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ZHANG Dongxiao
Chair Professor
Member of the National Academy of Engineering (USA)
zhangdx@sustech.edu.cn
Personal Homepage

Professor Zhang is the Provost at Southern University of Science and Technology, Shenzhen, China. He is a Member of the U.S. National Academy of Engineering, an Honorary Member of Society of Petroleum Engineers, and a Fellow of Geological Society of America. He had held positions as Senior Scientist at Los Alamos National Laboratory, Miller Chair Professor at the Department of Petroleum and Geological Engineering at the University of Oklahoma, Chair Professor at the University of Southern California, Executive Dean of Graduate School and Dean of College of Engineering at Peking University. He has authored 2 books and published over 180 peer-reviewed papers. He earned both his Master’s degree and Ph.D. in hydrology and water resources in 1992 and 1993, respectively, from the University of Arizona. Professor Zhang is an internationally well known expert in unconventional oil and gas production, groundwater hydrology, and geological carbon sequestration, whose research achievements in stochastic modeling, numerical simulation, inverse modeling and machine learning are widely adopted by his peers. Professor Zhang has been an associate editor for SPE Journal, Water Resource Research, Advances in Water Resources, SIAM Multiscale Modeling and Simulation, Journal of Computational Geosciences, Journal of Natural Gas Science and Engineering, and Vadose Zone Journal. He has served as a panelist on the RCUK Review of Energy, UK Research Councils, a member of US National Research Council’s Committee on New Research Opportunities in the Earth Sciences, and a council member of World Economic Forum Global Agenda Council on New Energy Architecture.

 

Education:

1/93-12/93Ph.D. in Hydrology. Dissertation: Conditional Stochastic Analysis of Solute Transport in Heterogeneous Geologic Media. Advisor: Regents’ Professor Shlomo P. Neuman. Dept. of Hydrology and Water Resources, College of Engineering, University of Arizona, Tucson.
8/91-12/92M.Sc. in Hydrology. Thesis: Some Aspects of Stochastic Flow and Transport in Complex Geologic Media. Advisor: Regents’ Professor Shlomo P. Neuman. Dept. of Hydrology and Water Resources, College of Engineering, University of Arizona, Tucson.
8/90-7/91Graduate Studies in Geological Engineering. Dept. of Mining and Geological Engineering, College of Engineering, University of Arizona, Tucson.
8/88-7/89Graduate Studies in Rock Mechanics. Dept. of Civil and Mining Engineering. Northeastern University, Shenyang, China.
8/84-7/88B.Sc. in Engineering. Bachelor’s Thesis: A Moire Gauge for Measuring Rock Strain (A Patent Awarded). Graduated first in a class of 60. Dept. of Civil and Mining Engineering, Northeastern University, Shenyang, China.

 

Experience:

07/19-presentProvost and Chair Professor, Southern University of Science and Technology (SUSTech), Shenzhen, China.
11/17-08/19Executive Dean, Graduate School, Peking University (PKU), Beijing, China.
07/13-07/19Dean, College of Engineering, Peking University (PKU), Beijing, China; Director, PKU Institute of Ocean Research; Chair Professor, Dept. of Energy and Resources Engineering.
08/10-06/13Executive Dean, College of Engineering; Chair Professor, Dept. of Energy and Resources Engineering, Peking University, Beijing, China.
08/07-08/10Gordon S. Marshall Professor of Water Resources & Petroleum Engineering, the Sonny Astani Dept. of Civil and Environmental Engineering and the Mork Family Dept. of Chemical Engineering and Materials Science, the University of Southern California.
07/05-08/10Guest Professor, and Founding Chair (2005-2007, Consulting), Dept. of Energy and Resources Engineering; Founding Vice Dean (2005-2007, Consulting), College of Engineering, Peking University, Beijing, China.
03/04-07/07Miller Chair Professor, Mewbourne School of Petroleum and Geological Engineering, the University of Oklahoma.
09/96-03/04Senior Research Scientist, and Team Leader (1999-2003), Earth and Environmental Sciences Division, Los Alamos National Laboratory.
08/02-12/02Visiting Faculty, Dept. of Civil Engineering, Hong Kong University of Science and Technology. Sabbatical leave from Los Alamos National Lab. Teaching: Stochastic Subsurface Hydrology. Research: Coupling of Surface/Subsurface Flows.
06/03-12/10Adjunct Professor, Dept. of Earth Sciences, Nanjing University, Nanjing, China.
12/01-12/09Associate Editor, Water Resources Research, American Geophysical Union.
08/02 -presentAssociate Editor, Society of Petroleum Engineers Journal (SPE Journal).
07/03-12/08Associate Editor, Vadose Zone Journal, the Soil Science Society of America.
07/04-presentEditorial Board, Advances in Water Resources Research.
01/05-12/11Associate Editor, SIAM Multiscale Modeling and Simulation.
01/07-presentAssociate Editor, Journal of Computational Geosciences.
01/10-presentConsultant Editor, Greenhouse Gases: Science and Technology.
03/95-08/96Senior Hydrologist, Daniel B. Stephens & Associates, Inc.
01/94-02/95Assistant Research Scientist, Dept. of Hydrology and Water Resources, University of Arizona.
01/93-12/93Graduate Research Associate, Dept. of Hydrology and Water Resources, University of Arizona.
08/91-12/92Graduate Research Assistant, Dept. of Hydrology and Water Resources, University of Arizona.
08/90-07/91Graduate Teaching Assistant, Dept. of Mining and Geological Engineering, University of Arizona.

 

Honors and Awards:

Elected Member, the U.S. National Academy of Engineering, 2017.
Honorary Membership Award, Society of Petroleum Engineers, 2017.
Distinguished Member Award, Society of Petroleum Engineers, 2017.
Recipient of “Top 100 Most Cited Chinese Papers Published in International Journals” Award, 2011.
Elected Member, The Phi Tau Phi Scholastic Honor Society of America, 2011.
Elected Fellow, Geological Society of America, 2009.
Society of Petroleum Engineers Journal, 2007 Outstanding Review Chair Award.
Society of Petroleum Engineers Journal, 2006 Outstanding Technical Editor Award.
Natural Science Foundation of China, Outstanding Young Researcher Award, 2007-2011.
Chinese Academy of Sciences, Outstanding Young Oversea Researcher Foundation Award, 2005-2007.
Elected Member of Chinese Academy of Sciences’ Oversea Evaluation Expert Committee, 2005-2007.
Elected Member, IPACES (International Professionals for the Advancement of Chinese Earth Sciences), since 2002.
Los Alamos Award, 1999.
LANL Outstanding Asian Employee, 1997.
Top Student Awards, 1984-1988.

 

Professional Memberships:

AGU, American Geophysical Union, since 1992.
SPE, Society of Petroleum Engineers, since 1999; Honorary Membership, since 2017.
GSA, Geological Society of America, since 2001; Fellow, since 2009.
ASCE, American Society of Civil Engineers, since 2003.
SIAM, Society of Industrial and Applies Mathematics, since 2005.
NAE, the U.S. National Academy of Engineering, Member, since 2017.

 

Publications

Researcher ID: https://publons.com/researcher/2968087/dongxiao-zhang/
Google Scholar Author Profile: Dongxiao Zhang (http://scholar.google.com/citations?user=HJdIx6QAAAAJ&hl=en)

 

Books:

  1. Zhang, D., Stochastic Methods for Flow in Porous Media: Coping with Uncertainties, Academic Press, San Diego, Calif., ISBN 012-7796215, pp.350, 2002.  (SCI citation: 410；Google Scholar: 610)

  2. Zhang, D., and C.L. Winter, editors, Theory, Modeling and Field Investigation in Hydrogeology, Geological Society of America, pp.245, 2000.

 

Papers in Refereed Journals (* indicates corresponding author):

 

Under Review:

  1. Zheng, Q., and Zhang*, Digital rock reconstruction with user-defined properties using conditional generative adversarial networks,Journal of Geophysical Research – Solid Earth, under review, 2020.

  2. Xu, H., D. Zhang*, N. Wang,Deep-learning based discovery of partial differential equations in integral form from sparse and noisy data, Journal of Computational Physics, under review, 2020.

  3. Wang, N., H. Chang, and D. Zhang*, Theory-guided Auto-Encoder for Surrogate Construction and Inverse Modeling, Computer Methods in Applied Mechanics and Engineering, under review, 2020.

  4. Xu, H., Zhang*, and J. Zeng, Deep-learning of Parametric Partial Differential Equations from Sparse and Noisy Data, Phys. Rev. Research, under review, 2020.(arXiv:2005.07916)

  5. Luo, X., D. Zhang*, and X. Zhu, Deep Learning Based Forecasting of Photovoltaic Power Generation via Theory-guided LSTM, Energy, under review, 2020. (Preprint available at www.enerarxiv.org/page/thesis.html?id=1878)

  6. Zheng, J., P. Tang, H. Li, and D. Zhang*, Simulating particle settling in inclined narrow channels with the unresolved CFD-DEM method, Phys. Rev. Fluids,under review, 2020.

  7. Wang, N., H. Chang, and D. Zhang*, Deep-Learning based Inverse ModelingApproaches:A Subsurface Flow Example, Journal of Geophysical Research – Solid Earth, under review, 2020.

  8. Xu, R., D. Zhang*, M. Rong, and N. Wang,Weak Form Theory-guided Neural Network (TgNN-wf) for Deep Learning of Subsurface Single and Two-phase Flow, Journal of Computational Physics, under review, 2020.

