Sensitivity Analysis Using One-Factor-at-a-Time and Response Surface Method in Liquid-Dominated Geothermal Reservoir

Abstract

In addition to extensive information that has been obtained from pre-feasibility, exploration, and drilling phase, we can improve our knowledge of reservoir behavior related to thermal extraction using sensitivity analysis. Such analysis is commonly applied to address technical uncertainty and risks in economic evaluation. The purpose of this study is to determine the parameters that have the most influence on thermal power generation using two different approaches named one-factor-at-a-time or OFAT and response surface method or RSM. Moreover, RSM analysis allowed us to make a predictive model for thermal power extracted in liquid-dominated geothermal reservoir. Literature study is conducted to understand various properties commonly encountered in a liquid-dominated geothermal reservoir including porosity, conductivity, reservoir temperature, and permeability. This information is then used to construct reservoir model in CMG STARS simulator with a single producer and injector. Two different sampling method, named OFAT and Box-Behnken are used to construct dataset, each contains different combination of levels of reservoir porosity, conductivity, temperature, permeability, and re-injection temperature. A total of 31 models using OFAT method with 7-level for each parameter are simulated to understand individual effect of each parameter. Meanwhile, 47 models are constructed using RSM method with 3-level for each parameter to evaluate the effect of interaction between parameters on thermal generation potential as well as constructing predictive model. Sensitivity analysis using both OFAT and RSM agree that the reservoir temperature is the most significant characteristic of geothermal reservoir to affect its thermal power potential. Meanwhile, re-injection temperature that initially expected to strongly effect the lifetime and sustainability of a liquid-dominated geothermal utilization is insignificant. This finding suggest that optimization re-injection temperature is solely for the purpose of maintaining sustainability of geothermal reservoir or cater the concern of environmental issue on wastewater management, and not for maximizing the thermal extraction.