Energy Scitech’s EnAble applies Bayes linear estimation to reduce bias in the conventional ‘history matching’ approach to reservoir simulation. Enable is a helper application that manages simulation run parameters for most all commercial and in-house simulators. This month’s EnAble meeting in London welcomed delegates from Shell, RWE-DEA, Eni-AGIP, Star Energy, Maersk and BG Group.
Heinrich Junker and Klaus Gaertner of RWE showed the results of a study on the Voelkersen gas field in Germany. The presentation showed how EnAble enhanced petroleum engineers’ productivity and allowed meaningful uncertainty estimates. The results are used in RWE’s decision making process and contribute to reserves assessment for annual reporting.
Stuart Pegg (Star Energy) showed how EnAble-based history matching of an extended reach onshore well helped resolve complex reservoir flow mechanisms in the presence of significant water encroachment.
Energy Scitech Director Nigel Goodwin outlined the new features of the latest EnAble release, many of which result from users’ suggestions. EnAble 1.9 is shipping now and extends design optimization to include well scheduling. This allows for a comprehensive field development plan that integrates subsurface uncertainty. Grid-based support is also included to spread computations across networks with multiple reservoir simulator licenses, such as Linux clusters. EnAble runs on large data sets on 32 bit and 64 bit Windows or Linux. Support now extends to Roxar’s Tempest/More, Saudi Aramco’s POWERS, Shell’s MoReS and CMG’s STARS.
Speaking at the 2005 SPE last month, Diana Bustamante (Pioneer) described use of EnAble’s Bayesian statistics to perform rapid analysis and integration of production data from the Gulf of Mexico Harrier and Raptor Fields. These offered ‘quick answers to reservoir analysis and reservoir management questions and [provided support for] well-intervention and deepwater rig availability decisions.’ More from SPE paper 95401.
© Oil IT Journal - all rights reserved.