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The problem of this research stems from the fact that in Bihor County there are 75 localities that have one or more thermal water wells, of which only 8 locations can provide balneological treatment. The purpose of the research is to evaluate whether the geothermal potential of the region would be sustainable for the development of balneology in other localities as well. In order to meet the above-mentioned requirement, an interdisciplinary methodology was necessary, starting from geophysics and geology, including hydrogeology, chemistry, physics and ending with elements of tourism and balneological potential. The research methods refer to field work, the inventory of all locations that have geothermal resources, the creation of a database, the analysis of the stability and continuity over time of the source of thermalism, the analysis of the stability and time continuity of those physical-chemical properties that are suitable for balneology. In conclusion, out of the 67 locations that still cannot provide balneological treatment, only 20 could fulfil the sustainability criteria and are able to diversify the exploitation of thermal waters. There are 47 other locations that have unexploited boreholes, but despite this, we have come to the conclusion that balneology and tourism based on geothermal waters in Bihor County has a sustainable future in dozens of localities.

The assessment of geothermal potential has gained prominence among scholars, with a focus on establishing a reliable prediction model to reduce development risks. However, little attention has been given to predicting and evaluating the geothermal potential in Dali's Eryuan area. This study introduces a novel hierarchical model integrating remote sensing, a Geographic Information System (GIS), and geophysics for the first-ever effective prediction of geothermal potential in Eryuan. The dataset includes lithology, seismic epicenter data, fault distribution, Bouguer gravity anomalies, SRTM-DEM images, and Landsat 8 remote sensing images. These datasets are converted into evidence maps and normalized to generate distinct evidence factor layers. Using the Analytic Hierarchy Process (AHP), a hierarchical model establishes weights for each evidence factor, resulting in a comprehensive prediction map. The results reveal the overall favorable geothermal potential in Eryuan, except the central area. Key hotspots include the Niujie–Sanying–Gromwell Lake and Liantie–Qiaohou, followed by the Youshou, Dengchuan, and Xixiang towns. Validation against known hot springs confirms the model's accuracy and reliability. [ABSTRACT FROM AUTHOR]

The geothermal field of the platform cover within the Grodno region is considered. The cover rests on a crystalline basement of Precambrian rocks. Temperature distribution maps for depths of 100; 200 and 300 m below ground level were compiled based on thermograms recorded in boreholes and were supplemented by the heat flow map. These reveal geothermal anomalies both of temperature and heat flow density distribution within the region. The temperature in the region monotonously increases with depth, while preserving the general features of the thermal field. The anomalies identified on the 100 m map persist for depths of 200 and 300 m. The main role in the formation of temperature anomalies is played by near-surface factors, such as groundwater circulation, and the influence of paleoclimatic changes on the Earth’s surface in the past. A low heat flow (< 30 mW/m2) in the eastern part of the region gradually increases up to 50 mW/m2 in the vicinity of Grodno. Its areal variation relates to the distribution of granitoid and blastomylonite rocks in the crystalline basement. Increased heat flow is typical of silicic rock massifs with elevated concentrations of long-living radioactive isotopes of uranium, thorium and potassium. Their decay creates an additional radiogenic component of heat flow.

This study intends to determine geothermal anomalies area using remote sensing data in the form of Landsat 8 and ASTER satellite imagery data which have Thermal Infrared Sensor (TIRS). Through pre-processing like georeferencing, radiometric calibration, and atmospheric correction, the Landsat 8 TIRS and ASTER data were wont to invert the land surface temperature of the study area during the daytime and night time using the inversion of planck function and emissivity separation algorithm. Result shows the land surface temperatures during daytime and night time of four natural land cover —water, vegetation, built up area, and bare soil—were classified and analyzed. According to the results, vegetation and bare soil show relatively thermal anomalies during the day and comparatively cold anomalies during the night. Otherwise water shows relatively cold anomalies during the day and relatively thermal anomalies during the night. Meanwhile built up area shows relatively thermal anomalies during the day and cold anomalies during the night. Superimposed and calculating mean of the night and day surface temperature can adequately eliminate the relatively cold/thermal anomalies of land cover caused by solar radiation, thus effectively highlighting geothermal anomalies. Thus, Nine geothermal anomalies areas were successfully extracted.

