Thermal Conductivity Of Rocks Research Articles

Terrestrial heat flow measurement and numerical simulation of lithospheric thermal structure in western Sichuan, China

The western Sichuan in the eastern Qinghai-Tibet plateau has significant geothermal potential. Heat flow is one of the most important parameters in geothermic, its measurement can help obtain a better understanding of the regional lithospheric thermal structure. In this study, we reported 4 heat flow data based on the continuous steady-state temperature logging and rock thermal conductivity test, including two class-A and two class-D data. Furthermore, we calculated the lithospheric thermal structure by a 2D steady-state thermal conduction equation in COMSOL, analyzing the lateral differences of lithospheric thermal structure in the eastern Qinghai-Tibet plateau. Our study has determined that the heat flow values in the western Sichuan range from 94.7 to 116.2 mW/m2, with a corresponding geothermal gradient of 32.1–37.3 °C/km. Moreover, numerical simulation results indicate significant differences in lithospheric thermal structure between western Sichuan and Sichuan Basin, where the Longmen Shan fault zone is a crucial regional tectonic boundary and a significant temperature gradient zone. Specifically, the Moho temperature in the western Sichuan region ranges from 1000 to 1200 °C with an average temperature of 1060 °C, while the Sichuan Basin ranges from 600 to 700 °C. Besides, the thermal lithosphere thickness in the western Sichuan and the Sichuan Basin is 88–97 km and 105–110 km, respectively. These observations suggest that the western Sichuan region is characterized by high thermal anomaly and provide theoretical evidence for the geodynamic and geothermal development in this area. Finally, we suggest that the high thermal anomaly in western Sichuan is the result of a combination of factors, such as thickened crust, high radioactive heat production, and shear frictional heating from deep fault and so on.

Effect of temperature-dependent rock thermal conductivity and specific heat capacity on heat recovery in an enhanced geothermal system

The modeling of heat recovery from an enhanced geothermal system (EGS) requires rock thermal parameters as inputs such as thermal conductivity and specific heat capacity. These parameters may encounter significant variations due to the reduction of rock temperature during heat recovery. In the present study, we investigate the effect of temperature-dependent thermal conductivity and specific heat capacity on the thermal performance of EGS reservoirs. Equations describing the relationships between thermal conductivity/specific heat capacity and temperature from previous experimental studies were incorporated in a field-scale single-fracture EGS model. The modeling results indicate that the increase of thermal conductivity caused by temperature reduction accelerates thermal conduction from rock formations to fracture fluid, and thus improves thermal performance. The decrease of specific heat capacity due to temperature reduction, on the contrary, impairs the thermal performance but the impact is smaller than that of the increase of thermal conductivity. Due to the opposite effects of thermal conductivity increase and specific heat capacity decrease, the overall effect of temperature-dependent thermal parameters is relatively small. Assuming constant thermal parameters measured at room temperature appears to be able to provide acceptable predictions of EGS thermal performance.

Machine learning algorithm optimization for intelligent prediction of rock thermal conductivity: A case study from a whole-cored scientific drilling borehole

Rock thermal conductivity (TC) is a key parameter in geothermal, petroleum geology, and basin research. Although experimental analysis relying on core samples is currently an effective way to obtain the TC of rocks, it is not always feasible as most boreholes have no or limited cores, making it difficult to establish TC model of geological body efficiently and accurately. This study sheds light on how machine learning algorithms can be used to accurately predict rock TC with easily accessible and high-resolution logging data. Based on 295 measured TC data, logging data, and vertical seismic profile (VSP) data collected from the whole-cored CSDP-2 borehole, the models including random forest (RF), convolutional neural network (CNN), support vector regression (SVR), and particle swarm optimization-SVR (PSO_SVR), were applied to predict the TC of the entire borehole section. Using a confusion matrix analysis, the primary-wave velocity (PWV) from the VSP survey, measured density, and logging data, including shallow lateral resistivity (LLS), compensated neutron log (CNL), density (DEN), gamma rays (GR), spontaneous potential (SP), and acoustic transit time (AC), were used as the input variables for training models and TC prediction. The results showed that the geophysical parameters reflecting those properties related to mineral composition, porosity and reservoir fluids of geological body can be well used to predict TC through machine learning algorithms. Regardless of unconsolidated sediments or rocks, the RF model showed stronger applicability and higher accuracy in TC prediction compared to the PSO_SVR and CNN models, while the SVR model showed poor applicability in this case study. The PWV data can effectively improve the accuracy of TC prediction of all models, and the RF model finally yielded the excellent performance with a correlation coefficient (> 0.86) and root mean squared error (8%) between the predicted and measured values. Future research should focus on studying the weighted analysis for the correlation between geophysical parameters and TC and developing more accurate predictive models for wider applications.

