Managing Risk in Well Placement Optimization within an Expected Utility Framework

Well placement optimization is one of the most crucial tasks in the petroleum industry. It often involves high risk in the presence of geological uncertainty due to a limited understanding of the subsurface reservoir. Well placement optimization is different from decision selection as countless alternatives are impossible to be enumerated in a decision model (such as the mean-variance model). In many practical applications, the decision criterion of well placement optimization is based on maximizing the risk-adjusted value (mean-variance optimization) to capture different risk attitudes. This approach regards variance as the measure of risk, and it is performed under the expected utility framework. However, investors only dislike the downside volatility below a certain benchmark. The downside-risk approach has been discussed in previous studies, in this paper, it will be introduced in the well placement optimization and discussed under the expected utility framework. It is demonstrated in a synthetic reservoir model with the consideration of spatial heterogeneity, and the comparison between the downside-risk optimization and mean-variance optimization is also presented in this example. The observation implies that well placement optimization is heavily influenced by individuals’ preference to risk. The downside-risk optimization outperforms the mean-variance optimization because it explicitly assesses risk and does not penalize high outcomes.