  9. Rong, M., D. Zhang*, and N. Wang, A Lagrangian Dual-based Theory-guided Deep Neural Network, Complex& Intelligent Systems, under review, 2020. (arXiv:2008.10159)

  10. Jiang, C., and D. Zhang*, Lithology identification from well log curves via neural networks with additional geological constraint, Geophysics, under review, 2020.

  11. Xia, Z., P. Zhang, and D. Zhang*, Nanopore characteristics of lacustrine shale oil reservoir in the Shahejie Formation, Bohai Bay Basin, China, Journal of Natural Gas Science & Engineering, under review, 2020.

  12. Yang, W., and D. Zhang*, Experimental investigate of multiphase flow in 3D-printed, filled fracture-vug media, Journal of Natural Gas Science & Engineering, under review, 2020.

  13. He, T. and Zhang*, Deep Learning of Dynamic Subsurface Flow via Theory-guided Generative Adversarial Network, Journal of Hydrology, under review, 2020.(arXiv:2006.13305)

  14. Zhang, W., D. Zhang*, and J. Zhao, Experimental investigation of water sensitivity effects on microscale mechanical behavior of shale, International Journal of Rock Mechanics and Mining Sciences, under review, 2020. (Preprint available online at ESSOAr: https://doi.org/10.1002/essoar.10502272.2)

 

2021 (2):

  1. Wang, N., H. Chang*, and Zhang*, Efficient Uncertainty Quantification for Dynamic Subsurface Flow with Surrogate by Theory-guided Neural Network, Computer Methods in Applied Mechanics and Engineering, https://doi.org/10.1016/j.cma.2020.113492, 2021. (arXiv:2004.13560)

  2. Chen, Y., and D. Zhang*, Theory guided deep-learning for load forecasting (TgDLF) via ensemble long short-term memory (EnLSTM), Advances in Applied Energy, doi.org/10.1016/j.adapen.2020.100004, 2020. (Preprint available at http://www.enerarxiv.org/page/thesis.html?id=2022)

 

2020 (20):

  1. Chen, Y., and D. Zhang*, Well log generation via ensemble long short-term memory (EnLSTM) network, Geophy. Res. Lett., DOI:10.1029/2020GL087685, 2020

  2. Li, S., A. Firoozabadi*, and Zhang*, Hydromechanical Modeling of Nonplanar Three-Dimensional Fracture Propagation Using an Iteratively Coupled Approach, Journal of Geophysical Research – Solid Earth, 10.1029/2020JB020115, 2020. (Preprint available online at ESSOAr: doi.org/10.1002/essoar.10503101.1)

  3. Zhao, J., W. Zhang, R. Wei, Y. Wang, and Zhang*, Influence of geochemical features on the mechanical properties of organic matter in shale, Journal of Geophysical Research – Solid Earth, 10.1029/2020JB019809, 2020. (Preprint available online at ESSOAr: doi.org/10.1002/essoar.10502590.1)

  4. Xu, H., H. Chang*, and Zhang*, DLGA-PDE: Discovery of PDEs with incomplete candidate library via combination of deep learning and genetic algorithm, Journal of Computational Physics, DOI: 10.1016/j.jcp.2020.109584, 2020. (arXiv:2001.07305)

  5. Xu, H., H. Chang*, and Zhang*, DL-PDE: Deep-learning based data-driven discovery of partial differential equations from discrete and noisy data, Commun. Comp. Phys., in press, 2020. (arXiv:1908.04463)

  6. Wang, N., D. Zhang*, H. Chang, and H. Li, Deep Learning of Subsurface Flow via Theory-guided Neural Network, Journal of Hydrology, 10.1016/j.jhydrol.2020.124700, 2020. (arXiv:1911.00103)

  7. Zhao, L., H. Li*, J. Meng, and D. Zhang, Efficient uncertainty quantification for permeability of three-dimensional porous media through image analysis and pore-scale simulations, Rev. E, 102, 023308, DOI: 10.1103/PhysRevE.102.023308, 2020.

  8. Wu, T., J. Zhao, W. Zhang, and D. Zhang*, Nanopore Structure and Nanomechanical Properties of Organic-Rich Terrestrial Shale: An Insight into Technical Issues for Hydrocarbon Production, Nano Energy, 69: 104426, 10.1016/j.nanoen.2019.104426, 2020.

  9. Zhao, J., and D. Zhang*, Dynamic crack propagation in heterogeneous shale at microscale, Engineering Fracture Mechanics, 10.1016/j.engfracmech.2020.106906, 2020.

  10. Chen, Y., and D. Zhang*, Physics-constrained deep learning of geomechanical logs, IEEE Transactions on Geoscience and Remote Sensing, 10.1109/TGRS.2020.2973171, 2020.

  11. Li, X., X. Li, D. Zhang*, and R. Yu, A dual grid, implicit, and sequentially coupled geomechanics-and-composition model for fractured reservoir simulation, SPE Journal, DOI: 10.2118/201210-PA, 2020.

  12. Lei, G., Q. Liao*, D. Zhang, S. Patil, A mechanistic model for permeability in deformable gas hydrate-bearing sediments, Journal of Natural Gas Science & Engineering, doi.org/10.1016/j.jngse.2020.103554, 2020.

  13. Yang, W., Zhang*, and G. Lei, Experimental study on multiphase flow in fracture-vug medium using 3D Printing Technology and Visualization Techniques, Journal of Petroleum Science and Engineering, 10.1016/j.petrol.2020.107394, 2020. (Preprint available online at ESSOAr: 10.1002/essoar.10502278.1)

  14. Li, S. Z. Kang, X.-T. Feng, Z. Pan, X. Huang, and Zhang*, Three‐dimensional hydrochemical model for dissolutional growth of fractures in karst aquifers, Water Resources Research, 56, e2019WR025631, https://doi.org/10.1029/2019WR025631, 2020.

  15. Wu, T., Zhang*, & X. Li, A radial differential pressure decay method with micro-plug samples for determining the apparent permeability of shale matrix, Journal of Natural Gas Science & Engineering, 74: 103126, 10.1016/j.jngse.2019.103126, 2020.

  16. Chen, Y., and Zhang*, Physics-constrained indirect supervised learning, Theoretical and Applied Mechanics Letters, 10: 1-6, http://dx.doi.org/10.1016/j.taml.2020.01.019, 2020.

  17. Yang, W., J. Zeng, and Zhang*, Contrasting phase field method and pairwise force smoothed particle hydrodynamics method in simulating multiphase flow through fracture-vug medium, Journal of Natural Gas Science and Engineering, https://doi.org/10.1016/j.jngse.2020.103424, 2020.

  18. Liao, Q., G. Lei, Z. Wei, Zhang*, and S. Patil, Efficient Analytical Upscaling Method for Elliptic Equations in Three-dimensional Heterogeneous Anisotropic Media, Journal of Hydrology, 10.1016/j.jhydrol.2020.124560, 2020.

  19. Zhang, Y., Q. Wen, and D. Zhang*, A novel targeted-plugging and fracture-adaptable gel used as a diverting agent in fracturing, Energy Science & Engineering, 10.1002/ese3.513, 2020.

  20. Teng, Y., and Zhang*, Comprehensive study and comparison of equilibrium and kinetic models in simulation of hydrate reaction in porous media, Journal of Computational Physics, 10.1016/j.jcp.2019.109094,2020.

 

2019 (13):

  1. Chang, H., and Zhang*, Identification of Physical Processes via Combined Data-driven and Data-assimilation Methods, J. Comp. Phy., DOI: 10.1016/j.jcp.2019.05.008, 393: 337-350, 2019.

  2. Chang, H., and Zhang*, Machine Learning Subsurface Flow Equations from Data, Comp. Geosci., DOI: 10.1007/s10596-019-09847-2, 2019.

  3. Chen, Y., H. Chang, J. Meng, and D. Zhang*, The Ensemble Neural Networks (ENN): A Stochastic Gradient-free Method, Neural Networks, DOI: 10.1016/j.neunet.2018.11.009, 110, pp. 170-185, 2019.

  4. Liu, X., and D. Zhang*, A Review of Phase Behavior Simulation of Hydrocarbons in Confined Space: Implications for Shale Oil and Shale Gas, Journal of Natural Gas Science and Engineering, 10.1016/j.jngse.2019.102901, 2019.

  5. Zhao, J., Zhang*, T. Wu, H. Tang, Q. Xuan, Z. Jiang, and C. Dai, Multiscale approach for mechanical characterization of organic-rich shale and its application, International Journal of Geomechanics, 19(1): 04018180, DOI: 10.1061/ (ASCE)GM.1943-5622.0001281,2019.

  6. Li, S., X. Feng, Zhang*, and H. Tang,Coupled Thermo-hydro-mechanical Analysis of Stimulation and Production for Fractured Geothermal Reservoirs, Applied Energy, DOI: 10.1016/j.apenergy.2019.04.036 , 247: 40-59, 2019.

  7. Lei, G., Q. Liao, and D. Zhang, A new analytical model for flow in acidized fractured-vuggy porous media, Scientific Reports, 9(1), doi.org/10.1038/s41598-019-44802-2, 2019.

  8. Liao, Q., L. Gang, D. Zhang, and S. Patil, Analytical Solution for Upscaling Hydraulic Conductivity in Anisotropic Heterogeneous Formations, Adv. Water Resour., DOI: 10.1016/j.advwatres.2019.04.011, 128: 97-116, 2019.

