ResX is the industry’s first commercially available software grounded in ensemble based methods, where the full range of geologically consistent reservoir models are history matched and used as basis for production forecasts.
By continuous data conditioning between static and dynamic data, ResX dramatically increases the team’s efficiency.
ResX provides reliable reservoir models, in time for your reservoir management decisions.
An automated workflow, using ResX, makes the reservoir modelling and history matching process repeatable and greatly simplifies the process of updating models as new data arrives.
Improved History Matching and Uncertainty Quantification for Gas Condensate Fields Using an Ensemble Based Approach
(A. Barliansyah, Bayerngas Norge, T. Skåre, Bayerngas Norge, T.F. Munck, Resoptima and J. Sætrom, Resoptima)
Consistent Integration of Drill-Stem Test Data into Reservoir Models on a Giant Field Offshore Norway
(J. Sætrom, Resoptima, H. Selseng, A. MacDonald, T. Kjølseth, O. Kolbjørnsen, Lundin Norway)
Improved Reservoir Management Decisions Using Ensemble Based Methods
(J. Sætrom, K. Klemens, T. F. Munck, Resoptima)
Consistently Integrating Static and Dynamic Data in the Facies Model Description Using an Ensemble Based Approach
(J. Sætrom, A. Phade, M. L. Vinther, T. F. Munck, Resoptima)
Selection of papers on the ensemble methodology:
History Matching Of The Norne Full Field Model Using An Iterative Ensemble Smoother
(Yan Chen, SPE, IRIS, and Dean S. Oliver, SPE, Uni CIPR)
An Ensemble Smoother for Assisted History Matching
(J.-A. Skjervheim and G. Evensen, Statoil Research Centre, Bergen, Norway, Mohn Sverdrup Center at Nansen Environmental and Remote Sensing Center, Bergen, Norway)
History Matching and Production Forecast Uncertainty by Means of the Ensemble Kalman Filter
(A. Bianco, A. Cominelli, L. Dovera, Eni E&P Division, G. Naevdal and B. Valles, Iris)