Subsurface Temperature Distribution Research Articles

A 3D thermal conductivity prediction method for deep strata based on temperature field estimation

Accurate predictions of earth’s interior thermal conductivity are essential for interpreting the mechanisms involved in geothermal systems and delineating geothermal resource targets. Existing thermal conductivity prediction methods, which typically involve measurements of rock samples and predictions based on geophysical well logging, cannot accurately predict regional thermal conductivity distributions. We develop a 3D thermal conductivity prediction based on temperature field estimation. First, the finite-element method is used for temperature forward modeling. Subsequently, the inexact Gauss-Newton method is implemented in the prediction algorithm. Synthetic studies indicate that the method can recover the true model well. The subsurface temperature distribution of the Xiong’an New Area is predicted using the coefficient correction method of the optimal temperature. Next, we obtain the 3D distribution of thermal conductivity of deep formation in the Xiong’an New Area with the predicted temperature field. The distribution of terrestrial heat flow also is estimated. In addition, the law of thermal accumulation of strata at different depths is analyzed, and the internal relation among resistivity, temperature, and thermal conductivity is studied. Thus, the 3D thermal conductivity prediction method provides the theoretical basis for interpreting mechanisms for the origin of geothermal systems and heat accumulation patterns. It could have significant utility for the analysis of geothermal fields and the sustainable development and use of geothermal resources.

Assessment of installation suitability of a vertical closed loop ground source heat pump system in regional scale

Installation suitability of a vertical closed loop GSHP system in the Echigo Plain of Japan was assessed considering the regional scale groundwater flow and heat transport analysis. For evaluating and understand the variation of development potential of the system, the necessary length of ground heat exchanger (GHE) was analyzed at different points, where groundwater, geology and subsurface temperature distribution varies. The computation was done for the model case of the Japanese single-family dwelling with reference to standard for energy saving in Japan. The necessary length of GHE ranged from 67 m to 101 m within the plain and found comparatively longer at the central coastal area around the Niigata City. These results showing the variation of the necessary length of GHE in the plain scale is significant and essential for the proper design and site selection of the system in the Echigo Plain, and can also be beneficial for the development of GSHP system in Japan. Influence of the existing groundwater pumping system was also evaluated to determine if the pumping system can enhance heat exchange performance for space-heating. The effect of groundwater pumping was not so significant to improve heat exchange rates due to the natural existence of groundwater flow.

Geothermal gradient variation in the Büyük Menderes Graben: implications for geothermal potential of the graben, Western Anatolia, Turkey

The Büyük Menderes Graben (BMG) is an E-W oriented active extensional geothermal basin within the Menderes Massif, a metamorphic core complex, in Western Anatolia, Turkey. 1500 
 (megawatts-energy) MWe of installed geothermal capacity for power production exist as of December 2019 in Western Anatolia, mostly generated in the BMG. While the BMG is a vastly producing geothermal resource, it is predicted that it has higher production potential. However, other studies do not include field scale 3D geologic models or geothermal gradient maps. This study aims to first quantitatively test the geothermal gradients in the Aydın-İncirliova-Osmanbükü Geothermal Field (IGF), then map the information. This study also aims to compare the IGF with a neighboring geothermal field. To complete this study, information from stratigraphic columns, bottom hole temperatures, and continuous temperature logs from 13 geothermal wells is utilized with Leapfrog Geothermal to create 3D models of the geology and subsurface temperature distribution. Then, isothermal contour maps of the field are created. The geologic modeling suggests that synextensional deposition has occurred within the graben. The temperature modeling suggests both that thermal breakthrough may have occurred in the field, and that the IGF has a higher geothermal gradient than the nearby Germencik Geothermal Field

On Averaging Eccentric Orbits: Implications for the Long-term Thermal Evolution of Comets

One of the common approximations in long-term evolution studies of small bodies is the use of circular orbits averaging the actual eccentric ones, facilitating the coupling of processes with very different timescales, such as the orbital changes and the thermal processing. Here we test a number of averaging schemes for elliptic orbits in the context of the long-term evolution of comets, aiming to identify the one that best reproduces the elliptic orbits’ heating patterns and the surface and subsurface temperature distributions. We use a simplified thermal evolution model applied on simulated comets both on elliptic and on their equivalent averaged circular orbits, in a range of orbital parameter space relevant to the inner solar system. We find that time-averaging schemes are more adequate than spatial-averaging ones. Circular orbits created by means of a time average of the equilibrium temperature approximate efficiently the subsurface temperature distributions of elliptic orbits in a large area of the orbital parameter space, rendering them a powerful tool for averaging elliptic orbits.

