| REYNOLDS, Numerical Analysis R Burden, JD Faire, AC Reynolds Prindle, Weber and Schmidt, 1978 | 2719* | 1978 |
| Inverse theory for petroleum reservoir characterization and history matching DS Oliver, AC Reynolds, N Liu Inverse Theory for Petroleum Reservoir Characterization and History Matching, 2008 | 1130 | 2008 |
| The ensemble Kalman filter in reservoir engineering—a review SI Aanonsen, G Nœvdal, DS Oliver, AC Reynolds, B Vallès Spe Journal 14 (03), 393-412, 2009 | 926 | 2009 |
| Ensemble smoother with multiple data assimilation AA Emerick, AC Reynolds Computers & Geosciences 55, 3-15, 2013 | 905 | 2013 |
| Boundary conditions for the numerical solution of wave propagation problems AC Reynolds Geophysics 43 (6), 1099-1110, 1978 | 523 | 1978 |
| Results of the Brugge benchmark study for flooding optimization and history matching E Peters, RJ Arts, GK Brouwer, CR Geel, S Cullick, RJ Lorentzen, Y Chen, ... SPE Reservoir Evaluation & Engineering 13 (03), 391-405, 2010 | 483 | 2010 |
| Markov chain Monte Carlo methods for conditioning a permeability field to pressure data DS Oliver, LB Cunha, AC Reynolds Mathematical geology 29, 61-91, 1997 | 354 | 1997 |
| History matching of three-phase flow production data R Li, AC Reynolds, DS Oliver SPE Journal 8 (04), 328-340, 2003 | 325 | 2003 |
| Production optimization in closed-loop reservoir management C Wang, G Li, AC Reynolds SPE journal 14 (03), 506-523, 2009 | 322 | 2009 |
| Conditioning permeability fields to pressure data DS Oliver, N He, AC Reynolds ECMOR V-5th European conference on the mathematics of oil recovery, cp-101-00023, 1996 | 313 | 1996 |
| History matching time-lapse seismic data using the ensemble Kalman filter with multiple data assimilations AA Emerick, AC Reynolds Computational Geosciences 16, 639-659, 2012 | 257 | 2012 |
| New pressure transient analysis methods for naturally fractured reservoirs K Serra, AC Reynolds, R Raghavan J. Pet. Technol.;(United States) 35 (12), 2,271 - 2,283, 1983 | 251* | 1983 |
| Assessing the uncertainty in reservoir description and performance predictions with the ensemble Kalman filter M Zafari, AC Reynolds SPE Annual Technical Conference and Exhibition?, SPE-95750-MS, 2005 | 227 | 2005 |
| Quantifying uncertainty for the PUNQ-S3 problem in a Bayesian setting with RML and EnKF G Gao, M Zafari, AC Reynolds SPE Reservoir Simulation Conference?, SPE-93324-MS, 2005 | 223 | 2005 |
| An Iterative Ensemble Kalman Filter for Data Assimlaton G Li, AC Reynolds SPE Journal, 2009 | 217 | 2009 |
| An improved implementation of the LBFGS algorithm for automatic history matching G Gao, AC Reynolds SPE Journal 11 (01), 5-17, 2006 | 213 | 2006 |
| Conditioning geostatistical models to two-phase production data Z Wu, AC Reynolds, DS Oliver SPE journal 4 (02), 142-155, 1999 | 209 | 1999 |
| A stochastic simplex approximate gradient (StoSAG) for optimization under uncertainty RRM Fonseca, B Chen, JD Jansen, A Reynolds International Journal for Numerical Methods in Engineering 109 (13), 1756-1776, 2017 | 204 | 2017 |
| Reparameterization techniques for generating reservoir descriptions conditioned to variograms and well-test pressure data AC Reynolds, N He, L Chu, DS Oliver SPE Journal 1 (04), 413-426, 1996 | 202 | 1996 |
| Investigation of the sampling performance of ensemble-based methods with a simple reservoir model AA Emerick, AC Reynolds Computational Geosciences 17, 325-350, 2013 | 197 | 2013 |
Dean S OliverChief scientist, NORCE Research, Bergen, NorwayVerified email at norceresearch.no
