Search Results (169)

Both ground source heat pumps (GSHPs) and energy underground structures are engineered systems that utilize shallow geothermal energy. However, due to the construction complexity and associated costs of energy tunnels, their heat exchange efficiency relative to GSHPs remains a topic worthy of in-depth investigation. In this study, a thermal–hydraulic (TH) coupled finite element model was developed based on a section of the Torino Metro Line in Italy to analyze the differences in and influencing factors of heat transfer performance between energy tunnels and GSHPs. The model was validated by comparing the outlet temperature curves under both winter and summer loading conditions. Based on this validated model, a parametric analysis was conducted to examine the effects of the tunnel air velocity, heat carrier fluid velocity, and fluid type. The results indicate that, under identical environmental conditions, energy tunnels exhibit higher heat exchange efficiency than conventional GSHP systems and are less sensitive to external factors such as fluid velocity. Furthermore, a comparison of different heat carrier fluids, including alcohol-based fluids, refrigerants, and water, revealed that the fluid type significantly affects thermal performance, with the refrigerant R-134a outperforming ethylene glycol and water in both heating and cooling efficiency. Full article

Medium-deep borehole heat exchanger (BHE) systems represent an emerging form of ground source heat pump technology. Their heat transfer process is significantly influenced by geothermal gradient and soil stratification, typically simulated using segmented finite line source (SFLS) models. However, this approach involves computationally intensive procedures that hinder practical engineering implementation. Building upon an SFLS model adapted for complex geological conditions, this study proposes a comprehensive simplified algorithm: (1) For soil stratification: A geothermally-weighted thermal conductivity method converts layered heterogeneous media into an equivalent homogeneous medium; (2) For geothermal gradient: A temperature correction method establishes fluid temperatures under geothermal gradient by superimposing correction terms onto uniform-temperature model results (g-function model). Validated through two engineering case studies, this integrated algorithm provides a straightforward technical tool for heat transfer calculations in BHE systems. Full article

Accurate prediction of reservoir temperature is critical for optimizing geothermal energy systems, yet the complexity of geothermal data poses significant challenges for traditional modeling approaches. This study conducts a comprehensive comparative analysis of advanced machine learning models, including support vector regression (SVR), random forest (RF), Gaussian process regression (GP), deep neural networks (DNN), and graph neural networks (GNN), to evaluate their predictive performance for reservoir temperature estimation. Enhanced feature engineering techniques, including accumulated local effects (ALE) and SHAP value analysis, are employed to improve model interpretability and identify key hydrogeochemical predictors. Results demonstrate that RF outperforms other models, achieving the lowest mean squared error (MSE = 66.16) and highest R² score (0.977), which is attributed to its ensemble learning approach and robust handling of nonlinear relationships. SVR and GP exhibit moderate performance, while DNN and GNN show limitations due to overfitting and sensitivity to hyperparameter tuning. Feature importance analysis reveals that SiO₂ concentration as the most influential predictor, aligning with domain knowledge. The study highlights the interplay between model complexity, dataset size, and predictive accuracy, offering actionable insights for optimizing geothermal energy systems. By integrating advanced machine learning with enhanced feature engineering, this research provides a robust framework for improving reservoir temperature prediction, contributing to the sustainable development of geothermal energy in alignment with sustainable energy development. Full article

This study proposes a polygeneration system that integrates an absorption cooling system, a heat transformer, and an organic Rankine cycle for the simultaneous production of power, cooling, and freshwater—the former operating with a water/lithium bromide mixture while the organic Rankine cycle operates with R123. The system was simulated at temperatures between 100 °C and 150 °C and with heat supply capacities that a geothermal field in Nayarit, Mexico, could provide. A parametric analysis was conducted by developing a mathematical model using the Engineering Equation Solver software. The geothermal source temperatures, ambient temperatures, and mass ratios were varied to determine the power, cooling load, freshwater production, and energy utilization factor under different operating conditions. The results showed that the system could produce up to 13 kW of power, 100 kW of cooling, and 50 L per hour at a heat source temperature of 150 °C. The energy utilization factor varied from 0.32 to 0.43, which means that up to 43% of the energy supplied to the system could be utilized to produce cooling, freshwater, or power. Full article

