Abstract
Besides the amount of a thermal fluid produced and its chemical composition, temperature is one of the key parameters for the utilization of hydrothermal heat. This applies in particular to geothermal fields with low temperature/low enthalpy, as too low extraction temperatures can mean the failure of a project, while higher temperatures can enable electricity generation or generally better economic efficiency. This concerns the undisturbed (natural) temperature in the reservoir as well as that of the produced fluid at the surface, which depends on the well completion, the undisturbed reservoir temperature, and the depth and contributions of hydraulically active zones. Subsequently, improved forecasts of both the undisturbed temperature and the production temperature with a valid estimate of their uncertainty are required to provide a reliable basis for field development and risk assessment. In the national projects Geothermal-Alliance Bavaria and KompakT, we studied the temperatures in the North Alpine Foreland Basin in Bavaria, Germany. The carbonate rocks form one of Europe’s most important reservoirs for the use of deep geothermal energy, and projects for district heating and electricity generation have been realized here for more than 30 years. We developed a good practice workflow for the correction of low-quality bottom hole temperature (BHT) values based on a probabilistic Monte Carlo approach. Using this workflow, we corrected BHTs from over 300 hydrocarbon and geothermal wells and predicted the natural temperature field inside the study area. The resulting temperature model is based on risk scenarios and contains a range of uncertainty, the extent of which depends on the uncertainty of the correction input parameters at the individual locations. To study the short-term and long-term thermal behavior in the reservoir and the wellbore during production conditions, in 2019, a fiber optic cable was installed below the pump into the reservoir of a geothermal production well. We used distributed temperature sensing (DTS) to observe the hydraulically active zones and to thermally derive their contribution to the available heat amount. The knowledge gained underlines the importance of flow zone characterization and can be used to improve existing temperature models and estimate what temperatures can really be expected during extraction.
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