Q-value estimation of Chang'e -4 lunar penetrating radar data

Abstract The geophysical quality Q involved in anelastic energy absorption plays a significant role in the study of subsurface pressure, rock types and temperature distributions. However, with respect to newly collected lunar penetrating radar (LPR) data, scholars mainly focused on related parameters such as the permittivity, density and chemical composition, while the Q-value has rarely been estimated. In this study, we improved the multi-channel quality factor Q estimation method to study shallow underground structures of the Moon, interpret the geological structure and provide reference for the exploration of lunar resources. The improved windowed multi-channel Q estimation method uses multiple spatial coherence-constrained inversion to achieve a stable Q estimation of the whole direction profile in the presence of noise. An example of a numerical simulation of the simple lunar geological model illustrates the feasibility of the proposed method in estimating the Q-value. Partial lunar data collected by Chang'e-4 LPR were used to demonstrate its value with respect to the interpretation of the stratigraphic development history, dislocation and relative permittivity of the Moon.

Artificial neural network for predicting the thermal conductivity of soils based on a systematic database

Thermal conductivity is a significant soil property that affects subsurface temperature distribution and plays an essential role in geotechnical engineering. Accurate evaluation of thermal conductivity is a challenging task since it can be affected by many factors. Although many prediction methods for thermal conductivity have been proposed, most of them are derived from limited experimental results and applied to specific soils. A unified prediction model that is suitable for various soils is still unavailable. This study establishes a general database including thermal conductivity and corresponding physical parameters obtained from experimental measurements and field tests. The Spearman correlation coefficient ranks the importance of influencing factors. In addition, a typical artificial neural network model is conducted and trained by 2197 samples to predict the thermal conductivity of soils. Results show that the thermal conductivity of soils has strong correlations with saturation, porosity and density. The proposed machine learning model has remarkable performance compared to existing prediction models for estimating soil thermal conductivity. This study builds a relatively systematic database of soil thermal conductivity and establishes a unified model to access the thermal conductivity of soils.

Surface heat flow in Western Anatolia (Turkey) and implications to the thermal structure of the Gediz Graben

Knowledge of heat flow density on the Earth's surface and subsurface temperature distribution is essential for the interpretation of several processes in the crust such as for the evaluation of the geothermal potential of a region. With this study, we investigate the conductive heat flow distribution in western Anatolia to understand the thermal state and its relationship to regional tectonics in the region. The new heat flow data are collected and combined with previously published data to obtain the new heat flow map of western Anatolia. Analysis of data sets after appropriate corrections yields a better picture of the regional distribution of heat flow within the region. Generally, high values are observed around the grabens of Menderes Massif due to the intense tectonic activity. We also present the 2D steady-state thermal model of Gediz. The modeled temperatures are validated by temperature measurements from two deep wells. Numerical simulation results show that the dominant heat transfer mechanism in Gediz graben can be explained by conduction. Temperature distribution in the deep subsurface of the graben is controlled by both thickness distribution and thermal properties of the different stratigraphic sections. Thermal conductivity contrast between different stratigraphic sections causes anomalously elevated heat flow values at the edges of the graben. The comprehensive results of this study will bring a new perspective to geothermal studies in particular Enhanced Geothermal Systems (EGS) resource estimations in Gediz graben.

DISTRIBUSI SUHU BAWAH PERMUKAAN MANIFESTASI PANAS BUMI UNTUK ANALISIS GRADIEN SUHU DI BUKIT KASIH KANONANG

The existence of geothermal resources below the surface can be shown, among others, by the presence of land which has a temperature higher than the surrounding soil temperature. This occurs due to the conduction of heat transfer from subsurface rocks to surface rocks. How is the temperature distribution below the surface, and the temperature gradient pattern of geothermal manifestations in Bukit Kasih Kanonang, is interesting to study considering that the area is a tourist area as well as a natural laboratory for the geothermal system. The research objective was to determine the subsurface temperature distribution of geothermal manifestations and temperature gradient patterns in the tourist area of ​​Bukit Kasih Kanonang. Data collection was carried out by means of direct measurements in the field. Measurements were made at 20 measuring points with a depth of 3 cm, 9 cm, and 15 cm respectively. Data processing using Ms. software. Office Excel and Surfer 12. The results showed that the geothermal manifestations in the tourist area of ​​Bukit Kasih Kanonang had an average temperature range of 3.83 0C to 97.97 oC at a depth of 3 cm, 48.43 0C to 96.93 0C at a depth of 9 cm, and 52.9 0C to 96 ,60C at a depth of 15 cm. The temperature gradient increases with each depth. Linear temperature gradient in the morning.

