Reservoir Performance Optimization under Uncertain Future Development Plans

Abstract Optimization workflows have received considerable attention in oilfield management and development. A major difficulty in field development optimization is the significant uncertainty and risks from various sources, especially at the early stages of the reservoir life. While field development optimization under geologic and economic uncertainties have been studied and investigated in the literature, future development plans and their associated uncertainties have not yet been considered. In life-cycle optimization, reservoirs are likely to undergo extensive development activities in the future. Disregarding the possibility of future developments can lead to field performance predictions and optimization results that do not represent real field conditions. Alternatively, future development activities may be considered either as decision variables to optimize or as uncertain input parameters that must be accounted for. In many cases, even when future development activities are optimized, for a variety of (often unpredictable) reasons, the implementation in real field may not follow the optimized plan. In this paper, we demonstrate that it is important to consider future development plans with their associate uncertainty when optimizing the field performance. We present stochastic formulations to account for the uncertainty in future development activities, necessitating the need to consider multiple possible development scenarios. Using stochastic optimization formulations, we optimize decision variables (e.g. well locations and operational settings) at the current stage of development while accounting for the uncertainty in possible future development plans. In this work, we assume that infill drilling uncertainty evolves over reservoir development stages as a discrete time stochastic process, resulting in a decision tree representation of future drilling scenarios. The performance of the developed stochastic framework is evaluated and discussed relative to existing approaches that do not account for future field development plans in the optimization procedure. The results show significant improvements in the production performance when the uncertainty in future field development planning is considered in the optimization problem. We conclude that incorporating the uncertainty in future development offers flexibility and robustness to accommodate alternative development options and can avoid solutions that significantly underperform when future reservoirs development (drilling) activities do not go as planned.