Geothermal Energy最新文献

Efficient and sustainable exploitation of geothermal energy depends critically on accurate characterization of reservoir permeability, which governs subsurface fluid flow and thermal performance. While well testing and core analysis remain essential for establishing ground-truth permeability, these methods can be costly and limited in spatial resolution, making it challenging to fully capture the fine-scale heterogeneity and fracture complexity characteristic of geothermal formations. Moreover, standard Nuclear Magnetic Resonance (NMR)-based permeability models, while widely used in hydrocarbon reservoirs, tend to underperform under geothermal conditions due to elevated temperatures and high fluid salinity. To address these challenges, this study proposes a novel data-driven framework for predicting absolute permeability in geothermal rocks using NMR laboratory measurements and advanced machine learning algorithms. A curated dataset of 72 core samples from the GBD4 geothermal well (Catinat M et al. in Geothermics 111:102707, 2023) was used, incorporating porosity, lithology, the logarithmic mean relaxation time (T2lm), and the mode of the relaxation time distribution (T2mode) as input features. Eight models were developed: Decision Trees, AdaBoost, K-Nearest Neighbor (KNN), Multilayer Perceptron (MLP), Ensemble Learning, Convolutional Neural Network (CNN), Support Vector Regression (SVR), and Random Forest. Outlier detection was performed using the Leverage method, and model robustness was validated via K-fold cross-validation. Among all models, MLP-ANN achieved the highest predictive accuracy with a test R² of 0.943 and a test RMSE of 68.52. Importantly, this study differs from prior NMR–ML permeability models by explicitly validating performance under geothermal temperature–salinity conditions. The results demonstrate that porosity is the most influential predictor of permeability, as confirmed by both Pearson correlation and SHAP analysis. This study integrates empirical core analysis with computational modeling, delivering a scalable and economical substitute for conventional laboratory techniques while propelling advancements in intelligent petrophysical characterization.

Geothermal field development requires decisions about data acquisition and the selection of an optimal development scenario (DS) under uncertainty. Effective planning must address two distinct types of risk: systematic risk, which affects the broader market, and unsystematic (idiosyncratic) risk, which is asset-specific. The inherent complexity of these decisions often leads to prolonged appraisal phases and suboptimal outcomes—particularly when it comes to incorporating risk into planning. This study applies decision-theoretic agents to assess the impact of explicitly incorporating both systematic and unsystematic risk into the development of low-enthalpy geothermal projects. We explore common practices, such as embedding unsystematic risk into discount rates—evaluating three rates: 7% (cost of capital), 10% (3% risk premium), and 13% (6% risk premium)—to examine their influence on project economics, data acquisition strategies, and DS selection. Our results show that including unsystematic risk in discount rates significantly reduces Expected Monetary Value (EMV), increases exploration costs, and impairs the ability to choose the most appropriate DS or to walk away when warranted. Crucially, this approach fails to meaningfully reduce expected losses. To overcome these limitations, we propose a more robust framework that integrates physical numerical models with probabilistic economic evaluations. This approach enables more accurate handling of both systematic and unsystematic risks, leading to better-informed decisions in geothermal field development.

Ground heat collectors represent shallow geothermal devices that are buried in the upper metres of the ground with strong thermal coupling to ground surface. Therefore, during seasonal operation, heat extraction in winter can cause temporal freezing of the soil surrounding the collector. The transient latent heat transfer during freezing and thawing can be crucial for the performance of a collector, and it adds complexity to the model-based representation of the devices. Here, a novel analytical model is presented that accounts for these processes and simulates the evolution of thermal ground conditions during operation of different collector variants. It combines heat source-based solutions with thermal power balancing depending on a given collector geometry and temporal superposition for varying heat loads. By comparison with high-resolution numerical model results, the obtained fast analytical predictions represent the thermal regime around horizontal pipe installations and vertical planar trench collectors within seconds very well, achieving temperature deviations of less than 1.4 K and accuracies over 85.6% for predicting of the thickness of the frozen ground. This regime is inspected in particular with respect to collector wall temperature and the maximum horizontal extension of the frozen soil. The findings demonstrate the suitability of the new model framework to be used in the planning and design phase for optimal layout of collectors, as well for straightforward representation of complex freezing and thawing processes during operation.Please check and confirm that the authors and their respective affiliations have been correctly identified and amend if necessary.The affiliations are correctly. My lastname is corrected.Please check and confirm whether the city has been correctly identified in Affiliation 1.The City has been adapted as there is more than one City called Biberach in Germany.

