Terrestrial Heat Research Articles

High-Resolution 3D Shear-Wave velocity structure in xiong’an New Area, Beijing (China), revealed by short-period dense seismic array

The 3D shear-wave velocity (Vs) structure in the shallow crustal of Xiong’an New Area can reveal the sediment characteristics and the tectonic features of the blind faults. They are essential for earthquake hazard reduction and geothermal resource exploration in urban areas. The dense array detection method has proved to be an effective technology tool for obtaining the 3D Vs model of the urban area. Using the seismic ambient noise recorded by Xiong’an dense array, we separately conducted the frequency-Bessel transform method and the fast marching technology to estimate short-period (0.4–2.4 s) and long-period (2.5–6 s) fundamental Rayleigh wave phase velocity dispersions. By jointly inverting these dispersions, we finally obtain a fine shallow-deep (0–5 km) 3D Vs model. Our Vs structure correlates well with the tectonic units and reveals the overall stability of the shallow crust structure of the Xiong’an New Area. We extract 3D depths distribution characteristics of the Quaternary and Neogene bottom boundaries from 3D Vs model, which respectively indicates that the Xiongan New Area has been in a relatively stable tectonic position since the Cenozoic. We also provide new evidence to further determine the buried depth and extension patterns of the pre-existing faults or unconformable contact interfaces. Lastly, we analyze and summarize the 3D characteristics of structural sedimentary and potential geothermal exploration areas through conducting comprehensive analysis and interpretation of the regional terrestrial heat flow and geological drilling, which propose a new technical idea for the prospecting and assessing of the geothermal resources based on 3D Vs model.

Bi-Level Operation Optimization and Performance Analysis for a Distributed Energy System with Energy Network

The increasing energy crisis and environmental problems promote the development of distributed energy systems (DESs) that utilize combined heat and power technology, renewable energy technology, and waste heat recovery technology to meet various load requirements. Although there is existing work and research on a variety of DESs, most previous studies tend to focus on energy production with little consideration of a distributed energy network and its energy loss, which results in large errors in energy-efficiency calculations and performance analyses. In this paper, a new DES model is proposed with full consideration of an energy network and the full use of solar energy, terrestrial heat, and exhaust gases. At the same time, an effective bi-level optimization method is also proposed for the daily operation of the DES in order to improve the system performance and benefits in the energy, the economy, and the environment. Specifically, the co-generation energy station and water heating network in the DES are optimized separately with two different optimization models. The first-level optimization model is used to seek the optimal values of water mass flow rate and water temperature of the water heating network, and the second-level optimization model is built to determine the optimal energy purchasing strategy and the optimal energy outputs of the co-generation energy station. In order to verify the advantages and effectiveness of the proposed system and method, a contrastive simulation study is undertaken to provide a comparison of the global optimization method. Simulation results show that energy loss, energy cost, and energy consumption of the DES using the bi-level optimization operation strategy only account for 22.51%, 33.42%, and 51.31% of the quantities of the global optimization method, respectively. The hourly curves of the optimal operating variables also demonstrate that the proposed bi-level optimization method can improve the operating stability of the DES better than the global optimization method.

Terrestrial Heat Flow and Lithospheric Thermal Structure Characteristics in Nanping City of Hainan

Terrestrial Heat Flow and Lithospheric Thermal Structure Characteristics in Nanping City of Hainan

Improved performance of thermophotovoltaic energy conversion with Tamm plasmon emitters enabled by back gapped reflectors

