Dr. Guochang Wang | Saint Francis University
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Dr. Guochang Wang

  • Guochang Wang

    Position: Assistant Professor of Petroleum and Natural Gas Engineering

    Department: Engineering, Petroleum and Natural Gas Engineering

    Office: Science Center 018

    Email Dr. Guochang Wang


    About Dr. Guochang Wang


    • Post Doctorate, College of Earth Science, University of Chinese Academy of Sciences
    • Ph.D., Department of Geology & Geography, West Virginia University, 2012
    • B.S., Petroleum Engineering, China University of Geosciences, 2006


    Guochang Wang is an Assistant Professor of Petroleum and Natural Gas Engineering at Saint Francis University. Dr. Wang earned his PhD from West Virginia University in Aug., 2012, and was a postdoctoral research fellow at the University of Chinese Academy of Sciences until Feb., 2015. In Mar. 2015, he joined Saint Francis University. The objective of his research is to make the unconventionals to be conventional. 

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    • Research Interests
    • Selected Publications
    • Professional Society
    • Peer Reviewer
    Research Interests
    • Reservoir Characterization for Shale Gas, Conventional Hydrocarbon and CO2 Sequestration
    • Well Log Analysis and Three-Dimensional Seismic Attribute Interpretation
    • Pore Structure Characterization by Microscopy Observation and Gas (N2, CO2 and Ar) Physisorption
    • Three-dimensional Geological Modeling and Numerical Simulation
    • Pattern Recognition, Artificial Intelligence, Mathematical Algorithms and Computer Coding
    Wang Research1Wang Research2Wang Research3


    Selected Publications

    Ph.D Thesis

    • Guochang Wang, 2012, Black Shale Lithofacies Prediction and Distribution Pattern Analysis of Middle Devonian Marcellus Shale in the Appalachian Basin, Northeastern U.S.A. West Virginia University, Morgantown WV.

    Peer Reviewed Articles

    • Guochang Wang, Yiwen Ju and Mingming Wei, 2014, Ultra-Low Pressure N2 Physisorption for Characterizing Micropores and Mesopores of Organic Shale: Experimental Procedure and Interpretation Model. Fuel, submitted (JFUE-D-14-02180).
    • Guochang Wang, Yiwen Ju and Kui Han, 2014, Early Paleozoic Shale Properties and Gas Potential Evaluation in Xiuwu Basin, Western Lower Yangtze Platform. Journal of Natural Gas Science and Engineering, in press.
    • Guochang Wang, Yiwen Ju, Zhifeng Yan and Qingguang Li, 2014, Pore Structure Characteristics of Coal–bearing Shale by Fluid Invasion Methods: A Case Study in Huainan–Huaibei Coalfield of China. Marine and Petroleum Geology, in revision.
    • Guochang Wang, Yiwen Ju and Timothy R. Carr, 2014, The hierarchical decomposition method and its application in recognizing Marcellus Shale lithofacies through combining with neural network. Journal of Petroleum Science and Engineering, accepted.
    • Guochang Wang, Yiwen Ju, Yuan Bao, Zhifeng Yan, Xiaoshi Li, Hongling Bu and Qingguang Li, 2014, Coal-Bearing Organic Shale Geological Evaluation of Huainan−Huaibei Coalfields, China. Energy & Fuels, v.28, no.8, p.5031-5042.
    • Guochang Wang, Timothy R Carr, Yiwen Ju and Chaofeng Li, 2014, Identifying Organic-rich Marcellus Shale Lithofacies by Support Vector Machine Classifier in the Appalachian Basin. Computers & Geosciences, v.64, p.52-60.
    • Guochang Wang and Timothy R Carr, 2013, Organic-rich Marcellus Shale lithofacies modeling and distribution pattern analysis in the Appalachian basin. AAPG Bulletin, v.97, no.12, p.2173-2205.
      Guochang Wang, Guojian Cheng and Timothy R Carr, 2013, The application of improved NeuroEvolution of Augmenting Topologies neural network in Marcellus Shale lithofacies prediction. Computer & Geosciences, v.54, p.50-65.
    • Guochang Wang and Timothy R Carr, 2012, Methodology of organic-rich shale lithofacies identification and prediction: a case study from Marcellus Shale in the Appalachian basin. Computer & Geosciences, v.49, p.151-163.
    • Guochang Wang and Timothy R Carr, 2012, Marcellus Shale lithofacies prediction by multi-class neural network classification in the Appalachian basin. Mathematical Geosciences, v.44, no.8, p.975-1004.
    • Guochang Wang and Xueju Lv, 2006, Application of Generalized Regression Neural Network and Genetic Algorithm to Production Decline Analysis. Xinjing Petroleum Geology, v.27, no.1, p.90-93.

    Conference Proceedings

    • Guochang Wang, Timothy R. Carr, Yiwen Ju, The identification and modeling of shale lithofacies based on mineral composition and organic matter richness and its significance. Annual Meeting of Chinese Geosciences Union, Beijing October 19-23, 2014.
    • Guochang Wang, Yiwen Ju, Timothy R Carr, Chaofeng Li and Guojian Cheng, Application of Artificial Intelligence on Black Shale Lithofacies Prediction in Marcellus Shale, Appalachian Basin. 2014 Unconventional Resources Technology Conference, Denver, August 25-27, 2014.
    • Guochang Wang, Timothy R Carr and Yiwen Ju, Statistical Reverse Model to Predict Mineral Composition and TOC Content of Marcellus Shale. SPE Unconventional Resources Conference, Woodlands, TX, USA, April 1-4, 2014.
    • Guochang Wang, Timothy R Carr and Yiwen Ju, Integrated Approach to Predict Mineral Composition AND TOC Content in Marcellus Shale, Appalachian Basin, USA. The Thirtieth Annual Pittsburgh Coal Conference, September 15-18, 2013, Beijing, China.
    Professional Society
    • American Association of Petroleum Geologists
    • The Society of Petroleum Engineers
    • International Association for Mathematical Geosciences
    • Chinese Sub-Society for Soft Rock Engineering & Deep Disaster Control
    • Society for Sedimentary Geology (SEPM)
    • Sigma Gamma Epsilon
    Peer Reviewer
    • Applied Geochemistry
    • Arabian Journal of Geosciences
    • Austrian Journal of Earth Sciences
    • British Journal of Applied Science & Technology
    • Computers & Geosciences
    • Energy
    • Journal of Earth Science
    • Journal of Hazardous Materials
    • Journal of Natural Gas Science & Engineering
    • Journal of Petroleum Science and Engineering
    • Journal of the Energy Institute
    • Marine and Petroleum Geology
    • Measurement