  9. Yao, M., H. Chang, X. Li, and D. Zhang*, An Integrated Approach for the History Matching of Multiscale-Fractured Reservoir, SPE Journal, doi.org/10.2118/195589-PA, in press, 2019.

  10. Zhou, S., D. Zhang*, H. Wang, and X. Li, A modified BET Equation to Investigate Supercritical Methane Adsorption Mechanisms in Shale, Marine & Petroleum Geology, DOI: 10.1016/j.marpetgeo.2019.04.036, 105: 284–292, 2019.

  11. Liao, Q., L. Zeng, H. Chang, and D. Zhang, Efficient History Matching using Markov Chain Monte Carlo via Transformed Adaptive Stochastic Collocation Method, SPE Journal,SPE194488, inpress, 2019.

  12. Zeng, J., H. Li, and D. Zhang, Numerical Simulation of Proppant Transport in Propagating Fractures with the Multi-phase Particle-in-cell Method, Fuel,245: 316-335, doi.org/10.1016/j.fuel.2019.02.056, 2019.

  13. Tan,Y., Z. Pan, X-T Feng, D. Zhang, L. D. Connell, and S. Li, Laboratory Characterisation of Fracture Compressibility for Coal and Shale Gas Reservoir Rocks: A Review, Int’l J. Coal Geol., 204:1-17, 10.1016/j.coal.2019.01.010, 2019.

 

2018 (8):

  1. Teng, Y., and D. Zhang*, Long-term Viability of Carbon Sequestration in Deep-sea Sediments, Science Advances, 4, 10.1126/sciadv.aao6588, 2018.

  2. Yao, M., H. Chang, X. Li, and Zhang*, Tuning Fractures with Dynamic Data, Water Resources Research, 54, https://doi.org/10.1002/2017WR022019, 2018.

  3. Li, S., and D. Zhang*, How Effective is Carbon Dioxide as an Alternative Fracturing Fluid? SPE J, SPE-194198-PA, https://doi.org/10.2118/194198-PA, 2018.

  4. Zhang, D., Y. Chen*, and J. Meng, Synthetic Well Logs Generation based on Recurrent Neural Networks, Petroleum Exploration and Development, 2018, 45(4): 629-639. [Chinese version: 张东晓, 陈云天, 孟晋. 基于循环神经网络的测井曲线生成方法[J]. 石油勘探与开发, 2018, 45(4): 598-607.]

  5. Li, X., X. Li, and D. Zhang, Generalized Prism Grid: a pillar-based unstructured grid for simulation of reservoirs with complicated geological geometries, Comput. Geosci., 22: 6, 1561-1581, 10.1007/s10596-018-9774-0, 2018.

  6. Jiang,Z., L. Zhao, and D.Zhang*, Study of Adsorption Behavior in Shale Reservoirs under High Pressure, J. Natural Gas Sci. & Eng., DOI: 10.1016/j.jngse.2017.11.009, 49: 275-285, 2018.

  7. Tang, H., S. Li, and D. Zhang*, The Effect of Heterogeneity on Hydraulic Fracturing,Journal of Petroleum Science and Engineering, 162: 292-308, 2018.

 

2017 (12):

  1. Wu, T, X. Li, J. Zhao, and D. Zhang*, MultiscalePore Structure and its Effect on Gas Transport in Organic-rich Shale, WaterResources Research, DOI: 1002/2017WR020780, 53(7): 5438–5450, 2017.

  2. Chen, Y., J. Su, Zhang*, C. Liu, Estimation of Shale Gas Resource via Statistical Learning, Applied Energy, DOI: 10.1016/j.apenergy.2017.04.029, 197: 327-341, 2017.

  3. Chang, H., and Zhang*, History Matching of Stimulated Reservoir Volume of Shale Gas Reservoirs Using an Iterative Ensemble Smoother, SPE Journal, SPE-189436-PA,DOI: 10.2118/189436-PA, 2017.

  4. Yang, T., X. Li, and D. Zhang*, Where Gas is Produced from a Shale Formation: A Simulation Study, J. Natural Gas Sci. & Eng., DOI:10.1016/j.jngse.2017.06.015, 45: 860-870, 2107.

  5. Lei, G., D. Zhang, W. Yang, and H. Wang, Mathematical Model for Wells Drilled in Large-Scale Partially Filled Cavity in Fractured-Cavity Reservoirs(缝洞型油藏井钻遇大尺度部分充填溶洞数学模型), Earth Science, 42(8): 1413-1420, 2017.

  6. Jiang, Z., D. Zhang*, J. Zhao, and Y. Zhou,Experimental Investigation of the Pore Structure of Triassic Terrestrial Shale in the Yanchang Formation, Ordos Basin, China, J. Natural Gas Sci. & Eng., DOI: 10.1016/j.jngse.2017.08.002, 2017.

  7. Zhang, Z., H. Li, and D. Zhang, Reservoir Characterization and Production Optimization using the Ensemble-based Optimization Method and Multi-layer Capacitance-resistive Models, J. Petrol. Sci. Eng., DOI: 10.1016/j.petrol.2017.06.020, 2017.

  8. Liao, Q., D. Zhang, and H. Tchelepi, Nested sparse grid collocation method with delay and transformation for subsurface flow and transport problems, Adv. Water Resour., DOI: 10.1016/j.advwatres.2017.03.020, 104: 158-173, 2017.

  9. Li, S., D. Zhang*, and X. Li. A New Approach to the Modeling of Hydraulic Fracturing Treatments in Naturally Fractured Reservoirs,SPE Journal, Doi:10.2118/181828-PA, 22(4): 1064-1081, 2017.

  10. Li, S., and D. Zhang*, A Fully Coupled Model for Hydraulic Fracture Growth during Multi-well Fracturing Treatments: Enhancing Fracture Complexity, SPE Production & Operations, DOI: 10.2118/182674-PA, inpress, 2017.

  11. Chang, H., Q. Liao, and D. Zhang, Surrogate Model based Iterative Ensemble Smoother for Subsurface Flow Data Assimilation, Adv. Water Resour., Doi:10.1016/j.advwatres.2016.12.001, 100: 96-108, 2017.

  12. Liao, Q., D. Zhang, and H. Tchelepi, A Two-stage Adaptive Stochastic Collocation Method on Nested Sparse Grids for Multiphase Flow in Randomly Heterogeneous Porous Media, J. Comp. Phys., DOI: 10.1016/j.jcp.2016.10.061, 330: 828-845, 2017.

 

2016 (6):

  1. Wu, T., and D. Zhang*, Impact of Adsorption on Gas Transport in Nanopores, Scientific Reports, 6:23629, DOI: 10.1038/srep23629, 2016.

  2. Li, X., Y. Xue, M. Zou, D. Zhang, A. Cao, and H. Duan, Direct Oil Recovery from Saturated Carbon Nanotube Sponges, ACS Appl. Mater. Interfaces, DOI: 10.1021/acsami.6b01623, 8(19): 12337–12343, 2016.

  3. Li, S., X. Li, and D. Zhang*, A Fully Coupled Thermo-Hydro-Mechanical, Three-Dimensional Model for Hydraulic Stimulation Treatments,J. Natural Gas Sci. & Eng.,DOI: 10.1016/j.jngse.2016.06.046, 34: 64-84, 2016.

  4. Dai, C., L. Xue, D. Zhang, and A. Guadagnini, Data-worth Analysis through Probabilistic Collocation-based Ensemble Kalman Filter, J. Hydrol., DOI: 10.1016/j.jhydrol.2016.06.037, 540: 488–503, 2016.

  5. Zeng, J., H. Li, and D. Zhang, Numerical Simulation of Proppant Transport in Hydraulic Fracture with Upscaling CFD-DEM Method, J. Natural Gas Sci. & Eng.,doi:10.1016/j.jngse.2016.05.030, 33: 264-277, 2016.

  6. Liao, Q., and D. Zhang*, Probabilistic Collocation Method for Strongly Nonlinear Problems: 3. Transform by Time, Water Resour. Res., 52, doi:10.1002/2015WR017724, 2016.

 

2015 (12):

  1. Chang, H., Q. Liao, and D. Zhang*, Benchmark Problems for Subsurface Flow Uncertainty Quantification,J. Hydrol.,doi:10.1016/j.jhydrol.2015.09.040, 531:168-186, 2015.

  2. Li, X., and D. Zhang*, A Multi-continuum Multiple Flow Mechanism Simulator for Unconventional Oil andGasRecovery, J. Natural Gas Sci. & Eng., doi: 10.1016/j.jngse.2015.07.005, 652-669, 2015.

  3. Lu, L., and D. Zhang*, Assisted History Matching for Fractured Reservoirs using Hough Transform based Parameterization, SPE Journal, http://dx.doi.org/10.2118/176024-PA, 20(5): 942-961,2015.

  4. Zhang, D.*, T. Yang, T. Wu, X. Li, and J. Zhao, Recovery Mechanisms and Key Issues in Shale Gas Development, Chin. Sci. Bull., 61: 62-71, 2015. (页岩气开发机理和关键问题, 科学通报)

  5. Chen, Y., Q. Kang, Q. Cai, M. Wang, and D. Zhang,Lattice Boltzmann Simulation of Particle Motion in BinaryImmiscible Fluids, Communications in Computational Physics, 18(3): 757-786, 2015.

