New study out in Geothermics led by Research Scientist Peter Johnson examines the assumptions in modeling geothermal systems. Geothermal systems are generally assumed to consist of hot fluids undergoing convective circulation above a heat source. These systems often extend to depths of several kilometers below the ground surface. Some model software cannot simulate these deep regions because the fluid is supercritical. Furthermore, in most geothermal systems, we do not have wells deep enough to establish what conditions are like at these depths. As a result, modelers working on geothermal reservoirs have customarily built their models to only include the top few kilometers of the reservoir, and represent upwelling water with a source of heat and mass. In this paper, Peter and his co-authors point out using clear, simple cases that the physics of the resulting model does not accurately represent what is believed to be occurring in these reservoirs. In the most extreme cases, the simplification of the convecting system into a model like this results in a model that does not actually have convective circulation. As the authors point out, if the physics of the model are not equivalent to those of the real geothermal field, it may be possible to calibrate the model still, but the parameters used in the calibration will take unrealistic values to compensate for the bad physics. The resulting forecasts may be badly biased by these corrupted parameters, rendering the model useless. Most perniciously, the modeler is unlikely to even be aware that this is occurring, because the calibration still seems to function properly.

You can access the article here: https://doi.org/10.1016/j.geothermics.2022.102391