Geothermal Resource Assessment Research Articles

Record of a pioneering geothermal borehole in London

This paper records the results of a pioneering exploration borehole drilled in 1984 to a depth of 403.84 m in the London Basin and underlying London–Brabant basement high. The key objectives of the project were to measure the equilibrium temperature in the Paleozoic basement, estimate the temperature gradient after climate impact corrections and assess the heat flow in the area. From this, estimates of temperature at depths of 2000 m could be made with a view to evaluating potential geothermal resources. From the downhole measurements, a temperature gradient of 16°C km −1 was estimated with a temperature range between 46°C and 51°C at a depth of 2000 m, considered to be consistent with other UK sites where there is no contribution from high heat production granites. The results of the Thamesmead exploration borehole suggested that the geothermal potential of the Devonian and the Paleozoic basement below London is poor, and no further work was carried out. The work has remained unpublished until now but in view of the current renewed interest in geothermal resources it is appropriate to make the work public. Although the results were not encouraging, they do remain as a contribution to the revitalized assessment of geothermal resources in the London area and the UK in general.

Exploring Medium and Low-Temperature Convective Geothermal Resources Through Controlled Source Audio Magnetotelluric Mothod

Medium and low-temperature convective geothermal resources are a crucial component of China's geothermal wealth, primarily concentrated in the eastern coastal regions. To maximize the utilization of these resources, geophysical surveys are essential, with controlled source audio magnetotelluric(CSAMT) being a prominent and effective method employed in geothermal resource assessments. This study focuses on applying CSAMT to survey specific geothermal sites, including the Xiu Yan Gou Tang Hot Spring, Fengcheng Gou Tang Hot Spring, and Hai Cheng Xi Huang di Geothermal Field. The results obtained through this method provide detailed insights into the distribution of both deep and shallow thermal storage spaces within these fields, shedding light on the intricate thermal circulation systems associated with them. These findings serve as a reliable foundation for planning and executing further geothermal resource development projects. CSAMT emerges as a comprehensive tool for understanding the nuances of medium and low-temperature convective geothermal resources.

Dynamic geothermal resource assessment: Integrating reservoir simulation and Gaussian Kernel Density Estimation under geological uncertainties

This paper presents a dynamic geothermal resource assessment method that integrates reservoir simulation and Gaussian kernel density estimation (KDE). This approach addresses geological uncertainties by employing reservoir simulation techniques to model the fluid and heat flow under the condition of permeability heterogeneity. Incorporating probabilistic resource assessment through Gaussian KDE, the study quantifies uncertainties, estimating the probability density function (PDF) of ensemble results under conditions like thermal breakthrough thresholds, fixed reservoir lifespans, and target energy production. The demonstrations of assessment start with a simple homogeneous model. The results show that larger doublet well distances result in extended lifespan, higher final production well temperatures, and increased energy production. Brugge reservoir emphasizes the impact of heterogeneity and uncertainty on production outcomes, especially at smaller doublet well distances. Assessment of fluvial Egg model reveals that drilling in fluvial channels causes rapid thermal breakthrough. This result indicates that, to optimize reservoir performance, it is recommended to refrain from drilling doublet wells within high-permeability fluvial channels. Furthermore, it is worthy of mention that the Gaussian kernel is not always favored for KDE, particularly in scenarios involving non-Gaussian distribution ensembles. The proposed method, which integrates reservoir simulation and Gaussian KDE, enhances understanding of geological uncertainties and the intricate nature of geothermal reservoirs, facilitating more reliable and accurate resource assessments.

