Analysis of influencing factors of the production performance of an enhanced geothermal system (EGS) with numerical simulation and artificial neural network (ANN)

Zhou, Lei; Zhang, Yanjun; Hu, Zhongjun; Yu, Ziwang; Luo, Yunlong; Lei, Yude; Lei, Honglei; Lei, Zhihong; Ma, Yanli

doi:10.1016/j.enbuild.2019.07.045

Cited by 45 publications

(19 citation statements)

References 35 publications

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“…The MSE values of the training and test sets were 0.447 and 0.587, respectively, and the R 2 values were 0.992 and 0.9885, respectively. These findings are consistent with the BP ANN study of the influencing factors of enhanced geothermal system production performance [43] and another study of surface roughness and energy consumption of machined parts [44]. The relative errors of the training and test sets were within 0.5 MPa, and the relative errors were within 20% except for the individual samples, showing that this method is more accurate and effective than other linear prediction methods [12].…”

Section: Analysis and Discussionsupporting

confidence: 89%

Breakthrough Pressure Prediction Based on Neural Network Model

et al. 2021

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The increasing carbon dioxide content is identified as the main cause of global warming. Capturing carbon dioxide in the atmosphere and transporting it to deep salt layer for storage have been proven and practiced in many aspects, which considered to be an effective way to reduce the content of carbon dioxide in the atmosphere. The sealing property of cap rocks is one of the key factors to determine whether CO2 can be effectively stored for a long time. In view of the disadvantages of tedious and time-consuming laboratory test methods for breakthrough pressure of cap rock, this paper explores the relationship between breakthrough pressure and other parameters such as porosity, permeability, density, specific surface area, maximum throat radius, and total organic carbon. The results show that the rock breakthrough pressure is closely related to the maximum throat radius and permeability determined by the mercury injection method, followed by the porosity and specific surface area, and less related to the density, depth, and TOC content of the rock itself. Then, with the selected parameters, a neural network model is established to predict the breakthrough pressure of cap rock, which can achieve good prediction results.

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Section: Analysis and Discussionsupporting

confidence: 89%

Breakthrough Pressure Prediction Based on Neural Network Model

et al. 2021

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“…Figures 10, 11 jointly reveal that geothermal research started with concept establishment, geophysical exploration, and geochemical exploration in the early stages (Studt and Thompson, 1969;Ólafur and Saemundsson, 1993;Tanaka, 2004) and then focused on the utilization and improvement of the thermal performance of hydrothermal geothermal resources (Qin et al, 2005;Han et al, 2010;Aneke et al, 2011;Saar, 2011). In recent years, mathematical statistics and big data analytics have been combined to generate numerical simulations and system optimizations of geothermal resources to attain the use and development of hot dry rock resources (Zeng et al, 2017;Song et al, 2018;Zhou et al, 2019;Liu et al, 2021;Aliyu and Archer, 2021;Zinsalo et al, 2021) and promote the establishment of geothermal power stations.…”

Section: Theme Evolutionmentioning

confidence: 99%

Visualization Analysis on the Current Status and Development Trend of Geothermal Research: Insights Into the Database of Web of Science

2022

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Geothermal energy is considered a renewable, clean, and environmentally friendly energy source. In addition, it is efficient and relatively cost effective. Therefore, the demand for the development and utilization of geothermal resources is increasing annually. To understand the current status and developments within the context of geothermal research, quantitative and qualitative analyses were carried out by combining two visualization software applications, namely, VOSviewer and CiteSpace; this analysis also entailed the secondary development of R language. The results showed that the USA, China, and Germany are the main contributors to geothermal research. We also found that geothermal research hot spots encompass five geothermal research clusters, such as renewable energy utilization, heat flow, numerical simulation, geochemistry, and groundwater. In addition, the strategic diagram and thematic structure revealed how geothermal research has evolved over time. Finally, the timeline view and burst term highlight the possible frontiers of geothermal power generation, enhanced geothermal systems, and ecological environment protection. These insights will provide scholars and policymakers with a systematic understanding of the current research and directions for future studies.

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“…Although the numerical simulation results of Wu et al were in agreement with the relevant literature, the roughness of the simulated cracks was more regular and may differ from the actual roughness. Zhou et al [69] analyzed the influence of various factors on the performance of thermal reservoirs of granite through numerical simulation and artificial neural network (ANN). 32 representative time points were selected to build 32 neural network models, which was to predict the 30-year production temperature of 32 time nodes in the system (The network architecture of the artificial neural network model is shown in Fig.…”

Section: Research Progress Of the Effect Of Fracture Structure Of Hot...mentioning

confidence: 99%

Progress on Heat Transfer in Fractures of Hot Dry Rock Enhanced Geothermal System

Wang¹,

Yu²,

Wu³

et al. 2021

Energy Engineering

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Hot Dry Rock (HDR) is the most potential renewable geothermal energy in the future. Enhanced Geothermal System (EGS) is the most effective method for the development and utilization of HDR resources, and fractures are the main flow channels and one of the most important conditions for studying heat transfer process of EGS. Therefore, the heat transfer process and the heat transfer mechanism in fractures of EGS have been the hot spots of research. Due to the particularity of the mathematical models of heat transfer, research in this field has been at an exploratory stage, and its methods are mainly experimental tests and numerical simulations. This paper introduces the progress on heat transfer in fractures of Hot Dry Rock EGS in detail, provides a comparative analysis of the research results and prospects for future research directions: It is suggested that relevant scholars should further study the mathematical equations which are applicable to engineering construction of seepage heat transfer in irregular fractures of the rock mass, the unsteady heat transfer process between multiple fractures of the rock mass and the heat transfer mechanism of the complex three-dimensional models of EGS.

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Analysis of influencing factors of the production performance of an enhanced geothermal system (EGS) with numerical simulation and artificial neural network (ANN)

Cited by 45 publications

References 35 publications

Breakthrough Pressure Prediction Based on Neural Network Model

Breakthrough Pressure Prediction Based on Neural Network Model

Visualization Analysis on the Current Status and Development Trend of Geothermal Research: Insights Into the Database of Web of Science

Progress on Heat Transfer in Fractures of Hot Dry Rock Enhanced Geothermal System

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