Papers Published in Refereed Journals

• Ethics of Artificial Intelligence Plays a Role in Engineering.  Journal Petroleum Technology (JPT) , Data Science and Digital Engineering. October 4, 2021.   https://jpt.spe.org/ethics-of-artificial-intelligence-plays-a-role-in-engineering 
• The Ethics of AI Evolves with the Technology.  Journal Petroleum Technology (JPT) , Data Science and Digital Engineering. September 24, 2021.   https://jpt.spe.org/the-ethics-of-ai-evolves-with-the-technology 
• Explainable Artificial Intelligence Thrives in Petroleum Data Analytics.  Journal Petroleum Technology (JPT) , Data Science and Digital Engineering. June 30, 2021.  https://jpt.spe.org/explainable-artificial-intelligence-thrives-in-petroleum-data-analytics 
• In Petroleum Data Analytics, Artificial Intelligence Avoids the Black Box.  Journal Petroleum Technology (JPT) , Data Science and Digital Engineering. June 18, 2021.  https://jpt.spe.org/in-petroleum-data-analytics-artificial-intelligence-avoids-the-black-box 
• Subsurface analytics: Contribution of Artificial Intelligence and Machine Learning to Reservoir Engineering, Reservoir Modeling, and Reservoir Management,  Journal of Petroleum Exploration and Development , Special Issue - April 2020 
• Applications of Smart Proxies for Subsurface Modeling,  Journal of Petroleum Exploration and Development , Special Issue - March 2020 
• Successful Implementation of Artificial Intelligence and Machine Learning in Multiphase Flow Smart Proxy Modeling: Two Case Studies of Gas-Liquid and Gas-Solid CFD Models,  Journal of Petroleum and Environmental Biotechnology , Vol. 11, Issue 1 No: 401 - March 2020 
• New Series Tackles Petroleum Data Analytics from the Subsurface up.  Journal Petroleum Technology (JPT) , Data Science and Digital Engineering. January 19, 2020.   https://jpt.spe.org/new-series-tackles-petroleum-data-analytics-subsurface 
• Predictive data analytics application for enhanced oil recovery in a mature field in the Middle East. Journal of Petroleum Exploration and Development 2020.
• Subsurface analytics: Contribution of Artificial Intelligence and Machine Learning to Reservoir Engineering, Reservoir Modeling, and Reservoir Management. Journal of Petroleum Exploration and Development 2020.
• Application of Machine Learning and Artificial Intelligence in Proxy Modeling for Fluid Flow in Porous Media Journal of Fluids, Fluids 2019, 4, 126; doi:10.3390/fluids4030126
• Modeling Average Pressure and Volume Fraction of a Fluidized Bed Using Data-Driven Smart Proxy Journal of Fluids, Fluids 2019, 4, 123; doi:10.3390/fluids4030123
• Smart Proxy Modeling of SACROC CO2-EOR. Journal of Fluids, Vol. 4, No. 85, 2019, doi:10.3390/fluids4020085
• Assisted history matching using pattern recognition technology. International Journal of Oil, Gas, and Coal Technology, Vol. 17, No. 4, 2018, Pages 412-442
• Determining the main drivers in hydrocarbon production from shale using advanced data-driven analytics - A case study in Marcellus shale. Journal of Unconventional Oil and Gas Resources, Vol. 15, 2016, Pages 146-157 http://dx.doi.org/10.1016/j.juogr.2016.07.004
• Techno-Economic Assessment of Industrial CO2 Storage in Depleted Shale Gas Reservoirs. Journal of Unconventional Oil and Gas Resources, Vol. 11, September 2015, Pages 82-94 doi:10.1016/j.juogr.2015.05.001
• Data-driven Proxy at Hydraulic Fracture Cluster Level: A Technique for Efficient CO2-Enhanced Gas Recovery and Storage Assessment in Shale Reservoir. Journal of Natural Gas Science and Engineering, doi: 10.1016/j.jngse.2015.06.039
• Full Field Reservoir Modeling of Shale Assets using Advanced Data-Driven Analytics. Geoscience Frontiers, 2015
  http://dx.doi.org/10.1016/j.gsf.2014.12.006