A thermophotovoltaic (TPV) system that can convert thermal radiation from terrestrial heat sources into electricity, plays an important role in energy utilization, waste heat recovery and so on. In order to enhance the conversion efficiency of a TPV system having a narrow-band thermal emitter, we propose to add a back gapped reflector (BGR) to recover more out-of band (OOB) photons. We first design a Tamm plasmon thermal emitter to yield a narrow-band emission peak matching well with the bandgap of the InGaAs cell. Then, we add a BGR on the PV cell to regulate the absorption spectrum of the cell. Results show that, compared to the back surface reflector (BSR), the TPV system with the Au BGR cell has a higher power conversion efficiency (PCE), because more OOB photons are reflected back to the emitter by the Au BGR cell, so that the absorbed power by the cell decreases while the output power is improved. Due to the contribution of recycled OOB photons, at 1500 K, a 1.7 % OOB reflectance gain of the BGR (h = 0.2 μm, t = 1.2 μm) can actually increase the PCE by about 4 %. In addition, a thin PV cell and an appropriately thick air gap layer of 0.4–0.6 μm are suggested to obtain a high η × Pout. The PCE of the TPV system based on the Tamm plasmon emitter is higher and becomes saturated at a lower temperature than the broad-band SiC emitter. This work may facilitate high-performance TPV energy conversion.

An updated terrestrial heat flow data set for the Junggar basin, northwest China: implications for geothermal resources

SUMMARY Terrestrial heat flow plays a vital role in determining the present thermal regimes of sedimentary basins, offering a robust foundation for understanding hydrocarbon maturation processes and the geothermal resource potential. The Junggar basin is one of the largest and most petroliferous superimposed petroleum basins in China. However, research on heat flow is scarce. In this study, 94 new high-quality heat flow values are derived from through borehole temperature analysis and thermal conductivity measurements of rocks. The results indicate that (1) the geothermal gradient in the basin varies from 11.4 to 28.3 °C km−1, with a mean value of 20.9 ± 3.4 °C km−1, and the heat flow varies from 23.4 to 64.5 mW m−2, with a mean value of 45.1 ± 8.4 mW m−2. The overall low geothermal gradient and heat flow are attributed to the continuous cooling during the Meso-Cenozoic. (2) At basin scale, the high heat flow values are primarily concentrated in areas characterized by basement uplift, whereas the low heat flow values are mainly located in the depressions. This suggests that thermal refraction is the primary factor influencing the heat flow variations. (3) Although large-scale development and utilization of geothermal resources face challenges, certain local areas in the basin show promise for geothermal resource utilization.

Lithospheric resistivity structure of the Xuefeng Orogenic Belt and its implications for intracontinental deformation in South China

The Xuefeng Orogenic Belt (XFOB), located in the central part of the South China Block, is a typical Mesozoic intracontinental orogen in the central Jiangnan Orogenic Belt. By collecting magnetotelluric (MT) data across the XFOB, we obtained the resistivity structure of the lithosphere, which sheds light on the Mesozoic intracontinental orogenic processes in the XFOB. The resistivity structure reveals a low-resistivity body (<10 Ω∙m), beneath the XFOB, dipping southeast wards from a depth of 10 km to the bottom of the crust. This conductor is interpreted as a relic of the lower detachment zone, which coincides with low-density areas obtained from joint inversion of seismic models. It is believed to result from mineral fluids migrating along the thrust fault and squeezing sulfides into folds. Four low-resistivity bodies were identified at three extensional locations along the Jiangshan-Shaoxing Fault and at the Cili-Baojing Fault. The low-resistivity body (<10 Ω∙m) at the junction of the Shaoyang and the Hengyang Basin is located at the point where the Moho depth thins. The variation trend of the terrestrial heat flow values, with this low-resistivity body as the plate boundary, is consistent with the average variation of the terrestrial heat flow values within the block. We propose that the low-resistivity body under the Qidong-Yongzhou-Guilin fault conforms to the characteristics of the suture zone in the resistivity structure. Its existence indicates that the missing location of the Jiangshan-Shaoxing suture zone of the Yangtze and Cathaysia Block in the middle-southwest section of the South China Block is the Qidong-Yongzhou-Guilin fault. The Yangtze Block and the Hengyang Basin show high resistivity, the depth of which reaches 100 km and 40 km, respectively. Based on the resistivity model and geological data, the XFOB experienced Triassic compression, leading to basement decollement, thrusting, and nappe structures due to low-angle Paleo-Pacific Plate subduction. This compression also led to the uplift of the orogenic belt. Moreover, under the tension caused by the high-angle retreat of the Paleo-Pacific Plate, the Cretaceous extensional tectonics led to detachment along the thrust faults, forming half-graben and basin structures along the margins.

