同济大学海洋与地球科学学院

研究兴趣

1.人工智能地球物理勘探、基于机器学习和深度学习的储层参数地震预测和地质特征地震刻画、海洋与地球科学大数据分析和挖掘

2.岩石物理和岩石力学：实验岩石物理、数字岩石物理、复杂多孔介质的模型表征、地质工程一体化研究

3.与地球能源有关的储层地球物理、定量地震解释、地震综合刻画相关研究

科研项目

1.基于水力压裂能量分析的页岩储层可压裂性评价：物理机理和模型表征（国家自然科学基金面上项目，42174134），项目负责人，2022/1-2025/12

2.不同成熟度陆相有机质泥页岩地震岩石物理响应机理（国家自然科学基金面上项目，41874124），项目负责人，2019/1-2022/12

3.基于叠前三维地震正演和机器学习的礁滩相储层非均质性分布预测，2021/6-2022/6，项目负责人，企业合作课题

4.基于南海大洋钻探岩石物理分析的弹性波地震数据定量解释研究（国家重点研发计划超深水海底飞行节点地震仪研发与油气勘探应用研究课题5），课题负责人，2018/8-2020/12

5.Machine Learning Based Carbonate Reservoir Properties Prediction(基于机器学习的碳酸盐岩储层参数预测，法国道达尔勘探和生产研发中心资助）,国际合作项目，项目负责人， 2018/10-2020/6.

6.Petrophysical and Geophysical characterization of pore types in carbonates, 2017/3-2018/6，法国道达尔勘探和生产研发中心资助, 国际合作项目, 负责人

7. 深储层岩石物理响应机理，2017/1-2021/1，中科院先导项目（深层油气储层地球物理分布预测），任务负责人

8. 基于深度学习的岩性预测和储层刻画，2019/10-2020/10, 企业合作课题，负责人

9. 机器学习框架下中深层碳酸盐岩储层地震刻画新方法，2019/09-2020/05, 企业合作课题，负责人

10. 非常规页岩油气储层参数的智能预测，2018/03-2019/10, 企业合作课题，负责人

11. 地震波在非均质多孔介质分界面上的反射特征及其对储层刻画的启示，2016/1-2018/12，国家自然科学青年基金, 41504087，负责人

12. 裂缝性多孔介质岩石物理建模和非常规储层可压裂性评价研究，2017/4-2018/12，中石油勘探开发研究院资助项目，负责人

13.《东海盆地天然气资源潜力评价》项目“长江坳陷油气资源潜力评价”, 2016/1 -2019/6, 国家重大科技专项，ZX05027001-008），主要研究人员

14. 中国陆相致密油（页岩油）形成机理与富集规律（国家973项目，2014CB239006），2014/1-2018/12主要研究人员

15. 复杂非均质含油气储层的频变AVO特征研究，2015/10-2016/12，中石化南京物探研究院资助，项目负责人

16. 不同成熟度有机质页岩储层地震岩石物理研，2015/10-2016/12，中石化勘探开发研究院资助，项目负责人

教学情况

主讲课程：

《岩石物理学》(本科生)、《计算机地学应用（MATLAB的地学应用）》（本科生）

《岩石物理与地质力学》（研究生）《深度学习与人工智能基础及其在地球物理中的应用》（研究生，承担部分）、储层地球物理学（研究生、承担部分）      

《地球物理学》全英文（博士生）《地球物理学进展》(博士研究生，承担部分)

指导研究生：

每年计划招收有地球物理学、地质学、物理学、数学、计算机背景的硕士生、博士生、博士后2~4名。

博士生

蔡佳宁（2023-）直博：同济大学

陈远远（2022-）硕士：同济大学

孟巾钰（2022-）硕士：中国石油大学（北京）

闫顶点（2021-）硕士：吉林大学

王一戎（2021-）硕士：同济大学

朱津琬（2020-）直博：中国地质大学（武汉））

阿卜杜拉（2019-）硕士：中国地质大学（北京）

蔡振家（2019-）硕士：中国科学院地质与地球物理研究所

硕士生：

邱宣淦（2023-）本科：中国海洋大学

徐澄贝（2023-）本科：长安大学

冯亚军（2022-）本科：中国地质大学（武汉）

赵亚喜（2022-）本科：同济大学

竺炫莹（2021-）本科：同济大学

刘婧宇（2021-）本科：中国地质大学（武汉）

许明辉（2020-2023）本科：同济大学   毕业去向：斯坦福大学读博士

陈景妍（2020-2023）本科：同济大学   毕业去向：杭州某知名高中任教

陈远远(2019-2022 )  本科：中国地质大学（武汉）   毕业去向：同济大学读博士

李珂瑊（2018-2021）本科：中国矿业大学   毕业去向：滴滴出行科技有限公司

王一戎（2018-2021）本科：同济大学   毕业去向：同济大学读博士

本科-课外科研项目

邹采枫（2018-2021），现在加州理工学院攻读博士

缪楠（2015-2017），现在腾讯科技公司工作

研究成果

发表的期刊论文 (*代表通讯作者)

