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Play Fairway Analysis (PFA) in geothermal exploration originates from a systematic methodology developed within the petroleum industry and is based on a geologic, geophysical, and hydrologic framework of identified geothermal systems. We tailored this methodology to study the geothermal resource potential of the Snake River Plain and surrounding region, but it can be adapted to other geothermal resource settings. We adapted the PFA approach to geothermal resource exploration by cataloging the critical elements controlling exploitable hydrothermal systems, establishing risk matrices that evaluate these elements in terms of both probability of success and level of knowledge, and building a code-based ‘processing model’ to process results. A geographic information system was used to compile a range of different data types, which we refer to as elements (e.g., faults, vents, heat flow, etc.), with distinct characteristics and measures of confidence. Discontinuous discrete data (points, lines, or polygons) for each element were transformed into continuous interpretive 2D grid surfaces called evidence layers. Because different data types have varying uncertainties, most evidence layers have an accompanying confidence layer which reflects spatial variations in these uncertainties. Risk layers, as defined here, are the product of evidence and confidence layers, and are the building blocks used to construct Common Risk Segment (CRS) maps for heat, permeability, and seal, using a weighted sum for permeability and heat, but a different approach with seal. CRS maps quantify the variable risk associated with each of these critical components. In a final step, the three CRS maps were combined into a Composite Common Risk Segment (CCRS) map, using a modified weighted sum, for results that reveal favorable areas for geothermal exploration. Additional maps are also presented that do not mix contributions from evidence and confidence (to allow an isolated view of evidence and confidence), as well as maps that calculate favorability using the product of components instead of a weighted sum (to highlight where all components are present). Our approach helped to identify areas of high geothermal favorability in the western and central Snake River Plain during the first phase of study and helped identify more precise local drilling targets during the second phase of work. By identifying favorable areas, this methodology can help to reduce uncertainty in geothermal energy exploration and development.

Objective In geothermal exploration, a clay cap is a typical hydrothermal geothermal system, and its depth and distribution range can provide crucial information for delineating the scope of geothermal resources and determining the location of geothermal drilling. Clay caps are usually composed of a clay layer formed through hydrothermal reactions and are characterized by low resistance. The low-resistivity cap can be effectively imaged using the audio-frequency magnetotelluric method. To obtain uncertainty information about the distribution of clay cap layers and imaging results, this paper employs the 1D trans-dimensional Bayesian inversion method to investigate the detection capabilities of low-resistance cap layers in geothermal areas through audio electromagnetic data. Methods In this paper, a model test is first carried out to establish a geoelectric model of a typical geothermal system.Subsequently, a 1D trans-dimensional Bayesian algorithm is used to invert the synthetic data to obtain the uncertainty information of the subsurface electrical structure and interface position. Then, the method was applied to the processing of measured audio frequency magnetotelluric data in the Yanggao geothermal area of Shanxi Province. Results This method has relatively accurate identification ability for low-resistivity clay caps, and the obtained uncertainty analysis results of the upper and lower interfaces of low-resistivity caps are also relatively reliable according to numerical tests. It was found that this method has a good ability to identify shallow low-resistivity caps and can provide an uncertainty evaluation of the clay cap interface position via field data tests. The 2D inversion results of this survey line verify the reliability of the 1D inversion. Conclusion This method has relatively accurate imaging capabilities and uncertainty analysis capabilities for shallow geothermal clay caprocks and has strong application prospects in geothermal detection.

Abstract The Upper Jurassic carbonate aquifer in the German Molasse Basin (S Germany) below Munich is the focus of exploitation of geothermal energy. To implement geothermal wells, meaningful prediction of reservoir quality (e.g., volume, temperature, location of aquifers, porosity, permeability) is required. However, permeability of this aquifer is often highly heterogeneous and anisotropic, as in other karst- and fracture systems. Based on geophysical well logs from six wells, a 3D porosity model, and side-wall cores, we provide a comprehensive characterisation of the reservoir. We investigate the correlation between rock porosity and matrix permeability, and the impact of hyper-facies on fractures and karstification. We locate and analyse hydraulic active zones and compare them with hydraulic inactive zones within equivalent depth ranges, to characterise promising exploration targets. We show that fracture system parameters vary strongly between wells and within a single well. However, we observe local trends between the fracture systems and rock properties. For instance, fracture intensities and compressional wave velocity increase, while porosity decreases, in dolomitic reefal build-ups (massive facies). We observed substantial karstification dominantly within the massive facies. The main indicators for hydraulic active zones in the reservoir seem to be karstification, fractures, and fault zones. Although matrix porosity has neglectable impact on permeability, the identified hydraulic active zones appear more frequently in sections with higher porosity. We conclude, similar to previous studies, that the massive facies is a suitable exploitation target. Despite the favourable conditions within the massive facies, the strongest hydraulic active zones are nevertheless in the bedded facies, often considered as aquitard, directly below the top of the reservoir within the lithostratigraphic group of the Purbeck, at the transition between the Jurassic and the Cretaceous.

Abstract This study introduces a rapid and efficient inversion algorithm designed for the interpretation of self-potential responses originating from mineralized and ore sources and hydrothermal activity, specifically addressing spherical, vertical, and horizontal cylindrical structures. The algorithm leverages local wavenumber and correlation imaging techniques to enhance accuracy in modeling. The correlation factor (C f value) is crucial in this approach, calculated as the correlation between the local wavenumber of the measured self-potential field and that of the computed field. The algorithm identifies the maximum correlation C f value (C F -max) as indicative of the optimal true model parameters. To validate the proposed algorithm, it was applied to three theoretical examples—one with contamination from regional background and another with multiple sources with and without different types of noises (random Gaussian and white Gaussian noises). Additionally, the approach was tested on three distinct real field cases related to mining, ore investigation and hydrothermal activity in India, Germany and USA. Through a comprehensive analysis of results from theoretical and real-world scenarios, including comparisons with different available data and literature information, the study concludes that the method is effective, applicable to multiple sources, accurate, and does not necessitate prior knowledge of the source shape. This algorithm presents a promising advancement in the field of self-potential interpretation for mineral exploration and geothermal exploration.