In this study, we set out to find unusual patterns in specific areas using data from Landsat 8 and ASTER satellites, including Thermal Infrared Sensor (TIRS) data. We used various techniques like georeferencing, radiometric calibration, and atmospheric correction to examine land surface temperatures (LST) during the day and night. We focused on four types of natural land cover: water bodies, vegetation, built-up areas, and barren land. Interestingly, we noticed that water bodies had cooler temperatures during the day but got warmer at night, while vegetation was cooler at night and warmer during the day. To accurately spot areas with higher temperature anomalies, while filtering out colder spots due to sunlight, we overlaid daytime and nighttime LST data based on land cover types. Additionally, we used thematic maps from satellite images to pinpoint village areas. To doublecheck the anomalies we observed, we compared our findings with geological maps. Through this approach, we successfully identified nine distinct regions where temperatures were 3 to 6 degrees Kelvin higher than the normal background temperature. [ABSTRACT FROM AUTHOR]

The problem of this research stems from the fact that in Bihor County there are 75 localities that have one or more thermal water wells, of which only 8 locations can provide balneological treatment. The purpose of the research is to evaluate whether the geothermal potential of the region would be sustainable for the development of balneology in other localities as well. In order to meet the above-mentioned requirement, an interdisciplinary methodology was necessary, starting from geophysics and geology, including hydrogeology, chemistry, physics and ending with elements of tourism and balneological potential. The research methods refer to field work, the inventory of all locations that have geothermal resources, the creation of a database, the analysis of the stability and continuity over time of the source of thermalism, the analysis of the stability and time continuity of those physical-chemical properties that are suitable for balneology. In conclusion, out of the 67 locations that still cannot provide balneological treatment, only 20 could fulfil the sustainability criteria and are able to diversify the exploitation of thermal waters. There are 47 other locations that have unexploited boreholes, but despite this, we have come to the conclusion that balneology and tourism based on geothermal waters in Bihor County has a sustainable future in dozens of localities. [ABSTRACT FROM AUTHOR]

With the recent increase in global focus on green energy, the application of thermal infrared remote sensing data for the detection of geothermal anomalies has attracted wide attention as it can overcome the difficulty of using only ground surveying. This study aimed to highlight areas of geothermal anomalies with land surface temperature (LST) time series data in winter derived from thermal infrared remote sensing. To extract LST anomaly areas in the Ruili Basin for geothermal prospecting, nine types of data on the study area in winter during 2014 ~ 2021 from Landsat 8 were analyzed. Landsat 8 LST inversion data based on the mono-window algorithm (MWA) can be used to identify hot springs, volcanoes, and other heat-related phenomena. Superimposing LST anomalies for each cycle through drilling data, excluding the heat island effect, geothermal anomaly regions could be plotted. The results show that the accuracy of MWA LST varied within 2 K, which is acceptable for geothermal energy and higher than those of the radiative transfer equation (RTE) algorithm and MODIS LST products. Three high-LST regions in the southeast of the study area were identified as geothermal anomaly areas (A, B, and C), and region B was further verified through a comprehensive field investigation of geothermal wells, supplemented by the temperature gradient (TG) method. The findings reveal that the distribution of geothermal anomaly areas and high-LST areas are highly consistent with the northeast trending fault structure; faults act as thermal channels and help in accurately detecting local LST anomalies. Overall, the infrared remote sensing method proved to be a valid technique for detecting LST anomalies. Considering the synergy between thermal infrared surface detection and subsurface exploration methods, the identification of known geothermal fields (B) and other possible areas (A and C) has significance in the upscaling of local geologic information to regional prospecting, thus providing a direction for future geothermal research. [ABSTRACT FROM AUTHOR]

