Geothermal Field Development Optimization under Geological Uncertainties: Application to a Real Case Study with Stacked Reservoirs

Abstract

Summary The success and growth of geothermal development activities in the Netherlands in the coming years strongly depend on the capability to increase the cost-effectiveness of heat recovery from subsurface reservoirs. Field development optimization can help achieve that goal. In this work we apply state-of-the-art optimization technology to assist geothermal operators in finding improved field development strategies. The computer-assisted framework takes advantage of modern stochastic gradient-based methods that enable it to handle a large number of optimization variables in a computationally efficient manner even when considering an ensemble of model realizations to characterize geological uncertainties. We present results of a recent application of our optimization framework to a real-life case study with stacked reservoir layers. Starting from well configuration provided by the asset operator, we optimize the type of wells (injector or producer) and production rates from the different stacked reservoirs while considering realistic physical and operational constraints and accounting for geological uncertainty with an ensemble of 40 model realizations. Significant improvements in terms of the project economics (+9.6%) and heat production (+5.6%) are obtained, confirming the potential of optimization as a decision support tool to boost the efficiency of geothermal production.