2023

[67] Gao, S., M. Xu, L. Zhao*,Y. Chen, J. Geng, 2023, Seismic predictions of fluids via supervised deep learning: Incorporating various class-rebalance strategies, Geophysics, 88 (4), 1-65

[66] Zhao, L., Z. Cai, X. Qin*, Y. Wang, L. Teng, D. Han, F. Zhang, and J. Geng, 2023, An Empirical Elastic Anisotropy Prediction Model in Self-sourced Reservoir Shales and Its Influencing Factors Analysis, Geophysics, 88 (3), 1-47

[65] Zhu, W., L. Zhao*, Z. Yang, H. Cao, Y. Wang, W. Chen, R. Chen, 2023, Stress Relaxing Simulation on Digital Rock: Characterize Attenuation due to Wave-induced Fluid flow and Scattering, Journal of Geophysical Research: Solid Earth, e2022JB024850

[64] Li, H, Q. Huang, L. Zhao*, Y. Wang, Z. Cai, J. Gao, and D. Han, 2023, The seismic dispersion and attenuation characteristics of organic shales, Geophysical Journal International, 232 (3), 1785-1802.

[63] Zou, C., L. Zhao*, F. Hong, Y. Chen, Y. Wang, and J. Geng, 2023, A comparison of machine-learning methods to predict porosity in carbonate reservoirs from seismic-derived elastic properties, Geophysics, 88 (2), B101-B120

[62] 何治亮*, 赵向原, 张文彪, 吕心瑞, 朱东亚,赵峦啸, 胡松, 郑文波, 刘彦锋, 丁茜, 段太忠, 胡向阳, 孙建芳, 耿建华, 深层-超深层碳酸盐岩储层精细地质建模技术进展与攻关方向, 石油与天然气地质, 2023, 44(1): 16-33 doi:10.11743/ogg20230102

[61] Sun, S., L. Zhao, H. Chen, Z. He, and J. Geng*, 2023, Pre-stack seismic inversion for elastic parameters using model-data-driven generative adversarial networks, Geophysics, 88 (2), M87-M103

[60] 赵峦啸，麻纪强，李珂瑊，朱津琬，高志前、何治亮、耿建华*，2023，超深层碳酸盐岩储层地震岩石物理特征和模型表征，地球物理学报，66(1),16-33

2022

[59] Qin, X, L. Zhao*, Z. Cai, Y. Wang, M. Xu, F. Zhang, D. Han, J. Geng, 2022, Compressional and shear wave velocities relationship in anisotropic organic shales, Journal of Petroleum Science and Engineering, 111070

[58] Ba, J., H. Zhu, L.Y. Fu*, and L. Zhao, 2022, Challenges in seismic rock physics, Journal of Geophysics and Engineering, 19 (6), 1367-1369

[57] Wu, S., B. Wang, L. Zhao, H. Liu, and J. Geng*, 2022, High‐efficiency and High‐precision Seismic Trace Interpolation for Irregularly Spatial Sampled Data by Combining an Extreme Gradient Boosting Decision Tree and Principal Component Analysis, Geophysical Prospecting, doi.org/10.1111/1365-2478.13270

[56] Qin, X*, D. Han, and L. Zhao, 2022,  Measurement of Grain Bulk Modulus on Sandstone Samples from the Norwegian Continental Shelf, Journal of Geophysical Research: Solid Earth, e2022JB024550

[55] Wang, Y., L. Zhao*, C. Cao, Q. Yao, Z. Yang, H. Cao, and J. Geng, 2022, Wave-induced fluid pressure diffusion and anelasticity in partially saturated rocks: the influences of boundary conditions, Geophysics, 87(5), MR247-MR263

[54] Xu, M.. L. Zhao*, S. Gao, X. Zhu, and J. Geng, 2022, Joint use of multi-seismic information for lithofacies prediction via supervised convolutional neural networks, Geophysics, 87(5), M151-M162

[53] Wang, Y., L. Zhao*, D. Han, Q. Wei, Y. Zhang, H. Yuan, and J. Geng, 2022，Experimental Quantification of the Evolution of the Static Mechanical Properties of Tight Sedimentary Rocks during Increasing-amplitude Load and Unload Cycling, Geophysics, 87（2）,MR73-MR83

