Geothermal Energy最新文献

Over the past decades there has been a significant increase in the direct utilization of geothermal power as a renewable energy resource. Low-enthalpy geothermal systems for direct heat production are commonly developed in sedimentary aquifers with high matrix permeability. Although such geothermal systems are not often associated with induced seismicity, the potential occurrence of induced seismic events is of concern in geothermal resource development and requires improved seismic hazard assessment associated with geothermal operations. Mechanical Analysis of Complex Reservoir for Induced Seismicity (MACRIS) is applied to evaluate the sensitivity for fault reactivation and induced seismicity potential in three-dimensional clastic reservoir models representative of low-enthalpy geothermal exploitation in the Netherlands. The reservoir models are separated by a single fault causing both no and normal reservoir offset, and, unlike previous induced seismicity studies, incorporate the effects of reservoir throw and flow compartmentalization. Results show the potential for fault reactivation and induced seismicity to be (i) substantially impacted by the three-dimensional interaction of injected cold-water volume and its destabilizing effect on complex faults in sedimentary aquifers, and (ii) characterized by moderately low seismic magnitudes for the majority of predicted events. Where reservoir throw is shown to contribute to the fault reactivation and seismicity potential, fault-related reservoir flow compartmentalization has an opposite effect and is shown to reduce the potential of a sealing or bounding fault. Results confirm the findings from previous studies by showing (i) a predominant sensitivity of induced seismicity potential to the thermo-elastic reservoir parameters and injection temperature, and the in situ stress conditions and fault frictional properties affecting slip length and resulting magnitude estimate of the seismic event. In particular, results show the seismic hazard potential to significantly decrease in the case of reservoir creep or stable in situ stress conditions, and by limiting reservoir thermal drawdown.

The single-well enhanced geothermal system (SEGS) is an innovative approach designed to overcome the limitations of traditional deep borehole heat exchangers (DBHEs). It achieves this by modifying the well structure and circulating working fluid through an engineered reservoir to enhance heat transfer. This study presents a laboratory-scale experimental investigation of a SEGS analog to identify key performance determinants. The research explores the impacts of injection flow rate, injection temperature, and the initial temperature of the sandbox on the system’s thermal performance and temperature distribution into the sandbox. A series of experiments were conducted under different conditions, and the results were analyzed to determine the optimal operating parameters for maximizing heat extraction while minimizing temperature decay. The study also investigates the influence of injection–production spacing on the thermal breakthrough and the overall efficiency of the SEGS. Based on the observed trade-offs within the tested range, a flow rate of 0.4 m³/h, an injection temperature of 31 °C, and a spacing of 120 cm provided the best compromise between high heat extraction rate and stable production temperature. These findings provide foundational insights into SEGS thermal behavior and a basis for optimizing system design, supporting the development of sustainable geothermal energy solutions.

Accurate assessment of geothermal resources potential is of vital importance for promoting the rational development and utilization of geothermal resources. This study aims to systematically explore the collaborative application of various methods for evaluating the potential of geothermal resources, providing more effective evaluation tools for the development of deep geothermal resources. The Xixian Campus of Xi’an Jiaotong University, which is located in the central area of the Guanzhong Basin in Northwest China, is taken as the case study area. The volumetric method and the Monte Carlo method are combined to evaluate the geothermal resource potential for heating/cooling, and hydro-thermal coupling simulation is conducted to investigate the flow field and temperature field responses of geothermal reservoirs under production and reinjection. Results show that the best estimated technical potential of geothermal resources in Xixian Campus is 191.19 × 10¹⁵ J (equivalent to 6.66 million tons of coal equivalent), sufficient to support heating and cooling demands for at least 51 years. The technical potential per unit area is 38.24 × 10¹⁵ J·km⁻². Besides, the technical potential of geothermal resources in the Sanmen Formation, the Zhangjiapo Formation, the Lantian-Bahe Formation, the Gaoling Group, and the Bailuyuan Formation constitute 4.12%, 8.85%, 22.99%, 30.92%, and 33.12% of the total technical potential, respectively. Modeling results indicate that the geothermal reservoirs of the Lantian-Bahe Formation are the most suitable for economic geothermal resource development. The implementation of this work can provide data support for the plans of geothermal resource development and utilization.