Geothermal Resource Assessment and Development Recommendations for the Huangliu Formation in the Central Depression of the Yinggehai Basin

As a renewable resource, geothermal energy plays an increasingly important role in global and regional energy structures. Influenced by regional tectonic activities, multi-stage thermal evolution, and continuous subsidence, the subsurface temperatures in the Yinggehai Basin has been consistently rising, resulting in the formation of multiple geothermal reservoirs. The Neogene Huangliu Formation, with its high geothermal gradients, suitable burial depths, considerable thickness, and wide distribution, provides excellent geological conditions for substantial geothermal resources. However, the thermal storage characteristics and geothermal resources of this formation have not been fully assessed, limiting their effective development. This study systematically collected and analyzed drilling, geological, and geophysical data to examine these reservoirs’ geometric structures, thermal properties, and physical characteristics. Further, we quantitatively evaluated the geothermal resource potential of the Huangliu Formation and its respective reservoirs through volumetric estimation and Monte Carlo simulations, pointing zones with high geothermal prospects and formulating targeted development strategies. The findings indicate: (1) The Yinggehai Basin exhibits an average geothermal gradient of 39.4 ± 4.7 °C/km and an average terrestrial heat flow of 77.4 ± 19.1 mW/m2, demonstrating a favorable geothermal background; (2) The central depression of the Huangliu Formation harbors considerable geothermal resource potential, with an average reservoir temperature of 140.9 °C, and a total geothermal resource quantified at approximately 2.75 × 1020 J, equivalent to 93.95 × 108 tec. Monte Carlo projections estimate the maximum potential resource at about 3.10 × 1020 J, approximately 105.9 ×108 tec. (3) Additionally, the R14 and R23 reservoirs have been identified as possessing the highest potential for geothermal resource development. The study also proposes a comprehensive utilization model that integrates offshore geothermal power generation with multiple applications. These findings provide a method for the evaluation of geothermal resources in the Yinggehai Basin and lay a foundation for the sustainable development of resources.

Terrestrial Heat Flow and Lithospheric Thermal Structure of the Hubao Basin, North Central China

Terrestrial Heat Flow and Lithospheric Thermal Structure of the Hubao Basin, North Central China

Underestimated Land Heat Uptake Alters the Global Energy Distribution in CMIP6 Climate Models

AbstractCurrent global warming results in an uptake of heat by the Earth system, which is distributed among the different components of the climate system. However, current‐generation climate models deliver heat inventory and partitioning estimates of Earth system components that differ from recent observations. Here we investigate the global heat distribution under warming by using fully‐coupled CMIP6 Earth system model experiments, including a version of the MPI‐ESM with a deep land model component, accommodating the required space for more realistic terrestrial heat storage. The results show that sufficiently deep land models exert increased subsurface land heat uptake, leading to a heat uptake partitioning among the Earth system components that is closer to observational estimates. The results are relevant for the understanding of Earth's heat partitioning and highlight the importance of the land heat sink in the Earth heat inventory.