  6. Zhang, D.*, and T. Yang,Environmental Impacts of Hydraulic Fracturing in Shale Gas Development in the United States, Petroleum Exploration and Development, 42(6): 876-883, 2015. (页岩气开发水力压裂技术的环境影响, 石油勘探与开发, 2015)

  7. Chang, H., and D. Zhang, Jointly Updating the Mean Size and Spatial Distribution of Facies in Reservoir History Matching, Comp. Geosci., DOI 10.1007/s10596-015-9478-7, 19(4): 727-746, 2015.

  8. Liao, Q., and D. Zhang*, Data Assimilation for Strongly Nonlinear Problems by Transformed Ensemble Kalman Filter, SPE Journal, 20(1): 202-221,DOI:10.2118/173893-PA, 2015.

  9. Yang, T., X. Li, and D. Zhang*, Quantitative Dynamic Analysisof Gas Desorption Contribution to Production in Shale Gas Reservoirs, J. Uncon. Oil & Gas Resour., doi:10.1016/j.juogr.2014.11.003, 9:18-30, 2015.

  10. Dai, C., H. Li, D. Zhang*, and L. Xue, Efficient Data-Worth Analysis for the Selection of Surveillance Operation in a Geologic CO2Sequestration System, Greenhouse Gases: Science and Technology, DOI:10.1002/ghg.1492, 5(5):513-529, 2015.

  11. Zhang, Z., H. Li, and D. Zhang, Water Flooding Performance Prediction by Multi-Layer Capacitance-Resistive Models Combined with the Ensemble Kalman Filter, J. Petrol. Sci. Eng., 1-19, 10.1016/j.petrol.2015.01.020, 2015.

  12. Liao, Q., and D. Zhang*, Constrained Probabilistic Collocation Method for Uncertainty Quantification of Geophysical Models, Comp. Geosci., DOI 10.1007/s10596-015-9471-1, 19(2): 311-326, 2015.

 

2014 (10):

  1. Li, W., G. Lin, and D. Zhang*, An Adaptive ANOVA-based PCKF for High-Dimensional Nonlinear Inverse Modeling, Journal of Computational Physics, 258C: 752-772, 10.1016/j.jcp.2013.11.019, 2014.

  2. Xue, L., and D. Zhang*,A Multimodel Data Assimilation Framework via the Ensemble Kalman Filter, Water Resour. Res., 50(5): 4197-4219,DOI:10.1002/2013WR014525, 2014.

  3. Liao, Q., and D. Zhang*, Probabilistic Collocation Method for Strongly Nonlinear Problems: 2. Transform by Displacement, Water Resour. Res., DOI:10.1002/2014WR016238, 2014.

  4. Xue, L., D. Zhang, A. Guadagnini, and S.P. Neuman, Multimodel Bayesian Analysis of Groundwater Data Worth, Water Resour. Res., DOI:10.1002/2014WR015503, 2014.

  5. Ping, J., and D. Zhang*, History Matching of Channelized Reservoirs with Vector-based Level Set Parameterization, SPE Journal, 19(3): 514-529, 10.2118/169898-PA, 2014.

  6. Dai, C., H. Li, and D. Zhang*, Efficient and Accurate Global Sensitivity Analysis for Reservoir Simulations Using Probabilistic Collocation Method, SPE Journal, 19(4): 621-634, 10.2118/167609-PA,2013.

  7. Chang, H., and D. Zhang, History Matching of Statistically Anisotropic Fields Using Karhunen-Loeve Expansion based Global Parameterization Technique, Comp. Geosci., 18(2): 265-282, 2014.

  8. Li, X. and D. Zhang*, A Backward Automatic Differentiation Framework for Reservoir Simulation,Comp. Geosci., 10.1007/s10596-014-9441-z, 18:1009-1022, 2014.

  9. Chang, H., and D. Zhang, History Matching of Facies Distribution with Varying Mean Lengths or Different Principle Correlation Orientations, J Petrol. Sci. Eng., DOI: 10.1016/j.petrol.2014.09.029, 124: 275-292, 2014.

  10. Zhang, D.*, and J. Song, Mechanisms for Geological Carbon Sequestration,Procedia IUTAM, 10: 319-327, 2014.

 

2013 (8):

  1. Song, J., and D. Zhang*, Comprehensive Review of Caprock-Sealing Mechanisms for Geologic Carbon Sequestration, Environmental Science and Technology, 10.1021/es301610p, 47: 9-22, 2013.

  2. Sun A.Y., M. Zeidouni, J.-P. Nicot, Z. Lu, and D. Zhang, Assessing Leakage Detectability at Geologic CO2Sequestration Sites using the Probabilistic Collocation Method, Adv. Water Resour., 10.1016/j.advwatres.2012.11.017, 2013.

  3. Wei, Z., and D. Zhang*, A Fully Coupled Multicomponent, Multiphase Flow and Geomechanics Model for Enhanced Coalbed Methane Recovery and CO2Storage, SPE Journal, 18(3): 448-467, 2013.

  4. Li, H., and D. Zhang, Stochastic Representation and Dimension Reduction for Non-Gaussian Random Fields: Review and Reflection, Stochastic Environmental Research and Risk Assessment, DOI 10.1007/s00477-013-0700-7, 27:1621–1635, 2013.

  5. Ping, J., and D. Zhang*, History Matching of Fracture Distributions by Ensemble Kalman Filter Combined with Vector Based Level Set Parameterization, Journal of Petroleum Science and Engineering, http://dx.doi.org/10.1016/j.petrol.2013.04.018i, 2013.

  6. Zhang*, D., T. Yang, An Overview of Shale-Gas Production, ACTA PETROLEI SINICA, 2013, 34 (4): 792-801. (张东晓, 杨婷云. 页岩气开发综述. 石油学报, 2013, 34 (4): 792－801.)

  7. Xie, X., and D. Zhang, A Partitioned Update Scheme for State-Parameter Estimation of Distributed Hydrologic Models based on the Ensemble Kalman Filter, Water Resour. Res., VOL. 49, 7350–7365, 10.1002/2012WR012853, 2013.

  8. Liao, Q., and D. Zhang*, Probabilistic Collocation Method for Strongly Nonlinear Problems: 1. Transform by location, Water Resour. Res., 49(12), 7911-7928, 10.1002/2013WR014055,2013.

 

2012(4):

  1. Jahangiri, H.R., and D. Zhang*, Ensemble Based Co-optimization of Carbon Dioxide Sequestration and Enhanced Oil Recovery, International Journal of Greenhouse Gas Control, 10.1016/j.ijggc.2012.01.013, 8: 22-33, 2012.

  2. Zeng, L., L. Shi, D. Zhang, and L. Wu, A Sparse Grid Based Bayesian Method for Contaminant Source Identification, Adv. Water Resour., 10.1016/j.advwatres.2011.09.011, 37:1-9, 2012.

  3. Shi, L., L. Zeng, D. Zhang, and J. Yang, Multiscale-Finite-Element-Based Ensemble Kalman Filter for Large-Scale Groundwater Flow, J. Hydrology, DOI: 10.1016/j.jhydrol.2012.08.003, 468: 22-34, 2012.

  4. Li, Z., D. Zhang, and X. Li, Tracking Colloid Transport in Real Pore Structures: Comparisons with Correlation Equations and Experimental Observations, Water Resour. Res., 48, doi:10.1029/2012WR011847, 2012.

2011(5):

  1. Zeng, L., H. Chang, and D. Zhang*, A Probabilistic Collocation Based Kalman Filter for History Matching, SPE Journal, SPE-140737-PA-P, 294-306, 2011.

  2. Li, H., P. Sarma, andD. Zhang*, A Comparative Study of the Probabilistic Collocation and Experimental Design Methods for Petroleum Reservoir Uncertainty Quantification,SPE Journal, SPE-140738-PA-P, 429-439, 2011.

  3. Jahangiri, H.R., and D. Zhang*, Effect of Spatial Heterogeneity on Plume Distribution and Dilution during CO2Sequestration, International Journal of Greenhouse Gas Control, 10.1016/j.ijggc.2010.10.003, 5:281-293, 2011.

  4. Jafroodia N., and D. Zhang, New Method for Reservoir Characterization and Optimization Using CRM-EnOpt Approach, J Pet. Sci. Eng., doi:10.1016/j.petrol.2011.02.011, 77: 155-171, 2011.

  5. Chen, Y., Q. Kang, Q.D. Cai, and D. Zhang, Lattice Boltzmann Method on Quadtree Grids, Physical Review E, 83, 026707, 2011.

 

2010(12):

  1. Xie, X.H., and D. Zhang, Data Assimilation for Distributed Hydrological Catchment Modeling via Ensemble Kalman Filter, Adv. Water Resources, doi:10.1016/j.advwatres.2010.03.012, 33: 678–690, 2010. (Selected as one of the “Top 100 Most Cited Chinese Papers Published in International Journals”)

  2. Zhang, D.*, L. Shi, H. Chang, and J. Yang, A Comparative Study of Numerical Approaches to Risk Assessment of Contaminant Transport, Stochastic Environmental Research and Risk Assessment, 10.1007/s00477-010-0400-5, 2010.

  3. Wei, Z., and D. Zhang*, Coupled Fluid Flow and Geomechanics for Triple-Porosity/Dual-Permeability Modeling of Coalbed Methane Recovery, International Journal of Rock Mechanics and Mining Sciences, 47: 1242–1253, 2010.

