Application of the CSTR in Series Model on Geothermal Tracer Returns to Evaluate Long-term Reservoir Temperature Stability

Abstract

Tracer studies in geothermal fields help quantify injection returns to production and can help predict thermal breakthrough. Often these returns are convoluted with the recycling associated with reinjection and require deconvolution to interpret the single-pass performance. The deconvolution technique discussed in this paper uses the CSTR in Series model, which is a simple model often applied in reactor design engineering for non-ideal residence time distribution analysis. A key advantage of the CSTR in Series model is its simple Laplacian transfer function which provides an analytical solution for impulse disturbances, such as tracer injection, regardless of the number of passes through the system. When applied to a geothermal system, the transfer functions between each injector-producer pair, or a field-average transfer function, can be determined and a temperature forecast can be created by introducing a step-change disruption to the transfer functions. An empirical correlation to re-scale the CSTR time parameter of the transfer function is being evaluated to improve temperature forecasts and better account for heat in place.