Link for citation: Krutenko D.S., Isaev V.I., Isaev S.G. Density of hydrocarbons and deep heat flow of the territory (southeast of Western Siberia). Bulletin of the Tomsk Polytechnic University. Geo Аssets Engineering, 2023, vol. 334, no. 7, рр. 148-163. In Rus. The relevance. According to the ruling theory for organic origin of petroleum, geothermal regime is considered to be the main factor, which is responsible for realization of potential for oil generation. Therefore, it is not irrelevant to develop geothermics as a method of exploration geophysics for forecasting and evaluating oil and gas potential. Forecast tasks are reduced to detection local geothermal anomalies and establishing its relation to hydrocarbon deposits. This method may make a good showing while supplementary exploration in the territories with well-developed infrastructure and a large amount of wells as it is based on modelling and analysing of available data and does not propose additional field works. The main aim: establishing qualitative and quantitative relations between deep heat flow and oil and gas potential, also between gradient zones of heat flow and localization of hydrocarbon fields in the west of Tomsk Region. Objects: thermal field and oil and gas potential in the west of Tomsk Region. Subjects. The thermal field is described with such parameters as deep heat flow density and horizontal gradient of heat flow. Hydrocarbon fields are divided depending on fluid type into oil, oil-gas-condensate and gas-condensate. Methods. The deep heat flow was determined through paleotemperature modelling. The grid with cells of 20×20 km was set on study territory in increments of 10 km. Heat flow values were determined in the centers of each cell using Kriging interpolation method. The absolute horizontal gradient of heat flow was calculated on the same grid using five spot formula. Quantitative parameter of oil and gas potential – hydrocarbon density – was determined on the same grid. Quantitative relations were investigated by correlation and regression analysis. Relationships of heat flow density and horizontal gradient of heat flow with localization of hydrocarbon fields of different fluid type were detected by one-way ANOVA test. Results. The main results of this study are established distribution patterns for deposits of different fluid type in thermal field. Correlation analysis showed highly significant correlation coefficients. The conclusion. Oil and oil-gas-condensate fields tend to the average heat flow values (52 mW/m2), while gas-condensate are associated with high heat flow values (57 mW/m2). The value of the absolute horizontal gradient of heat flow increases in row oil fields – oil-gas-condensate fields – gas-condensate fields. The difference between average values of gradient for all of field types is statistically significant. Therefore, we indicate appearance of geothermal quantitative criterion for forecasting fluid type of deposits in areas of high potential for hydrocarbons. Quantitative relation of high significance (r=0,53) between heat flow density and hydrocarbon density is established for high heat flow values (>56 mW/m2). Weak correlation (r=0,3) was indicated between horizontal gradient of heat flow and hydrocarbon density.

The assessment of geothermal potential has gained prominence among scholars, with a focus on establishing a reliable prediction model to reduce development risks. However, little attention has been given to predicting and evaluating the geothermal potential in Dali’s Eryuan area. This study introduces a novel hierarchical model integrating remote sensing, a Geographic Information System (GIS), and geophysics for the first-ever effective prediction of geothermal potential in Eryuan. The dataset includes lithology, seismic epicenter data, fault distribution, Bouguer gravity anomalies, SRTM-DEM images, and Landsat 8 remote sensing images. These datasets are converted into evidence maps and normalized to generate distinct evidence factor layers. Using the Analytic Hierarchy Process (AHP), a hierarchical model establishes weights for each evidence factor, resulting in a comprehensive prediction map. The results reveal the overall favorable geothermal potential in Eryuan, except the central area. Key hotspots include the Niujie–Sanying–Gromwell Lake and Liantie–Qiaohou, followed by the Youshou, Dengchuan, and Xixiang towns. Validation against known hot springs confirms the model’s accuracy and reliability.

Here, the geological factors controlling deep geothermal anomalies in mines were studied based on the geotemperature, lithologic thermal conductivity, and related geological data collected from the Qianjiaying Mine, China. A simulation of the change in magma waste heat, conducted using the ANSYS Workbench, revealed the distribution characteristics of geothermal anomalies in this mine and the corresponding geological control factors. The results revealed the following points. (1) First-degree heat hazard level (temperature = 31–37 ℃) occurred in the central and southwestern parts of the mine at an ~600-m depth, while second-degree heat hazard level (temperature ≥ 37 ℃) occurred at an ~800-m depth. The geotemperature and geothermal gradient in the southwestern part of the mine were anomalously high. (2) The geotemperatures measured in the mine generally reflected a standard increase with depth, while the geothermal gradient remained unchanged with depth. The geothermal gradient and its average value in the study area were 0.70–4.23 and 2.12 °C·hm−1, respectively. (3) A combination of stratum characteristics, geological structure, and groundwater characteristics led to geothermal anomalies in mines; additionally, the waste heat from magma had no significant effect on the geothermal field.

A mathematical model of the temperature field was constructed and the temperature values for hypsometric levels of 1000, 2000 and 3000 m were calculated. for these hypsometric levels, as well as a map of the isothermal surface +50 ºC. Working with this program involves the construction of digital models of the surface, ancillary operations with them and visualization of surfaces. The digital model of the surface has the form of values in the nodes of a rectangular regular grid, the dimension of which depends on the specific problem to be solved. The efficiency of the program of interpolation of two-dimensional functions is determined by the following aspects: a set of various interpolation methods; the ability of the researcher to control the various parameters of these methods; availability of means of an estimation of accuracy and reliability of the constructed surface; the opportunity to clarify the result based on the personal experience of the expert in view of various additional factors that could not be depicted as source data. It is confirmed that the patterns of distribution of the natural thermal field in the upper part of the earth’s crust are due to a number of reasons, the main of which are the lithological composition of rocks, features of tectonic structure and the nature of groundwater movement. As a result of the analysis of graphic constructions, a sharp decrease in the subsoil warming towards the Carpathian folded structure was witnessed. It has been scientifically proven that the subsoil warming within the Mukachevo basin is much higher than within the Solotvyno basin. The confinement of geothermal anomalies to zones of intensive development of deep faults has been confirmed mathematically and experimentally. Based on this feature, it can be argued that the presence of positive geothermal anomalies is a criterion of gas bearing capacity for predicting deposits within local defiection objects.

