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- W4385383249 abstract "Engineering case studies have revealed that multi-well enhanced geothermal system is efficient for large-scale geothermal energy utilization. However, current research on the productivity and lifespan of multi-well enhanced geothermal system is limited to rough estimation by thermal storage volume, without a fast and accurate prediction method. To solve this problem, the multi-well enhanced geothermal system is divided into several double-well enhanced geothermal systems. The numerical simulation and previous empirical formulas for double-well enhanced geothermal system are used to propose a new multi-well enhanced geothermal system empirical formula in this study. The proposed formula is applicated using the Rehai geothermal field in Yunnan, China by three-well model and six-well model respectively. The results show that the heat production and lifespan of the enhanced geothermal system with six wells arrangement are higher compared to the three wells arrangement. Moreover, the productivity and lifespan of enhanced geothermal system with injection pressure difference and injection temperature of 1.0MPa and 293.16K for thermal medium are significantly better than those of 2.5MPa and 353.16K, respectively. Therefore, during enhanced geothermal system construction, both productivity and investment should be considered, and the number of injection wells should be maximized. Low-temperature thermal medium and low injection-production pressure differences should be selected for maximum heat production during the operation. This research presents a fast and accurate prediction method for predicting and evaluating the heat transfer performance of large-scale multi-well EGS which is helpful for EGS commercial use." @default.
- W4385383249 created "2023-07-30" @default.
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- W4385383249 date "2023-11-01" @default.
- W4385383249 modified "2023-09-27" @default.
- W4385383249 title "Prediction and optimization of productivity and lifespan in multi-well enhanced geothermal system" @default.
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- W4385383249 doi "https://doi.org/10.1016/j.applthermaleng.2023.121155" @default.
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