Shear wave velocity (V_s) is a key geomechanical variable in subsurface exploration, essential for hydrocarbon reservoirs, geothermal reserves, aquifers, and emerging use cases, like carbon capture and storage (CCS), offshore geohazard assessment, and deep Earth exploration. Despite its broad significance, no comprehensive multidisciplinary review has evaluated the latest applications, estimation methods, and challenges in V_s prediction. This study provides a critical review of these aspects, focusing on energy-efficient prediction techniques, including geophysical surveys, remote sensing, and artificial intelligence (AI). AI-driven models, particularly machine learning (ML) and deep learning (DL), have demonstrated superior accuracy by capturing complex subsurface relationships and integrating diverse datasets. While AI offers automation and reduces reliance on extensive field data, challenges remain, including data availability, model interpretability, and generalization across geological settings. Findings indicate that integrating AI with geophysical and remote sensing methods has the potential to enhance V_s prediction, providing a cost-effective and sustainable alternative to conventional approaches. Additionally, key challenges in V_s estimation are identified, with recommendations for future research. This review offers valuable insights for geoscientists and engineers in petroleum engineering, mining, geophysics, geology, hydrogeology, and geotechnics. Full article

Enhanced or engineered geothermal systems (EGSs), or non-hydrothermal resources, are highly notable among sustainable energy resources because of their abundance and cleanness. The EGS concept has received worldwide attention and undergone intensive studies in the last decade in the US and around the world. In comparison, hydrothermal reservoir resources, the ‘low-hanging fruit’ of geothermal energy, are very limited in amount or availability, while EGSs are extensive and have great potential to supply the entire world with the needed energy almost permanently. The EGS, in essence, is an engineered subsurface heat mining concept, where water or another suitable heat exchange fluid is injected into hot formations to extract heat from the hot dry rock (HDR). Specifically, the EGS relies on the principle that injected water, or another working fluid, penetrates deep into reservoirs through fractures or high-permeability channels to absorb large quantities of thermal energy by contact with the host hot rock. Finally, the heated fluid is produced through production wells for electricity generation or other usages. Heat mining from fractured EGS reservoirs is subject to complex interactions within the reservoir rock, involving high-temperature heat exchange, multi-phase flow, rock deformation, and chemical reactions under thermal-hydrological-mechanical (THM) processes or thermal-hydrological-mechanical-chemical (THMC) interactions. In this paper, we will present a THM model and reservoir simulator and its application for simulation of hydrothermal geothermal systems and EGS reservoirs as well as a methodology of coupling thermal, hydrological, and mechanical processes. A numerical approach, based on discretizing the thermo-poro-elastic Navier equation using an integral finite difference method, is discussed. This method provides a rigorous, accurate, and efficient fully coupled methodology for the three (THM) strongly interacted processes. Several programs based on this methodology are demonstrated in the simulation cases of geothermal reservoirs, including fracture aperture enhancement, thermal stress impact, and tracer transport in a field-scale reservoir. Results are displayed to show geomechanics’ impact on fluid and heat flow in geothermal reservoirs. Full article

The energy pile integrates shallow geothermal energy extraction with underground structural engineering, thereby expanding the functional applications and scope of pile foundations. Due to its widespread adoption, research on energy pile analysis theory has advanced significantly. Among existing analytical methods, the load transfer method is widely employed owing to its computational simplicity and readily obtainable parameters. However, current load transfer models for energy piles remain imperfect, primarily because their results often fail to accurately reflect real-world loading conditions. This study investigates the underlying causes of this discrepancy and proposes an iterative method to eliminate unbalanced forces at the pile head, based on the displacement coordination algorithm for energy pile load transfer. The calculated results at the pile head show an 18% reduction in error compared to previous studies. The average error compared with field test results is within 20%, with consistent trend patterns, confirming the feasibility of the proposed method. Computational results demonstrate that the proposed method effectively captures the combined effects of mechanical load and temperature variations on the bearing behavior of energy piles. It should be noted that this paper focuses specifically on improving the temperature-dependent load transfer method for energy piles. Consequently, the conventional load transfer method and results under purely mechanical loading are not discussed herein. Full article

Deep borehole heat exchanger (DBHE) is a clean and efficient technology that utilizes geothermal energy for building heating. However, continuous heat extraction from a DBHE system can lead to its performance decline over time. In this paper, the seasonal heat extraction and storage of a DBHE were simulated to assess the impact of seasonal heat storage schemes on its thermal and economic performance. The numerical model was constructed based on real project parameters and validated using monitoring data. Simulation results indicate that the extracted heat after storage increases linearly with the injected heat, enabling a straightforward estimation of the storage input to mitigate short-term thermal attenuation of DBHEs under varying storage durations. However, when the same amount of heat was injected annually, DBHE heat extraction still exhibited a declining trend from the third year, suggesting that short-term improvements in heat extraction could not be sustained in the long term. Furthermore, heat storage efficiency improves over time as the surrounding borehole temperature gradually increases, reaching more than 27% after 10 years for all storage scenarios. For the first time, an economic analysis was conducted for DBHE heat storage, revealing that when a solar supplemental heat system is applied, the levelized cost of heat (LCOH) is slightly higher than the base case without storage, except in cases where solar collector costs are excluded. Given the modest thermal and economic improvements, seasonal heat storage is recommended for DBHEs, especially when low-cost surplus heat is readily available. Full article

