Abstract

Numerical reservoir simulation is a valuable tool to support the decision-making process in oil field projects. For this purpose, current reservoir engineering studies request numerous simulations runs for complex workflows, such as numerical reservoir characterization, data assimilation process, strategy optimisation, well placement studies, production management and supplementary project support. Thus, providing efficient and effective simulation numerical models is a critical task in reservoir simulation studies before starting the daily run demands.In this work, we propose, test and evaluate a practical workflow to improve the numerical performance of time-consuming reservoir simulation models. We provide a procedure to select representative numerical submodels and representative snapshots interval from simulation time (RSIST) to reduce the total time spent in numerical optimisation. The first approach allows the optimisation of the numerical parameters without the drawback of simulating long execution runtime. The second enables to select a range of simulation time where typical convergence problems of timestep cuts occur. The numerical parameters are then optimised using submodels and RSIST, where we highlight a workflow to reduce runtime of the optimisation of slow reservoir models. Following, the resultant set of parameters is applied to the entire (original) reservoir numerical model, improving its performance and allowing more effective execution of several simulation-runs in reservoir engineering studies.To conclude, we provide a workflow to be applied to any reservoir simulation model, especially those with complex structural grid and high-time consuming to run. Our results demonstrated remarkable improvements in the numerical performance of simulation models, with a high potential of saving days of work during probabilistic evaluations. Furthermore, we recommend this workflow as a first step before starting studies using reservoir simulation to avoid unphysical and time-demanding simulation runs that may affect future decisions.

Full Text
Paper version not known

Talk to us

Join us for a 30 min session where you can share your feedback and ask us any queries you have

Schedule a call

Disclaimer: All third-party content on this website/platform is and will remain the property of their respective owners and is provided on "as is" basis without any warranties, express or implied. Use of third-party content does not indicate any affiliation, sponsorship with or endorsement by them. Any references to third-party content is to identify the corresponding services and shall be considered fair use under The CopyrightLaw.