We have developed a non-isothermal lumped-parameter model for predicting both pressure and temperature behaviors of low temperature geothermal reservoirs containing a single-phase liquid water. Unlike the existing isothermal lumped-parameter models in the literature, the new model couples both energy (or heat) and mass balance equations and hence can be used to predict both temperature and pressure changes in the reservoir resulting from production of hot water, re-injection of a low temperature water into the system, and/or natural recharge. Variable production and re-injection rate histories are also handled. We have also developed an optimization code based on the Levenberg-Marquardt algorithm and coupled it with our new model to obtain a procedure for pressure and temperature data analysis. By considering semi synthetic pressure/temperature data sets, we demonstrate that we can generate estimates of reservoir bulk volume, porosity, temperature of the recharge source, recharge index, initial reservoir pressure and temperature by matching measured reservoir pressure and temperature data to our corresponding model responses by minimization of a weighted least-squares objective function. By using history matched models based on the new non-isothermal model, we also demonstrate that the future performance of a low-temperature geothermal reservoir can be predicted (yet more realistically, particularly for predicting the future reservoir temperature behavior, than those based on existing isothermal lumped-parameter models).

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