Scenario Based Optimization Methodology for Field Development Planning

Abstract

An innovative optimization methodology for field development planning is presented. A new mixed integer optimizer is described. The optimization tool's "user-friendly" plug-in in a commercial reservoir characterization and simulation package is developed, and methodology applications in exploration projects are outlined. An effective methodology is developed to optimize well placement and facility options in oil fields with multiple reservoirs. The optimized field development plan is selected for individual reservoirs from various well placements, well trajectories, injection strategies, and facility scenarios significantly impacting field oil recovery. Multiple subsurface models representing uncertainties in subsurface descriptions are applied in the optimization process. An effective mixed integer optimizer is developed. The optimizer is based on sequential cycles of a) selection of "promising" scenarios changing one decision variable per simulation and b) evaluations of combinations of the "promising" scenarios using Latin Hypercube sampling. The optimization workflow is implemented as a user-friendly plug-in to a commercial package, which allows one to a) define locations and trajectories of potential wells, b) define well placement and facility scenarios, c) run optimization workflows, and d) evaluate optimization results. The developed optimization methodology is successfully applied in several exploration projects. Effectiveness and significant benefits from the optimization applications are demonstrated. This paper can bring significant benefits to the state of knowledge in the petroleum industry by a) describing the novel methodology for optimizing field development scenarios that have significant impacts on oil recovery, b) applying the new optimizer, c) implementing the optimization plug-in in a commercial package.