Thermal Conductivity of Rocks and Estimates of Heat Flow in the Lena–Anabar Interfluve (Siberian Platform)

Abstract —We present results of measurements of the physical properties (thermal conductivity, porosity, permeability, and density) of 65 air-dry sedimentary-rock samples from the cores of six deep wells drilled in the Lena–Anabar interfluve. The rocks are compact low-porosity, almost impermeable siltstones, sandstones, and dolomites mainly of Paleozoic and Precambrian ages. Correlations of thermal conductivity with porosity and bulk density have been established. The available information about the thermal conductivity of rocks as well as the production thermograms recorded after drilling made it possible to estimate the geothermal gradient and heat flow (q) for the Ust’-Olenekskaya-2370, Charchykskaya-1, Khastakhskaya-930, and D’yappal’skaya-1 wells. The gradient was calculated from the temperature values at the lower boundary of the permafrost (0 ºC) and at the bottom-hole. The determined heat flow varies from 37 to 70 mW/m2. These q estimates are consistent with the available data on the distribution of heat flow in the north of the Siberian Platform. The proposed method for heat flow estimation is worthy of use in other northern regions of Siberia for obtaining more geothermal data.

Influencing factors of rock thermal conductivity and applicability evaluation of its mixing law predictive models

The thermal conductivity (TC) of rocks is a very important parameter in geothermal theory and applied research, its value is related to rock composition, mineral grains characteristics, rock porosity, and pore fluid etc., and simultaneously is affected by formation thermodynamic environment (temperature, pressure,etc.). Statistical analysis results of the thermophysical property parameters of borehole samples from Jizhong Depression indicated that the TC is mainly controlled macroscopically by lithology, compared with sandstone, mudstone, conglomerate, and gneiss, dolomite has a greater TC. In the dry state, the TC of dolomite samples showed a decrease with increasing temperature, the values of TC decreased by 12.3–27.5% in the temperature interval of 30–130 °C. Moreover, under the same temperature conditions, excluding the effects of water content and mineral fraction, the TC of medium–coarse crystalline dolomite, medium–fine crystalline dolomite, microcrystalline dolomite, and mud-powder crystalline dolomite decreased successively, reflecting the influence of the mineral grain size on TC. The validity and applicability of six commonly used mixing law predictive models for TC were evaluated based on X-ray diffraction (XRD) data from 70 borehole samples. The results showed that Geometric mean model displayed the best fit (goodness of fit, R2 = 0.878) for rocks, and Voigt-Ruess-Hill average also showed a good fit, with an R2 of 0.868, and had the best prediction for mudstone (AME = 10.16, RMSE = 0.25). In cases where the calculated values deviate significantly from the measured values, it may reflect the limitation that the mixing models consider only the composition of minerals but ignores the structural characteristics of rocks.

Numerical Simulation of Internal Factors that Influence the Thermal Conductivity of Rock

Numerical Simulation of Internal Factors that Influence the Thermal Conductivity of Rock

Performance of a hybrid heating system based on enhanced deep borehole heat exchanger and solar energy

Deep borehole heat exchanger (DBHE) is a closed loop system without the problem of fluid losses, scale formation and corrosion; however, low rock thermal conductivity limits its performance. Enlightened by drilling mud loss in oil and gas industry, here an enhanced DBHE (EDBHE) is proposed by filling materials with much higher thermal conductivity into leakage formation or depleted gas and oil reservoir to enhance the thermal conductivity performance of rock. Solar thermal energy is stored into EDBHE during the non-heating season to replenish the loss of heat energy extracted during the heating season. The results show that average heat mining rate for 20 years operations is, respectively, 3686.5 and 26,384.4 kW for EDBHE filled by ordinary drilling mud and by composite materials with high thermal conductivity. The percentage reduction of heat mining rate for 20 years operations for EDBHE and the hybrid system of geothermal and solar energy are, respectively, 16.1 and 5.8%, indicating that the hybrid system can make the heat mining rate more stable.