Medium-depth geothermal energy mainly consists of two types, hydrothermal and dry-heat rock. With huge resource reserves, its exploration and development are of great significance to the transformation of China's energy structure and the realization of the goal of "Double-Carbon". From the differences in the electrical characteristics between hydrothermal and hot dry rock geothermal resources, this project uses the numerical modeling of the wide field electromagnetic (WFEM) method as a tool to design a model of typical geothermal resources. Then, we summarize and analyze the detection capability of the WFEM by calculating the WFEM response under the conditions of different depths, resistivity values, thickness-to-depth ratios and other parameters. Moreover, aiming at the key problems faced by the WFEM in real applications, we discuss the factors affecting the detection accuracy and give solutions to improve the reliability of the detection results. Finally, the medium-depth geothermal energy detection in the Jiyang Depression of Shandong is presented as an example, showing how the WFEM detection technique was used with the inversion result profile obtained. By comparing the results of geomagnetic and seismic detection on the same survey line, it is demonstrated that the WFEM method has great potential in the exploration of medium-depth geothermal energy and can be the preferred method. [ABSTRACT FROM AUTHOR]

Petroleum accumulations may coincide with either positive or negative temperature anomalies, which are conventionally detected using in situ temperature measurements made in shallow boreholes 1‐3 m deep. Data gathered in this way, however, can be sparse and costly, and may require intensive fieldwork over a long time period. This article explores the possibility of detecting thermal anomalies associated with petroleum entrapment using satellite‐derived land surface temperature data. For this aim, a robust correction scheme based on a physically‐based land surface model was applied to night‐time kinetic temperature data derived from NASA's ASTER instrument. The numerical model, known as SKinTES, attempts to simulate diurnal effects and to remove them from the measured temperature data to yield a residual temperature anomaly map. The performance of this methodology was tested over the Alborz oilfield located on an anticline of the same name in the Qom region of Central Iran. The study area has an arid to semi‐arid climate and the surface geology is dominated by outcrops of the Lower Miocene Upper Red Formation. The modelling approach used successfully highlighted several negative temperature anomalies over the oil‐bearing parts of the Alborz structure. In comparison to the uncorrected data, the anomalies were shown to be highly enhanced in both spatial and magnitude terms. In addition, time series analysis indicated that the temperature anomalies were consistent over time. The authenticity of the anomalies was confirmed by a suite of in situ temperature measurements made at shallow boreholes. In conclusion, a unifying framework is proposed to explain the occurrence of both negative and positive temperature anomalies over petroleum accumulations. The new modelling and correction scheme is expected to broaden the application of remote sensing land surface temperature data not only in petroleum exploration but also in other types of geothermic investigations including geothermal exploration. [ABSTRACT FROM AUTHOR]

Borehole image data and a 1D-stress model built on open hole logs, leak-off tests (LOT) and image logs are used to evaluate the potential of seismicity caused by fault triggering during geothermal heat production in the city of Vienna. Data were derived from a 4220 m deep geothermal exploration well that investigated the geothermal potential of fractured carbonates below the Miocene fill of the Vienna Basin. The well penetrated several normal faults of the Aderklaa Fault System (AFS) that offset Pleistocene terraces at the surface and hence are regarded as active. Stress-induced borehole failures and 1D geomechanical modeling proves that the potential reservoirs are in a normal fault stress regime with Sv > SHmax > Shmin. While stress magnitudes in the upper part of the well (down to about 2000 m) are significantly below the magnitudes that would trigger the rupture of critically oriented faults including the AFS, stresses in the lower part of the drilled section in the pre-Neogene basement (below about 3300 m) are not. Data evidence a rotation of SHmax for about 45° at a fault of the AFS at 3694 m to fault-parallel below the fault suggesting that the fault is active. Critical or near-critical stressing of the fault is corroborated by the stress magnitudes calculated from the 1D geomechanical model. The safety case to exclude unintended triggering of seismic fault slip by developing geothermal reservoirs in close vicinity to one of the branch faults of the AFS may therefore be difficult or impossible to make. [ABSTRACT FROM AUTHOR]

The Upper Jurassic carbonate aquifer in the German Molasse Basin (S Germany) below Munich is the focus of exploitation of geothermal energy. To implement geothermal wells, meaningful prediction of reservoir quality (e.g., volume, temperature, location of aquifers, porosity, permeability) is required. However, permeability of this aquifer is often highly heterogeneous and anisotropic, as in other karst- and fracture systems. Based on geophysical well logs from six wells, a 3D porosity model, and side-wall cores, we provide a comprehensive characterisation of the reservoir. We investigate the correlation between rock porosity and matrix permeability, and the impact of hyper-facies on fractures and karstification. We locate and analyse hydraulic active zones and compare them with hydraulic inactive zones within equivalent depth ranges, to characterise promising exploration targets. We show that fracture system parameters vary strongly between wells and within a single well. However, we observe local trends between the fracture systems and rock properties. For instance, fracture intensities and compressional wave velocity increase, while porosity decreases, in dolomitic reefal build-ups (massive facies). We observed substantial karstification dominantly within the massive facies. The main indicators for hydraulic active zones in the reservoir seem to be karstification, fractures, and fault zones. Although matrix porosity has neglectable impact on permeability, the identified hydraulic active zones appear more frequently in sections with higher porosity. We conclude, similar to previous studies, that the massive facies is a suitable exploitation target. Despite the favourable conditions within the massive facies, the strongest hydraulic active zones are nevertheless in the bedded facies, often considered as aquitard, directly below the top of the reservoir within the lithostratigraphic group of the Purbeck, at the transition between the Jurassic and the Cretaceous. [ABSTRACT FROM AUTHOR]

This study introduces a rapid and efficient inversion algorithm designed for the interpretation of self-potential responses originating from mineralized and ore sources and hydrothermal activity, specifically addressing spherical, vertical, and horizontal cylindrical structures. The algorithm leverages local wavenumber and correlation imaging techniques to enhance accuracy in modeling. The correlation factor (Cf value) is crucial in this approach, calculated as the correlation between the local wavenumber of the measured self-potential field and that of the computed field. The algorithm identifies the maximum correlation Cf value (CF-max) as indicative of the optimal true model parameters. To validate the proposed algorithm, it was applied to three theoretical examples—one with contamination from regional background and another with multiple sources with and without different types of noises (random Gaussian and white Gaussian noises). Additionally, the approach was tested on three distinct real field cases related to mining, ore investigation and hydrothermal activity in India, Germany and USA. Through a comprehensive analysis of results from theoretical and real-world scenarios, including comparisons with different available data and literature information, the study concludes that the method is effective, applicable to multiple sources, accurate, and does not necessitate prior knowledge of the source shape. This algorithm presents a promising advancement in the field of self-potential interpretation for mineral exploration and geothermal exploration. [ABSTRACT FROM AUTHOR]

