Decision Maturation Using Ensemble Based Robust Optimization for Field Development Planning

A key aspect in the process of field development planning is to determine the optimal order in which production and injection wells will be drilled. For large fields typically many wells (50-100) are drilled which implies a significantly high number of possible combinations in which wells may be drilled. To evaluate all the possible combinations is computationally infeasible especially since in reality for field planning it is imperative to account for the range of uncertainties present to make a mature decision. The total number of simulations increases significantly when such uncertainties are accounted for. Decision maturation is the process of a user making an informed decision, in this case selecting an optimal drilling order, whilst including all the uncertainties known to the user in an automated optimization assisted framework. To achieve this goal we use the recently developed StoSAG formulation which is based on the increasingly popular Ensemble Optimization (EnOpt) method. In recent papers StoSAG was shown to be theoretically robust and numerically outperform EnOpt on a variety of synthetic test cases with continuous control variables. In this work we investigate the applicability of StoSAG to find the optimal drilling order of a real field case with approximately 700,000 active grid cells. The optimal drilling order control which is inherently a discrete/integer problem has been parameterized into continuous drilling priorities which highlight the flexibility of the method to different control types. In addition to the optimal drilling order we optimize the type of well (injector/producer) to be drilled as well as a time delay variable to find the optimal time at which a production well could possibly be converted into an injection well. We show that compared to a reference case we can achieve up to 18% increase in an economic objective function. A variety of experiments are performed which highlight the significant practical value achieved with our proposed decision maturation framework to find the optimal well types and drilling order over the life-cycle of the reservoir for a real field case under geological uncertainties.