Exploring Medium and Low-Temperature Convective Geothermal Resources in Eastern China Through Acoustic-Emission Geomagnetic Bathymetry

Medium and low-temperature convective geothermal resources are a crucial component of China's geothermal wealth, primarily concentrated in the eastern coastal regions. To maximize the utilization of these resources, geophysical surveys are essential, with acoustic-emission geomagnetic bathymetry being a prominent and effective method employed in geothermal resource assessments. This study focuses on applying acoustic-emission geodetic bathymetry to survey specific geothermal sites, including the Xiu Yan Gou Tang Hot Spring, Fengcheng Gou Tang Hot Spring, and Hai Cheng Xi Huang di Geothermal Field. The results obtained through this method provide detailed insights into the distribution of both deep and shallow thermal storage spaces within these fields, shedding light on the intricate thermal circulation systems associated with them. These findings serve as a reliable foundation for planning and executing further geothermal resource development projects. Acoustic-emission geomagnetic bathymetry emerges as a comprehensive tool for understanding the nuances of medium and low-temperature convective geothermal resources.

Numerical simulation of hydrothermal flow in the North China Plain: A case study of Henan Province

The distribution and flow of geothermal energy in the North China region are influenced by geological structures and rock thermal properties. However, the interactions between geothermal energy, groundwater movement, and hydrogeochemical processes are not well understood. In this study, a numerical model was developed to simulate these interactions under different geological conditions. The results showed that the stress field of geological structures affects the flow path and velocity distribution of geothermal fluid, leading to distortion and uneven temperature distribution. The distribution of high-mineralized zones of geothermal water indicated the main recharge area in the northern part of the North China Basin (Henan). Hydrochemistry analysis revealed a dynamic balance between centrifugal and centripetal flows in sandstone geothermal water. The study provides important insights for the exploration and development of underground geothermal water, as well as the assessment and optimization of geothermal resources in large basins.

Development of an Improved Decision Support Tool for Geothermal Site Selection in Nigeria Based on Comprehensive Criteria

Geothermal resource assessment is crucial for the rural electrification of Nigeria. A comprehensive set of criteria was used to appraise promising geothermal sites in Nigeria. The evaluation of the sites was performed using the multi-criteria decision analysis (MCDA) method and taking into account evidence of a wide range of criteria from a set of geological, geophysical, well log, environmental, remote sensing, and geochemical datasets to appraise promising geothermal sites and to add to the current debate on the needed criteria for geothermal development. To gather relevant data, various sources such as bottom-hole temperature (BHT) data from different boreholes and oil and gas wells, aeromagnetic maps, reduced-to-the-pole, magnetic, heat flow, seismic, and geothermal gradient data from aerogravity maps, Bouguer anomaly maps, earthquake epicenter maps, satellite images, and geological maps were obtained from the literature. A case study of the thirty-six states of Nigeria, including the federal capital territory, Abuja (FCT), was conducted to illustrate how these criteria would reveal the technical aspect of the geothermal energy situation. A model was developed to show that the application of a wide range of criteria to the six datasets identified and analyzed in this study reveals that the datasets complement each other and should not be used independently. It can be found from the overall suitability map that more than 20% of the study area is suitable for geothermal energy development. It can also be observed from the map that some of the promising sites in Nigeria may include but are not limited to Bauchi, FCT, Taraba, Ebonyi, Adamawa, Oyo, and Nasarawa states in Nigeria. The opportunities for the further application of the approach are discussed, including the use of the model to help policymakers decide where to invest in the future.

Electromagnetic prediction of rock thermal properties beyond boreholes: Soultz-sous-Forets (France) case study