Amagmatic geothermal systems within regional‐scale orogenic faults are promising renewable resources for heat and possibly electricity production. However, their behavior needs to be better understood to improve their exploration and assessment of energy potential. To provide more insight, we report geochemical, geological, and geophysical studies from seven hot spring sites strung along a 90 km segment of the Agua Blanca Fault, which traverses a mountainous region of northern Baja California, Mexico. Our results show that topographic heads drive infiltration of meteoric water deep into basement rocks, where it is heated according to the local geothermal gradients. Long paths lead to long water residence times and high 3He/Hetotal fractions. The hot water ascends along preferentially permeable zones within the ABF, discharging at temperatures from 37°C in inland springs to 102°C on the Pacific coast. Higher discharge temperatures correlate positively with the degree of extensional fault displacement (a proxy for fault permeability). Correlations between hydraulic head gradients, residence times, and 3He/Hetotal of the thermal waters show that the hydraulic head gradient controls the length and depth of the flow paths, whereas the magnitudes and locations of the discharge sites are controlled by fault permeability. Optimal conditions at the coast allow the 120°C temperature threshold for electricity production to be reached at relatively shallow depths (<2 km), demonstrating the potential of orogenic geothermal systems not only for exploitation of hot discharging water but also for EGS exploitation of the hot rocks that surround the water upflow zones. Plain Language Summary: The deep circulation of meteoric water in areas not affected by volcanic heat represents underexplored renewable energy sources for heat or electricity production. A challenge for exploration is that the processes and forces that drive the hot water circulation in such systems are not fully understood. To obtain new insights, we undertook a geochemical, geological, and geophysical study of seven hot spring sites strung along a 90 km long fault zone across the northern Baja California Peninsula in Mexico. Our data show that rainwater infiltrates deep into mountainous areas and modifies its chemical composition and temperature in the absence of any magmatic heat source. We also discovered that the local permeability of the fault zones controls the discharge temperature of the hot springs and, thus, the amount of thermal energy that could be potentially exploited from such systems. Other relevant system parameters, such as the depth of water infiltration and the subsurface water residence time, are controlled by the differences in water pressure under high and low points in the topography and by the distance between the point of infiltration of rainwater and its subsequent discharge location. Key Points: Topography‐driven circulation of rainwater through a permeable fault produces geothermal springs with temperatures up to 102°CFault permeabilities and hydraulic head gradients control the thermal–hydraulic behavior of amagmatic geothermal systemsTemperature of amagmatic geothermal systems reaches the threshold for electricity production at shallow depth (<2 km) [ABSTRACT FROM AUTHOR]

We have studied Rayleigh wave group velocities beneath the Aegean region of Türkiye using ambient noise tomography. Noise data were gathered from 43 broadband seismic stations belonging to three permanent broad-band arrays. The cross-correlation method was used to estimate empirical Green's functions. Group velocities of the fundamental mode Rayleigh waves were determined using multiple filter technique. We measured dispersion for each station pair in a period range of 2-12 s and computed maps of group velocity distribution using the fast marching surface tomography method. The group velocity maps correlate well with the geological and tectonic features of the region, displaying low velocities for the Quaternary alluvial basins, moderate velocities for Cretaceous rocks, and high velocities for the regions where gneiss and granitoid rocks outcrop. Low velocity anomalies may be associated with the grabens and horsts formed by faulting and to deep mantle flow. We detect potential offshore geothermal zones in Izmir and Candarli Bay. The information from broad-band networks improves the resolution of crustal surface wave velocity structures, particularly for shallow depths. This improvement will support the assessment of seismic hazard, as the shallow layers of the crust contribute significantly to seismic activity. [ABSTRACT FROM AUTHOR]

Abstract Türkiye relies on coal-fired power plants for approximately 18 GW of annual electricity generation, with significantly higher CO2 emissions compared to geothermal power plants. On the other hand, geothermal energy resources, such as Enhanced Geothermal Systems (EGS) and hydrothermal systems, offer low CO2 emissions and baseload power, making them attractive clean energy sources. Radiogenic granitoid, with high heat generation capacity, is a potential and cleaner energy source using EGS. The Anatolian plateau hosts numerous tectonic zones with plutonic rocks containing high concentrations of radioactive elements, such as the Central Anatolian Massif. This study evaluates the power generation capacity of the Hamit granitoid (HG) and presents a thermo-hydraulic-mechanical (THM) model for a closed-loop geothermal well for harnessing heat from this granitoid. A sensitivity analysis based on fluid injection rates and wellbore length emphasizes the importance of fluid resident time for effective heat extraction. Closed-loop systems pose fewer geomechanical risks than fractured systems and can be developed through site selection, system design, and monitoring. Geothermal wellbore casing material must withstand high temperatures, corrosive environments, and should have low thermal conductivity. The HG exhibits the highest heat generation capacity among Anatolian granitoid intrusions and offers potential for sustainable energy development through EGS, thereby reducing CO2 emissions.

This study presents a comprehensive geophysical investigation of the Sabalan geothermal area in Iran, utilizing magnetic, gravity, and magnetotelluric (MT) data. These data have been inverted to a depth of 5000 meters. Magnetic data inversion accurately identified faults or fractures. Gravity data inversion produced a density model distinguishing intrusive masses, reservoirs, and cover units. MT data inversion utilized apparent resistivity and phase data for both TM and TE modes. The resulting models were compared with geological cross-sections to assess their accuracy and consistency. The integration of geophysical models yielded a comprehensive geological conceptual model for the Sabalan region. Heat sources, hydrothermal reservoirs, and potential geothermal fluid pathways were identified, demonstrating the effectiveness of geophysical methods in subsurface mapping. Consistency with newer Sabalan models based on drilling and geological data increased confidence in findings.