Geothermal systems can be used to produce low-emission energy throughout the day and night, regardless of the weather conditions. These features make geothermal systems a sustainable and reliable energy source, which can be exploited on a much larger scale than it is now. Remote sensing techniques can support detecting areas potentially suitable for geothermal energy production, thereby reducing the costs of preliminary exploration. The Ecosystem Spaceborne Thermal Radiometer Experiment on Space Station (ECOSTRESS) can provide nighttime thermal imagery, which can be used for geothermal anomaly detection. This paper presents a method for automated detection of geothermal anomalies using nighttime ECOSTRESS data of the study area in Olkaria, Kenya. The proposed detection method is a kernel-based one, and includes adaptions of kernel size for the cases of large geothermal anomalies. The accuracy of the method is verified with reference data acquired during field work. A producer's accuracy of 82% is achieved, which is on average 56% points better than in randomised anomaly maps. The possible sources of errors in detection are heat capacity of surfaces, terrain features and vegetation masking the thermal signatures. The high producer's accuracy proves potential for application in global mapping of geothermal anomalies. [ABSTRACT FROM AUTHOR]

Groundwater offers an intriguing blend of distinctive physical and chemical conditions, constituting a challenge for microbial life. In Mallorca, the largest island of Balearic archipelago, harbours a variety of thermal anomalies (i.e., geothermal manifestation where surface aquifers exhibiting temperatures exceeding the regional average). The metagenomes of two aquifers in the centre and southern of the island showed Pseudomonadota to be the most represented phylum when using extracted 16S rRNA gene sequences. However, the microbial structures within and between aquifers were remarkably diverse but similar in their metabolic profiles as revealed by the metagenome-assembled genomes (MAGs) pointing to a prevalence of aerobic chemolithoautotrophic and heterotrophic metabolisms, especially in the Llucmajor aquifer. Also, some evidences of anaerobic lifestyles were detected, which would indicate that these environments either could suffer episodes of oxygen depletion or the anaerobes had been transported from deeper waters. We believe that the local environmental factors (temperature, external inputs or chemistry) seem to be more relevant than the connection and, eventually, transport of microbial cells within the aquifer in determining the highly divergent structures. Notably, most of the reconstructed genomes belonged to undescribed bacterial lineages and from them two high-quality MAGs could be classified as novel taxa named following the rules of the Code for Nomenclature of Prokaryotes Described from Sequence Data (SeqCode). Accordingly, we propose the new species and genus Costitxia debesea gen. nov., sp. nov., affiliated with the novel family Costitxiaceae fam. nov. , order Costitxiales ord. nov. and class Costitxiia class. nov.; and the new new species and genus Lloretia debesea gen. nov. sp. nov. affiliated with the novel family Lloretiaceae fam. nov. [ABSTRACT FROM AUTHOR]

[Display omitted] • The position of the magma heat source was firstly reported in the city of Ruili. • Geothermal anomalies are distributed along NE–SW oriented faults. • The geothermal anomalies on the NE side exhibited greater significance. • Day-Night LST integration improves geothermal anomaly detection. Thermal infrared remote sensing (TIRS) technology is intriguing for geothermal anomaly detection due to its time efficiency and cost-effectiveness. Land surface temperature (LST) derived from TIRS indicates potential geothermal anomalies. However, LST on different natural features, exhibiting relatively cold/hot anomalies in daytime and nighttime, affected the identification of abnormal areas. The aim of this study was to highlight geothermal anomalous areas by integrating multi-view daytime and nighttime LST data. Specifically, the winter LST time series of drillings on 2013–2023 was processed based on Landsat-8 TIRS in diurnal scenarios. An information aggregation classification method about Dempster-Shafer evidence theory was presented to target recognition at nighttime by the ASTER LST product. This day-night information fusion analysis effectively highlighted potential areas with geothermal anomalies. The results demonstrated that the geothermal anomalies were mainly distributed along the Ruili-Longling Fault and Wanding Fault in a Northeast (NE) – Southwest (SW) direction, and the NE side was more significant than the SW side. These findings suggested that the east side was closer to the magma heat source, and the presumed magma heat source location aligned closely with the detected geothermal anomalies. Geological data were employed for geological interpretation of the LST anomaly area, eliminating non-geothermal influences. Along with drilling data verification, this method was successfully used to identify geothermal anomaly areas in Ruili City, Yunnan Province. Overall, this study provided valuable insights into the detection of geothermal anomalies through TIRS, contributing to the successful development of geothermal resources. [ABSTRACT FROM AUTHOR]