The Cooper and Eromanga Basins of Australia, with old and hot basement rocks, offer promise for geothermal exploration. The basement rock radioactive decay has high radiogenic heat production exceeding 5 microwatts per cubic meter. The basement structure transitions from the 3.6 km deep Patchawarra Trough in the west with 3–4 μW/m3 radiogenic heat production to the 4.7 km deep Nappamerri Trough having 5–7 μW/m3 radiogenic heat production in the east (Beardsmore in Explor Geophys 35(4):223–35, 2004). This study integrates petrophysical analysis, seismic interpretation, and thermal energy assessment to evaluate the geothermal viability and prospectivity in the Hutton Sandstone formation of the Eromanga Basin in the vicinity of an unsuccessful geothermal well. The Hutton Sandstone is a potential geothermal aquifer where it contains temperatures exceeding 120 °C, high thermal conductivity of 5 W/mK (Beardsmore in Explor Geophys 35(4):223–35, 2004), net sand thickness over 60 m, and effective porosities > 10%. The 120 ºC isotherm occurs in several areas downslope of gas fields along the Warra–Merrimelia NE–SW ridge system. The highest Hutton net sand thickness (~ 50 m) and porosity thickness (~ 30) occur near the Gashnitz-001 well, where there are good reservoir characteristics and high thermal energy. Seismic interpretation indicates probable lateral reservoir continuity up to 11 km east of the well. A prospective area of 100–683 km² is interpreted as having over 50 m net sand in the Hutton with over 16% average effective porosity and temperatures exceeding 120 °C. The in-place potential thermal energy is as high as 245 MWth with a mean of 164 MWth. The Gashnitz-001 well drilled outside of structural closure benefited from high total heat content and less geological risk in terms of porosity thickness in the Hutton formation.

Urban aquifers are influenced by several natural and anthropogenic factors, such as geological and hydrogeological conditions and built infrastructure, such as heated basements, underground car parks, and train tunnels. Realistic 3D city-scale physics-based models of complex and heterogeneous aquifers must balance accuracy and efficiency to support scenario-based subsurface management. Hence, this study aims to provide an overview of the 3D thermal state of the urban subsurface of Berlin, Germany, with the goal of identifying groundwater and geothermal archetypes. Based on a detailed 3D geological model, covering an area of 118 km² and a depth of 250 m, block-divided (500 m × 500 m × 50 m), steady-state groundwater flow and heat transport models are created. These block models serve as a basis for identifying groundwater archetypes representing areas with similar hydrogeological and infrastructure conditions. The simulated, large-scale groundwater temperature patterns are generally in good agreement with interpolated temperatures from depth-oriented measurements. In addition, the block-scale models capture thermal hot spots and low spots that are not detected by interpolated maps. Using regression-based decision trees, 38 groundwater archetypes are identified for the shallow anthropogenically influenced layer of blocks and 21 archetypes at deeper layers (> 50 m bgl). Heated basements and groundwater head difference are the most contributing features in differentiating archetypes for the shallow layer of the blocks, while lower temperature boundary dominates selection of archetypes in deeper layers. Similarity of large-scale groundwater temperature patterns across different numbers of selected archetypes shows the robustness of the approach. Using thermal and geological criteria, 10 of the identified archetypes are classified as geothermal archetypes that indicate suitable conditions for ground source heat pump systems. The archetypes approach could be further developed to support other groundwater and subsurface uses, e.g., by considering groundwater-dependent ecosystems, legal aspects (e.g., groundwater contamination), and the interactions between different uses.

The northwest Ethiopian plateau (NWEP) has thick flood basalts from the Eocene–Miocene Trap provinces. While previous studies have established the Ethiopian Rift Valley as a region of significant geothermal potential, the NWEP has remained largely unexplored in this regard. This study aims to estimate the Curie point depth, heat flow, and geothermal gradient in the NWEP, through spectral analysis of magnetic data in the NWEP, covering the region between 9.8 and 14.1°N latitude and 36–39.64°E longitude. The magnetic anomaly map was processed using Reduction to the Pole (RTP) filter to generate the RTP corrected magnetic map of the study area. This map was subsequently partitioned into twenty four overlapping blocks, of which each one was analyzed by means of spectral methods. The estimated Curie point depths range from 14 to 75 km, while the geothermal gradient varies between 8 and 38 °C/km, with corresponding heat flow values ranging from 19 to 94 mW/m². The localities of Metema, Kora, Amanuel, Wukro, Wanzaye, Tsi Abay, Arb Gebeya, Dogolo, Alem Ketema, and Anchekorer exhibit Curie point depths (CPD) of less than 20 km. These regions exhibit high heat flow, elevated geothermal gradient, and shallow CPD, all of which indicate substantial geothermal potential. The findings contribute to a better understanding of the crustal thermal structure of the NWEP.