Estimation of deep temperature, thermo-hydro-dynamic and basin simulation, heat exchange and geothermal resource assessment require knowledge of the rock thermal properties beyond boreholes. At the absence of suitable methods and instruments for such estimates we propose a new approach to prediction of thermal conductivity, specific heat capacity and heat flow density based on results of electromagnetic sounding of the study area. Artificial neural network used to this end is taught by correspondence between laboratory measurements on cores from the drilled boreholes and adjacent electrical conductivity profiles determined by inversion of the electromagnetic sounding data collected in their vicinity. This approach is used to estimate rock thermal properties along NW-SE magnetotelluric profile crossing Soultz-sous-Forêts geothermal area, Alsace, France. We demonstrate that accuracy of such prediction both in depths below the boreholes and in the interwell space is comparable with that usually achievable in the borehole scale. In particular, it is shown that relative errors of thermal conductivity prediction at depths twice as large as the borehole depth are as small as 2%, and the accuracy of cross-well thermal conductivity prediction is 6% and 10% for dry and wet rocks, respectively. On the other hand, the prediction accuracy for matrix thermal conductivity of a rock from the known profile of dry thermal conductivity is about 8%. Based on the results of our studies, we constructed dry and wet thermal conductivity sections from the electrical conductivity model determined earlier by 2-D inversion of magnetotelluric data. The temperature model of the study area built along the same profile by means of electromagnetic geothermometer and the obtained thermal conductivity sections enabled estimating the profiles of the vertical component of heat flow density at the surface from dry and wet thermal conductivity sections. They could be considered as minimum and maximum constraints, respectively, bounding the area of its possible values, which, in turn, depend on in situ thermal conductivity of fluids filling the rock pores. The range of possible vertical heat flow density variations (100–150 ± 10% mW·m− 2) agrees well with heat flow estimates in the Upper Rhine graben and, in particular, in Soultz-sous-Forêts geothermal area roughly estimated earlier from borehole measurements. Using the artificial neural network trained on the correspondence between the specific heat capacity determined in the borehole and adjacent electrical conductivity profile, we built the model of specific heat capacity. Against the background, a zone of enhanced specific heat capacity ranging between 2.05 and 2.15 MJ·m− 3·K− 1 was observed in the domain located at the base of the sedimentary cover and upper part of the granitic basement.

Assessment of thermal water and energy recoverable rate based on express method: A case study of Reshuiwei geothermal field

Assessment of geothermal resources is the vital and difficult work during geothermal resources utilization. The aims of this study are to: (1) estimate the natural thermal water discharge and the mass flow rates of recoverable thermal water in boreholes by using “express method”. (2) evaluate the geothermal water and energy resources through estimating the convective heat and mass discharge/deep recharge of this geothermal field based on the calculation results. Results show that this geothermal field should be divided into three sections to calculate hot water resources: Reshuiwei section, Miaowan section and Dongqingshu downward section. Main controlling fault zones are F3, F6 and F7 fault zones, respectively. The total reached mass flow rates of recoverable thermal water are 49.32 kg/s. Reshuiwei section is a suitable area for underground hot water comprehensive utilization. The reached recoverable heat rates are 15.031 MW. In addition, the reservoir temperature potential of Reshuiwei geothermal field would be about 182.95 °C, the conceptual model of this geothermal field formation is summarized. Conclusions drawn from this study would provide reference for geothermal resources assessment of all geothermal fields.

Probabilistic Geothermal resources assessment using machine learning: Bayesian correction framework based on Gaussian process regression

Accurate determination of geothermal resources in the study area is of great importance for effective exploration and development. In the present study, geothermal resources in Qianguo County, Jilin Province, China, were selected as the research object, and we used the random forest sensitivity analysis method to determine the five most influential parameters among the nine parameters involved in the volumetric method: geothermal reservoir thickness (H), geothermal reservoir temperature (T), geothermal reservoir area (A), thickness porosity (Φ), and rock density (ρw). Among them, the uncertain parameters H and T show a significant positive effect on the output results. These parameters and geothermal resources estimated by volumetric method based on Monte Carlo were used as input parameters in the Gaussian process simulation, and the squared exponent (SE) with fewer hyperparameters was selected as the Gaussian process regression kernel function. During the analysis, six groups of different hyperparameter combinations were set, and the Earth Mover's distances (EMD) was applied to compare the priori distribution and simulation results with the posterior distribution (true distribution). The simulation results that are closest to the target distribution of geothermal resources were used as the final results of geothermal resources calculation. Based on the obtained results, it was concluded that the Qingshankou and Quantou formations located in the southern Changling sag have good geothermal development potential which the geothermal resources are 5.80 × 1010 kJ·km−2 and 6.22 × 1010 kJ·km−2, and the probability of occurrence is 4.65%, and 3.69%.