[52] Cai, J*., L. Zhao, F. Zhang, and W. Wei, 2022, Advances in multiscale rock physics for unconventional reservoirs, Advances in Geo-Energy Research, 6 (4), 271-275

[51] Guo, J.,L. Zhao, X. Chen*, Z. Yang, H. Li, C. Liu, 2022, Theoretical modelling of seismic dispersion, attenuation, and frequency-dependent anisotropy in a fluid saturated porous rock with intersecting fractures, Geophysical Journal International, 230, 580-606

[50] An, M., F. Zhang*, K. Min, D. Elsworth, C. He, and L. Zhao, 2022，Frictional Stability of Metamorphic Epidote in Granitoid Faults Under Hydrothermal Conditions and Implications for Injection-Induced Seismicity，JGR-solid earth, 127 (3), e2021JB023136

[49] Zhang, Y., J. Ma, Y. Wang*, F. Wang, X. Li, and L. Zhao, 2022, Quantification of the Fracture Complexity of Shale Cores After Triaxial Fracturing, Frontiers in Earth Science, 10:863773.doi: 10.3389/feart.2022.863773 

[48] Wang, Y., L. Niu, L. Zhao, B. Wang, Z. He, H. Zhang, D. Chen, and J. Geng*, 2022, Gaussian Mixture Model Deep Neural Network and Its Application in Porosity Prediction of Deep Carbonate Reservoir, Geophysics, 87 (2), M59-M72, doi.org/10.1190/geo2020-0740.1

[47] Wang, Y*, D. Han, L. Zhao, H. Li, T. Long, J. Hamutoko, 2022, Static and Dynamic Bulk Moduli of Deepwater Reservoir Sands: Influence of Pressure and Fluid Saturation, Lithosphere, 4266697, doi.org/10.2113/2022/4266697

[46] Li, S., K. Zhou, L. Zhao, Q. Xu, and J. Liu*, 2022, An improved lithology identification approach based on representation enhancement by logging feature decomposition, selection and transformation, Journal of Petroleum Science and Engineering, 109842

2021

[45] Zou, C., L. Zhao*, M. Xu, Y. Chen, and J. Geng, 2021, Porosity Prediction with Uncertainty Quantification from Multiple Seismic Attributes Using Random Forest, Journal of Geophysical Research: Solid Earth, 126（7）, e2021JB021826

[44] Chen, Y., L. Zhao*, J. Pan, C. Li, M. Xu, K. Li, F. Zhang, and J. Geng, 2021, Deep carbonate reservoir characterization using multi-seismic attributes via machine learning with physical constraints, Journal of Geophysics and Engineering, 18(5), 761-775

[43] Nie, J., Z. Qu, Y. Cheng*, X. Wang, J. Zhu, S. Sun, L. Zhao, and J Geng*, 2021, Diagnosing of clay distribution in argillaceous sandstone by a rock physics template, Geophysical Prospecting, 69 (8-9), 1700-1715

[42] Zhao, L*., C. Zou, Y. Chen, W. Shen, Y. Wang, H. Chen, and J. Geng, 2021, Fluids and lithofacies prediction based on integration of well-log data and seismic inversion: a machine learning approach, Geophysics, 86(4), M151–M165

[41] Ren, J., Y. Wang*, D. Han, L. Zhao, T. Long, and S. Tang, 2021, Determining crack initiation stress in unconventional shales based on strain energy evolution, Journal of Geophysics and Engineering, 18(5), 642-652.

[40] Yuan, H*., Y. Wang, D. Han, H. Li, and L. Zhao, 2021, Velocity measurement of North Sea heavy oil sands under changing pressure and temperature, Journal of Petroleum Science and Engineering, 205, 108825.

[39] Guo, J., L. Zhao*, Z. Yang, and H. Li, 2021, Analytical model for rock effective elastic properties with aligned elliptical cracks embedded in transversely‐isotropic background, Geophysical Prospecting, 69,1515-1530

[38] An, M., F. Zhang*, E. Donstov, D. Elsworth, H. Zhu, and L. Zhao, 2021, Stress Perturbation Caused by Multistage Hydraulic Fracturing: Implications for Deep Fault Reactivation, International Journal of Rock Mechanics and Mining Sciences, 141, 104704

[37] 朱伟，赵峦啸*，王一戎，2021, 数字岩心宽频带动态应力应变模拟方法及其对含裂隙致密岩石频散和衰减特征的表征, 地球物理学报，64（6），2086-2096

[36]Zhao, L*., Y. Wang, Q. Yao, J. Geng, H. Li, H. Yuan, and D. Han, 2021, Extended Gassmann Equation with Dynamic Volumetric Strain: Modeling Wave Dispersion and Attenuation of Heterogenous Porous Rocks, Geophysics, 86(3), MR149-MR164

[35] Teillet, T., F. Fournier, L. Zhao*, J. Borgomano, F. Hong, 2021, Geophysical pore type inversion in carbonate reservoir: integration of cores, well-logs, and seismic data (Yadana field, offshore Myanmar), Geophysics, 86(3), B149-B164.