  http://www.sciencedirect.com/science/article/pii/S1674987114001649#
• Coupling Numerical Simulation and Machine Learning to Model Shale Gas Production at Different Time Resolutions. Journal of Natural Gas Science and Engineering, Vol. 25 (2015) - pp 380-392
• Evaluation of Rapid Performance Reservoir Models for Quantitative Risk Assessment. Energy Procedia, Vol. 63 (2014) - pp 3425-3431
• Geomechanical Properties of Unconventional Shale Reservoirs. Journal of Petroleum Engineering, Vol. 2014, Article ID 961641, 10 pages, 2014. doi:10.1155/2014/961641
• Modeling Pressure and Saturation Distribution in a CO2 Storage Project using a Surrogate Reservoir Model(SRM). Greenhouse Gas Science and Technology - Society of Chemical Industry & John Wiley & Sons, LTD., Vol. 4, 2014. pp.1-27; DOI: 10.1002/ghg
• Converting Detail Reservoir Simulation Models into Effective Reservoir Management Tools using SRMs; Case Study Three Green Fields in Saudi Arabia. International Journal of Oil, Gas and Coal Technology, Vol. 7, No. 2, 2014. pp.115-131
• State of the Art of Artificial Intelligence and Predictive Analytics in the E&P Industry: A Technology Survey. SPE Journal, Volume 18, Number 4, August 2013
• Reservoir Modeling of Shale Formations. Journal of Natural Gas Science and Engineering, Vol. 12, (2013), pages 22-33
• A Field Study on Simulation of CO2 Injection and ECBM Production and Prediction of CO2 Storage Capacity in Unmineable Coal Seam. Journal of Petroleum Engineering, Vol. 2013, Article ID 803706, 8 Pages - DOI: http://dx.doi.org/10.1155/2013/803706
• Top-Down, Intelligent Reservoir Modeling of Oil and Gas Producing Shale Reservoirs: Case Studies. International Journal of Oil, Gas and Coal Technology, Vol. 5, No.1, 2012 pp. 3 - 28 - DOI: 10.1504/IJOGCT.2012.044175
• Intelligent Production Modeling Using Full Field Pattern Recognition. SPE Reservoir Evaluation and Engineering Journal, Volume 14, No. 6, December 2011, pp. 735-749 http://dx.doi.org/10.2118/132643-PA
• Fuzzy Upscaling in Reservoir Simulation: An Improved Alternative to Conventional Techniques. Journal of Natural Gas Science and Engineering, Volume 3 (2011), pp. 706-715
• Reservoir Simulation And Modeling Based On Artificial Intelligence And Data Mining (AI&DM). Journal of Natural Gas Science and Engineering, Volume 3 (2011), pp. 697-705
• A New Practical Approach in Modeling and Simulation of Shale Gas Reservoirs: Application to New Albany Shale. International Journal of Oil, Gas and Coal Technology, Volume 4, No. 2, 2011. pp 104-133
• Intelligent Seismic Inversion Workflow for High-Resolution Reservoir Characterization. Computers & Geosciences, An International Journal, Volume 37, Issue 2, 2011. pp 143-157
• Coalbed Methane Reservoir Simulation and Uncertainty Analysis with Artificial Neural Network. Scientia Iranica, Transactions C: Chemistry and Chemical Engineering, Volume 17, No. 1, pp. 65-76. June 2010
• Using Artificial Neural Networks to Generate Synthetic Well Logs. Journal of Natural Gas Science and Engineering, October 2009, Volume 2, Number 1. pp 2-23
• Artificial intelligence and Data Mining: Enabling Technology for Smart Fields. SPE's The Way Ahead Journal, Volume 5, Number 3, 2009. pp 14-19
• Development of Surrogate Reservoir Model (SRM) for Fast Track Analysis of a Complex Reservoir. International Journal of Oil, Gas and Coal Technology, February 2009, Volume 2, Number 1. pp 2-23
• An Intelligent System's Approach for Revitalization of Brown Fields Using Only Production Rate Data. International Journal of Engineering, February 2009, Volume 22, Number 1. pp 89-106
• A Parametric Study on the Benefits of Drilling Horizontal and Multilateral Wells in Coalbed Methane Reservoirs. SPE Reservoir Evaluation & Engineering, December 2008, Volume 11, Number 6.