Many islands of the Aegean Sea show strong geothermal activity due to volcanism in the area. In this paper, Robust Satellite Techniques (RST) are used to isolate, from other known possible sources, those thermal anomalies possibly related to geothermal activity in the Miocene volcanic field of Lesvos Island (Northern Aegean). For this purpose, 12 years (2003–2014) of daily Night-time Land Surface Temperature (LST) products, from Moderate Resolution Imaging Spectroradiometer (MODIS) acquisitions were analyzed. The final dataset contained 770 thermal anomalies whose spatial correlation with geological and structural data of Lesvos - such as caldera rims, ring faults, major tectonic lineaments and hydrothermal alterations mapped by processing SENTINEL-2 MSI satellite images – has been particularly investigated. In the approximately 20 ma geothermal field of Lesvos, geothermal activity seems to be also associated with the extensional regime of the broader area that leads to lithosphere thinning and consequent heat transfer in the multi-fractured terrain of Lesvos through volcanic and tectonic faults. Achieved results seem to confirm the possibility to use RST-based thermal anomalies to identify temporal variations in the geothermal activity probably due to the uplifting and circulation of the hydrothermal waters.

The present research is devoted to contributing on the characterization of the low-to-medium enthalpy geothermal resources existing in the broader Ferrara-Modena territory, Northern Italy. To achieve the goal, first, we analysed temperature data in selected deep boreholes to estimate the local thermophysical parameters of the underground. In order to discriminate the influence of the circulation fluids and then estimate the real temperature values of the surrounding rocks, we applied different methodological approaches. Secondly, different deep seismic reflection profiles for hydrocarbon exploration were analysed to evaluate the main lithological formation and tectonic assessment. Thirdly, we elaborated hydrochemical data obtained from borehole and temperature logs measurement to estimate the influence of the deep geothermal fluids on the shallow aquifer systems. Finally, the integrated analysis of all data allowed to infer both the horizontal and vertical temperature distributions, which are clearly strongly affected by the geological, hydrogeological and tectonic evolution of the eastern sector of the Po Plain, and especially to recognize the area with a highest geothermal potential within the region. [ABSTRACT FROM AUTHOR]

• Integrate approach: remote sensing (Landsat 8 and ASTER thermal infrared data) and geospatial data overlay analysis was used. • Land surface temperature (LST) during the daytime and nighttime were retrieved by the SC algorithm and TES algorithm. • The addition of LST during daytime and nighttime can eliminate the relatively cold/thermal anomalies between land features. • The threshold determined by statistical analysis can adequately reflect geothermal anomalies and urban heat islands. • In addition to the 3 known hot springs and the 3 urban heat islands, 6 geothermal anomalies were also discovered in Dandong area, China. Traditional ground survey methods have limited the development and use of renewable energy from geothermal resources. In this paper, the geothermal potential area of Dandong, China is studied using the thermal infrared (TIR) remote sensing data from daytime Landsat 8 and nighttime Advanced Spaceborne Thermal Emission and Reflection Radiometer (ASTER). Through pre-processing such as georeferencing, radiometric calibration, and atmospheric correction, the Landsat8 TIRS and ASTER data were used to invert the land surface temperature of the study area during the daytime and nighttime using the single-channel algorithm and temperature and emissivity separation algorithm. Furthermore, the land surface temperatures during daytime and nighttime of three natural land features—water, vegetation, and bare soil—were classified and analyzed. According to the results, vegetation and bare soil show relatively thermal anomalies during the day and relatively cold anomalies during the night. Conversely, water shows relatively cold anomalies during the day and relatively thermal anomalies during the night. Calculating the daytime and nighttime mean of land surface temperature (DNMLST) can eliminate the relatively cold/thermal anomalies exhibited by natural land features during the daytime and nighttime while highlighting the geothermal anomaly zone. Nine geothermal anomaly zones were identified using the threshold method. The auxiliary analysis of geological data excluded non-geothermal effects. Studies have shown that the distribution of the identified geothermal prospects is consistent with the development and distribution of faults. The fractures cut the land surface, causing groundwater to form structural fissure hot water through fracture structures and fissures after magma heating. The use of two higher-resolution TIR remote sensing data products to obtain the DNMLST for the detection of geothermal anomalies has proven cost-effective technical method. [ABSTRACT FROM AUTHOR]