[34] Wang, Y., L. Zhao*, D. Han, A. Mitra, H. Li, ans S. Aldin, 2021, Anisotropic Dynamic and Static Mechanical Properties of Organic-rich Shale: The Influence of Stress, Geophysics,86(2), C51-C63

[33] 赵峦啸,刘金水，姚云霞，钟锴，麻纪强，邹采枫，陈远远，付晓伟，朱晓军，朱伟林，耿建华*, 2021, 基于随机森林算法的陆相沉积烃源岩定量地震刻画：以东海盆地长江坳陷为例,地球物理学报，64(2), 700-715

[32] Niu, L., J. Geng*, X. Wu, L. Zhao, and H. Zhang, 2021, Data-driven method for an improved linearised AVO inversion, Journal of Geophysics and Engineering, 18, 1-22

2020 

[31] Li, H., L. Zhao*, D. Han, J. Gao, H. Yuan, and Y. Wang, 2020,Experimental study on frequency-dependent elastic properties of weakly consolidated marine sandstone: effects of partial saturation, Geophysical Prospecting, 68 (9), 2808-2824.

[30] 钟广法*，张迪，赵峦啸，大洋钻探天然气水合物储层测井评价研究进展，2020, 天然气工业，40(8), 25-44

[29] Li, H*., D. Han, Q. Huang, L. Zhao, Q. Yao, and J. Gao, 2020, Precision analysis of dynamic force-deformation measurement: numerical modeling and experimental data, Journal of Geophysics and Engineering, 17(6), 980-992

[28] Wang, Y., L. Zhao*, D. Han, X. Qin, J. Ren, and Q. Wei, 2020, Micro-mechanical Analysis of the Effects of Stress Cycles on the Dynamic and Static Mechanical Properties of Sandstone, InternationalJournal of Rock Mechanics and Mining Sciences, 134,104431

[27] Yang, J., J. Geng*, and L. Zhao, 2020, A frequency-decomposed nonstationary convolutional model for amplitude-versus-angle-frequency forward waveform modeling in attenuative media, Geophysics,85(6), T301-T314.

[26] Yuan, H., D. Han, H. Li, L. Zhao*, and W. Zhang, 2020, The effect of rock frame on elastic properties of bitumen sands, Journal of Petroleum Science and Engineering, 194, 107460

[25] Li, H., D. Wang, J. Gao, M. Zhang, Y. Wang, L. Zhao*, Z. Yang, 2020, Role of saturation on elastic dispersion and attenuation of tight rocks: An experimental study. Journal of Geophysical Research: Solid Earth, 125（4），e2019JB018513.

[24] Zhao, L*., C. Cao, Q. Yao, Y. Wang, H. Li, H. Yuan, J. Geng, and D. Han, 2020, Gassmann Consistency for Different Inclusion-based Effective Medium Theories: Implications for Elastic interactions and Poroelasticity, Journal of Geophysical Research: Solid Earth, 125(3), e2019JB018328.

[23] Wang, Y., H. Li*, D. Han, L. Zhao, J. Ren, and Y. Zhang, 2020, A comparative study of the stress-dependence of dynamic and static moduli for sandstones, Geophysics, 85(4), MR179-MR190.

[22] 朱伟，赵峦啸*，王晨晨，单蕊，2020，基于数字岩心动态应力应变模拟的非均匀孔隙介质波致流固相对运动刻画，地球物理学报，63(6)，2386-2399

[21] Zhou, K., J. Zhang, Y. Ren, Z. Huang, and L. Zhao*, 2020, A gradient boosting decision tree algorithm combining synthetic minority over-sampling technique for lithology identification, Geophysics, 85(4), WA147-WA158

[20] 陈树民*, 韩德华, 赵海波, 陈丰, 王团, 唐晓花, 赵峦啸, 秦玄, 2020，松辽盆地古龙页岩油地震岩石物理特征及甜点预测技术, 大庆石油地质与开发，39（3），107-116

[19] Zhao, L.*, Y. Wang, X. Liu, J. Zhang, Y. Liu, X. Qin, K. Li, and J. Geng, 2020, Depositional impact on the seismic elastic characteristics of the organic shale reservoir: A case study of Longmaxi-Wufeng shale in Fuling gas field, Sichuan Basin, Geophysics, 85(2), B23-B33.