Application of Soft Computing Techniques for Predicting Thermal Conductivity of Rocks

Due to the different challenges in rock sampling and in measuring their thermal conductivity (TC) in the field and laboratory, the determination of the TC of rocks using non-invasive methods is in demand in engineering projects. The relationship between TC and non-destructive tests has not been well-established. An investigation of the most important variables affecting the TC values for rocks was conducted in this study. Currently, the black-boxed models for TC prediction are being replaced with artificial intelligence-based models, with mathematical equations to fill the gap caused by the lack of a tangible model for future studies and developments. In this regard, two models were developed based on which gene expression programming (GEP) algorithms and non-linear multivariable regressions (NLMR) were utilized. When comparing the performances of the proposed models to that of other previously published models, it was revealed that the GEP and NLMR models were able to produce more accurate predictions than other models were. Moreover, the high value of R-squared (equals 0.95) for the GEP model confirmed its superiority.

Study on transient performance of geothermal desalination with variable geothermal fluid temperature

Geothermal desalination is one of renewable energy-driven desalination technologies. Due to the continuous decrease of geothermal fluid temperature, desalination rate changes with running of the system. Therefore, this paper presents a theoretical study on the transient performance of geothermal desalination with variable geothermal fluid temperature. Firstly, a comprehensive model coupling with transient geothermal extraction and heat and mass transfer in desalination unit was built to simulate the transient performance. Deep coaxial borehole heat exchanger is used for geothermal extraction and humidification-dehumidification unit is taken for thermal desalination. Then the transient performances of the system, freshwater production rate, geothermal fluid temperature and extraction were studied and the effects on the transient performances were also investigated. The simulation results show that freshwater production rate drops by about 60 % during 20-years operation with continuous declination of geothermal fluid temperature and extraction, and the drop trend is strengthened with BHE depth and geothermal gradient rising, but weakened with increase of rock thermal conductivity. The production rate increases with air flow rate rising but decreases with increase of seawater flow rate. Both production rate and humidifying capacity can be enhanced by improving air temperature at inlet of humidifier and reducing the inlet relative humidity.

Differential Thermal Regimes of the Tarim and Sichuan Basins in China: Implications for Hydrocarbon Generation and Conservation

AbstractThe uncertainty surrounding the thermal regimes of the ultra‐deep strata in the Tarim and Sichuan basins, China, is unfavorable for further hydrocarbon exploration. This study summarizes and contrasts the present‐day and paleo heat flow, geothermal gradient and deep formation temperatures of the Tarim and Sichuan basins. The average heat flow of the Tarim and Sichuan basins are 42.5 ± 7.6 mW/m2 and 53.8 ± 7.6 mW/m2, respectively, reflecting the characteristics of ‘cold’ and ‘warm’ basins. The geothermal gradient with unified depths of 0–5,000 m, 0–6,000 m and 0–7,000 m in the Tarim Basin are 21.6 ± 2.9 °C/km, 20.5 ± 2.8 °C/km and 19.6 ± 2.8 °C/km, respectively, while the geothermal gradient with unified depths of 0–5,000 m, 0–6,000m and 0–7,000 m in the Sichuan Basin are 21.9 ± 2.3 °C/km, 22.1 ± 2.5 °C/km and 23.3 ± 2.4 °C/km, respectively. The differential change of the geothermal gradient between the Tarim and Sichuan basins with depth probably results from the rock thermal conductivity and heat production rate. The formation temperatures at depths of 6,000 m, 7,000 m, 8,000 m, 9,000 m and 10,000 m in the Tarim Basin are 80°C–190°C, 90°C–220°C, 100°C–230°C, 110°C–240°C and 120°C–250°C, respectively, while the formation temperatures at depths of 6,000 m, 7,000 m, 8,000 m and 9,000 m in the Sichuan Basin are 120°C–200°C, 140°C–210°C, 160°C–260°C and 180°C–280°C, respectively. The horizontal distribution pattern of the ultra‐deep formation temperatures in the Tarim and Sichuan basins is mainly affected by the basement relief, fault activity and hydrothermal upwelling. The thermal modeling revealed that the paleo‐heat flow in the interior of the Tarim Basin decreased since the early Cambrian with an early Permian abrupt peak, while that in the Sichuan Basin experienced three stages of steady state from Cambrian to early Permian, rapidly rising at the end of the early Permian and declining since the late Permian. The thermal regime of the Sichuan Basin was always higher than that of the Tarim Basin, which results in differential oil and gas generation and conservation in the ultra‐deep ancient strata. This study not only promotes theoretical development in the exploration of ultra‐deep geothermal fields, but also plays an important role in determining the maturation phase of the ultra‐deep source rocks and the occurrence state of hydrocarbons in the Tarim and Sichuan basins.

