Probabilistic analysis of heat extraction performance in enhanced geothermal system based on a DFN-based modeling scheme

Xinxin Li, Chengyu Li, Wenping Gong, Yanjie Zhang and Junchao Wang

Energy, 2023, vol. 263, issue PC

Abstract: With the uncertain fractures involved in the water-rock interaction in the enhanced geothermal system (EGS) taken into account, numerical simulation of heat extraction is challenging to implement, especially in the situation where the EGS is conducted in a complex fracture network. In this study, a discrete fracture network (DFN) modeling procedure based on finite element method (FEM) is proposed to simulate the uncertainty of heat extraction performance in the fractured hot dry rock (HDR), in which the rock matrix and fractures are discretized into triangular elements and zero-thickness elements, respectively. To verify the effectiveness of the established numerical model, the simulation results are compared with the analytical solution and a good agreement is reached. Further, Monte Carlo simulation (MCS) method is adopted to probabilistically study the production performance of EGS considering the randomness of the fracture network. According to the MCS results, heat production performance, i.e., outlet average temperature, EGS lifetime, output thermal power, heat extraction ratio, and levelized cost of energy (LCOE), are statistically analyzed. The study results indicate that the heat extraction performance can be more effectively assessed by the probabilistic analysis, and the uncertainties involved in the heat extraction process cannot be ignored.

Keywords: EGS; Heat extraction performance; DFN; FE algorithm; Probabilistic analysis (search for similar items in EconPapers)
Date: 2023
References: View references in EconPapers View complete reference list from CitEc
Citations: View citations in EconPapers (7)

Downloads: (external link)
http://www.sciencedirect.com/science/article/pii/S0360544222025609
Full text for ScienceDirect subscribers only

Related works:
This item may be available elsewhere in EconPapers: Search for items with the same title.

Export reference: BibTeX RIS (EndNote, ProCite, RefMan) HTML/Text

Persistent link: https://EconPapers.repec.org/RePEc:eee:energy:v:263:y:2023:i:pc:s0360544222025609

DOI: 10.1016/j.energy.2022.125674

Access Statistics for this article

Energy is currently edited by Henrik Lund and Mark J. Kaiser

More articles in Energy from Elsevier
Bibliographic data for series maintained by Catherine Liu ().