The development of geo-energy resources, including oil, gas, and geothermal reservoirs, is being transformed through the creation of low-energy processes and innovative technologies. This Special Issue compiles cutting-edge research aimed at enhancing efficiency, sustainability, and recovery during geo-energy extraction. The published studies explore a diverse range of methodologies, such as the nanofluidic analysis of shale oil phase transitions, deep electrical resistivity tomography for geothermal exploration, and hybrid AI-driven production prediction models. Their key themes include hydraulic fracturing optimization, CO₂ injection dynamics, geothermal reservoir simulation, and competitive gas–water adsorption in ultra-deep reservoirs, and these studies combine advanced numerical modeling, experimental techniques, and field applications to address challenges in unconventional reservoirs, geothermal energy exploitation, and enhanced oil recovery. By bridging theoretical insights with practical engineering solutions, this Special Issue provides a comprehensive foundation for future innovations in low-energy geo-energy development. Full article

When developing deep subsurface infrastructure in areas with intense geothermal activity, the significant temperature gradient inevitably leads to low-temperature contraction and high-temperature expansion of the rock body, resulting in changes in the rock’s mechanical properties. These thermodynamic effects can easily lead to the destabilization and subsequent collapse of the rock. There exists a pressing necessity to methodically evaluate the surrounding rock stability encountered in deep underground engineering under the action of thermal-solid coupling. This study constructed a multi-physical field coupling nonlinear calculation model based on a high-precision three-dimensional finite difference method, systematically analyzed the interdependent effects between the original rock temperature and excavation-induced disturbance, and then analyzed the dynamic changes in temperature, stress, and displacement fields along with plastic zone of surrounding rock of the deep underground engineering under thermal-solid coupling. The results indicate that the closer to the excavation contour surface, the lower the surrounding rock temperature, while the temperature gradient increased correspondingly. The farther away from the excavation contour face, the closer the temperature was to the original rock temperature. As the original rock temperature climbed from 30 °C to 90 °C, the increment of vault displacement was 2.45 times that of arch bottom displacement, and the influence of temperature change on vault deformation was more significant. The horizontal displacement magnitudes at the different original temperatures followed the following order: sidewall > spandrel > skewback, and at an original rock temperature of 90 °C, the sidewall horizontal displacement reached 15.31 cm. With the elevation of the original rock temperature, the distribution range and concentration degree of the maximum and minimum principal stresses increased obviously, and both were compression-dominated. The types of plastic zones in the surrounding rock were mainly characterized by shear stress-induced yielding and tensile stress-induced damage failure. When the original rock temperature increased to 90 °C, the rock mass extending up to 1.5 m from the excavation contour surface formed a large area of damage zone. The closer the working face was to the monitoring section, the faster the temperature dropped, and the displacement changed in the monitoring section. The findings offer a theoretical basis for engineering practice, and it is of great significance to ensure the safety of the project. Full article

To enhance the efficient development of geothermal energy, this study investigates the heat transfer enhancement mechanisms in medium-depth coaxial underground heat exchangers (CUHEs) integrated with corrugated fins, using computational fluid dynamics (CFD) simulations. Nine distinct corrugated fin geometries were modeled, and the streamlines, velocity fields, temperature fields, and turbulent kinetic energy were analyzed across Reynolds numbers (Re) ranging from 12,000 to 42,000. The results demonstrate that corrugated fins significantly promote fluid turbulence and mixing, thereby augmenting convective heat transfer. Compared to smooth inner tubes, the Nusselt number (Nu) is enhanced by a factor of 1.43–2.19, while the friction factor (f) increases by a factor of 2.94–6.79. The performance evaluation criterion (PEC) improves with increasing fin width and decreasing fin spacing. The optimal configuration, featuring a fin width of 15 mm, a spacing of 60 mm, and a thickness of 15 mm, achieves a maximum PEC value of 1.34 at Re = 12,000, indicating a substantial improvement in heat transfer performance within acceptable pressure drop limits. This research innovatively explores the performance enhancement of CUHEs at high Re, systematically elucidates the influence of geometric parameters on heat transfer and flow resistance, and employs the PEC index to optimize the structural design. This provides significant theoretical support for the efficient engineering application of CUHEs in geothermal utilization. Full article

