The study, performed on the Gjøa field offshore Norway, illustrates how ResX can be used to solve problems in a matter of hours or days, compared to months or years using traditional tools.
The paper discusses how combining efficient machine learning algorithms, reservoir physics and the knowledge of the subsurface team led to an improved understanding of sand distribution and intra-compartment communication on Gjøa, as well as to the identification of promising infill well targets with associated risks.
Resoptima’s technology makes subsurface teams more efficient and enables them to extract and use the information found in all the gathered reservoir data. Get in touch to get to know how we can help your team succeed in making the right decisions to increase recovery and produce efficiently.
We would like to acknowledge ENGIE E&P Norge AS and the Gjøa partners: Petoro, Wintershall, A/S Norske Shell and DEA Norge AS for permission to publish the paper.