The interplay between geothermal technologies, risk perception, social acceptability and acceptance is critical in the context of geothermal energy projects. Induced seismicity is of particular concern to citizens, and the perception of seismic risk plays an important role in the acceptability of geothermal projects. Starting point for our considerations is the DeepStor research infrastructure project and observations made within this research environment. We establish a conceptual framework for participatory monitoring of seismicity in geothermal projects and explore its possible influence on socio-psychological factors related to risk perception and technology acceptability and acceptance. The participatory monitoring is based on a citizen science approach in which citizens are invited to actively participate in seismic measurements around a geothermal project using plug-and-play seismometers. The potential individual, societal and scientific implications of this approach are analyzed by introducing established participatory and social scientific concepts within the geothermal context. Our conceptual analysis suggests that participatory monitoring could effectively address seismic risk perception and acceptability by enhancing transparency, providing non-experts with first-hand experiences, and fostering discussions and informed decision-making. From a technical perspective, implementing this approach to create dense seismic networks enhances the evidence base in research projects and supports more balanced risk management strategies. This article lays the conceptual groundwork for combining social scientific and geophysical approaches and recommends citizen science demonstration projects accompanied by social scientific research to evaluate this approach. As case example, the planned implementation of the participatory monitoring approach within the DeepStor project is presented. Our findings aim to contribute to the ongoing discourse on sustainable energy transition, risk management and governance, and the role of public participation in geothermal energy development.

High-temperature aquifer thermal energy storage (HT-ATES) can play a key role in the energy transition. For well completion of conventional low-temperature ATES and groundwater wells, grout and/or clay pellets are typically utilised as annular materials to ensure the long-term well integrity. It is not yet known if such materials can also be used in HT-ATES working conditions. In this work, a novel approach to evaluate the sealing performance for such completion materials is proposed and tested over multiple thermal heating and cooling cycles representative of the conditions of HT-ATES operation. The experimental framework utilises a novel experimental design to test the apparent transmissivity of the annular material, followed by micro-CT scanning. During each test, up to 11 thermal cycles are applied, with temperature variations between 22(^o)C and 90(^o)C. For grouts after 7 days of curing, micro-CT scans reveal debonding and the occurrence of micro-annuli with an equivalent diameter of approximately 26% of the original cross-section. After 28 days of curing, the thermal cycles had a much reduced impact on micro-annulus formation. The corresponding apparent transmissivity decreased up to 80% for samples containing a high percentage of cementitious minerals and a low water-to-grout ratio. The clay pellets, saturated with fresh water, demonstrated effective sealing capacity and an impermeable behaviour. However, clay pellets saturated with 0.25 mol/L NaCl, showed up to an 85% decrease in swelling capacity yet still exhibited impermeable behaviour. The results indicated that thermal cycles affect the integrity of grouts, while clay pellets show resilience to them. Furthermore, longer curing periods and specific chemical compositions improve sealing performance and provide resilience to thermal cycles.

This study evaluates the CO₂ sequestration capability of the Tuzla Geothermal Field (TGF) in northwest Türkiye under reservoir conditions (200 °C and 4.4 MPa). While ongoing studies at TGF have investigated CO₂ co-injection primarily for geothermal heat extraction, the present study focuses on the associated potential for long-term CO₂ storage. To this end, CO₂–brine–rock interactions were examined through batch reactor experiments and reaction path modeling using the PhreeqC geochemical tool. The experiments revealed complex dissolution/precipitation reactions that altered reservoir properties, with mineralogical analyses (XRD, XRF, SEM, and EDS) showing the formation of secondary phases such as calcite, kaolinite, and Ca-rich aluminosilicates. These results indicate that the Tuzla reservoir rocks provide sufficient divalent cations to support mineral trapping under reservoir conditions. Overall, our findings highlight that, in addition to its promise for heat extraction, CO₂ co-injection at TGF offers an opportunity for permanent geological storage, thereby strengthening the dual benefits of this approach.

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.