A companion paper titled "New Lumped Parameter Models for Simulation of Low-Temperature Geothermal Reservoirs" presents practical analytical models for simulation of low-temperature geothermal reservoirs. This paper deals with the applications of the new lumped-parameter models to field cases. The models are used to match the long-term observed water level or pressure response to a given production history. For history matching purposes, we use an optimization algorithm based on the Levenberg-Marquardt method to minimize an objective function based on weighted least-squares for estimating relevant aquifer/reservoir parameters. In addition, we constrain the parameters during nonlinear minimization process to keep them physically meaningful and compute statistics (e.g, standard 95% confidence intervals) to assess uncertainty in the estimated parameters. Three field examples taken from the literature are considered to show the use of the models and optimization algorithm. The observed and simulated water level changes obtained from the models are discussed. Results show a very good agreement between the observed field data and simulated data from the lumped models given in this work, in spite of long data sets.

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