  4. Chang, H., D. Zhang*, and Z. Lu, History Matching of Facies Distribution with the EnKF and Level Set Parameterization, J. Comp. Phys., 229:8011-8030, DOI:10.1016/j.jcp.2010.07.005, 2010.

  5. Li, X.*, Z. Li, and D. Zhang*, Role of Low Flow and Backward Flow Zones on Colloid Transport in Pore Structures Derived from Real Porous Media, Environmental Science & Technology, 44(13), 4936-4942, 2010.

  6. Chen, C., and D. Zhang*, Pore-Scale Simulation of Density-Driven Convection in Fractured Porous Media during Geological CO2Sequestration, Water Resour. Res., 46, W11527, DOI: 10.1029/2010WR009453, 2010.

  7. Li, Z., D. Zhang, and X. Li, Tracking Colloid Transport in Porous Media Using Discrete Flow Fields and Sensitivity of Simulated Colloid Deposition to Space Discretization, Environmental Science & Technology, 44(4), 1274-1280, 2010.

  8. Chang, H., Y. Chen, and D. Zhang*, Data Assimilation of Coupled Fluid Flow and Geomechanics Using Ensemble Kalman Filter, SPE Journal, SPE-118963-PA, 15(2): 382-394, 2010.

  9. Zeng, L., and D. Zhang*, A Stochastic Collocation Based Kalman Filter for Data Assimilation, Computational Geosciences, 10.1007/s10596-010-9183-5, 2010.

  10. Wei, Z., and D. Zhang, Coupled Fluid Flow and Geomechanics in Coalbed Methane Recovery Study, Mod. Phy. Lett. B, 24(13): 1291-1294, DOI: 10.1142/S0217984910023451, 2010.

  11. Chen, C., A. Packman, D. Zhang, and J. -F. Gaillard, A Multi-scale Investigation of Interfacial Transport, Pore Fluid Flow, and Fine Particle Deposition in a Sediment Bed, Water Resour. Res., vol. 46, W11560, DOI: 10.1029/2009WR009018, 2010.

  12. Shi, L., D. Zhang*, L. Lin, and J. Yang, A Multiscale Probabilistic Collocation Method for Subsurface Flow in Heterogeneous Media, Water Resour. Res., VOL. 46, W11562, DOI:10.1029/2010WR009066, 2010.

 

2009 (12):

  1. Chen, Y., D. Oliver, and D. Zhang, Efficient Ensemble-based Closed-Loop Production Optimization, SPE Journal, 10.2118/112873-PA, 14(4): 634-645, 2009.

  2. Chen, Y., D. Oliver, and D. Zhang, Data Assimilation for Nonlinear Problems by Ensemble Kalman Filter with Reparameterization, J. Petroleum Science & Engineering,DOI:10.1016/j.petrol.2008.12.002, 66(1-2): 1-14, 2009.

  3. Rapaka, S., R. Pawar, P. Stauffer, D. Zhang, S. Chen, Onset of Convection Over a Transient Base-State in Anisotropic and Layered Porous Media, J. Fluid Mech., 641: 227-244, DOI:10.1017/S0022112009991479, 2009.

  4. Shi, L., J. Yang, D. Zhang, and H. Li, Probabilistic Collocation Method for Unconfined Flow in Heterogeneous Media, J. Hydrology, 365(1-2):4-10, 2009.

  5. Li, W., Z. Lu, D. Zhang*, Stochastic Analysis of Unsaturated Flow with Probabilistic Collocation Method, Water Resour. Res.,45, W08425, DOI: 10.1029/2008WR007530, 2009.

  6. Li, H., and D. Zhang*, Efficient and Accurate Quantification of Uncertainty for Multiphase Flow with Probabilistic Collocation Method, SPE Journal, 10.2118/114802-PA, 665－679, 2009.

  7. Chang, H., and D. Zhang*, A Comparative Study of Stochastic Collocation Methods for Flow in Porous Media, Commun. Comput. Phys.,6(3): 509-535, 2009.

  8. Shi, L.S., J.Z. Yang, and D. Zhang, A Stochastic Approach to Nonlinear Unconfined Flow Subject to Multiple Random Fields, Stochastic Environmental Research and Risk Assessment, 23: 823-835, DOI: 10.1007/s00477-008-0261-3, 2009.

  9. Shi, L., J. Yang,andD. Zhang, Evaluating the Uncertainty of Darcy Velocity with Sparse Grid Collocation Method, Science in China Series E: Technological Sciences, 52(11): 3270-3278, 10.1007/s11431-009-0353-4, 2009.

  10. Lu, G., D. J. DePaolo, Q. Kang, and D. Zhang, Lattice Boltzmann Simulation of Snow Crystal Growth in Clouds, J. Geophys. Res., 114, D07305, DOI: 10.1029/2008JD011087, 2009.

  11. Chen, C., and D. Zhang*, Lattice Boltzmann Simulation of the Rise and Dissolution of Two-Dimensional Immiscible Droplets, Physics of Fluids, 21, 103301, DOI: 10.1063/1.3253385, 2009.

  12. Feng, X.T., W.X. Ding, and D. Zhang, Multi-Crack Interaction in Limestone Subject to Stress and Flow of Chemical Solutions, International Journal of Rock Mechanics and Mining Sciences, 46(1):159-171,10.1016/j.ijrmms.2008.08.001, 2009.

 

2008 (6):

  1. Liu, G., Y. Chen, and D. Zhang, Investigation of Flow and Transport Processes at the MADE Site Using Ensemble Kalman Filter, Adv. Water Resour., doi:10.1016/j.advwatres.2008.03.006, 31: 975–986, 2008.

  2. Rapaka, S., S. Chen, R. Pawar, P.H. Stauffer, and D. Zhang, Nonmodal Growth of Perturbations in Density-driven Convection in Porous Media, J Fluid Mech., vol. 609, pp. 285–303, 2008.

  3. Gainis, B., H. Klie, M.F. Wheeler, T. Wildey, I. Yotov, and D. Zhang, Stochastic Collocation and Mixed finite elements for Flow in Porous Media, Comput. Methods Appl. Mech. Engrg., 197: 3547–3559,2008.

  4. Ding, Y., T. Li, D. Zhang, and P. Zhang, Adaptive Stroud stochastic collocation method for flow in random porous media via Karhunen-Loeve expansion, Communications in Comp. Phys., 4(1):102-123, 2008.

  5. Shi, L., J. Yang, and D. Zhang, A Stochastic Approach to Unconfined flow Subject to Multiple Random Fields, Stochastic Environmental Research and Risk Assessment, 10.1007/s00477-008-0261-3, 2008.

  6. Ding, G., J.J. Jiao, and D. Zhang, Modelling Study on the Impact of Deep Building Foundations on the Groundwater System, Hydrol. Process., 22(12): 1857-1865, DOI: 10.1002/hyp.6768, 2008.

 

2007 (7):

  1. Li, H., and D. Zhang*, Probabilistic Collocation Method for Flow in Porous Media: Comparisons with Other Stochastic Methods, Water Resour. Res., 43, W09409, DOI:10.1029/2006WR005673, 2007.

  2. Kang, Q., P.C. Lichtner, and D. Zhang, An Improved Lattice Boltzmann Model for Multi-Component Reactive Transport in Porous Media at the Pore Scale, Water Resour. Res., 43, W12S14, DOI:10.1029/2006WR005551,2007.

  3. Zhang, D.*, Z. Lu, and Y. Chen, Dynamic Reservoir Data Assimilation with an Efficient, Dimension-Reduced Kalman Filter, SPE Journal, 12(1), 108-117, 2007.

  4. Lu, Z., Zhang, D., and B. Robinson, Explicit Analytical Solutions for One-Dimensional Steady State Flow in Layered, Heterogeneous Unsaturated Soils under Uncertainties, Water Resour. Res., 43, W09413, DOI:10.1029/2005WR004795,2007.

  5. Liu, G., Z. Lu, and D. Zhang*, Stochastic Uncertainty Analysis for Solute Transport in Randomly Heterogeneous Media Using a Karhunen-Loeve Based Moment Equation Approach, Water Resour. Res., 43, W07427, DOI:10.1029/2006WR005193, 2007.

  6. Xu, X., S. Chen, and D. Zhang*, Comment on the Effect of Anisotropy on the Onset of Convection in a Porous Medium-Reply, Adv. Water Resour., 30 (3): 698-699, 2007.

  7. Lu, Z., andD. Zhang, Stochastic Simulations for Flow in Nonstationary Randomly Heterogeneous Porous Media Using a KL-based Moment-equation Approach, SIAM Multiscale Modeling and Simulation, 6(1), 228-245, DOI. 10.1137/060665282, 2007.

 

2006 (6):

  1. Chen, Y., and D. Zhang*, Data Assimilation for Transient Flow in Geologic Formations via Ensemble Kalman Filter, Adv. Water Resour., doi:10.1016/j.advwatres.2005.09.007, 29, 1107–1122, 2006. (ISI Highly Cited Paper)

  2. Xu, X., S. Chen, and D. Zhang*, Convective Stability Analysis of the Long-Term Storage of Carbon Dioxide in Deep Saline Aquifers, Adv. Water Resour., doi:10.1016/j.advwatres.2005.05.008, 29(3):397-407, 2006.

  3. Kang, Q., P.C. Lichtner, and D. Zhang, Lattice-Boltzmann Pore-Scale Model for Multi-component Reactive Transport in Porous Media, J. Geophy. Res., VOL. 111, B05203, DOI: 10.1029/2005JB003951, 2006.