One solution for reducing the scaling risk of lead (Pb)-containing phases consists of removing the aqueous Pb²⁺ ions from the brine by sorption before oversaturation at unwanted locations within the geothermal fluid loop. Hence, this study investigated the known capacity of fungal biomass to biosorb Pb²⁺ ions to remove Pb²⁺ from the brine. So far, biosorption studies have neither been done at high temperatures or salinity, nor under high pressure, three conditions that must be considered within geothermal power plants. Thus, the overall goal of this study was to assess the Pb²⁺ biosorption potential of dead biomass of the fungus Penicillium citrinum strain HEK1 under conditions mimicking those of natural highly saline geothermal fluids. This specific strain was isolated from geothermal brine circulating in a plant in which Pb²⁺ scaling occurs. To assess biosorption, dead biomass of P. citrinum was added to synthetic solutions containing 260 g/L NaCl, 1 g/L Pb, and (in half of the treatments) 60 mg/L acetic acid. These synthetic solutions, including the dead biomass, were then incubated at high pressure (8 bar), at different temperatures (25 °C, 60 °C, 98 °C), and for different time intervals (1 h, 2 h, 3 h). Results showed that the structure of the biomass was stable in such conditions, at all temperatures tested, but small amounts of organic compounds, with a wide variety of low molecular weight (< 350 Da to 10,000 Da) were released into the fluids from the biomass. In general, increased temperature resulted in an increase in dissolved organic carbon (DOC) concentration. The biosorption potential of P. citrinum HEK1 biomass was overall low (0.72% of total Pb²⁺). While it was not affected by changes in temperature, time of exposure or by the presence of organic acids within the fluids, salinity showed to be influential as biosorption increased to up to 19.22% of Pb²⁺ removal in non-saline conditions. Therefore, the high salinity of the fluids was the factor limiting biosorption to the highest extent, highlighting that working with highly saline geothermal fluids might be limiting for biosorption processes to happen efficiently.

Ancient crystalline basement cratons are traditionally considered challenging geothermal targets due to their low heat flow, limited porosity, and low matrix permeability. However, fractured and hydrothermally altered crystalline basement rocks can exhibit substantial permeability and fluid storage capacity, making them viable unconventional geothermal prospects. This study examines the brittle deformation processes of the Vehmaa Batholith, a Proterozoic rapakivi intrusion emplaced in Southern Finland, and has implications for geothermal exploration in stable cratonic regions. It evaluates the batholith’s potential to host kilometer-scale geothermal reservoirs and offers insights for exploring geothermal resources in crystalline rocks affected by faulting and hydrothermal alteration. Detailed structural mapping, drone photogrammetry, remote sensing, and paleostress analysis reveal two principal ENE–WSW and NNW–SSE strike-slip fault systems transecting the batholith, interpreted to result from distinct Mesoproterozoic tectonic events. These faults generated extensive fracture networks that align with regional lineaments traceable for ~10–25 km, with scaling relationships indicating damage zones ~100–250 m wide. These fracture networks also exhibit high connectivity, with topological relationship values well exceeding the threshold for continuous fluid pathways, and are typically associated with intense hydrothermal alteration, including chloritization, sericitization, and dissolution-related porosity. The spatial association between brittle structures and hydrothermal alteration supports a model where fluid circulation is controlled by post-magmatic faults, which significantly enhance reservoir properties in crystalline rocks. This has direct implications for geothermal exploration in cratonic regions, where such structures may compensate for otherwise poor hydraulic conditions and enhance advective heat flow. Based on structural criteria, we define five major fault-controlled geothermal targets within the Vehmaa Batholith, representing new exploration opportunities in crystalline basement. Our findings provide the first systematic evidence of large-scale fracture connectivity and reservoir development in rapakivi granites and contribute to broader strategies for identifying geothermal resources in stable continental crust.