Field-scale experimental and numerical analysis of a downhole coaxial heat exchanger for geothermal energy production

The experimental and computational analyses of a 500 m deep coaxial borehole heat exchanger system for geothermal power generation are studied in this paper. The experiments are carried out on a high temperature resourced well with an average thermal gradient of 0.38 °C/m. The experiment lasts 456 h, and the findings are described in terms of fluid inlet and outlet temperatures, subsurface temperature distribution profiles over time, and flowrate. The in-situ ground temperature distribution profile is measured using Distributed Temperature Sensing System for different hours of the experiment. A detailed, three-dimensional, unsteady-state, finite volume-based computational model has been developed, which solves conjugate fluid-flow and heat transfer phenomena. The simulation outcomes are compared to the results of the experiments. With validated numerical model, to determine the circle of influence, temperature profile of the ground is observed at various radial distances from the borehole. A parametric study is performed by varying inlet temperature of the fluid, mass flow rate, and the thermal conductivity of the ground. The numerical model developed also predicts the temperature recovery behavior of the ground. The results indicate that the average output thermal power for 456 h from the geothermal system ranges from 172 kW to 262 kW based on operating condition chosen and the total thermal energy generated changes between 82 MWh and 194 MWh from a single borehole. After the extraction is terminated, around 86% of the initial ground temperature is restored after 456 h.

Subsurface temperature estimation in a geothermal field based on audio-frequency magnetotelluric data

In geothermal exploration, the subsurface temperature distribution is an important parameter since it is closely related to the existing geothermal system. However, subsurface temperature information can only be obtained from boreholes, requiring a considerable cost and a limited number. A new geothermometry technique based on the relationship between temperature and resistivity has been proposed to overcome this difficulty. In order to enhance the reliability of this method, the subsurface heat condition in a different geological and geographical location was reconstructed. The temperature up to some depth beneath the surface could be estimated incorporating the back-propagation neural network using resistivity determined by high-resolution audio-magnetotelluric soundings. The temperature profiles resulting from the neural network fit with those observed from nearby boreholes, providing a satisfying evaluation result of the model’s predictive powers. Joint interpretation was then carried out following the one-dimensional resistivity inversion result and temperature cross-section. Both resistivity and temperature anomalies show an excellent agreement, so that subsurface anomaly such as altered layers, reservoir zone, and some possible faults was detected. With an appropriate training strategy, this technique can help to significantly reduce the costs at estimating the subsurface temperature.

PROFIL VERTIKAL HANTARAN PANAS BAWAH PERMUKAAN MANIFESTASI PANAS BUMI DI BAGIAN BARAT GUNUNG TAMPUSU

Indonesia is an area that has enormous geothermal potential. In North Sulawesi itself, there are three geothermal locations, including Lahendong, which is the first geothermal field in Eastern Indonesia to produce electricity, then other locations, namely in Tompaso and Kotamobagu. Strategically, Tampusu Mount is located between Tondano Lake and Linow Lake where the two lakes are the largest types of manifestation in North Sulawesi. This manifestation occurs due to the conduction of heat transfer from subsurface rock to surface rock. This study aims to analyze the distribution of temperature at shallow depths to predict the vertical profile of the thermal conductivity of geothermal manifestations in the western part of Tampusu Mount. By using surfur 11 software, it was found that the subsurface temperature distribution at shallow depths was dominated by high temperatures ranging from 30ºC - 43ºC. The lowest temperature ranges from 20ºC - 23ºC and the vertical profile of subsurface heat conduction in the western part of Tampusu Mount is not evenly distributed in each soil layer, because the temperature data obtained varies.