Well and reservoir characterization using combined temperature and pressure transient analysis: A case study

Significant temperature variations are measured in oil and gas production wells with large pressure drawdown such as high production rate wells and tight formations. The considerable heating or cooling effects in the wellbore sandface invalidates the assumption of isothermal fluid flow in porous media. While this assumption satisfies most of the classic reservoir engineering analyses, the potential of slight thermal effects are attracting extensive interest and numerous thermal models have been proposed recently.The pitfalls and weaknesses of pressure transient analysis have been extensively investigated since 1930's which is still persistence despite developments of more accurate analytical and numerical models. Some of the weaknesses are rooted in the assumption of isothermal fluid flow in well test analysis methods.In this paper, we show the power and added value of combining temperature transient analysis to complement pressure transient analysis. Interestingly, the characteristics of skin effect such as radius and permeability of the damaged zone can be determined from temperature measurements. We study various parameters such as rock and fluid heat capacity, rock thermal conductivity, rock porosity, rock permeability and skin properties to illustrate the effect of each parameter on wellbore temperature data and hence the application of TTA for reservoir characterization. Using an accurate thermal flow mode, a case study has been done to investigate the importance of temperature transient analysis to better characterize an oil field well.

Lithospheric Thermal Structure in Jinggangshan City: Implications for High Geothermal Background

Jinggangshan City, which is located in the southwestern part of Jiangxi Province, is rich in hot springs. However, lack of geothermal studies has limited the exploration and utilization of the geothermal resources in this city. This study estimated the terrestrial heat flow in Jinggangshan City through well logging and analyses of rock thermal conductivity and heat production. Based on this and the surrounding geoscience transect and the Crust 1.0 model, this study constructed a one-dimensional lithospheric thermal structure by solving the steady-state heat conduction equation. Furthermore, the deep temperature distribution in Jinggangshan City was obtained to better understand the geodynamic condition of the geothermal resources in this city. The results show that the heat flow in this city is around 83.52 mW/m2, indicating the high heat background for the formation of geothermal resources. According to the lithospheric thermal structure of Jinggangshan City, the mantle contributes more to the terrestrial heat flow (qm/qc > 1) than the crust. The temperature of the Mohorovicic discontinuity (the Moho) is 671.7°C, which is consistent with that below the Tanlu deep fault (620–690°C). Moreover, the calculated depth of the Curie surface (585°C) is 27 km, which is consistent with the Curie isotherm depth estimated from aeromagnetic data. This consistency verifies the validity of the lithospheric thermal structure of Jinggangshan City constructed in this study. In summary, the high heat background plays an important role in the formation of geothermal resources in Jinggangshan City.

A comprehensive investigation on U-tube ground heat exchanger performance considering insulation layer in deep geothermal system

This study established a full-size coupling model of unsteady flow and heat transfer between U-tube and ground considering the insulation layer, which was solved by the finite volume method. The model's reliability was validated through experimental data of geothermal U-tube in Xi'an. The maximum relative error of this model was 6.46% in 2–6 h, and the average relative error was 0.51% in 7–72 h. This model performed better than the other two models published. According to the outlet temperature, thermal power, quantity of heat, and the temperature distribution of the U-tube at different insulation depths, the optimal insulation depth was the intersection of the ground temperature and the temperature curve in the tube and the insulation depth was 1615.85 m. Analyzed the influence of flow rate and other parameters on outlet temperature and thermal power, the sensitivity of each factor to heat extraction power was obtained by orthogonal test. The results showed that the flow rate was the most sensitive factor to thermal power, and the percentage loss of water and the thermal conductivity of rock were generally sensitive to thermal power. This study could provide a theoretical reference for developing and utilizing u-tube geothermal in deep layers.