Metode magnetotellurik (MT) merupakan salah satu teknik dalam metode geofisika yang menggunakan sumber alami dalam bentuk medan elektromagnetik yang berasal dari medan listrik dan variasi medan magnet di bumi. Dalam proses interpretasi kondisi bawah permukaan bumi, data MT masih dipengaruhi oleh noise atau distorsi yang akan menutupi dimensionalitas sebenarnya. Oleh karena itu dilakukan analisis tensor fase untuk menentukan dimensionalitas dan arah geoelectrical strike guna mengidentifikasi struktur bawah permukaan yang tidak dipengaruhi oleh distorsi galvanic. Berdasarkan hasil yang diperoleh, daerah penelitian memiliki dimensionalitas 2D dengan orientasi barat laut – tenggara dengan arah N345 E. Hasil inversi 2D menunjukkan bahwa nilai resistivitas 10 diidentifikasi sebagai zona alterasi atau clay cap yang didominasi oleh mineral smektit. Nilai resistivitas 20 – 250 diidentifikasi sebagai reservoar yang bersifat permeabel yang tersusun atas batu pasir kasar, kerikil, basal, andesit, riolit, riodasit tuff dan konglomerat. Lapisan dengan nilai resistivitas 250 diidentifikasi sebagai Upper Triassic Metasediment yang mengalami sedimentasi yang sangat keras, hal tersebut disebabkan tekanan dan suhu tinggi. Lapisan ini tersusun atas meta batu lanau, batu lempung, meta batu pasir, dan meta konglomerat.

Accurately determining the favorable areas of geothermal resources and selecting the target positions of exploration wells are extremely important for exploration and efficient development. This study used the Pearson correlation coefficient and Gini gain to analyze five influencing factors related to the presence of economically viable geothermal potential. The evaluation model of the favorable areas was constructed by using different Machine Learning (ML) methods: Bayesian classifier (Bayes), Support Vector Machine, Bootstrap Aggregating (Bagging), BP neural network, Decision Tree and Logistic Regression classification. The quality of each model was verified by statistical evaluation indicators: Accuracy (ACC), F1 score (F1) and Receiver Operating Characteristic curve (ROC curve). The methodology was applied to the case study of Xinjiang Uygur Autonomous Region, China. Due to the results obtained, all ML models showed strong prediction and classification performance on the target area selection of geothermal exploration, as evidenced by each model’s metrics: the ACC was above 80%, the F1 was above 0.8, and the Area Under the ROC Curve (AUC) was greater than 0.85. The metrics obtained by the Bagging method were the highest. Finally, the results of the six ML models were combined to classify the study area’s geothermal potential, which was consistent with the available information. This study provides a specific basis and technical support for applying the method in further surveys and campaigns. [ABSTRACT FROM AUTHOR]

This study presents a comprehensive geophysical investigation of the Sabalan geothermal area in Iran, utilizing magnetic, gravity, and magnetotelluric (MT) data. These data have been inverted to a depth of 5000 meters. Magnetic data inversion accurately identified faults or fractures. Gravity data inversion produced a density model distinguishing intrusive masses, reservoirs, and cover units. MT data inversion utilized apparent resistivity and phase data for both TM and TE modes. The resulting models were compared with geological cross-sections to assess their accuracy and consistency. The integration of geophysical models yielded a comprehensive geological conceptual model for the Sabalan region. Heat sources, hydrothermal reservoirs, and potential geothermal fluid pathways were identified, demonstrating the effectiveness of geophysical methods in subsurface mapping. Consistency with newer Sabalan models based on drilling and geological data increased confidence in findings. [ABSTRACT FROM AUTHOR]

Abstract Amagmatic geothermal systems within regional‐scale orogenic faults are promising renewable resources for heat and possibly electricity production. However, their behavior needs to be better understood to improve their exploration and assessment of energy potential. To provide more insight, we report geochemical, geological, and geophysical studies from seven hot spring sites strung along a 90 km segment of the Agua Blanca Fault, which traverses a mountainous region of northern Baja California, Mexico. Our results show that topographic heads drive infiltration of meteoric water deep into basement rocks, where it is heated according to the local geothermal gradients. Long paths lead to long water residence times and high 3He/Hetotal fractions. The hot water ascends along preferentially permeable zones within the ABF, discharging at temperatures from 37°C in inland springs to 102°C on the Pacific coast. Higher discharge temperatures correlate positively with the degree of extensional fault displacement (a proxy for fault permeability). Correlations between hydraulic head gradients, residence times, and 3He/Hetotal of the thermal waters show that the hydraulic head gradient controls the length and depth of the flow paths, whereas the magnitudes and locations of the discharge sites are controlled by fault permeability. Optimal conditions at the coast allow the 120°C temperature threshold for electricity production to be reached at relatively shallow depths (

Cuitzeo Lake, in the central part of the Trans Mexican Volcanic Belt, is in an extensional region associated with the Cuitzeo graben, where magmatic ascent appears to provide the heat sources for the surface, geothermal manifestations. A profuse distribution of andesitic rocks is observed throughout the study area of 50×50 km2. Gravity and magnetic field 3D inversions are calculated to obtain density and magnetic susceptibility distributions to 7000 m depth, from which we analyze N-S and E-W cross-sections and obtain density and magnetic susceptibility geosurfaces that help characterize anomaly areas of interest. We use satellite-derived gravity and magnetic data in our evaluation, owing to their high-resolution characteristics and uniform coverage of the study area. Analysis initiates with the San Agustín del Maíz region (SAM), exhibiting surface geothermal manifestations, to characterize its density and susceptibility characteristics, then the analysis is extended to the whole study area. Several outcropping, low magnetic susceptibility regions, like the one associated with SAM, are suggested as potential geothermal targets. Density geosurfaces point to two volumes where magmatic material may intrude, coinciding with active geologic faults. The analysis presented here can be extended to neighboring regions in the Cuitzeo Lake area and may constitute a fast, unexpensive exploration methodology in similar geothermal districts.

We have studied Rayleigh wave group velocities beneath the Aegean region of Türkiye using ambient noise tomography. Noise data were gathered from 43 broadband seismic stations belonging to three permanent broad-band arrays. The cross-correlation method was used to estimate empirical Green’s functions. Group velocities of the fundamental mode Rayleigh waves were determined using multiple filter technique. We measured dispersion for each station pair in a period range of 2–12 s and computed maps of group velocity distribution using the fast marching surface tomography method. The group velocity maps correlate well with the geological and tectonic features of the region, displaying low velocities for the Quaternary alluvial basins, moderate velocities for Cretaceous rocks, and high velocities for the regions where gneiss and granitoid rocks outcrop. Low velocity anomalies may be associated with the grabens and horsts formed by faulting and to deep mantle flow. We detect potential offshore geothermal zones in Izmir and Candarli Bay. The information from broad-band networks improves the resolution of crustal surface wave velocity structures, particularly for shallow depths. This improvement will support the assessment of seismic hazard, as the shallow layers of the crust contribute significantly to seismic activity.

