Probability Concepts for the Evaluation of the Risk Concerning the Production and Injection Rate in Hydrothermal Reservoirs

Abstract

The economic success of a geothermal power project depends very much on the production rate and the injection rate which can be established in the wells tabbing the reservoir. The risk to reach the predicted rates is crucial for developers and investors of geothermal power plants. Therefore models are being set up to cover this risk. The concepts are either to cover the risk using private insurance or setting up a fund which is fed by different sources. Both concepts need an evaluation mechanism to assess the probability of success in other words the probability to reach the proposed production and injection rate. Evaluating the probability usually is based on statistics. Data availability in the geothermal reservoirs is scarce. In the Molasse region more than 30 data are available. They are of different quality and are spread irregularly in the region. The spatial distribution of the data calls for a geostatistical evaluation. This cannot be reduced to a mathematical approach only, but geology plays the decisive role in the geostatistical evaluation of the data. The type of reservoir focusing on karst features and on fault zones in the Malm limestone has to be taken into account. The data evaluation has to be coupled with data available from seismic surveys. The geostatistical approach bears the advantage that not only an assessment of the production flow value but also the quality of the assessment is given, based on the spatial distribution of the data in the region. In the case of the upper Rhine valley the data availability is even worse. There are less than 10 data available to assess the hydrothermal production in the geothermal reservoirs of the Buntsandstein and the Upper Muschelkalk. The successful wells are coupled with hydraulic active fault zones in the graben. The geostatistic approach is based on data availability. There need to be more wells drilled and tested to start following this approach for the assessment of the production rate directly. A concept is presented to cope with the problem assessing the probability of finding the planned production. The concept is based on the scarce data available, geostatistical values derived from other spatially distributed variables in the geothermal region of the upper Rhine valley. With the scarce data available at the moment there are also soft facts to be looked at to come to an assessment of probability. Soft facts are the quality of the exploration of the project being assessed and stimulation methods which give the best chance to reach the productivity desired in an economically bearable way. The types and sequence of stimulation methods should lead to a probability of success which can be accepted by insurance companies and funds.