  4. Chen, M., A. Keller,D. Zhang, Z. Lu, and G.A. Zyvoloski, A Stochastic Analysis of Transient Two-Phase Flow in Heterogeneous Porous Media, Water Resour. Res., 42(3), W03425, DOI:10.1029/2005WR004257, 2006.

  5. Lu, Z., andD. Zhang*, Accurate, Efficient Quantification of Uncertainty for Flow in Heterogeneous Reservoirs using the KLME Approach, SPE Journal, 11(2), 239-247, 2006.

  6. Liu, G., D. Zhang, and Z. Lu, Stochastic Uncertainty Analysis for Unconfined Flow Systems, Water Resour. Res., VOL. 42, W09412, DOI:10.1029/2005WR004766, 2006.

 

2005 (4):

  1. Kang, Q., D. Zhang, and S. Chen, Displacement of a Three-Dimensional Immiscible Droplet in a Duct, J. Fluid Mech., 545: 41-66, 2005.

  2. Kang, Q., I.N. Tsimpanogiannis, D. Zhang, and P. Lichtner, Numerical Modeling of Pore-scale Phenomena during CO2 Sequestration in Oceanic Sediments, Fuel Processing Technology, 86:1647-1665, 2005.

  3. Chen, M.,D. Zhang, A. Keller, and Z. Lu, A Stochastic Analysis of Steady State Two-Phase Flow in Heterogeneous Media, Water Resour. Res., Vol. 41, W01006, DOI:10.1029/2004WR003412,2005.

  4. Lu, Z., and D. Zhang, Analytical Solutions of Statistical Moments for Transient Flow in Two-Dimensional Bounded, Randomly Heterogeneous Media, Water Resour. Res., Vol.41, W01016, DOI:10.1029/2004WR003389, 2005.

 

2004 (12):

  1. Zhang, D.*, and Z. Lu, An Efficient, High-Order Perturbation Approach for Flow in Random Porous Media via Karhunen-Loeve and Polynomial Expansions, J. of Computational Physics, 194(2), 773-794, doi:10.1016/j.jcp.2003.09.015, 2004.

  2. Kang, Q., D. Zhang, and P. Lichtner, and I. Tsimpanogiannis, Lattice Boltzmann Model for Crystal Growth from Supersaturated Solution, Geophysical Research Letters, DOI: 10.1029/2004GL021107, 31, L21604(1-5), 2004.

  3. Lu, Z., and D. Zhang*, Comparative Study on Quantifying Uncertainty of Flow in Randomly Heterogeneous Media Using Monte Carlo Simulations, the Conventional and KL-based Moment-equation Approaches, SIAM Journal on Scientific Computing, 26(2), 558-577, doi:10.1137/S1064827503426826, 2004.

  4. Kang, Q., D. Zhang, and S. Chen, Immiscible Displacement in a Channel: Simulations of Fingering in Two Dimensions, Adv. Water Resources, 27(1), 13-22, 2004.

  5. Lu, Z., and D. Zhang, Conditional Simulations of Flow in Randomly Heterogeneous Porous Media Using a KL-based Moment-equation Approach, Adv. Water Resources, 27:859-874, 2004.

  6. Zhang, D., and Q. Kang, Pore Scale Simulation of Solute Transport in Fractured Porous Media, Geophysical Research Letters, vol.31(6), 2004.

  7. Lu, Z., andD. Zhang, Analytical Solutions to Unsaturated Flow in Layered, Heterogeneous Soils via Kirchhoff Transformation, Adv. Water Resources, 27:775-784, 2004.

  8. Zhang, Y.K., and D. Zhang,Forum: The State of Stochastic Hydrology, Stochastic Environmental Research and Risk Assessment, 18(4):265, 2004.

  9. Zhang, D.*, and Z. Lu,Stochastic Delineation of Well Capture Zones, Stochastic Environmental Research and Risk Assessment, 18(1), 39-46, 2004.

  10. Hu, B.X., J. Wu, and Zhang, D., A Numerical Method of Moments for Solute Transport in Physically and Chemically Nonstationary Formations: Linear Equilibrium Sorption with Random Kd, Stochastic Environmental Research and Risk Assessment, 18(1), 22-30, 2004.

  11. Sun, A., and D. Zhang, A Solute Flux Approach to Transport through Bounded, Unsaturated Heterogeneous Porous Media, Vadose Zone Journal, 3:513-526, 2004.

  12. Yang, J., D. Zhang*, and Z. Lu, Stochastic Analysis of Saturated-Unsaturated Flow in Heterogeneous Media by Combining Karhunen-Loeve Expansion and Perturbation Method, J. Hydrology, vol.294, 18-38, 2004.

 

2003 (8)

  1. Kang, Q., D. Zhang*, and S. Chen, Simulation of Dissolution and Precipitation in Porous Media, J. Geophysical Research-Solid Earth, 108(B10), 2505, DOI:10.1029/2003JB002504, 2003.

  2. Lu, Z., and D. Zhang, On Importance Sampling Monte Carlo Approach to Uncertainty Analysis of Flow and Transport in Porous Media, Adv. Water Resources, 26(11), 1177-1188, 2003.

  3. Li, L., H.A. Tchelepi, and D. Zhang*, Perturbation-based Moment Equation Approach for Flow in Heterogeneous Porous Media: Applicability Range and Analysis of High-Order Terms, J. of Computational Physics, doi:10.1016/S0021-9991(03)00186-4, 188(1), pp 296 - 317, 2003.

  4. Lu, Z., and D. Zhang, On Stochastic Study of Well Capture Zones in Bounded, Randomly Heterogeneous Media, Water Resour. Res., 39(4), DOI:10.1029/2002WR001633, 2003.

  5. Lu, Z., and D. Zhang, Solute Spreading in Nonstationary Flows in Bounded Heterogeneous Saturated-Unsaturated Media, Water Resour. Res., 39(3), 1049, DOI:10.1029/2001WR000908, 2003.

  6. Wu, J., B.X. Hu, D. Zhang, and C. Shirley, A Three-Dimensional Numerical Method of Moments for Groundwater Flow and Solute Transport in a Nonstationary Conductivity Field, Adv. Water Resources, 26(11), 1149-1169, 2003.

  7. Wu J., B.X. Hu, and D. Zhang, Applications of Nonstationary Stochastic Theories to Solute Transport in Multi-scale Geological Media, Journal of Hydrology, 275:208-228, 2003.

  8. Hu, B.X., J. Wu, A.K. Panorska, D. Zhang, and C. He, Stochastic Study on Groundwater Flow and Solute Transport in Porous Media with Multi-Scale Heterogeneity, Adv. Water Resources, 26:541-560, 2003.

 

2002 (9):

  1. Kang, Q., D. Zhang, and S. Chen, Displacement of a Two-Dimensional Immiscible Droplet in a Channel, Physics of Fluids, 14(9), 3203-3214, 2002.

  2. Kang, Q., D. Zhang, S. Chen, and X. He, Lattice Boltzmann Simulations of Chemical Dissolution in Porous Media, Physical Review E, 65(3), 2002.

  3. Lu, Z., and D. Zhang*, On Stochastic Modeling of Flow in Multimodal Heterogeneous Formations, Water Resour. Res., 38(10), DOI:10.1029/2001WR001026, 2002.

  4. Kang, Q., D. Zhang, and S. Chen, Unified Lattice Boltzmann Method for Flow in Multiscale Porous Media, Physical Review E, 66(11), 056307, 2002.

  5. Zhang, D.*, and Z. Lu, Stochastic Analysis of Flow in a Heterogeneous Unsaturated-Saturated System, Water Resour. Res., 38(2), DOI:10.1029/2001WR000515, 2002.

  6. Valentine, G., D. Zhang, and B.A. Robinson, Modeling Complex, Nonlinear Geological Processes, Annual Review of Earth and Planetary Sciences, 30: 35-64, 2002.

  7. Lu, Z., and D. Zhang*, Stochastic Analysis of Transient Flow in Heterogeneous, Variably Saturated Porous Media: The van Genuchten-Mualem Constitutive Model, Vadose Zone Journal, 1(1), 137-149, 2002.

  8. Lu, G., and D. Zhang*, Nonstationary Stochastic Analysis of Flow in a Heterogeneous Semiconfined Aquifer, Water Resour. Res., 38(8), DOI:10.1029/2001WR000546, 2002.

  9. Hu, B.X., H. Huang, and D. Zhang, Stochastic Analysis of Solute Transport in Heterogeneous, Dual-Permeability Media, Water Resour. Res., 38(9), DOI:10.1029/2001WR000442, 2002.

 

2000 (5):

  1. Zhang, D.*, R. Zhang, S. Chen, and W.E. Soll, Pore Scale Study of Flow in Porous Media: Scale Dependency, REV, and Statistical REV, Geophysical Research Letters, 27(8), 1195-1198, 2000.

  2. Zhang, D.*, R. Andricevic, A.Y. Sun, X.B. Hu, and G. He, Solute Flux Approach to Transport Through Spatially Nonstationary Flow in Porous Media, Water Resour. Res., 36(8), 2107-2120, 2000.

  3. Zhang, D.*, and A.Y. Sun, Stochastic Analysis of Saturated Flow through Heterogeneous Fractured Porous Media: A Double-Permeability Approach, Water Resour. Res., 36(4), 865-874, 2000.