The Acoculco Caldera Complex (ACC), located in eastern Mexico, began its activity during the Pleistocene ~ 2.7 Ma. One of the most relevant and largest rhyolitic eruption in the complex, the Piedras Encimadas Ignimbrite (PEI), occurred during the late post-caldera phase at ~ 1.2 Ma. This ignimbrite is unique with respect to the other caldera products and other contemporaneous ignimbrites in the Trans-Mexican Volcanic Belt (TMVB) because of its ultra-high crystallinity and the absence of pumice fragments. The PEI is made almost entirely of crystals where the main constituents are k-feldspars and silica polymorphs that range from ≤ 5 µm to tens of centimeters in size. XRD on bulk rock, geochemical modeling, FTIR, Raman, and EPMA analyses were carried out in all mineral phases to assess the origin and the causes of high crystallinity within the PEI. We interpret the high crystallinity on the basis of magmatic crystallization of a magma body that was remobilized and altered by post-depositional hydrothermal alteration processes. We suggest that ACC rhyolites are geochemically influenced by at least one crystal mush established during the Pleistocene. We suggest that the PEI could be the result of an erupted crystal mush (melt + crystals), or a cumulate, or an ancient and crystallized reservoir generated after the first ACC collapse due to intrusion or underplating of mafic hot magmas. Extensional episodes within the ACC facilitated the ascent of mafic magmas. This interaction increased the liquid fraction of the mush through partial melting/crystal dissolution, generating a drop in density and viscosity in the mush, thus triggering eruption. The PEI provides evidences for an association between the geochemically-diverse ACC rhyolites with the complex interaction between mafic transitional alkaline magmas and a crustal mush system, promoted by continuous changes in the stress field during the Pleistocene. [ABSTRACT FROM AUTHOR]

Geothermal resource is a kind of crucial clean, renewable energy with high potential development and application. However, it involves great exploiting risks since it buried deep beneath the crust of the Earth. The location and depth of geothermal resources can be determined using the geophysical methods. Controlled source audio-frequency magnetotellurics (CSAMT) and transient electromagnetic method (TEM) have relatively high efficiency and robustness. In this paper, a simplified geothermal system resistivity model was established, which allowed TEM and CSAMT to differentiate target faults with various characteristics (resistivity, dip angle and width). Through a comprehensive electromagnetic exploration in Huairen County, Shanxi Province, China as an example, the performance of TEM and CSAMT in determining geothermal resources was evaluated. The results showed that both methods could examine the geoelectrical structures from various perspectives, and the effectiveness of comprehensive electromagnetic method for geothermal resources was presented. [ABSTRACT FROM AUTHOR]

Copyright of Geology & Resources is the property of Geology & Resources Editorial Office and its content may not be copied or emailed to multiple sites or posted to a listserv without the copyright holder's express written permission. However, users may print, download, or email articles for individual use. This abstract may be abridged. No warranty is given about the accuracy of the copy. Users should refer to the original published version of the material for the full abstract. (Copyright applies to all Abstracts.)

This document is a corrigendum for an article titled "Ambient noise tomography of the Aegean region of Türkiye from Rayleigh wave group velocity." The corrigendum acknowledges errors in the references of the published article, specifically incorrect publication years and missing authors. The correct references are provided in the corrigendum. The authors apologize for the errors and state that they do not affect the scientific conclusions of the article. The corrigendum also includes information about the authors and their affiliations. [Extracted from the article]

Medium-depth geothermal energy mainly consists of two types, hydrothermal and dry-heat rock. With huge resource reserves, its exploration and development are of great significance to the transformation of China’s energy structure and the realization of the goal of “Double-Carbon”. From the differences in the electrical characteristics between hydrothermal and hot dry rock geothermal resources, this project uses the numerical modeling of the wide field electromagnetic (WFEM) method as a tool to design a model of typical geothermal resources. Then, we summarize and analyze the detection capability of the WFEM by calculating the WFEM response under the conditions of different depths, resistivity values, thickness-to-depth ratios and other parameters. Moreover, aiming at the key problems faced by the WFEM in real applications, we discuss the factors affecting the detection accuracy and give solutions to improve the reliability of the detection results. Finally, the medium-depth geothermal energy detection in the Jiyang Depression of Shandong is presented as an example, showing how the WFEM detection technique was used with the inversion result profile obtained. By comparing the results of geomagnetic and seismic detection on the same survey line, it is demonstrated that the WFEM method has great potential in the exploration of medium-depth geothermal energy and can be the preferred method.

Copyright of Boletín Geológico y Minero is the property of Instituto Tecnologico Geominero De Espana and its content may not be copied or emailed to multiple sites or posted to a listserv without the copyright holder's express written permission. However, users may print, download, or email articles for individual use. This abstract may be abridged. No warranty is given about the accuracy of the copy. Users should refer to the original published version of the material for the full abstract. (Copyright applies to all Abstracts.)

Abstract The Upper Jurassic carbonates are the prime target for deep geothermal exploration in the Molasse basin, South Germany. The carbonates have a thickness of over 500m (1640 ft) and consist of two major facies: (1) bedded marly limestone and (2) massive limestone and dolostone. The massive limestone facies is composed of sponge-microbial biohermal buildups It is considered the main geothermal reservoir facies. Only this facies type may be (1) karstified, (2) dolomitized, and/or (3) faulted and fractured, and therefore can yield very high flow rates of >100 l/sec = 26 gps. The main data source used in this study is the 3D seismic survey of the Freiham geothermal field in the western part of Munich/Germany. Blended in were cutting logs to describe the lithology from 2 wells and borehole image logs from the two geothermal wells. Lithologies derived from these wells were upscaled in support of the seismic interpretation. The study presents an integrated workflow of 3D seismic attribute analysis to analyze the distribution and quantification of reservoir facies (massive limestone) versus non-reservoir facies (bedded marly limestone) per time slice. The attribute “sum of magnitude” is mapped for 9-time slices based on the vertical resolution of the Freiham 3D cube. The seismic facies interpretation is compared with upscaled borehole image facies associations of two geothermal wells. BHI log data is calibrated with an interpretation of the depositional environment based on cutting analysis Reservoir geometries were derived from an outcrop analog study to better understand the 3D seismic facies interpretation and to construct the conceptual depositional model of the Upper Jurassic carbonates. This technique is commonly used in hydrocarbon exploration but is not yet adapted to geothermal projects, which are often based on little data, smaller company sizes, tight budgets, and limited access to specialized geomodelling software and experience. The approach of using 3D seismic attribute analysis presented in this study provides a quantitative subsurface model of geothermal reservoir facies in the Freiham geothermal field. It is quick and straightforward and can easily be applied in the exploration workflow for similar fields and reservoirs.

