[88] Xu, M., L. Zhao*, J. Liu,  and J. Geng, 2024, Enhancing seismic porosity estimation through 3D sequence-to-sequence deep learning with data augmentation, spatial and geologic constraints, Geophysics, 89 (4), M93-M108

[87]  Zhao, L., J. Liu, M. Xu*, Z. Zhu, Y. Chen,  and J. Geng, 2024, Rock Physics guided machine learning for shear sonic log prediction, Geophysics, 89(1), D75-D87

[86]  Yan, D.,  L. Zhao*, X. Song, J. Tang,  and F. Zhang, 2024, Fracability evaluation model for unconventional reservoirs: From the perspective of hydraulic fracturing performance, International Journal of Rock Mechanics and Mining Sciences，183, 105912

[85] Zhao, L., X. Zhu, X. Zhao, C. You, M. Xu, T. Wang*, and J. Geng, 2024, Deep carbonate reservoir characterization using multi seismic attributes：A comparison of unsupervised machine learning approaches, Geophysics, 89 (2), B65-B82

[84] Zhao, L., Y. Zhao, D. Yan, J. Zhu, and J. Cai*, Integrated rock physics characterization of unconventional shale reservoir: A multidisciplinary perspective, Advances in Geo-Energy Research, 14 (2), 86-89

[83] Yang, Z., H. Cao, L. Zhao, X. Yan, Y. Wang, and W. Zhu*, The Effects of Pore Structure on the Wave Dispersion and Attenuation Due to Squirt Flow: Dynamic Stress-Strain Simulation on a Simple Digital Pore-Crack Mode, Geophysics, 89 (3), MR155-MR166

[82] Chen, M*., J. Geng, and L. Zhao, A hybrid numerical model for coupled hydro-mechanical analysis during CO2 injection into heterogeneous unconventional reservoirs, Gas Science and Engineering, 205244

[81] Long, T., X. Qin, Q. Wei, L. Zhao*, Y. Wang, F. Chen, M. Myers, Y. Zheng, and D. Han, Quantifying the influences of clay-bound water on wave dispersion and attenuation signatures of shale: An experimental study, Geophysics, 89 (2), MR77-MR90

[80] Liu, W., L. Zhao*, X. Qiu, Y. Wang, Y. Wang, and W. Zhu, 2024, Use digital rock physics to characterize velocity and attenuation signatures of deep cavity-fracture carbonate reservoir, Journal of Geophysics and Engineering, gxae086

[79] Cao, S., F. Zhang*, M. An*, D. Elsworth, M. He, H. Liu, and L. Zhao, Gouge stability controlled by temperature elevation and obsidian addition in basaltic faults and implications for moonquakes, International Journal of Mining Science and Technology, doi.org/10.1016/j.ijmst.2024.04.012

[78] Hussein, A., L. Zhao*, A. Masgari and H. Handoyo, Shear strength characteristics of marine sediments: the influences of lithofacies and sedimentological environment, Marine Geophysical Research, 2024, 45:14

[77] Cai, Z., L. Zhao*, T. Long, J. Ma, Y. Wang, Y. Lei, J. Zhou, D. Han, and J. Geng, Elastic and anisotropic properties of organic-rich lacustrine shales: An experimental study, Geophysical Prospecting, 2024, 72(8), 2958-2977

2023

[76] Zhao, L*., J. Zhu, X. Qin, R. Gong, Z. Cai, F. Zhang, D. Han, and J. Geng, Joint geochemisty-rock physics modeling: Quantifying the effects of thermal maturity on the elastic and anisotropic properties of organic shale, Earth-Science Reviews, 247,104627

[75] Yan, D., L. Zhao*, Y. Wang, Y. Zhang, Z. Cai, X. Song, F. Zhang, and J. Geng, 2023, Heterogeneity Indexes of unconventional reservoir shales: quantitatively characterizing mechanical properties and failure behaviors, International Journal of Rock Mechanics and Mining Sciences, 171, 105577  

[74] Wang. J*, B. Ma, L. Zhao, P. Su*,  and S. Wu, 2023, Rock physics diagnostics to characterize early diagenetic processes in hemipelagic calcareous ooze in the northern South China Sea margin, Marine Geophysical Research, 44, 20

[73] Liu, J., L. Zhao*, M. Xu, X. Zhao, Y. You, J. Geng, 2023, Porosity prediction from prestack seismic data via deep learning: Incorporating low-frequency porosity model, Journal of Geophysics and Engineering, 20, 1016–1029

[72] 耿建华*， 赵峦啸， 麻纪强， 朱津琬， 姚秋粮， 高志前， 何治亮，2023,超深碳酸盐岩油气储层岩石弹性性质高温高压超声实验研究，地球物理学报, 66(9), 3959-3974

[71] Qin, X., L. Zhao*, J. Zhu, and D. Han, 2023, Modeling the elastic characteristics of overpressure due to thermal maturation in organic shales, Advances in Geo-Energy Research 10 (3), 174-188

[70] Wang, Y., L. Zhao*, Z. Yang, H. Cao, and J. Geng, 2023, Rock Physics Modeling Elastic Properties of Multiscale Fractured Rocks, Geophysics, 88 (6), MR289–MR304.

[69] 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), M185-M200

[68] 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), MR117-MR126

[67] 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

[66] 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.

[65] Sun, S., J. Nie, B. Wang, L. Zhao, Z. He, H. Zhang, D. Chen, J. Geng*, 2023, Generating complete synthetic datasets for high‐resolution amplitude‐versus‐offset attributes deep learning inversion, Geophysical Prospecting, 71 (6), 891-913

[64] Hussein, A., L. Zhao*, Y. Chen, and J. Wang, 2023,  Rock Physics characteristics of marine sediments in the South China Sea: link between the geological factors and elastic properties, Frontiers in Earth Science, 10, 931611

[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, International Journal 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.