More Like this

1. Geology Matters for Antarctic Geothermal Heat

   https://doi.org/10.1029/2024GL110098  

   Stål, Tobias; Halpin, Jacqueline A; Goodge, John W; Reading, Anya M (July 2024, Geophysical Research Letters)

   Abstract Geothermal heat plays a vital role in Antarctic ice sheet stability. The continental geothermal heat flow distribution depends on lithospheric composition and ongoing tectonism. Heat‐producing elements are unevenly enriched in the crust over deep time by various geological processes. The contribution of crustal heat production to geothermal heat flow is widely recognized; however, in Antarctica, crustal geology is largely hidden, and its complexity has frequently been excluded in thermal studies due to limited observations and oversimplified assumptions. Li and Aitken (2024),https://doi.org/10.1029/2023GL106201take a significant step forward, focusing on Antarctic crustal radiogenic heat. Utilizing gravity inversion and rock composition data, they show that the crustal heterogeneity introduces considerable variability to heat flow. However, modeling crustal heat production proves challenging because it lacks distinct associations with geophysical observables and has a narrow spatial association. Robust quantification of geothermal heat production and heat flow must incorporate explicit aspects of geology. 

   more » « less
2. Applying machine learning to characterize and extrapolate the relationship between seismic structure and surface heat flow

   https://doi.org/10.1093/gji/ggae218  

   Zhang, Shane; Ritzwoller, Michael_H (June 2024, Geophysical Journal International)

   SUMMARY Geothermal heat flow beneath the Greenland and Antarctic ice sheets is an important boundary condition for ice sheet dynamics, but is rarely measured directly and therefore is inferred indirectly from proxies (e.g. seismic structure, magnetic Curie depth, surface topography). We seek to improve the understanding of the relationship between heat flow and one such proxy—seismic structure—and determine how well heat flow data can be predicted from the structure (the characterization problem). We also seek to quantify the extent to which this relationship can be extrapolated from one continent to another (the transportability problem). To address these problems, we use direct heat flow observations and new seismic structural information in the contiguous United States and Europe, and construct three Machine Learning models of the relationship with different levels of complexity (Linear Regression, Decision Tree and Random Forest). We compare these models in terms of their interpretability, the predicted heat flow accuracy within a continent and the accuracy of the extrapolation between Europe and the United States. The Random Forest and Decision Tree models are the most accurate within a continent, while the Linear Regression and Decision Tree models are the most accurate upon extrapolation between continents. The Decision Tree model uniquely illuminates the regional variations of the relationship between heat flow and seismic structure. From the Decision Tree model, uppermost mantle shear wave speed, crustal shear wave speed and Moho depth together explain more than half of the observed heat flow variations in both the United States [$$r^2 \approx 0.6$$ (coefficient of determination), $$\mathrm{RMSE} \approx 8\, {\rm mW}\,{\rm m}^{-2}$$ (Root Mean Squared Error)] and Europe ($$r^2 \approx 0.5, \mathrm{RMSE} \approx 13\, {\rm mW}\,{\rm m}^{-2}$$), such that uppermost mantle shear wave speed is the most important. Extrapolating the U.S.-trained models to Europe reasonably predicts the geographical distribution of heat flow [$$\rho = 0.48$$ (correlation coefficient)], but not the absolute amplitude of the variations ($r^2 = 0.17$), similarly from Europe to the United States ($$\rho = 0.66, r^2 = 0.24$$). The deterioration of accuracy upon extrapolation is caused by differences between the continents in how seismic structure is imaged, the heat flow data and intrinsic crustal radiogenic heat production. Our methods have the potential to improve the reliability and resolution of heat flow inferences across Antarctica and the validation and cross-validation procedures we present can be applied to heat flow proxies other than seismic structure, which may help resolve inconsistencies between existing subglacial heat flow values inferred using different proxies. 

   more » « less
3. The Green’s Function-Based Thermal Analysis of a Spherical Geothermal Tank in a Semi-Infinite Domain

   https://doi.org/10.1115/1.4054568  

   Wang, Tengxiang; Wu, Chunlin; Zhang, Liangliang; Yin, Huiming (July 2022, Journal of Applied Mechanics)