• Essential Components of an Integrated Data Mining Tool for the Oil and Gas Industry with an Example Application in the DJ Basin. Scientia Iranica, August 2008, Volume 15, Number 4. pp 469 - 479.
• Building the Foundation for Prudhoe Bay Oil Production Optimization Using Neural Networks. International Journal of Oil, Gas and Coal Technology, January 2008, Volume 1, Numbers 1&2. pp 65 - 80.
• An Integrated Technique for Production Data Analysis (PDA) with Application to Mature Fields. SPE Production & Operations Journal, November 2007, Volume 22, Number 4. pp 403 - 416.
• A New Methodology for the Identification of Best Practices in the Oil and Gas Industry, Using Intelligent Systems. Journal of Petroleum Science and Engineering, December 2005, pp 239-260.
• Recent Developments in Application of Artificial Intelligence in Petroleum Engineering. Journal of Petroleum Technology, Distinguished Author Series, April 2005, pp 86-91.
• Performance Drivers in Restimulation of Gas Storage Wells. SPE Reservoir Evaluation & Engineering Journal, December 2001, pp 536-543.
• Intelligent Systems Application in Candidate Selection and Treatment of Gas Storage Wells. Journal of Petroleum Science and Engineering, November 2001, Vol. 31, Issue 2-4, pp 125-133.
• Use of Intelligent Systems in Reservoir Characterization via Synthetic Magnetic Resonance Logs. Journal of Petroleum Science and Engineering, May 2001, Vol. 29, Issue 3-4, pp 189-204.
• Virtual Intelligence Applications in Petroleum Engineering: Part 3; Fuzzy Logic. Journal of Petroleum Technology, Distinguished Author Series, November 2000, pp 82-87.
• Virtual Intelligence Applications in Petroleum Engineering: Part 2; Evolutionary Computing. Journal of Petroleum Technology, Distinguished Author Series, October 2000, pp 40-46.
• Virtual Intelligence Applications in Petroleum Engineering: Part 1; Artificial Neural Networks. Journal of Petroleum Technology, Distinguished Author Series, September 2000, pp 64-73.
• Design Optimum Frac Jobs Using Virtual Intelligence Techniques. Computers and Geosciences Journal, October 2000, Vol. 26, Issue 8, pp 927-939.
• Hydraulic Fracture Design and Optimization of Gas Storage Wells. Journal of Petroleum Science and Engineering, October 1999, Vol. 23, Issue 3-4, pp 161-171.
• Determination of Permeability From Well Log Data. SPE Formation Evaluation Journal, September 1997, pp 170-174.
• Petroleum Reservoir Characterization with the Aid of Artificial neural networks. Journal of Petroleum Science and Engineering, December 1996, Vol. 16, pp 263-274.
• Predicting Well Stimulation Results in a Gas Storage Field in the Absence of Reservoir Data, Using Neural Networks. SPE Reservoir Engineering Journal, November 1996, pp 54-57.
• Performance of a Virtual Runoff Hydrograph System (VROHS). Journal of Water Resources Planning and Management, November 1996.
• Performance of a Virtual Adsorber System for Removal of Lead. Journal of Separation Science and Technology, April 1996, Vol. 31, issue 7, pp 965-985.
• Virtual Measurement of Heterogeneous Formation Permeability Using Geophysical Well Log Responses. The Log Analyst, March-April, 1996, pp 32-39.
• Identification of Parameters Influencing the Response of Gas Storage Wells to Hydraulic Fracturing With the Aid of a Neural Network. SPE Computer Applications Journal, April 1996, pp 54-57.
• Design and Development of an Artificial Neural Network for Estimation of Formation Permeability. SPE Computer Applications Journal, December 1995, pp 151-154.
• Production Decline Curves for Low-Pressure Gas Reservoirs Undergoing Simultaneous Water Production. SPE Formation Evaluation Journal, March, 1995, pp 57-62.
• Neural Network: What It Can Do For Petroleum Engineers. Journal of Petroleum Technology, January, 1995, page 42.
• Predicting the Production Performance of Gas Reservoirs Using Production Type Curves. Scientia Iranica, 1993.