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. [ABSTRACT FROM AUTHOR]

Geothermal resources are a type of important renewable clean energy with high development and usage potential. However, at the same time, geothermal resources are buried deep below the Earth's surface, they involve significant exploiting hazards. Geophysical methods are frequently required to determine the depth and location of geothermal resources. Among geophysical methods, transient electromagnetic method (TEM) and controlled source audio-frequency magnetotellurics (CSAMT) have comparably high effectiveness and accuracy. This article first introduces the algorithm theory of the finite volume method, then establishes a simplified geothermal system resistivity model. Next, based on this model, simulation analyses of the abilities of CSAMT and TEM were performed to distinguish target faults with different resistivities, dip angles and widths. Finally, combined with theoretical analysis, taking a comprehensive electromagnetic exploration of CSAMT and TEM in Huairen County, Shanxi Province, China as an example, the effectiveness of these two methods in exploring typical geothermal resources is verified. It is shown that both methods can reflect the geoelectric structure from different perspectives, and the efficacy in geothermal exploration using comprehensive electromagnetic method is demonstrated. [ABSTRACT FROM AUTHOR]

Dense distribution of granites and surrounding hot springs, the high anomalous heating rates of geothermal fluids and the high geothermal gradients in shallow crust in Southeast China are revealed by previous geothermal explorations. However, there have always been debates on the genesis of geothermal anomalies of Southeast China. It is imperative to look into the genesis mechanism of geothermal anomalies through selecting a typical geothermal field, and constructing fine crustal thermostructure. In this study, in-depth excavation is implemented for the previous data of geophysical exploration and deep drilling exploration in the Huangshadong area. We synthetically analyze the results of radioactive heat productions (RHPs), thermophysical properties of rocks and audio-frequency magnetotellurics (AMT) sounding. This study concludes that the coefficient of radioactive heat generation (RHG) of crustal rocks and conduction heat of concealed granites is the main formation mechanism of geothermal anomalies of South China, where occurs a Great Granite Province. There is a regional indicating implication for the genesis of geothermal anomalies, taking the Huangshadong geothermal field as a typical example. It is also an important reference to guide the exploration, evaluation, development and utilization of geothermal resources in this region. [ABSTRACT FROM AUTHOR]

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Copyright of Geology & Resources is the property of Geology & Resources Editorial Office and its content may not be copied or emailed to multiple sites or posted to a listserv without the copyright holder's express written permission. However, users may print, download, or email articles for individual use. This abstract may be abridged. No warranty is given about the accuracy of the copy. Users should refer to the original published version of the material for the full abstract. (Copyright applies to all Abstracts.)

Geothermal resources have potential for providing cost‐effective and sustainable energy. Monitoring of production‐induced changes in geothermal reservoirs using seismic waves requires understanding of the elastic properties of the rock and how they change due to injection of fluids and opening and closing of natural and hydraulic fractures. P‐ and S‐wave velocities measured in a granitic geothermal reservoir using sonic logging are systematically lower than those predicted using the composition of the rock. Cracks may occur in granitic rocks from tectonic stresses and from the thermal expansion mismatch between differently oriented anisotropic crystals. An isotropic orientation distribution of microcracks causes a significant reduction in both the P‐ and S‐velocities, consistent with the observed sonic P‐ and S‐velocities. Vertical fractures cause a difference in the velocity of vertically propagating shear waves polarized parallel and perpendicular to the fractures. An assumption that the lower measured velocities are caused by the presence of vertical fractures is inconsistent with the sonic data. This is because vertical fractures cause a decrease in slow S‐wave velocity that greatly exceeds the decrease in P‐wave velocity, in contrast to the observed data. The growth of vertical fractures in the geothermal reservoir may be monitored using the difference in velocity of the fast and slow shear waves, while the change in P‐velocity in a crossplot of measured P‐ and slow S‐velocities is useful for estimating the ratio of the normal‐to‐shear compliance of the fractures. [ABSTRACT FROM AUTHOR]

Copyright of World Nuclear Geoscience is the property of World Nuclear Geoscience Editorial Office and its content may not be copied or emailed to multiple sites or posted to a listserv without the copyright holder's express written permission. However, users may print, download, or email articles for individual use. This abstract may be abridged. No warranty is given about the accuracy of the copy. Users should refer to the original published version of the material for the full abstract. (Copyright applies to all Abstracts.)

The Upper Jurassic carbonates are the prime target for deep geothermal exploration in the Molasse basin, South Germany. The carbonates have a thickness of over 500m (1640 ft) and consist of two major facies: (1) bedded marly limestone and (2) massive limestone and dolostone. The massive limestone facies is composed of sponge-microbial biohermal buildups It is considered the main geothermal reservoir facies. Only this facies type may be (1) karstified, (2) dolomitized, and/or (3) faulted and fractured, and therefore can yield very high flow rates of >100 l/sec = 26 gps. The main data source used in this study is the 3D seismic survey of the Freiham geothermal field in the western part of Munich/Germany. Blended in were cutting logs to describe the lithology from 2 wells and borehole image logs from the two geothermal wells. Lithologies derived from these wells were upscaled in support of the seismic interpretation. The study presents an integrated workflow of 3D seismic attribute analysis to analyze the distribution and quantification of reservoir facies (massive limestone) versus non-reservoir facies (bedded marly limestone) per time slice. The attribute "sum of magnitude" is mapped for 9-time slices based on the vertical resolution of the Freiham 3D cube. The seismic facies interpretation is compared with upscaled borehole image facies associations of two geothermal wells. BHI log data is calibrated with an interpretation of the depositional environment based on cutting analysis Reservoir geometries were derived from an outcrop analog study to better understand the 3D seismic facies interpretation and to construct the conceptual depositional model of the Upper Jurassic carbonates. This technique is commonly used in hydrocarbon exploration but is not yet adapted to geothermal projects, which are often based on little data, smaller company sizes, tight budgets, and limited access to specialized geomodelling software and experience. The approach of using 3D seismic attribute analysis presented in this study provides a quantitative subsurface model of geothermal reservoir facies in the Freiham geothermal field. It is quick and straightforward and can easily be applied in the exploration workflow for similar fields and reservoirs. [ABSTRACT FROM AUTHOR]

