Abstract
Reinjection of geothermal water into reservoirs could help maintain the reservoir pressure but may lead to thermal breakthrough. Therefore, the calculation of an optimal distance between the production and reinjection wells is required to balance the changes of pressure and temperature in the reservoir. In this work, a procedure has been designed to optimize well-doublet placement by integrating numerical simulations and economic analyses. The procedure is composed of two subsequent steps, which makes the method more flexible. The first step is the numerical simulation, which incorporates the geological and physical processes. The second step is to optimize the cost by varying the well distance. An example shows that it is better to place the reinjection well in the downstream of the production well. A distance of 400 m between the wells was found to be optimal for the given scenario. Through a further comparison with economic parameters in different countries, the optimal distance was found to be more relevant to the ratio of heat price over electricity than a single parameter for heat or electricity prices.
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Acknowledgements
This study is supported by the National Natural Science Foundation of China (Grant Nos. 41372257 and 41430319). The authors appreciate the International Postdoctoral Exchange Fellowship Program China (20130019) and the project funded by China Postdoctoral Science Foundation (2013M540138 and 2015M581168) for the financial support of this work. The support for the research stay of Dr. Kong with the Helmholtz Centre for Environmental Research, Department of Environmental Informatics, by the Helmholtz Association under the “Renewable Energy Program” is greatly acknowledged.
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This article is part of a Topical Collection in Environmental Earth Sciences on “Subsurface Energy Storage II”, guest edited by Zhonghe Pang, Yanlong Kong, Haibing Shao, and Olaf Kolditz.
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Kong, Y., Pang, Z., Shao, H. et al. Optimization of well-doublet placement in geothermal reservoirs using numerical simulation and economic analysis. Environ Earth Sci 76, 118 (2017). https://doi.org/10.1007/s12665-017-6404-4
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DOI: https://doi.org/10.1007/s12665-017-6404-4