  4. Zhang, D.*, L. Li, and H.A. Tchelepi, Stochastic Formulation for Uncertainty Assessment of Two-Phase Flow in Heterogeneous Reservoirs, SPE Journal, 5(1), 60-70, 2000.

  5. Sun, A.Y., and D. Zhang*, Prediction of Solute Spreading in Unsaturated, Bounded Heterogeneous Porous Media, Water Resour. Res., 36(3), 715-723, 2000.

 

1999 (5):

  1. Zhang, D.*, Nonstationary Stochastic Analysis of Transient Unsaturated Flow in Randomly Heterogeneous Media, Water Resour. Res., Vol.35, No.4, 1999.

  2. Zhang, D.*, and C.L. Winter, Moment Equation Approach to Single-Phase Fluid Flow in Heterogeneous Reservoirs, SPE Journal, Vol.4, No.2, 1999.

  3. Harter, T., and D. Zhang, Water Flow and Solute Spreading in Heterogeneous Soils with Spatially Variable Water Content, Water Resour. Res., Vol.35, No.2, 1999.

  4. Zhang, D.*, and H. Tchelepi, Stochastic Analysis of Immiscible Two-Phase Flow in Heterogeneous Media, SPE Journal, 4(4), 380-388, 1999.

  5. Zhang, D.*, Quantification of Uncertainty for Fluid Flow in Heterogeneous Petroleum Reservoirs, Physica D, 133, 488-497, 1999.

 

1998 (4):

  1. Zhang, D.*, Numerical Solutions to Statistical Moment Equations of Groundwater Flow in Nonstationary, Bounded Heterogeneous Media, Water Resour. Res., Vol.34, No.3, 1998.

  2. Zhang, D.*, and C.L. Winter, Nonstationary Stochastic Analysis of Steady-State Flow through Variably Saturated, Heterogeneous Media, Water Resour. Res., Vol.34, No.5, 1998.

  3. Zhang, D.*, T. Wallstrom, and L. Winter, Stochastic Analysis of Steady-State Unsaturated Flow in Heterogeneous Media: Comparison of Brooks-Corey and Gardner-Russo Models, Water Resour. Res., Vol.34, No.6, 1998.

  4. Xin, J., and D. Zhang*, Stochastic Analysis of Biodegradation Fronts in One-Dimensional Heterogeneous Porous Media, Adv. Water Resources, Vol.22, No.2, 1998.

 

1997 (2):

  1. Zhang, D.*, Conditional Stochastic Analysis of Multiphase Transport in Randomly Heterogeneous, Variably Saturated Media, Transport in Porous Media, Vol.27, No.3, 1997.

  2. Zhang, Y.-K., and D. Zhang, Time-Dependent Dispersion of Non-ergodic Solute Transport in Two-Dimensional Heterogeneous Porous Media, ASCE Journal of Hydrologic Engineering, Vol.2, No.2, 1997.

 

1996 (4):

  1. Hsu, K.-C., D. Zhang, and S.P. Neuman, Higher-Order Effects on Flow and Transport in Randomly Heterogeneous Porous Media, Water Resour. Res., Vol.32, No.3, 1996.

  2. Zhang, D., and S.P. Neuman, Effect of Local Dispersion on Solute Transport in Randomly Heterogeneous Porous Media, Water Resour. Res., Vol.32, No.9, 1996.

  3. Zhang, D., and S.P. Neuman, Head and Velocity Covariances Under Quasi-Steady State Flow and Their Effects on Advective Transport, Water Resour. Res., Vol.32, No.1, 1996.

  4. Zhang, Y.-K., D. Zhang, and J. Lin, Non-ergodic Solute Transport in Three-Dimensional Heterogeneous Isotropic Aquifers, Water Resour. Res., Vol.32, No.9, 1996.

 

1995 (5):

  1. Zhang, D., and S.P. Neuman, Eulerian-Lagrangian Analysis of Transport Conditioned on Hydraulic Data: 1. Analytical-Numerical Approach, Water Resour. Res., Vol.31, No.1, 1995.

  2. Zhang, D., and S.P. Neuman, Eulerian-Lagrangian Analysis of Transport Conditioned on Hydraulic Data: 2. Effects of Log Transmissivity and Hydraulic Head Measurements, Water Resour. Res., Vol.31, No.1, 1995.

  3. Zhang, D., and S.P. Neuman, Eulerian-Lagrangian Analysisof Transport Conditioned on Hydraulic Data: 3. Spatial Moments, Travel Time Distribution, Mass Flow Rate and Cumulative Release Across a Compliance Surface, Water Resour. Res., Vol.31, No.1, 1995.

  4. Zhang, D., and S.P. Neuman, Eulerian-Lagrangian Analysis of Transport Conditioned on Hydraulic Data: 4. Uncertain Initial Plume State and Non-Gaussian Velocities, Water Resour. Res., Vol.31, No.1, 1995.

  5. Zhang, D., Impacts of Local Dispersion and First-Order Decay on Solute Transport in Randomly Heterogeneous Porous Media, Transport in Porous Media, Vol.21, No.2, 1995.

 

Others (2):

  1. Zhang, D., and S.P. Neuman, Comment on “A Note on Head and Velocity Covariances in Three-Dimensional Flow through Heterogeneous Anisotropic Porous Media” by Y. Rubin and G. Dagan, Water Resour. Res., Vol.31, No.12, 1992. (Published during M.Sc. studies)

  2. Zhang, D., Rotating Sense Determination in Planar Gear Train by Use of Complex Number, Journal of Northeastern University, P. R. China, No.1, 1988. (Published during undergraduate studies)

 

Papers in Books and Conference Proceedings:

  1. Li, S., and D. Zhang, A Fully Coupled Model for Hydraulic Fracture Growth during Multi-well Fracturing Treatments: Enhancing Fracture Complexity, the SPE Reservoir Simulation Conference, held in Montgomery, TX, USA 20–22 February 2017.

  2. Li, S., D. Zhang, and X. Li. A New Approach to the Modeling of Hydraulic Fracturing Treatments in Naturally Fractured Reservoirs, SPE Asia Pacific Hydraulic Fracturing Conference, Beijing, China, SPE-181828-MS, 2016.

  3. Wu, T., Z. Jiang, and D. Zhang, A Case Study of Fluid Transport in Shale Crushed Samples: Experiment and Interpretation, 2014 International Symposium of the Society of Core Analysis, Avignon, France, 8-12 September 2014.

  4. Ghods, P., and D. Zhang, Automatic Estimation of Fracture Properties in Multi-stage Fractured Shale Gas Horizontal Wells, SPE Western Regional Meeting, Bakersfield, CA: SPE 153913, 2012.

  5. Zhang, D., H. Li, and H. Chang, History Matching for Non-gaussian Random Fields Using the Probabilistic Collocation Based Kalman Filter, SPE 141893, 2009 SPE Reservoir Symposium, The Woodlands, Texas, Feb. 21-23, 2011.

  6. Li, W., D. Oyerinde, D. Stern, X.H. Wu, and D. Zhang, Probabilistic Collocation Based Kalman Filter for Assisted History Matching, SPE 141930, 2009 SPE Reservoir Symposium, The Woodlands, Texas, Feb. 21-23, 2011.

  7. Jahangiri, H.R., and D. Zhang, Optimization of Carbon Dioxide Sequestration and Enhanced Oil Recovery in Oil Reservoir, SPE Western Regional Meeting, Anaheim, CA: SPE 133594, 2010.

  8. Ghods, P., and D. Zhang. Ensemble Based Characterization and History Matching of Naturally Fractured Tight/Shale Gas Reservoirs, SPE Western Regional Meeting, Anaheim, CA: SPE133606, 2010.

  9. Jahangiri, H.R., and D. Zhang, Optimization of the Net Present Value of Carbon Dioxide Sequestration and Enhanced Oil Recovery, OTC 21985, 2011 Offshore Technology Conference, Houston, Texas, USA, 2–5 May 2011.

  10. Chang, H., Y. Chen, and D. Zhang, Data Assimilation of Coupled Fluid Flow and Geomechanics via Ensemble Kalman Filter, SPE 118963, 2009 SPE Reservoir Symposium, The Woodlands, Texas, Feb. 2-4, 2009.

  11. Li, H., H. Chang, and D. Zhang, Stochastic Collocation Methods for Efficient and Accurate Quantification of Uncertainty in Multiphase Reservoir Simulations, SPE 118964, 2009 SPE Reservoir Symposium, The Woodlands, Texas, Feb. 2-4, 2009.

  12. Zhang, D., H. Li, H. Chang, and G. Yan, Non-Intrusive Stochastic Approaches for Efficient Quantification of Uncertainty Associated with Reservoir Simulations, 11th European Conference on the Mathematics of Oil Recovery, Bergen, Norway, 8-11 September 2008.

  13. Lu, Z., D. Zhang, and Y. Chen, Information Fusion Using the Kalman Filter Based on Karhunen-Loeve Decomposition, in Quantitative Information Fusion for Hydrological Sciences by X. Cai and T.C. J. Yeh, 2008.

  14. Klie, H.M., M.F. Wheeler, G. Liu, and D. Zhang, Stochastic Subspace Projection Methods for Efficient Multiphase Flow Uncertainty Assessment, 10th European Conference on the Mathematics of Oil Recovery, Amsterdam, The Netherlands, 4-7 September 2006.