Analysis of heat extraction performance and long-term sustainability for multiple deep borehole heat exchanger array: A project-based study

In the context of reducing carbon emission, Deep Borehole Heat Exchanger (DBHE) array has a large potential in extracting geothermal energy to provide building heating in densely populated urban areas. To investigate the thermal interaction among the DBHE, a comprehensive numerical model has been built with the OpenGeoSys software, and it is validated by monitoring data from a pilot project in Xi’an, China. The long-term simulations manifest that the outlet temperature of the DBHE array has a noticeable draw-down of 4.70°C over 20 years in comparison to the single borehole setup. The maximum difference of outlet temperature among individual DBHE can reach up to 0.88°C over 20 years, which will lead to a shifted thermal load of 23.35kW (12.25% of the designed average value). Based on the predicted subsurface temperature distribution, a non-linear correlation can be established between the drawdown in working fluid temperature and the accumulated amount of extracted heat. The finding of work implies that the thermal interaction among individual DBHE is of significance for the sustainability of the system, and comprehensive numerical modeling should be considered in the designing procedure.

Deep geothermal energy in northern England: Insights from 3D finite difference temperature modelling

Many of the most widely used deep geothermal resource maps for the UK are produced by contouring around sparsely distributed and often unreliable data points. We thus present a MATLAB-based 3D finite difference temperature modelling methodology, which provides a means for producing more resolute and geologically realistic versions of these maps. Our case study area in northern England represents an area where both sedimentary basins and radiothermal granite bodies comprise potential geothermal resources. We divide our 3D model into geological units, which are then assigned separate thermal properties. Assuming conductive heat transfer and steady-state and fixed boundary conditions, we calculate 3D regional subsurface temperature. Due to our averaging technique for thermal properties, the resolution of our geological model is scarcely compromised with respect to similar finite element methods. One predicted ‘hot spot’ at 1 km depth in the central part of our case study area corresponds with the granitic North Pennine Batholith. Other shallow hot spots correspond with thermally insulating sedimentary rock units and geological structures that incorporate these units. Predictive heat flow density maps highlight areas with accelerated surface heat flow associated with shallow conductive basement rock and heat producing granite bodies. Our predicted subsurface temperatures show broad similarities with measured equilibrium borehole temperatures. Inaccuracies may relate to convective heat transfer involving fault systems, or input variables relating to the geological model. Our predictive subsurface temperature and heat flow density maps are more resolute and geologically realistic relative to pre-existing contoured maps. The method presented here represents a useful tool for understanding controls on subsurface temperature distribution and geothermal potential.

Uncertainty and Risk Evaluation of Deep Geothermal Energy Source for Heat Production and Electricity Generation in Remote Northern Regions

The Canadian off-grid communities heavily rely on fossil fuels. This unsustainable energetic framework needs to change, and deep geothermal energy can play an important role. However, limited data availability is one of the challenges to face when evaluating such resources in remote areas. Thus, a first-order assessment of the geothermal energy source is, therefore, needed to trigger interest for further development in northern communities. This is the scope of the present work. Shallow subsurface data and outcrop samples treated as subsurface analogs were used to infer the deep geothermal potential beneath the community of Kuujjuaq (Nunavik, Canada). 2D heat conduction models with time-varying upper boundary condition reproducing climate events were used to simulate the subsurface temperature distribution. The available thermal energy was inferred with the volume method. Monte Carlo-based sensitivity analyses were carried out to determine the main geological and technical uncertainties on the deep geothermal potential and risk analysis to forecast future energy production. The results obtained, although speculative, suggest that the old Canadian Shield beneath Kuujjuaq host potential to fulfill the community’s annual average heating demand of 37 GWh. Hence, deep geothermal energy can be a promising solution to support the energy transition of remote northern communities.