2019

[18] Yuan, H*., D. Han, L. Zhao, Q. Huang, and W. Zhang, 2019, Attenuation analysis of heavy oil sands –based on lab measurements, Geophysics, 84(5), B299-B309

[17] Wang, J*., S. Wu, L. Zhao, W. Wang, J. Wei, and J. Sun, 2019, An effective method for shear-wave velocity prediction in sandstones, Marine Geophysical Research, 40 (4), 655-664

[16] Qin, X*., D. Han, and L. Zhao, 2019, Elastic characteristics of overpressure due to smectite-to-illite transition based on micro-mechanism analysis, Geophysics, 84(4), WA23-WA42.

2018

[15] Zhao, L*., X. Qin, J. Zhang, X. Liu, D. Han, J. Geng, and Y. Xiong, 2018, An effective reservoir parameter for seismic characterization of organic shale reservoir, Surveys in Geophysics, 2018, 39(3), 509-541

[14] Yuan, H*., D. Han, L. Zhao, Q. Huang, and W. Zhang, 2018, Rock physics characterization of bitumen carbonates: a case study, Geophysics, 83(3), B119-B132.

2017 

[13] Zhao, L*., H. Yuan, J. Yang, D. Han, J. Geng, R. Zhou, H. Li, and Q. Yao, 2017, Mobility Effect on Poroelastic Seismic Signatures in Partially Saturated Rocks with Applications in Time-lapse Monitoring of a Heavy Oil Reservoir, Journal of Geophysical Research-Solid Earth, 122 (11), 8872-8891

[12] Zhao, L*., Q. Yao, D. Han, R. Zhou, J. Geng, and H. Li, 2017, Frequency- and angle- dependent poroelastic seismic analysis for highly attenuating reservoirs, Geophysical Prospecting, 65(6), 1630-1648.

[11] Zhu W*., L. Zhao, R. Shan, Modeling effective elastic properties of digital rocks using a new dynamic stress-strain simulation method, 2017, Geophysics, 82(6), MR163-MR174.

2016

[10] Zhao, L*., X. Qin, D. Han, J. Geng, Z. Yang, H. Cao, Rock-Physics modeling for the elastic properties of organic shale at different maturity stages, 2016, Geophysics, 81(5), D527-D541.

[9] Zhao, L*., Q. Yao, D. Han, F. Yan, and M. Nasser,2016, Characterizing the effect of elastic interactions on the effective elastic properties of porous, cracked rocks, Geophysical Prospecting, 64(1), 157-169.

[8] Li, H*., L. Zhao, D. Han, M. Sun, and Yu Zhang, 2016, Elastic properties of heavy oil sands: effects of temperature, pressure, and microstructure, Geophysics, 81(4), D453-464. SCI

[7] Li, H*., D. Han, H. Yuan, X. Qin, and L. Zhao, 2016, Porosity of heavy oil sand: laboratory measurement and bound analysis, Geophysics, 81(2), D83-D90.

2015 

[6] Zhao, L*., D. Han, Q. Yao, R. Zhou and F. Yan, 2015, Seismic reflection dispersion due to wave-induced fluid flow in heterogeneous reservoir rocks, Geophysics, 80(3), D221-D235.

[5] Yao, Q*., D. Han, F. Yan, and L. Zhao, 2015, Modeling attenuation and dispersion in porous heterogeneous rocks with dynamic fluid modulus, Geophysics, 80(3), D183-D194.

2014 

[4] Zhao, L*., J. Geng, J. Cheng, D. Han, and T. Guo,2014, Probabilistic lithofacies prediction from prestack seismic data in a heterogeneous carbonate reservoir, Geophysics, 79(5), M25-M34.

[3] Yan, F*., Han, D, Q. Yao, and L. Zhao, 2014, Prediction of seismic wave dispersion and attenuation from ultrasonic velocity measurements, Geophysics, 79(5), WB1-WB8.

2013 

[2] Zhao, L*., M. Nasser, and D. Han, 2013, Quantitative geophysical pore type characterization and geological implications in carbonate reservoir, Geophysical Prospecting, 61(4), 827-841.

[1] Zhao, L*, J. Geng, S. Zhang, and D. Yang, 2008, 1-D Controlled source electromagnetic forward modeling for marine gas hydrates studies: Applied Geophysics, 5(2), 121-126.