Geothermal Resources of European Continent: A Regional Assessment

A regional assessment of geothermal resources of the continental region of Europe is attempted in the present work. It is based on results of observational data on heat transfer by conduction as well as hydrothermal and magmatic processes in the upper crust and makes use of geothermal data reported at the website of IHFC and also estimates based on available information on occurrences thermal springs and volcanic events. The resource assessment has been carried out for 8109 sites distributed in 39 countries. These datasets were reevaluated and spatially gridded using kigrid interpolation to construction of regional distribution maps of geothermal resources and interpreted on the basis of available information on tectonic setting and geological characteristics. The estimates for volcanic areas are based on a modified method of magmatic heat budget (MHB). has been employed in deriving estimates of geothermal resources in areas of recent volcanic activity. According to results obtained the total resource base (RB) at 6km on depth is estimated to be 8.653.306 ± 7 GJ. The mean resource base per unit area (RBUA) is ~ 985 GJ. The prominent features in geothermal maps are the presence of localities with significantly high values of resource base greater than 2000 GJ in countries such as Russia, Italy, Iceland, and west Norway. In addition, vertical distributions of temperatures were calculated in for depths reaching down to 6 km. The results obtained indicate potential availability of high temperature resources in vast regions of the European continent.

Machine Learning for Geothermal Resource Exploration in the Tularosa Basin, New Mexico

Geothermal energy is considered an essential renewable resource to generate flexible electricity. Geothermal resource assessments conducted by the U.S. Geological Survey showed that the southwestern basins in the U.S. have a significant geothermal potential for meeting domestic electricity demand. Within these southwestern basins, play fairway analysis (PFA), funded by the U.S. Department of Energy’s (DOE) Geothermal Technologies Office, identified that the Tularosa Basin in New Mexico has significant geothermal potential. This short communication paper presents a machine learning (ML) methodology for curating and analyzing the PFA data from the DOE’s geothermal data repository. The proposed approach to identify potential geothermal sites in the Tularosa Basin is based on an unsupervised ML method called non-negative matrix factorization with custom k-means clustering. This methodology is available in our open-source ML framework, GeoThermalCloud (GTC). Using this GTC framework, we discover prospective geothermal locations and find key parameters defining these prospects. Our ML analysis found that these prospects are consistent with the existing Tularosa Basin’s PFA studies. This instills confidence in our GTC framework to accelerate geothermal exploration and resource development, which is generally time-consuming.

Hululais Field Review from Geoscientific Exploration to Exploitation Stage

Geothermal studies in Hululais carried out by Pertamina was started in 1993 with an exploration survey. The detailed geological mapping as the earliest geothermal resource assessment of Hululais was done internally by Pertamina. The geochemical study was done together with the geological study. The geophysical study was carried out using three methods. The gravity survey was run in 1993 for 320 points along 12 trace lines, while the magnetotelluric survey was conducted in 2006 and 2012 for 64 locations with 1-2 km spacing. The microearthquake survey was done in 2012 for 115 days monitoring time by six sensors in 10 km spacing and in 2019. The conceptual model as a product of the integrated study of three geoscientific surveys shows that the upflow zone is interpreted in Suban Agung – Suban Gregok in the southern area. Fumarole, mud pool and steam-heated hot spring are found in this zone. The outflow zone is interpreted towards the north in Semelako area supported by the chloride hot spring. The appearance of these manifestations is possibly controlled by fault structure in Musi Segment zone of Sumatra Fault Zone (SFZ). The heat source comes from granodiorite intrusion below Bukit Beriti Besar – Bukit Gedang Hululais. The cap rock has 500 meters thick in the upflow zone and increases to 800 meters thick towards the outflow zone in the northern part of the study area. The upflow zone was proved by two exploration wells that drilled until 3000 mMD. The first well in Suban Agung has a high temperature reach 300°C with neutral reservoir fluids and good fault structure permeability. The second exploration well that drilled towards outflow zone shows a temperature of 205°C with neutral reservoir fluids but with low permeability. In the exploitation stage, 21 development wells have been drilled for making the update conceptual model. Among them, ten wells are production wells and the remains are reinjection ones. The permeability in the reinjection wells is not so good compared to the production wells. It might be due to secondary mineral filling in the fault structure permeability zone, so this situation causes a problem in injection water to the reservoir. Investigation of the subsurface permeability distribution in the Hululais reservoir is challenging, so further research should be done to answer this challenge.