3D thermal modeling of two selected regions on comet 67P and comparison with Rosetta/MIRO measurements

Context. The Microwave Instrument for the Rosetta Orbiter (MIRO) was one of the key instruments of the Rosetta mission, which acquired a wealth of data, in particular as the orbiter moved in the close environment of comet 67P/Churyumov-Gerasimenko (August 2014–September 2016). It was the only instrument of the Rosetta payload that was able to measure temperatures in the near-subsurface layers of the cometary nucleus down to a depth of some centimeters. This range is most relevant for understanding the mechanisms of cometary activity. Aims. We simulate the 3D temperature distribution for two selected regions that were observed by MIRO in March 2015 when the comet was at a distance of about 2 au from the Sun. The importance of a full 3D treatment for a realistic subsurface temperature distribution and the thermal heat balance in the uppermost subsurface is investigated in comparison with analogous 1D simulations. Methods. For this purpose, we developed a numerical heat transfer model of the surface as well as the near-subsurface regions. It enabled us to solve the heat transfer equation in the subsurface volume with appropriate radiation boundary conditions taken into account. The comparison with 1D simulations was made on the basis of the same solar irradiation history. Results. Although the temperature gradient is predominantly normal to the comet surface, we still find that tangential flows may be responsible for local temperature differences of up to 30 K (a few Kelvin on the average) in the uppermost subsurface layers. From the results of the 3D simulations, we calculated the MIRO antenna temperature. A comparison with the actual measurements shows good agreement for the MIRO submillimeter channel, but there is a notable discrepancy for the millimeter channel. This last assessment is not related to the use of the 3D model; potential causes are discussed in some detail with a view to future studies.

Quantification of thermal conductivity uncertainty for basin modeling

Thermal conductivity is a major influencing factor on subsurface conductive heat transport and resulting temperature distribution, which in turn is a key parameter in basin modeling. Basin modeling studies commonly use representative literature values of thermal conductivity despite their impact on modeling results. We introduce a workflow for quantifying the effect of uncertain thermal conductivity on subsurface temperature distribution and thus on basin modeling results and test this workflow on a two-dimensional generic model from the Nordkapp Basin; a prior ensemble of possible models is conditioned according to Bayes’ theorem to incorporate prior knowledge of temperature data. This conditional probability yields a posterior ensemble of temperature fields with a significantly reduced standard deviation. To verify our approach, we use five characteristic scenarios from the posterior ensemble for transient petroleum systems modeling. How considering uncertain thermal conductivity affects variance in hydrocarbon generation is assessed by modeling corresponding vitrinite reflectances (Ro). Temperature uncertainty increases with depth. It also increases with increasing offset from the salt diapirs, which can be associated with a large lateral heat-flow component in the complex tectonic environment of the Nordkapp Basin. The introduced workflow can reduce temperature uncertainty significantly, especially in regions with high prior uncertainty. The Ro is very sensitive to changes in thermal conductivity because the onset depth of the gas window in the Nordkapp Basin may vary by up to 800 m (2600 ft) within the 95% confidence interval. This demonstrates the importance of quantification of the uncertainty in thermal conductivity on thermal basin modeling.

A study of ultraprecision mechanical polishing of single-crystal silicon with laser nano-structured diamond abrasive by molecular dynamics simulation

In the present study, a newly proposed mechanical polishing method of single-crystal silicon with nano-structured diamond abrasives fabricated by laser was investigated, using molecular dynamics (MD) simulations. The results were compared to conventional mechanical polishing under the same machining parameters. Polishing forces, atomic displacement, development of hydrostatic and von Mises stresses in the subsurface zone, temperature distribution, and polished surface morphologies during nano-polishing were investigated. An analysis model was also built to explore the subsurface damage mechanism in terms of examining the hydrostatic and shear stress distributions during nano-polishing. The analyses demonstrated that structured abrasives in silicon polishing lead to lower polishing forces, thinner subsurface damage layer, lower hydrostatic stresses, lower defect atom numbers, and less compressive normal stresses. Nevertheless, structured nanoscale abrasive polishing leads to lower material removal rates. Additionally, more Si-II forms from Si-I, when polishing with #-shaped groove abrasive is performed.

Construction of Deep Thermal Models Based on Integrated Thermal Properties Used for Geothermal Risk Management