• The aim is to create a conceptual model and thermal history of the geothermal system using geological, mineralogical, geochemical and geophysical data. • It is possible that there are higher temperature waters in Salar region. • The distribution of alteration zones and geothermal waters demonstrates that they were under the influence of similar tectonic processes. • Neutral-alkaline environment conditions is effective in the Salar area. The intense investment demand in the geothermal sector in Afyonkarahisar province in recent years has enabled the utilization of geothermal waters such as district heating and greenhouse heating, electricity generation, and spa facilities and accelerated the exploration of new geothermal areas in the region. In this study, the Salar (Afyonkarahisar) region's geothermal potential was investigated using the mineralogy and geochemistry of hydrothermal alteration, hydrogeochemistry, and resistivity models obtained from magnetotelluric data. The Salar region is located within the Afyon-Akşehir Graben (AAG) and 10 km south of Afyonkarahisar province. The most important manifestations of the geothermal system are the geothermal water at temperatures of 25 °C and 31 °C obtained from the boreholes and hydrothermal alteration in Salar. Afyon volcanoclastics are reservoir rocks. Smectite and illite are the most important clay minerals in the hydrothermal alteration zones. The transformation from volcanic glass and alkali feldspar to smectite and illite reflects neutral-alkaline alteration conditions in felsic rocks. The clay minerals' stable isotopes (δ D and δ18O) indicate hypogene conditions. Discharge temperature, electrical conductivity and pH of Salar region geothermal waters vary from 25 to 31 °C, 320–357 µs/cm, and 6.8, respectively. The Salar geothermal waters are Ca-(Na)-HCO 3 type chemically. The electric resistivity models reveal shallow low resistivity (10 < ρ < 80 Ωm) layer related to the alluvium, Gebeceler formation, and Afyon volcanoclastics and deeper high resistivity (80 <ρ < 200 Ωm and ρ > 200 Ωm) layer based on Deresinek and Değirmendere formation respectively. The difference in electrical resistivity arises from the geothermal waters and hydrothermal alteration zones, influenced by the AAG tectonics. The stable isotopes (δ D and δ18O) and alpha cristobalite geothermometer calculations indicate that the condition of the temperature in the active and fossil geothermal systems in the Salar does not change, and the condition of the temperature is between 44 °C and 112 °C. [ABSTRACT FROM AUTHOR]

Although many Known Geothermal Resource Areas in Oregon and Idaho were identified during the 1970s and 1980s, few were subsequently developed commercially. Because of advances in power plant design and energy conversion efficiency since the 1980s, some previously identified KGRAs may now be economically viable prospects. Unfortunately, available characterization data vary widely in accuracy, precision, and granularity, making assessments problematic. Here we suggest a procedure for comparing test areas against proven resources using Principal Component Analysis and cluster identification. The result is a low-cost tool for evaluating potential exploration targets using uncertain or incomplete data.

Although many Known Geothermal Resource Areas in Oregon and Idaho were identified during the 1970s and 1980s, few were subsequently developed commercially. Because of advances in power plant design and energy conversion efficiency since the 1980s, some previously identified KGRAs may now be economically viable prospects. Unfortunately, available characterization data vary widely in accuracy, precision, and granularity, making assessments problematic. Here we suggest a procedure for comparing test areas against proven resources using Principal Component Analysis and cluster identification. The result is a low-cost tool for evaluating potential exploration targets using uncertain or incomplete data.

The in-situ stress state in the shallow crust of the coastal region of Southeastern China (CRSC) remains poorly understood. We conducted anelastic strain recovery measurements in a 2 km deep geothermal borehole to investigate the in-situ stress state. Four high-quality granite core samples were employed to successfully estimate the full stress tensors. The results show that the maximum principal stress σ1 is nearly vertical, implying an extensional shallow crust that is controlled by normal faulting. From ~1865 to ~1959 m in depth, the maximum and minimum horizontal principal stresses (SHmax and Shmin) are 36.1–48.7 MPa and 34.0–38.5 MPa, respectively. Based on the paleomagnetic analysis, the orientation of the maximum horizontal compressive stress SHmax is determined as N43° ± 19°W and aligned with the subduction direction of the Philippine Sea plate. According to the compiled stress data, the SHmax orientations in the CRSC rotate counterclockwise towards the Chinese mainland, which are consistent with those of the earthquake focal mechanisms and regardless of earthquake type, indicating a heterogeneous stress field dominancy in the CRSC. Our findings manifest that there is a lower horizontal compressive stress state in the upper crust in the study region. We also discussed the possible influence of in-situ stress on wellbore stability and fracture propagation in hot dry rock exploration and further quantitatively analyzed the reactivation possibility of natural fractures under different injection pressures. This study will provide scientific data for geodynamic research, fault seismicity, and geothermal development in the region in the future. Highlights: We used the anelastic strain recovery (ASR) method to obtain the in-situ stress state at 2 km depth in Xiamen, Fujian, China, indicating that Xiamen is controlled by normal-faulting stress. In ASR experiments, rock mechanics and rock compliance experiments were conducted to help better constrain the in-situ stress state. The collision of the Eurasian and Philippine Sea plates controls shallow crustal stress pattern and shows a relatively low horizontal compressive stress state in the coastal region of Southeastern China. Implications of in-situ stresses on geothermal resource development were discussed and quantitatively analyzed. [ABSTRACT FROM AUTHOR]

Exploration of geothermal resources involves analysis and management of a large number of uncertainties, which makes investment and operations decisions challenging. Remote Sensing (RS), Machine Learning (ML) and Artificial Intelligence (AI) have potential in managing the challenges of geothermal exploration. In this paper, we present a methodology that integrates RS, ML and AI to create an initial assessment of geothermal potential, by resorting to known indicators of geothermal areas namely mineral markers, surface temperature, faults and deformation. We demonstrated the implementation of the method in two sites (Brady and Desert Peak geothermal sites) that are close to each other but have different characteristics (Brady having clear surface manifestations and Desert Peak being a blind site). We processed various satellite images and geospatial data for mineral markers, temperature, faults and deformation and then implemented ML methods to obtain pattern of surface manifestation of geothermal sites. We developed an AI that uses patterns from surface manifestations to predict geothermal potential of each pixel. We tested the Geothermal AI using independent data sets obtaining accuracy of 92–95%; also tested the Geothermal AI trained on one site by executing it for the other site to predict the geothermal/non-geothermal delineation, the Geothermal AI performed quite well in prediction with 72–76% accuracy. • Novel deep learning model uses geological and geophysical information as data source. • Automated labeling process using unsupervised learning for training, and testing. • Preprocessing to create input and label layers for the deep learning model. • Artificial intelligence using independent data sets obtained accuracy of 92–95%. [ABSTRACT FROM AUTHOR]