Thermal conductivity, density and porosity of sedimentary and metamorphic rocks from the Lower and Higher Himalaya, Western Himalaya, India

SUMMARY Thermal conductivity at ambient conditions is a vital parameter in the determination of heat flow, thermal modelling and various geoengineering purposes. We have measured thermal conductivity in the laboratory at ambient conditions using a steady-state method on 69 samples of sedimentary and metamorphic rocks from the Western Himalaya, India, for the first time covering major lithologies of the region. Density and porosity measurements have been carried out along with petrographic and geochemical studies to characterize these rocks. The investigated rocks include sandstone, limestone, dolomitic limestone, quartzite, slate, phyllite and schist. The average thermal conductivity is found to be the highest (5.4 W m–1 K–1) for quartzite, moderate (ranges between 3.2 and 4.2 W m–1 K–1) for sandstone, limestone and dolomitic limestone and lowest (ranges between 2.6 and 2.9 W m–1 K–1) for the slate, phyllite and schist. The average values of the porosity for the rocks are less than 2 per cent. The variations in thermal conductivity within each rock type more or less reflect the compositional change, rather than the porosity. The measured thermal conductivity of the sandstone and limestone is found much higher than usually observed in such rocks, while it is on the lower side in the case of quartzite, phyllite and schist. Moreover, sedimentary rocks have higher density and lower porosity than usually found in such rocks. In fact, in this region, the sedimentary rocks show a similar density to that of the metamorphic rocks. The average density in sedimentary and metamorphic rocks varies from 2590 to 2780 kg m–3 and 2630 to 2740 kg m–3, respectively. The study region comes under the seismic gap, and several hot springs also exist here. Therefore, the obtained results will be useful in thermal modelling, which is critical for the understanding of earthquake nucleation.

Experimental Determination of Polycrystalline Salt Rock Thermal Conductivity, Diffusivity and Specific Heat From 20 to 240°C

Salt rock is recognized as one of the most suitable parent rocks for geological disposal of high level radioactive waste due to its low permeability, good ductility, good thermal conductivity and damage self-healing properties. The thermal conductivity of salt rock directly affects the temperature of disposal storage and surrounding rock, high temperature will lead to a series of problems such as nuclear waste storage tank rupture, mechanical and permeability reduction of surrounding rock. In this paper, the thermal conductivity, specific heat and thermal diffusion coefficient of NaCl single crystal made by crystallization method in the laboratory and polycrystalline salt rock from Khewra salt mine were measured in the range of 22–240°C by the transient plane source method. The results showed that the thermal conductivity and thermal diffusivity of salt rock decrease gradually with the increase of temperature, while the specific heat capacity increases with the increase of temperature. The thermal conductivity of salt rock is slightly lower than that of single-crystal NaCl. The reason for this phenomenon may be that there are a few pores in salt rock. Based on the experimental data, the models of thermal conductivity, thermal diffusivity and specific heat of salt rock with temperature were established. The results can provide a reference for the construction of underground salt rock high-level radioactive waste disposal repository. Based on the thermal conductivity model of polycrystalline salt rock established in this paper, the temperature field evolution during the operation of the underground salt rock high-level nuclear waste repository in 1,000 years was studied. It was found that the temperature of the glass solidified of high-level radioactive waste reached the highest (177.6°C) and then dropped rapidly. The decay heat radiation influence radius of the nuclear waste reaches its maximum in about 50 years of operation of the repository and then gradually decreases.

A study on modeling a deep sand geothermal field in South China

It is crucial for financial providers, investment groups, resource developers and exploration companies to rate a new geothermal project in the respect of resource and reserve. The existing volumetric method is generally constrained by limited information when projects at the early stage of development. The objective of this study is to estimate the potential of a geothermal field by a refined geological model and 3D numerical temperature model. We establish a fine geological model of a geothermal field in South China and thereby calculate the conductive 3D numerical temperature model. Based on a comprehensive analysis and interpretation of borehole measured data and well-log data, the regional variation and spatial distribution of thermal and petrophysical properties are both incorporated in the geological model. The results show that the Neogene and Quaternary strata in the study area have an average porosity of 36% and an average rock thermal conductivity of 3.15 W (m K)−1, the Weizhou Formation have an average porosity of 29% and an average rock thermal conductivity of 2.54 W (m K)−1, the Liushagang Formation have an average porosity of 22 % and an average thermal conductivity of 2.21 W (m K)−1, the Changliu Formation have an average porosity of 13% and an average thermal conductivity of 2.75 W (m K)−1. Based on the fine geothermal geological model, the heat is assumed to be driven by conduction, and the results show that the bottom temperature of the Weizhou Formation in the hydrothermal sandstone reservoir is 96-168 degrees Celsius, and the high temperature area is concentrated near the down-thrown side of the fault, indicating that the geothermal resources are favorable area and the geothermal energy is 7.89 × 1014 J.

