Mixed integer simulation optimization for petroleum field development under geological uncertainty

Optimal development of oil and gas fields involves determining well locations in oil reservoirs and well control through the production time. Field development problems are mixed-integer optimization problems because the well locations are dened by integer-valued block indices in the discrete reservoir model, while the well control variables such as bottom hole pressures or injection rates are continuous. Reservoir simulation software is used to evaluate production performance given a well placement and control plan. In the presence of reservoir uncertainty, we sample and simulate multiple model realizations to estimate the expected eld performance. We present a retrospective optimization using dynamic simplex interpolation (RODSI) algorithm for oil field development under uncertainty. The numerical results show that the RODSI algorithm efficiently finds a solution yielding a 20% increase (compared to a solution suggested from heuristics) in the expected net present value (NPV) over 30 years of reservoir production for the considered Brugge case.