Fiber-optic distributed temperature sensing (DTS) has been widely used since the end of the 20th century, with various industrial, Earth sciences, and research applications. To obtain precise thermal measurements, it is important to extend the currently available DTS calibration methods, considering that environmental and deployment factors can strongly impact these measurements. In this work, a laboratory experiment was performed to assess a currently available duplexed single-ended DTS calibration algorithm and to extend it in case no temperature information is available at the end of the cables, which is extremely important in geothermal applications. The extended calibration algorithms were tested in different boreholes located in the Atacama Desert and in the Central Andes Mountains to estimate the geothermal gradient in these regions. The best algorithm found achieved a root mean square error of 0.31 ± 0.07 °C at the far end of a ~1.1-km cable, which is much smaller than that obtained using the manufacturer algorithm (2.17 ± 0.35 °C). Moreover, temperature differences between single- and double-ended measurements were less than 0.3 °C at the far end of the cable, which results in differences of ~0.5 °C km−1 when determining the geothermal gradient. This improvement in the geothermal gradient is relevant, as it can reduce the drilling depth by at least 700 m in the study area. Future work should investigate new extensions of the algorithms for other DTS configurations and determining the flow rate of the Central Andes Mountains artesian well using the geothermal profile provided by the DTS measurements and the available data of the borehole [ABSTRACT FROM AUTHOR]

Northeast China is an area with high energy consumption and high carbon emissions, and the utilization of geothermal resources can effectively overcome these problems. However, there are few geothermal manifestations in Northeast China and no systematic method for geothermal exploration at present, which hinders the utilization of geothermal resources. Here, a systematic analysis, including hydrochemistry, petrology, isotopes, controlled source audio magnetotelluric sounding, drilling, and temperature curve of two boreholes was carried out to investigate the genesis of geothermal resources in Tonghe County, Northeast China, along the Yilan-Yitong lithospheric fault (YYF). We found that the geothermal water is alkaline Na-HCO3 type water, is of local meteoric origin, and is recharged from the hilly area with an elevation of ~280 m around the study area. We established a geothermal water circulation path model: (1) cold water infiltrated along the YYF to a depth of 2–3 km, (2) cold water was heated by mantle heat, and (3) hot water was stored in sandstone/siltstone, forming a sandstone geothermal reservoir with a temperature of ~70 ℃. These results have important guiding significance for the scientific exploration of geothermal resources in Northeast China. [ABSTRACT FROM AUTHOR]

The region surrounding the Modoc Plateau, encompassing parts of northeastern California, southern Oregon, and northwestern Nevada, lies at an intersection between two tectonic provinces; the Basin and Range province and the Cascade volcanic arc. Both of these provinces have substantial geothermal resource base and resource potential. Geothermal systems with evidence of magmatic heat, associated with Cascade arc magmatism, typify the western side of the region. Systems on the eastern side of the region appear to be fault controlled with heat derived from high crustal heat flow, both of which are typical of the Basin and Range. As it has the potential to host Cascade arc-type geothermal resources, Basin and Range-type geothermal resources, and/or resources with characteristics of both provinces, and because there is relatively little current development, the Modoc Plateau region represents an intriguing potential for undiscovered geothermal resources. It remains unclear however, what specific set(s) of characteristics are diagnostic of Modoc-type geothermal systems and how or if those characteristics are distinct from Basin and Range-type or Cascade arc-type geothermal systems. In order to evaluate the potential for undiscovered geothermal resources in the Modoc area, we integrate a wide variety of existing data in order to evaluate geothermal resource potential and exploration risk utilizing ‘play-fairway’ analysis. We consider that the requisite parameters for hydrothermal circulation are: 1) heat that is sufficient to drive circulation, and 2) permeability that is sufficient to allow for fluid circulation in the subsurface. We synthesize data that indicate the extent and distribution of these parameters throughout the Modoc region. ‘Fuzzy logic’ is used to incorporate expert opinion into the utility of each dataset as an indicator of either heat or permeability, and thus geothermal favorability. The results identify several geothermal prospects, areas that are highly favorable for the occurrence of both heat and permeability. These are also areas where there is sufficient data coverage, quality, and consistency that the exploration risk is relatively low. These unknown, undeveloped, and under-developed prospects are well-suited for continued exploration efforts. The results also indicate to what degree the two ‘play-types,’ i.e. Cascade arc-type or Basin and Range-type, apply to each of the geothermal prospects, a useful guide in exploration efforts.

The region surrounding the Modoc Plateau, encompassing parts of northeastern California, southern Oregon, and northwestern Nevada, lies at an intersection between two tectonic provinces; the Basin and Range province and the Cascade volcanic arc. Both of these provinces have substantial geothermal resource base and resource potential. Geothermal systems with evidence of magmatic heat, associated with Cascade arc magmatism, typify the western side of the region. Systems on the eastern side of the region appear to be fault controlled with heat derived from high crustal heat flow, both of which are typical of the Basin and Range. As it has the potential to host Cascade arc-type geothermal resources, Basin and Range-type geothermal resources, and/or resources with characteristics of both provinces, and because there is relatively little current development, the Modoc Plateau region represents an intriguing potential for undiscovered geothermal resources. It remains unclear however, what specific set(s) of characteristics are diagnostic of Modoc-type geothermal systems and how or if those characteristics are distinct from Basin and Range-type or Cascade arc-type geothermal systems. In order to evaluate the potential for undiscovered geothermal resources in the Modoc area, we integrate a wide variety of existing data in order to evaluate geothermal resource potential and exploration risk utilizing ‘play-fairway’ analysis. We consider that the requisite parameters for hydrothermal circulation are: 1) heat that is sufficient to drive circulation, and 2) permeability that is sufficient to allow for fluid circulation in the subsurface. We synthesize data that indicate the extent and distribution of these parameters throughout the Modoc region. ‘Fuzzy logic’ is used to incorporate expert opinion into the utility of each dataset as an indicator of either heat or permeability, and thus geothermal favorability. The results identify several geothermal prospects, areas that are highly favorable for the occurrence of both heat and permeability. These are also areas where there is sufficient data coverage, quality, and consistency that the exploration risk is relatively low. These unknown, undeveloped, and under-developed prospects are well-suited for continued exploration efforts. The results also indicate to what degree the two ‘play-types,’ i.e. Cascade arc-type or Basin and Range-type, apply to each of the geothermal prospects, a useful guide in exploration efforts.