Highlights • This research was done in the Main Ethiopian Rift Valley that is geological active area in East Africa. • Integrate approach: remote sensing (Landsat 8 thermal infrared data) and geospatial data overlay analysis was used. • Land Surface Temperature (between 292.2–315.8 K) was retrieved by means of split window (SW) algorithm. • The LST data was validated based on the comparison between MODIS LST and has a maximum difference of 1.47 K. • The LST anomalous (3–9 K higher than background), which could be geothermal sites were discovered in Tulu Moye area. Abstract Despite the high geothermal potential of the Main Ethiopian Rift (MER), risks associated with the industry and the difficulty of identifying possible targets using ground surveys alone continue to impede the development of geothermal power diligence in Ethiopia. In this paper, we investigate the geothermal potential of the Tulu Moye prospect area in the MER using Landsat 8, which is an important and cost-effective method of detecting geothermal anomalies. Data with a path/row of 168/054 were obtained from the Landsat 8 Operational Land Imager (OLI) and Thermal Infrared (TIR) sensors for October 17, 2014. Based on radiometric calibration, atmospheric correction (with the 6S model) and an NDVI-based threshold method for calculating land surface emissivity, a split-window algorithm was applied to retrieve the land surface temperature (LST) of the study area. Results show LST values ranging from 292.2 to 315.8 K, with the highest values found in barren lands. A comparison of LST between the Moderate Resolution Imaging Spectroradiometer (MODIS) and Landsat 8 shows a maximum difference of 1.47 K. Anomalous areas were also discovered, where LST was about 3-9 K higher than the background area. We identified seven of these as areas of high geothermal activity in the Tulu Moye prospective geothermal area. Auxiliary data and overlay analysis tools eliminated any non-geothermal influences. The research reveals that the distribution of highy prospective geothermal areas is consistent with the development and distribution of faults in the study area. Magmatism is the thermal source and faults provide conduits for the heat to flow from earth's interior to the surface, facilitating the presence of geothermal anomalies. Finally, TIR remote sensing methods prove to be a robust and cost-effective technique for detecting LST anomalies in the geologically active area of MER. Moreover, combining TIR remote sensing with knowledge of the structural geology of the area and geothermal mechanisms is an efficient approach to detecting geothermal areas. [ABSTRACT FROM AUTHOR]

• The Kopaonik Mt. of southern Serbia represents a highly complex segment of the Mesozoic Neotethyan suture. • The Kopaonik Mt. is an elevated productive core complex-related geothermal field (Jošanička spa and Slanište). • The investigated thermal aquifers of the Kopaonik Mt. are controlled by the complex extensional conduit–barrier faults systems. • Composite hydrogeological study yields a subsurface geothermal anomaly that is connecting the shallow and deeper fault-related thermal water reservoir network. A composite hydrogeothermal survey of the magmatic-metamorphic post-NeoTethyan late Paleogene - Neogene crustal core-complex of the Kopaonik Mt., southwestern Serbian highlands, provides new constraints on the subsurface hydraulic across- and along-fault flow fluid regimes and geothermal anomalies associated with the two shallow reservoirs. The study is involving synergistic approach by combining structural geology, exploratory drilling, temperature logging, hydrochemical and hydrodynamic constraints further illustrating a complex conduit–barrier fault-controlled spatial compartmentalization of the two thermal water reservoir(s). The thermal waters of the Kopaonik Mt. geothermal field are channeled by the major regional faults and associated fracture zones that are crosscutting the volcanics and the adjoining metamorphites. The results show that the subsurface compartmentalization of the active reservoirs, which are supplying the spa town of Jošanička banja, are controlled by a seismically active regional faults (including the fault that is crosscutting the Slanište locality, having N-S trending). Owing to the linear channeling of the fault-controlled reservoirs, in which the main quantitative water circulation takes place, it was possible to identify the thermal fluid flow paths and associated recharge zones (catchments). The Jošanička banja thermal waters reservoir is accommodated at ca. 400–500 m depth, whereas the Slanište aquifer maintains a shallower position. The new surface - subsurface constraints allowed the estimation of the subsurface reservoir elevations, pinpointing the origin of shallow crustal geothermal processes. Of particular importance is better understanding of the subsurface spatial distribution and the ultimate depth of the developing Kopaonik Mt. geothermal field. The new interpretation shows a qualitative agreement with the core-complex-related heat sourcing, as well as the fault-controlled reservoir compartments, impacting the efficient extraction of the thermal waters, in terms of quantity, quality and water temperature. [ABSTRACT FROM AUTHOR]

