| Virtual-intelligence applications in petroleum engineering: Part 1—Artificial neural networks S Mohaghegh Journal of Petroleum Technology 52 (09), 64-73, 2000 | 621* | 2000 |
| State-of-the-art in permeability determination from well log data: Part 1-A comparative study, model development B Balan, S Mohaghegh, S Ameri SPE Eastern Regional Meeting, SPE-30978-MS, 1995 | 264 | 1995 |
| Design and development of an artificial neural network for estimation of formation permeability S Mohaghegh, R Arefi, I Bilgesu, S Ameri, D Rose SPE Computer Applications 7 (06), 151-154, 1995 | 253 | 1995 |
| Petroleum reservoir characterization with the aid of artificial neural networks S Mohaghegh, R Arefi, S Ameri, K Aminiand, R Nutter Journal of Petroleum Science and Engineering 16 (4), 263-274, 1996 | 235 | 1996 |
| Neural network: What it can do for petroleum engineers S Mohaghegh Journal of Petroleum Technology 47 (01), 42-42, 1995 | 209 | 1995 |
| Recent developments in application of artificial intelligence in petroleum engineering SD Mohaghegh Journal of Petroleum Technology 57 (04), 86-91, 2005 | 186 | 2005 |
| A new approach for the prediction of rate of penetration (ROP) values HI Bilgesu, LT Tetrick, U Altmis, S Mohaghegh, S Ameri SPE Eastern Regional Meeting, SPE-39231-MS, 1997 | 171 | 1997 |
| Using artificial neural networks to generate synthetic well logs L Rolon, SD Mohaghegh, S Ameri, R Gaskari, B McDaniel Journal of Natural Gas Science and Engineering 1 (4-5), 118-133, 2009 | 169 | 2009 |
| Permeability determination from well log data S Mohaghegh, B Balan, S Ameri SPE formation evaluation 12 (03), 170-174, 1997 | 152 | 1997 |
| A methodological approach for reservoir heterogeneity characterization using artificial neural networks S Mohaghegh, R Arefi, S Ameri, MH Hefner SPE Annual Technical Conference and Exhibition?, SPE-28394-MS, 1994 | 136 | 1994 |
| Virtual-intelligence applications in petroleum engineering: part 3—fuzzy logic S Mohaghegh Journal of petroleum technology 52 (11), 82-87, 2000 | 134 | 2000 |
| State of the art of artificial intelligence and predictive analytics in the E&P industry: a technology survey C Bravo, L Saputelli, F Rivas, AG Pérez, M Nikolaou, G Zangl, ... Spe Journal 19 (04), 547-563, 2014 | 125 | 2014 |
| Reservoir simulation and modeling based on artificial intelligence and data mining (AI&DM) SD Mohaghegh Journal of Natural Gas Science and Engineering 3 (6), 697-705, 2011 | 125 | 2011 |
| Full field reservoir modeling of shale assets using advanced data-driven analytics S Esmaili, SD Mohaghegh Geoscience Frontiers 7 (1), 11-20, 2016 | 116 | 2016 |
| A parametric study on the benefits of drilling horizontal and multilateral wells in coalbed methane reservoirs N Maricic, SD Mohaghegh, E Artun SPE Reservoir Evaluation & Engineering 11 (06), 976-983, 2008 | 110 | 2008 |
| Application of machine learning and artificial intelligence in proxy modeling for fluid flow in porous media S Amini, S Mohaghegh Fluids 4 (3), 126, 2019 | 105 | 2019 |
| Shale analytics SD Mohaghegh, SD Mohaghegh Shale Analytics: Data-Driven Analytics in Unconventional Resources, 29-81, 2017 | 101 | 2017 |
| Artificial intelligence (AI) assisted history matching A Shahkarami, SD Mohaghegh, V Gholami, SA Haghighat SPE Western Regional Meeting, SPE-169507-MS, 2014 | 101 | 2014 |
| Development of an intelligent systems approach for restimulation candidate selection S Mohaghegh, S Reeves, D Hill SPE Unconventional Resources Conference/Gas Technology Symposium, SPE-59767-MS, 2000 | 96 | 2000 |
| Data-driven reservoir modeling: top-down modeling (TDM): a paradigm shift in reservoir modeling, the art and science of building reservoir models based on field measurements SD Mohaghegh (No Title), 2017 | 83 | 2017 |