This study presents a constitutive model for simulating the behavior of weak rock masses under various stress conditions, including the effects of pore pressure and temperature. Addressing the limitations of existing models in accurately representing the complex anisotropic response of these materials, the model utilizes Monte Carlo simulations to integrate stress anisotropy, pore pressure effects, and deviatoric stress states. This approach aims to capture the impact of geological factors such as foliation and jointing on the mechanical behavior of weak rock masses, which are often characterized by low strength and high deformability. Five rock types (claystone, mudstone, sandstone, shale, and siltstone) were simulated, generating 1000 cases per type with variability modeled using Weibull distributions. Statistical validation, employing the Kolmogorov–Smirnov test and Q–Q plots, demonstrated a strong agreement between simulated and experimental data. The results suggest that the proposed model can effectively predict deformation patterns in weak rock masses, offering potential applications in mining, geothermal energy extraction, and other engineering projects involving these challenging geological formations. Full article

Geothermal resources are crucial for sustainable energy development, yet accurately detecting geothermal anomalies in complex terrains remains a significant challenge. This study develops a multi-source thermal infrared approach to enhance geothermal anomaly detection using Landsat 8 and ASTER land surface temperature (LST) data. The Yangbajing–Yangyi Basin in Tibet, characterized by high altitude and rugged topography, serves as the study area. Landsat 8 winter time-series data from 2013 to 2023 were processed on the Google Earth Engine (GEE) platform to generate multi-year average LST images. After water body removal and altitude correction, a local block thresholding method was applied to extract daytime geothermal anomalies. For nighttime data, ASTER LST products were analyzed using global, local block, elevation zoning, and fault buffer strategies to extract anomalies, which were then fused using Dempster–Shafer (D–S) evidence theory. A joint daytime–nighttime analysis identified stable geothermal anomaly regions, with results closely aligning with known geothermal fields and borehole distributions while predicting new potential anomaly zones. Additionally, a 21-year time-series analysis of MODIS nighttime LST data identified four significant thermal anomaly areas, interpreted as potential magma chambers, whose spatial distributions align with the identified anomalies. This multi-source approach highlights the potential of integrating thermal infrared data for geothermal anomaly detection, providing valuable insights for exploration in geologically complex regions. Full article

Geothermal energy is typically produced from underground reservoirs using water as the working fluid to transfer heat energy to surface and eventually to the delivery point. CO₂ has been proposed as an alternative working fluid due to its improved mobility, density and its supercritical phase state, leading thus to so-called CPG (CO₂ Plume Geothermal) systems. As a positive side effect, the injected CO₂ mass circulation in the reservoir can be considered a CO₂ storage mechanism, which, depending on the size of the porous medium, may account for few millions of CO₂ tons. Moreover, the thermosiphon effect, owned to the significant change of fluid density between the injection (cold) and the production wells (hot) as well as to its change along the wells, significantly reduces the need for pumping, hence the operating costs. In this work, we setup a mathematical model that fully describes flow in the production/injection wells doublet as well as in the geothermal reservoir. Subsequently, the model is used to evaluate the sensitivity of the beneficial effects of circulating CO₂ rather than water. Parameters such as reservoir properties, injection temperature and thermal effects, are tweaked to demonstrate the sensitivity of each one to the system performance. The results can be utilized as a guideline to the design of such systems and to the emphasis needed to be paid by the engineers. Full article

This paper reviews recent advancements in integrated thermoelectric power generation and water desalination technologies, driven by the increasing global demand for electricity and freshwater. The growing population and reliance on fossil fuels for electricity generation pose challenges related to environmental pollution and resource depletion, necessitating the exploration of alternative energy sources and desalination techniques. While thermoelectric generators are capable of converting low-temperature thermal energy into electricity and desalination processes that can utilize low-temperature thermal energy, their effective integration remains largely unexplored. Currently available hybrid power and water systems, such as those combining conventional heat engine cycles (e.g., the Rankine and Kalina cycles) with reverse osmosis, multi-effect distillation, and humidification–dehumidification, are limited in effectively utilizing low-grade thermal energy for simultaneous power generation and desalination, while solid-state heat-to-work conversion technology, such as thermoelectric generators, have low heat-to-work conversion efficiency. This paper identifies a key research gap in the limited effective integration of thermoelectric generators and desalination, despite their complementary characteristics. The study highlights the potential of hybrid systems, which leverage low-grade thermal energy for simultaneous power generation and desalination. The review also explores emerging material innovations in high figure of merit thermoelectric materials and advanced MD membranes, which could significantly enhance system performance. Furthermore, hybrid power–desalination systems incorporating thermoelectric generators with concentrated photovoltaic cells, solar thermal collectors, geothermal energy, and organic Rankine cycles (ORCs) are examined to highlight their potential for sustainable energy and water production. The findings underscore the importance of optimizing material properties, system configurations, and operating conditions to maximize efficiency and output while reducing economic and environmental costs. Full article