• Ground surface temperature (GST) monitoring network tested as a geothermal resource exploration tool. • Daily GST variation in the snow free season shows clear environmental and topographic footprints, and a snow curtain period of near zero GST in winter with thick snow. • Two GST anomalies associated likely with subsurface heat flow identified during snow curtain period when solar irradiation and surface weather effects were greatly suppressed. • Non-supervised machine learning partitions observation stations into mutually exclusive clusters statistically, useful in data analysis and interpretation. The southern Mount Meager area has been studied for its geothermal resource potential for a half century. Although attempts to commercialize the resource were unsuccessful in the past, a large volume of surface and subsurface geoscience data have been collected and made publicly available, making the Mount Meager area a unique natural laboratory for testing new ideas or tools for geothermal exploration. This study investigates the potential of using a ground surface temperature (GST) monitoring network as a tool in geothermal resource exploration. Twenty-two temperature data loggers were deployed in, and surrounding, the core area of the geothermal prospect for nearly one year. The collected temperature time series were analyzed statistically, and machine learning methods such as hierarchical clustering and k-means classification, were applied to data interpretation. The temporal variation of measured temperature can be divided into four segments: 1) snow free, 2) snow affected, 3) snow curtain, and 4) snow melt seasons. The intensity of daily ground temperature variation in the snow free season shows clear environmental and topographic footprints and is complicated by soil properties. The sites with a short period of near zero GST during the snow curtain period is spatially coincident with high heat flow areas. The measured mean GST shows a close affinity with subsurface heat flow and shallow ground water circulation, suggesting that GST time series contain information indicative of subsurface geothermal anomalies and that a GST monitoring network could be an effective tool for geothermal resource exploration in high latitude and/or elevation areas with seasonal snow cover. [ABSTRACT FROM AUTHOR]

The Hellenic Peninsula and the adjacent Aegean and Ionian seas are segmented into regions on the basis of Terra satellite-MODIS instrument derived land surface temperatures (LST) to test if they can be used in the field reconnaissance for potential geothermal targets, each region representing a different thermal signature. The method has been used successfully to identify hot spot and geothermal activity in the Afar Triangle and in the Red Sea. Night monthly average LST values per pixel, since 2001, are used in this work for geothermal field identification. Average LST seasonal variability is expressed by a common centroid curve of pixel cluster. Clusters were subsequently ranked in increasing LST according to their centroids. Cluster-2 represents by far the Aegean volcanic arc (AVA) which comprises the high enthalpy (320 and 350°C, respectively) geothermal fields of Milos and Nisyros. The interpretation of LST terrain segmentation into sub-clusters of Cluster-2 is consistent with thermal anomalies related to the volcano-islands of the AVA, the occurrence of thermal anomalies related to granodiorite plutons in the Cyclades and to the volcano-related anomalies of the Dodecanese Province. We conclude that the identification of such thermal anomalies obtained by a combination of remote sensing (LST), regional geology and field data (borehole, thermal spring and subsurface hydrothermal reservoir temperatures) can be a particularly useful exploration tool for localizing geothermal anomalies. [ABSTRACT FROM AUTHOR]

Heat-flow, temperature gradient, and gravity data are analyzed along five profiles crossing from the Colorado Plateau or Great Plains to the high topographic areas of the Southern Rocky Mountains. These profiles cross large, negative, Bouguer gravity anomalies associated with the high topography in the region, and are within the area studied by two recent seismic investigations. The heat-flow and gravity profiles typically cross from maximum to minimum values in the region, allowing an FFT (fast Fourier transform) algorithm to be applied to the data so that high frequencies can be filtered. The resulting smoothed data can be fitted by the first few terms of a sine series to estimate mid-depths of crustal and upper mantle step sources, although anomalies could also be caused by different source geometries at much shallower or much deeper depths. The analysis provides a depth comparison for thermal- and gravity-anomaly sources modeled with similar geometries, and a comparison of thermal source depths with seismic-velocity anomalies. There is considerable similarity along the profiles between the gravity and heat-flow data, and anomaly sources appear to be both in the crust and upper mantle. There often appears to be spatial coincidence between thermal- and gravity-anomaly sources and seismic-velocity anomalies proposed in the upper mantle, implying thermal influence to these gravity and seismic anomalies. Thermal anomalies proposed to have sources in the crust in some areas are consistent with gravity and shear-wave anomalies and support studies in those areas, suggesting high crustal radiogenic concentrations in relatively less dense, granitic crustal rocks. [ABSTRACT FROM AUTHOR]

