A Stochastic Approach to Estimating Gas Field Resources under Input Data Uncertainty

Abstract

we studied an integrated approach to estimating gas field resources by combining statistical methods with dynamic reservoir simulation. We developed a simulation model that accounts for geological and physical properties of the reservoir, as well as fluid flow characteristics. We proposed an algorithm that enables resource estimation under input data uncertainty. We tested the method on real gas fields and compared it with conventional approaches. The results show that the proposed approach improves estimation reliability and performance.