Rock heat production and its contribution to terrestrial heat flow in the Northern Songliao Basin, Northeast China

Rock heat production and its contribution to terrestrial heat flow in the Northern Songliao Basin, Northeast China

Machine Learning-Based Prediction of Terrestrial Heat Flow in the Songliao Basin

Machine Learning-Based Prediction of Terrestrial Heat Flow in the Songliao Basin

Multimodel ensemble estimation of Landsat-like global terrestrial latent heat flux using a generalized deep CNN-LSTM integration algorithm

Accurate estimates of high-spatial-resolution global terrestrial latent heat flux (LE) from Landsat data are crucial for many basic and applied research. Yet current Landsat-derived LE products were developed using single algorithm with large uncertainties and discrepancies. Here we proposed a convolutional neural network-long short-term memory (CNN-LSTM)-based integrated LE (CNN-LSTM-ILE) framework that integrates five Landsat-derived physical LE algorithms, topography-related variables (elevation, slope and aspect) and eddy covariance (EC) observations to estimate 30-m global terrestrial LE. CNN-LSTM-ILE not only conserves good performance of LE estimation from pure deep learning (DL) algorithm, but partially inherits physical mechanism of the individual physical algorithms for improving the generalization of the integration algorithms for extreme cases. CNN-LSTM is an algorithm that combines two deep learning structures (CNN and LSTM) to effectively utilize the spatial and temporal information contained in the forcing inputs. The data were collected from 190 globally distributed EC observations from 2000 to 2015 and were provided by FLUXNET. The cross-validation results indicated that the CNN-LSTM integration algorithm improved the LE estimates by reducing the root mean square error (RMSE) of 5–8 W/m2 and increasing Kling-Gupta efficiency (KGE) of 0.05–0.16 when compared with the individual LE algorithms and the results of three other machine learning integration algorithms (multiple linear regression, MLR; random forest, RF; and deep neural networks, DNN). The CNN-LSTM integration algorithm had highest KGE (0.81) and R2 (0.66) compared to ground-measured and was applied to generate the Landsat-like regional and global terrestrial LE. An innovation of our strategy is that the CNN-LSTM-ILE model integrates pixel proximity effects and daily LE variations to enhance the accuracy of 16-day LE estimations. This approach can produce a more reliable Landsat-like global terrestrial LE product to improve the representativeness of heterogeneous regions for monitoring hydrological variables.

Analysis of the factors influencing heat transfer and control strategy optimization for Medium-Shallow array borehole heat exchangers

Medium-shallow array borehole heat exchangers (MSABHEs) exhibit high heat transfer capacity and low initial investments. However, limited research has been conducted on utilizing medium-shallow geothermal energy utilization for heating and cooling. In this study, a heat transfer model for MSABHEs was established. Second, the suitability of the heat transfer model was validated using experimental data. Subsequently, the model was used to analyze the impacts of the borehole spacing, terrestrial heat flow, circulating fluid flow rate, and ground depth on heat transfer in MSABHEs. Finally, an optimization strategy for the circulating fluid was proposed based on dynamic building loads, and the impacts of various circulating liquid control strategies on the heat pump performance were compared. The results indicated that the heat transfer capacity of the MSABHEs increased with increasing borehole spacing. When the spacing was greater than 8 m, thermal interference between the boreholes could be ignored. Under the condition of imbalanced cooling and heating loads, the variable flow strategy could increase the heating coefficient of performance (COP) and cooling COP of the heat pump by approximately 11.12 % and 14.28 %, respectively. Through this control method, the power consumption of the water pump could be reduced from 15840 kW to 8527 kW. These findings could provide a theoretical basis and technical guidance for MSABHE applications.

Terrestrial Heat Flow and Thermal Models of the Lithosphere

Terrestrial Heat Flow and Thermal Models of the Lithosphere

Prediction of Terrestrial Heat Flow in Songliao Basin Based on Deep Neural Network