Geodetic imaging of ground deformation and reservoir parameters at the Yangbajing Geothermal Field, Tibet, China

SUMMARYMonitoring and modeling ground surface deformation are crucial for the dynamic assessment of geothermal resources and sustainable exploitation in a geothermal field. In this study, we extract the deformation in the Yangbajing geothermal field by the small baseline-synthetic aperture radar interferometry (SBAS-InSAR) method using 141 Sentinel-1A images collected between March 2017 and November 2021. The InSAR result indicates both uplift and subsidence in the geothermal field. Subsequently, we use a dual-source model combining a dipping ellipsoid and a rectangular surface to model the shallow reservoir that contracted to cause the complex subsidence field in the north of the geothermal field. The shallow reservoir that expanded to cause the uplift in the south is modeled by an ellipsoid source. The parameters inversion is processed by the nonlinear Bayesian inversion method which has been applied to search the optimal parameters setting in a priori space and evaluate the uncertainties by the confidence intervals. To validate our inversion results, we collect the data from 31 wells including extraction and injection wells, detailed tectonic survey data and geothermal isotherms of the Yangbajing geothermal field. The modeled shallow reservoir in the north is within a 140 °C ground isotherm and a 160 °C underground isotherm. The thickness and depth of the reservoir slightly exceed the data from producing wells, probably due to the structural subsidence of the reservoir. The geometric structure is consistent with the channel faults that control the formation and development of the shallow reservoirs. The modeled reservoir under the rebound area in the south is also validated by comparing the data. Furthermore, we estimate the volume loss and recovery of the contracting and expanding reservoirs. We analyse the deformation mechanisms by considering the tectonic formation, the reservoir structure, and the extraction and rechargeability of the reservoirs. This research suggests the deformation pattern of shallow porous reservoirs that have similar layer composition and tectonic structure elsewhere in the world. Moreover, it provides a theoretical model to explore the parameters and volume change of geothermal reservoirs in plateau-embedded basins around the world. Our work is significant for the conservation and development of geothermal energy in geothermal fields that experience deformation, both subsidence and uplift.

When less is more: How increasing the complexity of machine learning strategies for geothermal energy assessments may not lead toward better estimates

Previous moderate- and high-temperature geothermal resource assessments of the western United States utilized data-driven methods and expert decisions to estimate resource favorability. Although expert decisions can add confidence to the modeling process by ensuring reasonable models are employed, expert decisions also introduce human and, thereby, model bias. This bias can present a source of error that reduces the predictive performance of the models and confidence in the resulting resource estimates.Our study aims to develop robust data-driven methods with the goals of reducing bias and improving predictive ability. We present and compare nine favorability maps for geothermal resources in the western United States using data from the U.S. Geological Survey's 2008 geothermal resource assessment. Two favorability maps are created using the expert decision-dependent methods from the 2008 assessment (i.e., weight-of-evidence and logistic regression). With the same data, we then create six different favorability maps using logistic regression (without underlying expert decisions), XGBoost, and support-vector machines paired with two training strategies. The training strategies are customized to address the inherent challenges of applying machine learning to the geothermal training data, which have no negative examples and severe class imbalance. We also create another favorability map using an artificial neural network.We demonstrate that modern machine learning approaches can improve upon systems built with expert decisions. We also find that XGBoost, a non-linear algorithm, produces greater agreement with the 2008 results than linear logistic regression without expert decisions, because the expert decisions in the 2008 assessment rendered the otherwise linear approaches non-linear despite the fact that the 2008 assessment used only linear methods. The F1 scores for all approaches appear low (F1 score < 0.10), do not improve with increasing model complexity, and, therefore, indicate the fundamental limitations of the input features (i.e., training data). Until improved feature data are incorporated into the assessment process, simple non-linear algorithms (e.g., XGBoost) perform equally well or better than more complex methods (e.g., artificial neural networks) and remain easier to interpret.

