Well Placement Optimization for Improved Recovery of a Heavy Oil Reservoir – A Case Study of Heavy Oil Reservoir in Niger-Delta Area

Abstract

Abstract Efficient development tactics for oil fields, including well placement, pattern, and quantity, are critical to optimizing oil and gas production yields in mature reservoirs worldwide. However, because of the different API density of the crude oils in the reservoir, enormous number of grid blocks and multiple proxy tests that must be generated, optimizing well placement becomes difficult for reservoirs with significantly larger areal extent. The objective of this study is to optimize the placements of injector and producer wells in the Field XY field, a heavy oil reservoir under chemical flooding and production in the Niger- Delta region, adopting NPV as the objective function. The optimal configurations of the injection and producer wells are chosen using the differential evolution approach and particle swarm optimization techniques. The technique was programmed for the numerical simulator CMG STARS. The outcomes of the numerical simulation is produced by the CMOST AI-based CMG artificial intelligence optimization technique. The EOR project's net present value has increased by 57%, according to the optimization method's results. Additionally, following production and injection during a 20-year simulation period, the differential evolution optimization method outperformed the particle swarm optimization.