The USGS volumetric estimation method together with Monte Carlo simulations is often used to provide estimates of the probable electrical generation capacity of a geothermal system. The methodology consists of combining probability density functions for uncertain estimates of the temperature, area, and thickness of a geothermal reservoir to obtain the probability distribution function for the stored energy (“heat in place”) and the resulting electrical capacity of the potential geothermal reservoir. Taken at face value, the methodology is deceptively simple. However, geothermal reservoir assessment and the prediction of the electrical capacity should be regarded as a continuing process – from the early exploration phase to the time when the reservoir becomes depleted. The key to a proper use of the technique is the specification of the probability distributions of the reservoir parameters. The data acquired during each phase of the reservoir development and production provides continuing refinement of reservoir parameters and, therefore, the electrical capacity. Very often, these parameters are designated based on data from other geothermal reservoirs. Conditions vary widely between and within the various geothermal provinces around the world. Thus, it is essential that, as far as possible, actual field data should be used when prescribing reservoir parameters. Without data-driven reservoir parameters, use of Monte Carlo simulations is liable to generate unreliable estimates of reservoir capacity for electrical generation.

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