The development of deep geothermal energy may be at risk from the economic point of view if the estimated deep thermal field is far from its real state. The strong heterogeneity of geological units makes it challenging to perform a reliable estimation on the construction of the deep thermal field over a large region. Additionally, the thermal properties of rocks, such as thermal conductivity and the radiogenic element concentration, whether they are from laboratory measurements or inversed from well logs, may strongly control the deep thermal field at a local scale. In this paper, the thermal conductivities of rocks from the Trois-Rivieres region in the Saint Lawrence Lowlands sedimentary basin in eastern Canada are obtained from two methods: (i) direct experimental measurement and (ii) indirect inversionmethod using well logs, including gamma ray, neutron porosity, density, and photoelectric absorption factor. The spatial distribution of subsurface temperature in the study area in the Trois-Rivieres region is numerically investigated by considering four case studies that include different values (minimum, average, and maximum) of the thermal properties by applying the Underworld simulator. The results show that thermal properties play a large role in controlling the subsurface temperature distribution and heat flux. The temperature difference can reach 15 °C in the basement, caused by the difference in thermal properties in the Trois-Rivieres region. The highest heat flux is found in the Trenton–Black River–Chazy groups, and the lowest heat flux is in the Potsdam group, which also has the highest thermal conductivity. Vertical heat flux does not change linearly with depth but is highly related to the thermal properties of specific geological formations. Furthermore, it does not have a positive correlation with the vertical temperature changes. This demonstrates that the assessment of the potential of deep geothermal energy depending merely on the surface heat flux may greatly overestimate or underestimate the geothermal capacity. Construction of the thermal models based on the integrated thermal properties from both the experimental measurement and well logs in this paper is useful in reducing the exploration risk associated with the utilization of deep geothermal energy.

Estimates of Pliocene Tropical Pacific Temperature Sensitivity to Radiative Greenhouse Gas Forcing

AbstractThe Western Equatorial Pacific (WEP) warm pool, with surface temperatures >28 °C and a deep thermocline, is an important source of latent and sensible heat for the global climate system. Because the tropics are not sensitive to ice‐albedo feedbacks, the WEP's response to radiative forcing can be used to constrain a minimum estimate of Earth system sensitivity. Climate modeling of pCO2‐radiative warming projections shows little change in WEP variability; here we use temperature distributions of individual surface and subsurface dwelling fossil foraminifera to evaluate past variability and possible radiative and dynamic climate forcing over the Plio‐Pleistocene. We investigate WEP warm pool variability within paired glacial‐interglacial (G‐IG) intervals for four times: the Holocene‐Last Glacial Maximum, ~2, ~3, and ~4 Ma. Our results show that these surface and subsurface temperature distributions are similar for all G‐IG pairs, indicating no change in variability, even as pCO2‐radiative forcing and other boundary conditions changed on G‐IG timescales. Plio‐Pleistocene sea surface temperature (SST) distributions are similar to those from the Holocene, indicating WEP SSTs respond to pCO2‐radiative forcing and associated feedbacks. In contrast, Plio‐Pleistocene subsurface temperature distributions suggest subsurface temperatures respond to changes in thermocline temperature and depth. We estimate tropical temperature sensitivity for the mid‐Pliocene (~3 Ma) using our individual foraminifera SST data set and a previously published high‐resolution boron isotope‐based pCO2 reconstruction. We find tropical temperature sensitivity was equal to, or less than, that of the Late Pleistocene.

Subsurface temperature model of the Hungarian part of the Pannonian Basin

Abstract Hungary is one of the most suitable countries in Europe for geothermal development, as a result of large amounts of Miocene extension and associated thermal attenuation of the lithosphere. For geothermal exploration, it is crucial to have an insight into the subsurface temperature distribution. A new thermal model of Hungary is presented extending from the surface down to the lithosphere-asthenosphere boundary (LAB) based on a new stochastic thermal modeling workflow. The model solves the heat equation in steady-state, assuming conduction as the main heat transfer mechanism. At the top and the base, we adopt a constant surface temperature and basal heat flow condition. For the calibration of the model, temperature measurements were collected from the Geothermal Database of Hungary. The model is built up in a layered structure, where each layer has its own thermal properties. The prior thermal properties and basal condition of the model are updated through the ensemble smoother with multiple data assimilation technique. The prior model shows a misfit with the observed temperatures, which is explained fundamentally by transient thermal effects and non-conductive heat transfer. Other misfits can be attributed to a-priori assumptions on thermal properties, boundary conditions, and uncertainty in the model geometry. The updated models considerably improve the prior model, showing a better fit with measured records. The updated models are capable to reproduce the thermal effect of lithospheric extension and the sedimentary infill of the Pannonian Basin. Results indicate that the hottest areas below 3 km are linked to the basement highs surrounded by deep sub-basins of the Great Hungarian Plain. Our models provide an indication on the potential sites for future EGS in Hungary and can serve as an input for geothermal resource assessment.