| Integrated cluster analysis and artificial neural network modeling for steam-assisted gravity drainage performance prediction in heterogeneous reservoirs E Amirian, JY Leung, S Zanon, P Dzurman Expert Systems with Applications 42 (2), 723-740, 2015 | 86 | 2015 |
| Practical implementation of knowledge-based approaches for steam-assisted gravity drainage production analysis Z Ma, JY Leung, S Zanon, P Dzurman Expert Systems with Applications 42 (21), 7326-7343, 2015 | 57 | 2015 |
| Integration of artificial intelligence and production data analysis for shale heterogeneity characterization in steam-assisted gravity-drainage reservoirs Z Ma, JY Leung, S Zanon Journal of Petroleum Science and Engineering 163, 139-155, 2018 | 51 | 2018 |
| Data-driven modeling approach for recovery performance prediction in SAGD operations E Amirian, JY Leung, S Zanon, P Dzurman SPE Canada Heavy Oil Conference, SPE-165557-MS, 2013 | 48 | 2013 |
| Practical data mining and artificial neural network modeling for steam-assisted gravity drainage production analysis Z Ma, JY Leung, S Zanon Journal of Energy Resources Technology 139 (3), 032909, 2017 | 37 | 2017 |
| Correlating stochastically distributed reservoir heterogeneities with steam-assisted gravity drainage production C Wang, Z Ma, JY Leung, SD Zanon Oil & Gas Sciences and Technology–Revue d’IFP Energies nouvelles 73, 9, 2018 | 24 | 2018 |
| Direct prediction of reservoir performance with Bayesian updating under a multivariate Gaussian model CV Deutsch, SD Zanon PETSOC Canadian International Petroleum Conference, PETSOC-2004-047, 2004 | 22 | 2004 |
| In-situ reflux: an improved in-situ recovery method for oil sands TG Harding, S Zanon, M Imran, RK Kerr SPE Canada Heavy Oil Conference, D021S006R001, 2016 | 16 | 2016 |
| Implementation aspects of sequential simulation S Zanon, O Leuangthong Geostatistics Banff 2004, 543-548, 2004 | 15 | 2004 |
| Integration of artificial intelligence and production data analysis for shale heterogeneity characterization in SAGD reservoirs Z Ma, JY Leung, S Zanon SPE Canada Heavy Oil Conference, D011S004R003, 2016 | 14 | 2016 |
| An integrated application of cluster analysis and artificial neural networks for SAGD recovery performance prediction in Heterogeneous Reservoirs E Amirian, JY Leung, SD Zanon, PJ Dzurman SPE Canada Heavy Oil Conference, D011S004R003, 2014 | 13 | 2014 |
| Practical data mining and artificial neural network modeling for SAGD production analysis Z Ma, Y Liu, JY Leung, S Zanon SPE Canada Heavy Oil Conference, SPE-174460-MS, 2015 | 11 | 2015 |
| Comparative study of SAGD and solvent and water assisted electrical heating: effect of shale layers M Ma, M Rabiei Faradonbeh, H Hassanzadeh, TG Harding, S Zanon SPE Canada Heavy Oil Conference, D021S008R001, 2017 | 8 | 2017 |
| Procedures and guidelines for assessing and reporting uncertainty in geostatistical reservoir modeling CV Deutsch, M Monteiro, S Zanon, O Leuangthong Centre for Computational Geostatistics (CCG) 4, 21, 2002 | 8 | 2002 |
| UltimateSGSIM: Non-stationary sequential gaussian cosimulation by rock type CV Deutsch, S Zanon Center for Computational Geostatistics, Report 4, 2002 | 8 | 2002 |
| Practical implementation of knowledge-based approaches for SAGD production analysis Z Ma, JY Leung, SD Zanon, PJ Dzurman SPE Canada Heavy Oil Conference, D011S004R004, 2014 | 7 | 2014 |
| Advanced aspects of sequential Gaussian simulation. SDJ Zanon | 7 | 2000 |
| In-situ reflux: a low cost in-situ recovery method for oil sands TG Harding, S Zanon, M Imran, RK Kerr 65th Canadian chemical engineering conference calgary, Alberta, 4-7, 2015 | 6 | 2015 |
| Power law averaging revisited S Zanon, H Nguyen, CV Deutsch Center for Computational Geostatistics Annual Report Papers; Centre for …, 2002 | 6 | 2002 |
| Methods, systems and devices for modelling reservoir properties S Zanon, D Campagna, GAR Noble US Patent App. 16/088,949, 2019 | 5 | 2019 |