  15. Zhang, D., Z. Lu, and G. Liu, An Efficient Stochastic Decomposition Approach for Large-Scale Subsurface Flow Problems, Computational Method for Water Resources - XVI, 18-22 June 2006, Copenhagen, Denmark.

  16. Kang, Q., P. Lichtner, and D. Zhang, Recent Progresses in Lattice Boltzmann Simulations of Flow and Multi-Component Reactive Transport in Porous Media, Computational Method for Water Resources - XVI, 18-22 June 2006, Copenhagen, Denmark.

  17. Zhang, D., Z. Lu, and Y. Chen, Dynamic Reservoir Data Assimilation with an Efficient, Dimension-Reduced Kalman Filter, 2005 SPE Annual Technical Conference and Exhibition, Dallas, Texas, U.S.A., 9 – 12 October 2005.

  18. Zhang, D., Multiscale Modeling of Flow and Transport in Fractured Porous Media via the Lattice Boltzmann Method, 3rd Biot Conference on Poromechanics, Norman, OK, May 24-27, 2005.

  19. Lu, Z., and D. Zhang, Accurate, Efficient Quantification of Uncertainty for Flow in Heterogeneous Reservoirs Using the KLME Approach, SPE paper #93452, 2005 SPE Reservoir Symposium, Houston, Texas, Jan. 31-Feb. 2, 2005.

  20. Lu, Z., Higdon, and D. Zhang, A Markov Chain Monte Carlo Method for the Groundwater Inverse Problem, Proceedings of the 15th International Conference on Computational Methods in Water Resources, June 13-17, 2004, Chapel Hill, NC, USA.

  21. Lu, Z., and D. Zhang, Stochastic Analysis of Flow in Heterogeneous, Nonstationary Unsaturated-Saturated Porous Media, Proceedings of the 10th International High-Level Radioactive Waste Management Conference, American Nuclear Society, 13-19, 2003

  22. Lu, Z., and D. Zhang, An Efficient Approach for Simulating Saturated Flow in Randomly Heterogeneous Porous Media Conditioned on Hydraulic Conductivity Measurements, Proceedings of MODFLOW and More 2003: Understanding through Modeling, Sept 16-20, Boulder, CO.

  23. Zhang, D., and Z. Lu, Monte Carlo Simulations of Solute Transport in Bimodal Randomly Heterogeneous Porous Media, Proceeding of World Water & Environmental Resources Congress 2003 and Symposium of Probabilistic Approaches and Groundwater Modeling, June 22-26, 2003, Philadelphia, PA.

  24. Lu, Z., and D. Zhang, Higher-Order Approximations for Saturated Flow in Random Heterogeneous Media via Karhunen-Loeve Decomppsition, Proceeding of World Water & Environmental Resources Congress 2003 and Symposium of Probabilistic Approaches and Groundwater Modeling, June 22-26, 2003, Philadelphia, PA.

  25. Pawar, R.J., N. Warpinski, B. Stubbs, and D. Zhang, Numerical Modeling of CO2 Sequestration in a Depleted Oil Reservoir, Proceedings of the 2nd Annual Conference on Carbon Sequestration, Alexandria, VA, May 5-8, 2003.

  26. Lu, Z., and D. Zhang, Stochastic Analysis of Flow in Heterogeneous, Nonstationary Unsaturated-Saturated Porous Media, Proceeding of the International High-Level Radioactive Waste Management Conference, March 30-April 2, 2003, Las Vegas, NV.

  27. Zhang, D., Q. Kang, and S. Chen, Study of Fluid Flow, Transport and Reaction in Porous Media with the Lattice Boltzmann Method, the XIV International Conference on Computational Methods in Water Resources, Delft, The Netherlands, June 23-28, 2002.

  28. Zhang, D., and Z. Lu, Stochastic Analysis of Well Capture Zones in Heterogeneous Porous Media, the 4th International Conference on Calibrating and Reliability in Groundwater Modeling (ModelCARE 2002), Prague, Czech Republic, June 17-20, 2002.

  29. Hu, B.X., J. Wu, D. Zhang, and C. Shirley, A Numerical Method of Moments for Solute Flux in Nonstationary Flow Fields, the 4th International Conference on Calibrating and Reliability in Groundwater Modeling (ModelCARE 2002), Prague, Czech Republic, June 17-20, 2002.

  30. Krumhansl, J., R. Pawar, H. Westrich, N. Warpinski, D. Zhang, and others, Geological Sequestration of Carbon Dioxide in a Depleted Oil Reservoir, SPE/DOE Thirteenth Symposium on Improved Oil Recovery, Tulsa, Oklahoma, April 13-17, 2002.

  31. Lu, Z., and Zhang, D., and E. Keating, Applicability of Unimodal Stochastic Approaches in Simulating Flow in Bimodal Heterogeneous Formations, International Groundwater Symposium on “Bridging the Gap between Measurement and Modeling in Heterogeneous Media”, Berkeley, California, March 25-28, 2002.

  32. Pawar, R.J., D. Zhang, D., H.R. Westrich, and C. Byrer, Sequestration of CO2 in a Depleted Oil Reservoir: Numerical Simulations Related to a Field Demonstration, International Pittsburgh Coal Conference, Newcastle NSW, Australia, December 4-7, 2001.

  33. Pawar, R.J., D. Zhang, D., B. Stubbs, and H.R. Westrich, Sequestration of CO2 in a Depleted Oil Rreservoir: Preliminary Simulation Study, the 1st National Carbon Sequestration Conference Proceedings, May 15-17, 2001.

  34. Zhang, D., among others, Sequestration of CO2 in a Depleted Oil Reservoir: An Overview, the 1st National Carbon Sequestration Conference Proceedings, May 15-17, 2001.

  35. Zhang, D., L. Li, and H.A. Tchelepi, Stochastic Formulation for Uncertainty Assessment of Two-Phase Flow in Heterogeneous Reservoirs, the 15th Reservoir Simulation Symposium, 1999.

  36. Harter, Th., D. Zhang, and S. Ezzedine, Non-point Source Pollution on the Field Scale: Heterogeneity and Uncertainty, in 1997 Joint Chapman/SSSA Outreach Conference: Applications of GIS, Remote Sensing, Geostatistics, and Solute Transport Modeling to the Assessment of Non-Point Source Pollutants in the Vadose Zone, 1997.

  37. Zhang, D., and Y.-K. Zhang, Higher-Order Velocity Covariance and Its Effect on Advective Transport in Three-Dimensional Heterogeneous Anisotropic Media, in Computational Methods in Water Resources XI, 1996.

  38. Ksu, K.-C., D. Zhang, and S. P. Neuman, Higher-Order Effects on Flow and Transport in Randomly Heterogeneous Porous Media, in Advances in Ground Water Pollution Control and Remediation, ed. by M. M. Aral, Kluwer Academic Pub., Dordrecht, pp. 75-96, 1996.

  39. Zhang, D., and S.P. Neuman, A Stochastically-Derived, Deterministic Model of Solute Transport Conditioned on Hydraulic Data, in Models for Assessing and Monitoring Groundwater Quality, ed. by B.J. Wagner, T.H. Illangasekare and K.H. Jensen, IAHS Publ. no. 227, 1995.

  40. Harter, Th., and D. Zhang, Conditional Prediction of Transport in Unsaturated, Heterogeneous Porous Media: Monte Carlo Simulation vs. Eulerian-Lagrangian Theory, in Models for Assessing and Monitoring Groundwater Quality, ed. by B.J. Wagner, T.H. Illangasekare and K.H. Jensen, IAHS Publ. no. 227, 1995.

  41. Zhang, D., and S.P. Neuman, Information-Dependent Prediction of Solute Transport in Heterogeneous Geologic Media, in Computational Methods in Water Resources X, ed. by A. Peters, G. Wittum, B. Herling, and U. Meissner, Kluwer Academic Publ., Netherlands, Vol.1, 545--552, 1994.

  42. Neuman, S.P., and D. Zhang, Considerations of Scale and Information Content in Subsurface Flow and Transport Modeling, in Proc. Joint USGS/USNRC Technical Workshop on Research Related to Low-Level Radioactive Waste Disposal, Reston, Virginia, 1994.

  43. Neuman, S.P., O. Levin, S. Orr, E. Paleologos, D. Zhang, and Y.-K. Zhang, Nonlocal Representations of Subsurface Flow and Transport by Conditional Moments, Computational Stochastic Mechanics, ed. by A.H.-D. Cheng and C.Y. Yang, Computational Mechanics Publications, Southampton, United Kingdom, 1993.

 

 

Patents and Copyrights:

  1. Zhang, D., S. Li, J. Wu, X. Sun, X. Li, and H. Qiao, CO2Frac V1.0 (二氧化碳压裂模拟器软件V1.0), Software copyright: 2017SR120808, date issued: April 17, 2017.

  2. Zhang, D., and S. Li, FracTHM (A coupled thermal-hydro-mechanic hydraulic fracturing simulator), Software copyright: 2016SR347861, date issued: December 1, 2016.

  3. Li, X., and D. Zhang, 基于逆向自动微分的油藏动态模拟方法 (A dynamic reservoir simulation framework with backward automatic differentiation), Chinese patent: ZL201310242744.X, date issued: December 4, 2015.

  4. Li, X., and D. Zhang, UNCONG_S V1.0 (Unconventional Oil & Gas Reservoir Simulator), Software copyright: 2015SR148669, date issued: June 7, 2015.


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