Deep geothermal resource assessment of early carboniferous limestones for Central and Southern Great Britain

Early Carboniferous limestones (ECL) host active geothermal systems in Central and Southern Britain. Equivalent rocks have been successfully developed for geothermal energy in Belgium and the Netherlands, but the ECL has yet to be fully assessed as a geothermal resource in Britain. We use established statistical methods to assess the depth, distribution, and geothermal potential of the ECL in Central and Southern Britain. Total heat in place (HIP) resources of 1415 (P10)–1528 (P90) EJ may be present, with a tentative potential recoverable thermal power of 106–222 GW. Further work is needed to understand the resource by identifying areas with sufficient flow rates for successful development such as enhanced permeability zones around faults, fractures or karsts.

Exploratory assessment of geothermal resources in some parts of the Middle Benue Trough of Nigeria using airborne potential field data

Some parts of the Middle Benue Trough (MBT) of Nigeria were evaluated with the aim of detecting prospective geothermal potential regions. Spectral depth analysis using a modified centroid procedure was applied to analyze high-resolution airborne magnetic data. The Curie point depth (CPD) within the study area is in the range of 6.0 and 16 km. It was observed that the Gboko Anticlines (GA) that are interrelated with the Santonian intrusions of Abakaliki Anticlinorium (AA) are characterized by thin CPD (6.0–8.0 km). The mapped geothermal anomalies within the GA with shallow CPD (<8.0 km) are dominated by the high geothermal gradient (GG) (>74 °C/km) and heat flow (HF) (>155 mW/m2) values. The adjoining areas within the study area are defined by medium-deep CPD (8.0–16.0 km), medium–low GG (<74 °C/km), and HF (<155 mW/m2) values. The further integrated geophysical investigation and subsequent exploitation programs should be sited in the delineated GA and adjoining AA

Techno-Economic Assessment of Geothermal Resources in the Variscan Basement of the Northern Upper Rhine Graben

Deep geothermal energy represents an essential component of the future energy supply because the resources greatly exceed the demand, and the base load capability can compensate for temporal fluctuations in wind and solar power. By far, the largest amount of heat is contained in the crystalline basement, accessible almost everywhere through deep drilling. An interdisciplinary approach for a techno-economic resource assessment was applied to provide stakeholders with a more reliable basis for decision-making in the Northern Upper Rhine Graben. This approach incorporated data from various sources such as boreholes, outcrops, geophysical surveys, geomechanical models, and operating geothermal power plants. Emphasis was placed on resources tied to large-scale fault zones, exhibiting preferential hydraulic properties. Uncertainties in the calculations were quantified using Monte Carlo simulations. The resource base in the basement of the Northern Upper Rhine Graben is about 830 PWhth, of which about 8.2–16.1 PWhth could potentially be extracted with current technologies in enhanced geothermal systems. A comprehensive sensitivity analysis was carried out, examining the economic influence of nine parameters. Considering the reference power plant and the energy prices before the Ukraine war began in February 2022, the geothermal reserves are about 65% of the resources. However, given the massive recent increase in heat and electricity prices, a higher percentage is also possible. Finally, a socio-economic-environmental assessment shows that in the Northern Upper Rhine Graben, geothermal resources largely coincide with favorable conditions at the surface, making the region a preferred target for geothermal utilization.