Thermal Property of Granite in Deep Strata and Its Effect on Thermal Zone of Surrounding Rock

In order to clarify the changes in the thermophysical properties of rocks in deep high-temperature strata and their influence on the temperature field of the surrounding rocks, thermal property tests were conducted on rock samples taken from 1,500 to 2,000 m depth in the Xiling well construction area of Sanshandao gold mine. According to the difference equation based on the principle of heat balance, the numerical solution of unsteady heat conduction of surrounding rock can be deduced. In addition, we can explore the dynamic process of the heat-regulating ring that under ventilation measures in deep high geothermal strata and analyze its influence on the dynamic process based on the equation. The result of the research shows that the thermal conductivity of rock is mainly determined by the mineral composition and is influenced by factors such as mesostructure. Calcite and muscovite of granite have a great impact on lithology, even they just account for a relatively small percent. As the ground temperature increases step by step, the variation of the thermal conductivity of rock is less and the thermal diffusion coefficient of rock and its ability to transmit temperature changes both decrease. On the contrary, as the specific heat capacity of rock increases, its heat storage capability enhanced. Therefore, the expansion range of the heat-regulating ring of surrounding rock is influenced by mineral composition and the temperature of the environment, and the influence of the former is much greater than the latter.

Machine Learning Algorithm Optimization for Intelligent Prediction of Rock Thermal Conductivity: A Case Study from a Whole-Cored Scientific Drilling Borehole

Machine Learning Algorithm Optimization for Intelligent Prediction of Rock Thermal Conductivity: A Case Study from a Whole-Cored Scientific Drilling Borehole

Joint interpretation technology of favorable HDR geothermal resource exploration in Northern Songliao Basin

Hot dry rock (HDR) is considered a new clean and renewable energy source. China is rich in HDR resources, but viable and reliable resource evaluation techniques and exploration methods have not been available yet. This research method, consisting of deep exploration combined with shallow drilling, screens the geothermal anomaly regions using heavy magnetic, electric measurement, seismic and thermal joint interpretation technology, and verifies the geophysical multiplicity with massive oilfield drilling data to locate the favorable HDR target region. The research results show a regionally geothermal abnormal area. We use relative impedance combined with seismic profile to recognize the HDR target region. The geophysical exploration and geological joint interpretation technology are faster and more accurate than the single geophysical exploration technology. The comprehensive analysis believes that the high resistance granite body in the southern Paleo-central uplift zone, with its area 500km2, its thickness 150–330m, its static formation temperature reaching 152° in the depth of 3360m, its high rock thermal conductivity, its good deep fracture, and base fracture development, is a fragmented granite and weathered shell, easy for artificial reservoir re-constructing. There is high preciseness in locating the favorable target region for HDR development.

Characteristics of the Siberian coal basins permafrost: An example of Ytymdja depression

Ytymdja depression is one of the Mesozoic structures with discovered large coal deposits of the Aldan Upland. Lack of industrial development and farness from agglomerations explain the knowledge gap about the environmental conditions of the Ytymdja depression. A field monitoring network with existing deep boreholes was absorbed to investigate permafrost conditions and to assess potential impacts of local factors and climate change. This paper describes analyse temperatures at the depth down to 240 m by these boreholes with air and ground temperatures of the Ytymdja depression to determinate permafrost conditions. The research was carried out in a 1800 km2 area of the South Yakutia, Siberia, using satellite imagery-based classification. The field investigations and analysis of ground temperatures indicated that permafrost underlies of the ground entire area of Ytymdja depression, but likely absent under large rivers. Permanent negative temperatures have been detected in the borehole, which shows evidence of the existing of widespread permafrost conditions nowadays in the coal basins in Siberia. Permafrost temperatures vary between −3.1 °C and −1.5 °C at 35 m below the surface, and annual ground temperatures at 1 m depth ranged from −4.9 °C to −1.2 °C. Thermal conductivity of rocks determined by individual core samples varies from 1.1 to 2.9 W m−1 °C−1 with geothermal heat flux in the permafrost zone of 0.02 W m−2 and an increase in the zone below permafrost to 0.03 W m−2. Spatial modelling for the entire territory of the Ytymdja depression deduced a continuous permafrost distribution with a thickness between 106 and 251 m. The considerable thickness of permafrost probably prevents the emission of greenhouse gases from coal seams into the atmosphere, but detailed studies in this direction have yet to be carried out.