AbstractHeat flow is a geothermal parameter for indicating the heat source distribution and evaluating geothermal reservoirs. Only 1,230 heat flow points are distributed unevenly in China, mainly concentrated in high‐temperature geothermal and southeast regions. The Songliao Basin is a potential geothermal field in China. Still, only 20 measurement points are known, making evaluating the geothermal genetic mechanism difficult. Sparse data interpolation using deep learning methods is highly accurate and widely used in fields such as image processing. In this work, we propose a deep neural network for predicting heat flow in the Songliao Basin. More than 4,000 global heat flows and 23 geological and geophysical parameters are used as reference constraints for training. The uncertainty error of the prediction is estimated based on the correlation and distance‐based generalized sensitivity analysis. The results show that the maximum heat flow is 85 mW/m2, the average is 67.1 mW/m2, and the error with the measured data is 10.64%. The previous geophysical and geological interpretation results indicate that the heat flow is higher in the west and lower in the east, with high anomalies in the central region, which may be related to the uplift of the deep mantle and the depression of the shallow low‐velocity sedimentary layer. Some high‐temperature melt bodies are in the deep layers, forming the current potential geothermal field. The measured data validates that the DNN is an effective method for predicting regional‐scale heat flow, providing reliable heat source information for evaluating geothermal resources.

Terrestrial heat flow and subsidence of the Eastern Mediterranean Sea

We analysed the bathymetry and both marine and continental heat-flow data of the Eastern Mediterranean Sea basins. Bathymetry was corrected for the subsidence caused by sediment deposition to obtain the water-loaded seafloor depth. The thermal measurements were critically reviewed and corrected for sedimentation by 1–13 mW m−2 and for climatic changes by 4–5 mW m−2 to infer the purely conductive terrestrial heat flow. The seafloor depths and thermal data of the Ionian, Herodotus and Levantine basins were compared to reference models of continental lithosphere stretching and ocean plate cooling. In the Levantine Basin, the seafloor depth of 5.0 km argues for a continental crust that thinned ∼100 Ma ago by a factor of 2.7. The seafloor depth of the Herodotus and Ionian basins (7.5 and 6.3 km, respectively) does not match the continental stretching model predictions, suggesting they are floored by oceanic lithosphere. The reference models for the plate cooling and subsidence only partly account for the seafloor depth of the Eastern Mediterranean Sea basins. The seafloor of the Ionian agrees or is slightly deeper than the reference models, while in the Herodotus, it may exceed the expected subsidence of about 1 km. Compared to the reference models of plate cooling, the heat flow of the Herodotus and Ionian basins is lower by about 10 mW m−2. Together with the seafloor depth and gravity anomaly pattern, this argues for a cold and thick lithosphere beneath the Ionian and Herodotus basins. The lower heat flow may suggest that the basins escape from classical schemes of oceanic lithosphere cooling or that the reference models cannot be used for such old seafloors.

Study on effective elastic thickness of lithosphere and its tectonic significance in surrounding area of Ordos Block

Based on EIGEN6C4 gravity field model data and ETOPO1 topographic data, we adopt the correlation analysis method based on Fan wavelet to calculate and analyze the distribution characteristics of effective elastic thickness (Te) and load ratio (F) of lithosphere in surrounding of Ordos block. On this basis, the relationship between the lithosphere Te and geological structure, seismic distribution, terrestrial heat flow and crustal deformation is analyzed. The results show that the lithosphere Te in the surrounding area of the Ordos block is obviously different among the tectonic blocks. The lithosphere Te value is low in the south of Qinling orogenic belt and the east of Fen-Wei graben basin. The maximum lithosphere Te value is distributed in the northwest and northeast margin of Ordos block. The lithosphere Te value is negatively correlated with the load ratio F. Earthquakes mainly occur in areas with low lithosphere Te value. Small lithosphere Te value indicates low strength of lithosphere. In such areas, the ability to resist crustal deformation is weak, and it is easy to generate stress accumulation and breed earthquakes. The area with high terrestrial heat flow value corresponds to low lithosphere Te value, showing a negative correlation. However, this negative correlation does not exist in the northwest margin of Ordos Block and Alashan border area, and the eastern margin of Ordos Lvliangshan area. Haiyuan-Liupanshan area has strong tectonic activity, frequent earthquakes and low lithosphere Te value. The internal strain accumulation of Ordos block is small, and the lithosphere Te value is high. The strain rate of the northern Shanxi fault depression zone is large, but the lithosphere Te value is also large, it is speculated that the terrestrial heat flow is the main factor affecting the lithosphere Te value.