This study evaluates the geothermal potential of the Akiri Hot Spring (AHS) region, Middle Benue Trough (MBT), Nigeria, using airborne magnetic data. Advanced geophysical processing techniques were employed to analyze the subsurface structures and identify geothermal reservoirs of the region by revealing the fault zones, delineating the lithological variations, and mapping the structural discontinuities critical for assessing thermal energy prospects zones of the region. Qualitatively, the magnetic anomaly map reveals lithological variation with magnetic intensity values ranging − 31.4–117.3 nT. Low magnetic intensity values (< 23.7 nT) were found around the AHS region, while high-intensity values (> 78.2 nT) found in the north and eastern regions. Low Analytic Signal (AS) values (< 0.001 nT/m) were observed around the Akiri region, and they were linked to the alluvial sandstones of the Pliocene age, whereas higher AS values (> 0.007 nT/m) are revealed in the southeastern regions of the research area and it is an indicative of intrusive rock bodies. Quantitative investigation using spectral analysis reveals depth to top (left( {d_{{{text{top}}}} } right)) and depth to centroid (left( {d_{c} } right)) (ranging from 0.587 ± 0.015 to 1.106 ± 0.038 km and 4.830 ± 0.048–6.150 ± 0.044, respectively). The calculated Curie point depth (left( {d_{{{text{CP}}}} } right)) and heat flow ranges from 8.559 ± 0.046 to 11.380 ± 0.059 km and 124.700–129.6 mW/m², respectively. A three-dimensional model integrating (d_{{{text{top}}}}) and (d_{{{text{CP}}}}) highlights a heat flow depression in the vicinity of AHS, where (d_{{{text{CP}}}}) has an average depth of approximately 10.2 km. High heat flow values in the AHS region indicate significant geothermal energy potential, possibly linked to magmatic activity, fault zones, or deep-seated thermal anomalies. Euler deconvolution indicates dominant E–W structural trends, with minor NE–SW orientations. Findings highlight substantial geothermal potential, driven by subsurface anomalies and faulting. This study enhances the understanding of geothermal systems in the MBT and provides a framework for exploring similar volcanic regions across Africa.

Biological clogging in injection wells for ground water heat pump (GWHP) systems presents a significant operational challenge. The initial stage of clogging involves bacterial fouling attaching to the screen slots of the well pipes. However, few studies have systematically investigated its proliferation under different coupled conditions of injection water temperatures and horizontal groundwater flows. This study conducted a tank experiment to measure fouling weights on inserted steel plates under various test conditions involving two factors. Untreated groundwater from the bottom was supplied, and groundwater with adjusted temperature and dissolved oxygen from the top was introduced. The mass increase of iron-oxidation biofouling on the slotted steel plates was measured under varying conditions of injection water temperature and flow velocity through the slots. Results showed that higher flow velocities and elevated injection water temperatures increased biofouling mass. Specifically, the mass increased by up to 1.6 times due to differences in flow velocity and by up to 2.7 times due to differences in injection temperature. These results indicate that iron-oxidizing bacteria are activated by rising injection temperatures, as corroborated by previous studies, and that faster flow velocities provide a greater supply of substrates in the groundwater. Finally, the relationship between biofouling mass and injection temperatures was analyzed using an Arrhenius plot. This analysis yielded apparent activation energy values of 62.6 kJ/mol at a flow velocity of 1 m/d and 54.5 kJ/mol at a flow velocity of 0.1 m/d, with respective determination coefficients of 0.94 and 0.95.