The Krsˇko basin with its thermal springs is a syncline, filled with low permeable Tertiary and some Quaternary sediments. Their thickness reaches about 1.8 km in its central eastern part. This is perceivable also in geotherms reflecting a conductive temperature field. In the syncline basement, especially in Triassic and Jurassic carbonates, but less in Cretaceous rocks, convective thermal field predominates. The syncline pattern and structure have been determined from the results of gravimetric, seismic and geoelectrical measurements and deep drilling since 1959. The most important geothermal anomaly is the Cˇatezˇ field with the greatest concentration of investigations. There, the highest borehole temperatures have been reached, ranging from 50 to 64 °C. Geothermal anomalies at other localities have been less investigated, and temperatures do not exceed 36 °C. Deep boreholes which were available for geothermal measurements are found mostly along the southern rim of the basin. In much wider area the only source of data for the construction of geotherms were geoelectrical soundings, applied to elaborate geothermal maps and cross-sections. This was enabled by a conversion from resistivity and borehole lithology into temperature data, using one-dimensional simplified solution of Laplace’s equation. In such a way an approximative knowledge of geothermal conditions below surface and beyond known geothermal anomalies has been extended. Circulation of meteoric water into few kilometers deep fissured and fractured hot zones is the only heating possibility for thermal water in the Cˇatezˇ field. Water circulation is probably the deepest there than elsewhere in the Krsˇko basin. Taking into account all information collected until now, we assume that geothermal reservoir could extend at least 2–2.5 km deep below the surface. [Copyright &y& Elsevier]

Detailed investigations of the temperature distribution in the Rhine Graben indicate a regular pattern of graben-parallel thermal anomalies following major north–south striking faults. These faults, which might imply north–south convection pattern due to higher permeability, have been ignored in conventional models based on 2D east–west striking sections. The present study investigates small-scale temperature anomalies in the Rhine Graben, focusing on its north–south striking major faults and their important permeability structures. Analytical solutions for convective flow in vertical faults were applied to a clearly observable anomalous temperature pattern. Through these calculations the fault geometry, minimal fault permeability and time to convective onset were derived from observed distances between anomalies. Since analytical solutions are limited to simple model geometries, further improvement was achieved through numerical model simulations, which allow the assumption of more complex initial and boundary conditions. Using the finite volume code TOUGH2 we investigated in detail the convective fluid flow pattern along the Γ-fault in the Landau region through a 3D model. There, regions of alternatively higher and lower temperatures follow each other at an average distance of 1800 m. Focusing on the predominant north–south permeability structure, our model consists of a vertical north–south striking fault and surrounding matrix with fault geometries based on analytical predictions. The observed temperature could be explained by a numerical model indicating fluid velocities in the fault of ∼10−9 m s−1 and an anomaly whose minimal age is 77,000 years. The study proves that the observed small-scale graben-parallel temperature anomalies can be explained only by convection systems within north–south striking fault zones. The regional flow regime is therefore significantly influenced by the convective fluid flux in major north–south striking faults. Investigations of temperature anomalies in the Rhine Graben must take into account this north–south flow. Since the presented results correlate with findings from other geothermal anomalies in the Rhine Graben such as the one at Soultz, we suspect this to be a general feature of the major north–south striking faults there. Moreover, since in most grabenlike structures thermal anomalies are associated with the Graben master faults, the present study may provide common clues for investigating other graben-parallel temperature anomalies. [Copyright &y& Elsevier]

From a collection of > 140 strains isolated from groundwater with thermal anomalies for the purpose of obtaining good candidates with applications in the cosmetic industry, two strains were selected because of their taxonomic novelty. Among the isolates, strains TMF_100T and TFM_099 stood out for their potential biotechnological relevance, and a comparative analysis of 16S rRNA gene sequences indicated that these strains represented a new species of the genus Hydrotalea. In addition, from the public genomic databases, metagenome-assembled genomes (MAGs) and single-cell amplified genomes (SAGs) could be retrieved that affiliated with this genus. These MAGs and SAGs had been obtained from different environmental samples, such as acid mine drainage or marine sediments. In addition to the description of the new species, the ecological relevance of the members of this genus was demonstrated by means of denitrification, CRISPR-Cas system diversity and heavy metal resistance, as well as their wide geographical distribution and environmental versatility. Supported by the taxonomic study, together with physiological and morphological differences and ecological features, we concluded that strain TMF_100T represented a novel species within the genus Hydrotalea , for which we propose the name Hydrotalea lipotrueae sp. nov. [ABSTRACT FROM AUTHOR]