   Abstract The Green’s function of a bimaterial infinite domain with a plane interface is applied to thermal analysis of a spherical underground heat storage tank. The heat transfer from a spherical source is derived from the integral of the Green’s function over the spherical domain. Because the thermal conductivity of the tank is generally different from soil, the Eshelby’s equivalent inclusion method (EIM) is used to simulate the thermal conductivity mismatch of the tank from the soil. For simplicity, the ground with an approximately uniform temperature on the surface is simulated by a bimaterial infinite domain, which is perfectly conductive above the ground. The heat conduction in the ground is investigated for two scenarios: First, a steady-state uniform heat flux from surface into the ground is considered, and the heat flux is disturbed by the existence of the tank due to the conductivity mismatch. A prescribed temperature gradient, or an eigen-temperature gradient, is introduced to investigate the local temperature field in the neighborhood of the tank. Second, when a temperature difference exists between the water in the tank and soil, the heat transfer between the tank and soil depends on the tank size, conductivity, and temperature difference, which provide a guideline for heat exchange design for the tank size. The modeling framework can be extended to two-dimensional cases, periodic, or transient heat transfer problems for geothermal well operations. The corresponding Green’s functions are provided for those applications. 

   more » « less
4. An Observational and Modeling Study of Inverse‐Temperature Layer and Water Surface Heat Flux

   https://doi.org/10.1029/2023GL104358  

   Wang, Jingfeng; Liu, Heping; Shen, Lian (August 2023, Geophysical Research Letters)

   Abstract An “inverse‐temperature layer” (ITL) of water temperature increasing with depth is predicted based on physical principles and confirmed by in situ observations. Water temperature and other meteorological data were collected from a fixed platform in the middle of a shallow inland lake. The ITL persists year‐around with its depth on the order of one m varying diurnally and seasonally and shallower during daytimes than nighttimes. Water surface heat flux derived from the ITL temperature distribution follows the diurnal cycle of solar radiation up to 300 W m⁻²during daytime and down to 50 W m⁻²during nighttime. Solar radiation attenuation in water strongly influences the ITL dynamics and water surface heat flux. Water surface heat flux simulated by two non‐gradient models independent of temperature gradient, wind speed and surface roughness using the data of surface temperature and solar radiation is in close agreement with the ITL based estimates. 

   more » « less
5. The northeastern Algeria hydrothermal system: gravimetric data and structural implication

   https://doi.org/10.1186/s40517-023-00258-2  

   Bayou, Yasser; Abtout, Abdeslam; Renaut, Rosemary A.; Bouyahiaoui, Boualem; Maouche, Said; Vatankhah, Saeed; Berguig, Mohamed Cherif (May 2023, Geothermal Energy)

   Abstract The Tell Atlas of Algeria has a huge potential for hydrothermal energy from over 240 thermal springs with temperatures up to$$98^\circ$$ ${98}^{\circ }$C in the Guelma area. The most exciting region is situated in the northeastern part which is known to have the hottest hydrothermal systems. In this work, we use a high-resolution gravity study to identify the location and origin of the hot water, and how it reaches the surface. Gravimetric data analysis shows the shapes of the anomalies arising due to structures at different subsurface depths. The calculation of the energy spectrum for the data also showcases the depths of the bodies causing anomalies. 3D-Euler deconvolution is applied to estimate the depths of preexisting tectonic structures (faults). These preprocessing steps assist with assessing signal attenuation that impacts the Bouguer anomaly map. The residual anomaly is used in a three-dimensional inversion to provide a subsurface density distribution model that illustrates the locations of the origin of the dominant subsurface thermal systems. Overall, the combination of these standard processing steps applied to the measurements of gravity data at the surface provides new insights about the sources of the hydrothermal systems in the Hammam Debagh and Hammam Ouled Ali regions. Faults that are key to the water infiltrating from depth to the surface are also identified. These represent the pathway of the hot water in the study area. 

   more » « less