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.

Geochemical and H–O–Sr–B isotope signatures of Yangyi geothermal fields: implications for the evolution of thermal fluids in fracture-controlled type geothermal system, Tibet, China

High-temperature hydrothermal systems are mainly distributed in the north–south graben systems of southern Tibet as an important part of the Mediterranean–Tethys Himalayan geothermal belt in mainland China. As the largest unit capacity and second stable operating geothermal power station in China, Yangyi is the fracture-controlled type geothermal field in the center of Yadong–Gulu Graben. In this paper, hydrogeological and hydrochemical characteristics, isotope composition (δD and δ18O, 87Sr/86Sr and δ11B) of borehole water, hot springs, and surface river samples were analyzed. From the conservative elements (such as Cl− and Li+) and δD and δ18O values, the geothermal water of the Yangyi high-temperature geothermal field is estimated to be of meteoric origin with the contributions of chemical components of the magmatic fluid, which is provided by partially molten granite as a shallow magmatic heat source. According to logging data, the geothermal gradient and terrestrial heat flow value of the Yangyi high-temperature geothermal field are 6.48 ℃/100 m and 158.37 mW m−2, respectively. Combining the hydrothermal tracer experiment, 87Sr/86Sr and δ11B ratios obtained with gradually decreasing reservoir temperatures from the Bujiemu stream geothermal zone to Qialagai stream geothermal zone, we suggested the deep geothermal waters were mixed with local cold groundwater and then flow northeastward, forming the shallow reservoir within the crushed zone and intersect spot of faults in the Himalayan granitoid. Furthermore, in the process of ascent, the geothermal water is enriched in K+, Na+, and HCO3− during the interaction with underlying Himalayan granitoid and pyroclastic rocks that occur as wall rocks. The detailed description and extensive discussion are of great significance for the further exploitation and utilization of north–south trending geothermal belts in Tibet.

Present geothermal field of the Santos Basin, Brazil

The Santos Basin, located in the southeastern waters of Brazil, is a passive continental margin basin with the most abundant deepwater petroleum resources in the world discovered to date. However, few studies have been conducted on the present geothermal fields of the Santos Basin, which severely restricts the oil and gas resource evaluation of the basin. This study first utilizes 35 temperature data from 16 post-salt drilling wells and 370 temperature data from 31 pre-salt drilling wells to calculate the post-salt and pre-salt geothermal gradients and terrestrial heat flows in the Santos Basin. Then, the basin simulation software BasinMod 1D is used to quantitatively evaluate the impacts of salt rock sedimentation on the present geothermal fields and the maturity of pre-salt hydrocarbon source rocks. The results demonstrate that the present post-salt geothermal gradient in the Santos Basin is 2.20–3.97 °C/100 m, with an average value of 2.99 °C /100 m, and the post-salt terrestrial heat flow is 54.00–97.32 mW/m2, with an average value of 73.36 mW/m2, while the present pre-salt geothermal gradient is 2.21–2.95 °C/100 m, with an average value of 2.53 °C/100 m, and the pre-salt terrestrial heat flow is 61.85–82.59 mW/m2, with an average value of 70.69 mW/m2. These values are characteristic of a low-temperature geothermal field in a zone with a stable structure. The sedimentation of the salt rock causes a decrease in the temperature of the pre-salt strata, which inhibits pre-salt hydrocarbon source rock maturity, with an inhibition rate of up to 1.32%. The inhibition degree decreases with increasing salt rock thickness. At the same time, the salt rock thickness is positively correlated with the present surface heat flow. The unique distribution of the salt rock and related salt structures lead to present terrestrial heat flow differences among different structural units in the basin. This study is of great significance for evaluating and exploring the pre-salt oil and gas resources in the Santos Basin.