A robust assessment method of recoverable geothermal energy considering optimal development parameters

It is known that development parameters such as injection and production rate, injection temperature, and well location and spacing play an important role in determining the recoverable geothermal energy in a licensed region during the exploitation stage, but they are seldomly considered in geothermal resource assessment. In this study, a robust assessment method of recoverable geothermal energy considering the optimal development parameters is developed. To maximize the recoverable geothermal energy whilst avoid environmental disasters including reservoir pressure declining, thermal breakthrough and surface subsidence, an efficient approach of optimizing development parameters is proposed using the fully coupled thermo-hydro-mechanical reservoir model, experimental design and proxy model, and multiple response optimization method. Based on the case study of two doublets in the Tongzhou district, China, the robustness and reasonability of the developed assessment method are demonstrated. The results show that the optimal development parameters can significantly increase the recoverable geothermal energy, but the optimal development parameters for different doublets are different due to the complexity in geological structures and the heterogeneity in reservoir parameters. Therefore, it is highly recommended to maximize the recoverable geothermal energy by selecting the optimal development parameters.

Assessment of geothermal resources in the west area of Taikang town in Dumeng geothermal field, NE China

Combined with geothermal drilling, well logging, geological and geophysical investigations, this study established a conceptual model of the Dumeng geothermal field, Songliao Basin, and evaluated the potential of the geothermal resources of western Taikang town, an area under concentrated development in the geothermal field, based on transient groundwater flow equation. The results show that the Dumeng geothermal field is part of a conductive type geothermal system. The evaluated heat reserve is 8.76×1017 J, the storage of thermal water is 4.94×109 m3, the recoverable reserve of the thermal water is 9.85×105 m3/a, which is equivalent to an outpower of 5.59 MW, and is comparable to a small geothermal field. This study provides a basis for scientific management of the further exploration and utilization of the geothermal resources and application of the mining rights.

Geothermal resources assessment using temperature–depth relationships in the fault-controlled hydrothermal system of Aristino-Traianoupolis area, Northern Greece

Aristino-Traianoupolis area hosts one of the most significant water-dominated low-temperature geothermal fields in Greece. It is located on the southwestern uplifted margin of the Tertiary Evros Delta molassic basin, 10 km east of the town of Alexandroupolis (Thrace, NE Greece). The upper hydrothermal system of the Aristino Geothermal Field (AGF), one of the most promising in continental Greece, contains fluids with temperatures ranging from 51 to 99 °C, within a series of overlapping aquifers at very low depths (100–430 m). The main geothermal anomaly for temperatures higher than 90 °C covers an area of 6 km2, to a maximum prospected depth of 500 m below ground surface. The scattered regional anomaly exceeds 50 km2 and is characterized by excessively high and abruptly changing thermal gradient (42 to 450 °C/km) and heat flow (80–800 mW/m2), that are both typical of a fault-controlled hydrothermal system. Since 1993, the AGF has undergone non-systematic geothermal investigation, with emphasis on low-depth (100–500 m) drilling. This paper provides, for the first time, a synthetic and detailed evaluation of all available temperature data gathered in the last 25 years. The steady-state temperature logs reveal the dominant role of conduction for the upper geothermal system, accompanied, in most cases, by rapidly changing and abnormally high thermal gradients (100–450 °C/km), triggered, most probably, by a deeper system of higher temperature. This hypothesis is also supported by the applied chemical geothermometers, which suggest initial fluid temperatures at 140–150 °C, the hydrochemical characteristics of the fluids hosted in the deeper and most promising investigated reservoir (ignimbrite) of the upper system, and the extrapolated temperatures from the conductive temperature–depth profiles. The lower widespread medium enthalpy hydrothermal system should extend at depths 500–1000 m within volcanics and the expected Eocene limestones and basal clastic series of the Tertiary sequence that have filled the basin. Nevertheless, these assumptions need to be verified by appropriate investigations and new drillings at depths greater than 600–700 m, which would confirm the presence of a productive medium enthalpy reservoir.