262.
[44] Wang Y.F., Zhou H., Zhao X.B., et al., 2019, CuQ-RTM: A CUDA-based code package for stable and efficient Q-compensated RTM, Geophysics, 84(1), F1–F15.
[45] Wang Y.F., Zhou H., Zhao X.B., et al., 2019, Q-compensated viscoelastic reverse time migration using mode-dependent adaptive stabilization scheme, Geophysics, 84(4), S301–S315.
[46] Li Q.Q., Fu L.Y., Zhou H., et al., 2019, Effective Q compensated reserve time migration using a new decoupled fractional Laplacian viscoacoustic wave equation, Geophysics, 84(2), S57–S69.
[47] Zhang Q.C., Mao W.J., Zhou H., et al., 2018, Hybrid-domain simultaneous-source full waveform inversion without crosstalk noise, Geophysical Journal International, 215, 1659–1681.
[48] Zhao X.B., Zhou H., et al., 2018, A stable approach for Q-compensated viscoelastic reverse time migration using excitation amplitude imaging condition, Geophysics, 83(5), S459–S476.
[49] Zu S.H., Zhou H., Mao W.J., et al., 2018, 3D deblending of simultaneous source data based on 3D multi-scale shaping operator, Journal of Applied Geophysics, 151, 274–289.
[50] Fang J.W., Zhou H., et al., 2018, Effect of surface-related Rayleigh and multiple waves on velocity reconstruction with time-domain elastic FWI, Journal of Applied Geophysics, 148, 33–43.
[51] Wang N., Zhou H., Chen H.M., et al., 2018, A constant fractional-order viscoelastic wave equation and its numerical simulation scheme, Geophysics, 83(1), T39-T48.
[52] Wang Y.F., Ma X., Zhou H., Chen Y.K., 2018, L1-2 minimization for exact and stable seismic attenuation compensation, Geophysical Journal International, 213(3), 1629-1646.
[53] Xia M.M., Zhou H., Chen H.M., Zhang Q.C., Li Q.Q., 2018, A rectangular lattice spring model for modeling elastic waves in Poisson solids, Geophysics, 83(2), T69–T86.
[54] Wang Y.F., Zhou H., Chen H.M., Chen Y.K., 2018, Adaptive stabilization for Q-compensated reverse time migration, Geophysics, 83(1), S15-S32.
[55] Zu S.H., Zhou H., Mao W.J., et al., 2017, Iterative deblending of simultaneous-source data using a coherency-pass shaping operator, Geophysical Journal International, 2017, 211(1):541-557.
[56] Xia M.M., Zhou H., Li Q.Q., et al., 2017, A general three- dimensional lattice spring model for modeling elastic waves, Bulletin of the Seismological Society of America, 107(5): 2194-2212.
[57] Xia M.M., Wang S.C., Zhou H., Shan X.W., Chen H.M., Li Q.Q., Zhang Q.C., 2017, Modelling viscoacoustic wave propagation with the lattice Boltzmann method, Scientific Reports, 7: 10169 | DOI:10.1038/s41598-017-10833-w.
[58] Wang Y.F., Zhou H., Zu S.H., et al. 2017, Three-operator proximal splitting scheme for 3D seismic data reconstruction, IEEE Geoscience and Remote Sensing Letters, 14(10), 1380-1384.
[59] Zu S., Zhou H., Li Q.Q., Chen H.M., et al., 2017, Shot-domain deblending using least-squares inversion, Geophysics, 82(4), V241–V256.
[60] Zu S.H., Zhou H., Chen H.L., et al., 2017, Two field trials for deblending of simultaneous source: why we failed and why we succeeded? Journal of Applied Geophysics, 143, 182–194.
[61] Chen H.M., Zhou H., Xia M.M., 2017, Efficiency improved scalar wave low-rank extrapolation with an effective perfectly matched layer, Journal of Geophysics and Engineering, 14, 113-119.
[62] Chen H.M., Zhou H., Zhang Q.C., et al., 2017, Modeling elastic wave propagation using K-Space operator based temporal high-order staggered-grid finite-difference method, IEEE Transactions on Geoscience and Remote Sensing, 55(2), 801-815.
[63] Wang Y., Zhou H., Yuan S.Y., Ye Y.M., 2017, A fourth order accuracy summation-by-parts finite difference scheme for acoustic reverse time migration in boundary-conforming grids, Journal of Applied Geophysics, 136, 498-512.