Estimation of Geothermal Reservoir Properties Using the Ensemble Kalman Filter

Abstract

Information on the permeability at depth is important for the exploitation of geothermal reservoirs. The Ensemble Kalman Filter (EnKF) is tool for property estimation if temporal observations are available. Observations can be temperature, hydraulic head during pumping tests, and chemical concentrations from tracer experiments at a few boreholes. The EnKF is a recursive Bayesian method incorporating observations in a Monte-Carlo-ensemble of reservoir simulations considering probability distributions. We present in synthetic test cases the application of the EnKF for estimating permeability and demonstrate its use for exploration planning. We apply the method to the 2005-tracer experiment of the Soultz-sous-Forêts geothermal reservoir.