This study investigates the thermal performance of closed-loop advanced geothermal systems under the influence of groundwater flow in deep sedimentary formations. By integrating advective heat transport into a 3D numerical model, we evaluate the combined effects of groundwater flow in deep sedimentary aquifers and geothermal heat transport and extraction using U-shaped closed-loop geothermal wells. The model is developed to simulate heat-transfer dynamics, incorporating well design with realistic casing and cement layers, layered geology with associated petrophysical uncertainties, and varying operational conditions. As study area, we selected the Midyan basin in Saudi Arabia, characterized by thick sedimentary formations and an elevated geothermal gradient. The results show that the advective heat transfer, induced by groundwater flow, significantly enhances system efficiency. Improvement in thermal power output increases by up to 27% over a 40-year operational period compared to conduction-only scenarios, particularly if groundwater flow is perpendicular to the lateral section of the wellbore. Sensitivity analysis reveals that geothermal gradient and reservoir depth are the most impactful geological parameters. Operational parameters such as injection rates (10—100 kg/s) and injection temperatures (25—45 °C) can be adjusted to further optimize the system performance, with 30 kg/s identified as the optimal injection rate that balances energy extraction and parasitic pumping losses. Well-design parameters, including diameters (0.114–0.245 m) and lateral length (0.5–3 km), also play a critical role, with longer lateral sections and larger diameters increasing the overall power output. These findings show the potential of U-shaped closed-loop advanced geothermal systems in sedimentary basins with dynamic groundwater flow and provide insights for optimizing geothermal energy systems in similar geological settings.

Geothermal zoning is an important tool for systematizing geological data and assessing resource potential. In Ukraine, geothermal research has been conducted since the mid-twentieth century, but by various institutions using different approaches. The application of a modern classification based on geothermal play types makes it possible to integrate existing results into a unified system aligned with international practice, which will contribute to the further development of geothermal energy. The advantage of this approach lies in the ability to systematize information in the form of geothermal catalogs, which can be supplemented with new data obtained at subsequent stages of research. The classification of geothermal resources by geothermal play types has been applied to the main geological structures of Ukraine, enabling territorial zoning based on geothermal conditions. Six promising regions (structures) have been identified and thoroughly characterized; each assigned a corresponding Moeck index. In addition, new subtypes adapted to the specific geothermal conditions of Ukraine have been proposed. The next stage of research involves zoning based on lower-order structures, assessing their geothermal reserves, and selecting the most promising sites for implementing geothermal energy projects. Particular attention should be paid to clarify the terminology of “resources” and “reserves”: the former is recommended for use in a generalized or qualitative sense, while the latter should denote quantitatively defined characteristics. This approach helps avoid terminological confusion, as the terms themselves clearly reflect the research focus.

Geothermal resources are abundant, widely distributed, and environmentally friendly as a renewable energy source, making their utilization and genesis studies highly significant. In the Tibet's Ali region, geothermal potential is considerable but development is limited. Based on hydrogeochemical data from 15 geothermal sampling sites and 2 cold-water sampling sites, this study analyzes the formation and evolution of regional hot spring waters. Results show that the hot springs are predominantly of the HCO₃–Na type, with other water types, including HCO₃·Cl–Na and HCO₃·SO₄–Na. The hydrochemical composition is controlled by the dissolution of silicate minerals, weathering of evaporites, and cation exchange. Water–rock interactions cause enrichment of trace elements, such as B, I, and Li, and their mobility reflects a complex multiphase recharge system with varied hydrogeodynamic processes using the silica–enthalpy method to estimate the original reservoir temperature ranges from 173.1 to 266.3 °C. As the geothermal fluids ascend, mixing with cold water accounts for 59–93%. The mixed temperatures range from 58.22 to 135.43 °C. Hydrological and geochemical indicators suggest that Zone II exhibits strong system enclosure, long fluid residence time, and slow runoff; Zone III shows moderate enclosure with secondary water–rock interactions; Zone I represents an open circulation with rapid groundwater recharge. This study provides scientific basis and guidance for understanding the genesis of Ali hot spring waters and the sustainable development of regional geothermal resources. However, limitations include a lack of isotopic constraints and insufficient sampling spatial resolution, which should be addressed in future research.