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(a) Average ruggedness and standard deviation (1σ) associated with observed heat flow measurements. The dotted line (15 mWm⁻² is considered as the natural variability of heat flow in absence of hydrothermal circulation. (b) Cumulative hydrothermal heat loss with respect to Model 2 (see Figure 2). The red line represents the cumulative perturbation according to an empirical relationship from local studies (Le Gal et al., 2018), which relates the fraction of conductive heat flow QQ0 to the local relief S: QQ0=3.8792S−0.4. The black line corresponds to an estimate of the hydrothermal heat flux based on the standard deviation. The yellow line is the difference between Model 2 and measurements published after 1990. The green line is the Spinelli and Harris (2011) estimate, and the green dash line is the same estimate offset by 1.7 TW, which corresponds to the hydrothermal heat loss for ages >65 Ma.
Source publication
The number of heat flow measurements at the Earth surface has significantly increased since the last global analysis (Pollack et al., 1993, https://doi.org/10.1029/93RG01249), and the most recent of them provide insights into key locations. This paper presents a new compilation, which includes approximately 70,000 measurements. Continental heat flo...
Citations
... The implications of this for hazard in Europe need to be understood, and a more extensive analysis of the models and their comparison to ground motions in the eastern Mediterranean and Romania would be an important starting point for subduction GMMs in Europe. No ground motions from Europe were included in the NGA Subduction database (Bozorgnia and Stewart, 2020), yet the volume of records from non-crustal seismicity in Europe is growing (Manea et al., 2022;Luzi et al., 2020) and the site characterisation of recording stations improving. While we are unlikely to witness many large subduction or deep seismicity earthquakes in Europe within the following few years, there remains scope to use this growing body of data to attempt to calibrate certain parameters of the NGA Subduction GMMs for application to the Hellenic Arc and to explore the issue of regionalisation in more detail. ...
Current practice in strong ground motion modelling for probabilistic seismic hazard analysis (PSHA) requires the identification and calibration of empirical models appropriate to the tectonic regimes within the region of application, along with quantification of both their aleatory and epistemic uncertainties. For the development of the 2020 European Seismic Hazard Model (ESHM20) a novel approach for ground motion characterisation was adopted based on the concept of a regionalised scaled-backbone model, wherein a single appropriate ground motion model (GMM) is identified for use in PSHA, to which adjustments or scaling factors are then applied to account for epistemic uncertainty in the underlying seismological properties of the region of interest. While the theory and development of the regionalised scaled-backbone GMM concept have been discussed in earlier publications, implementation in the final ESHM20 required further refinements to the shallow-seismicity GMM in three regions, which were undertaken considering new data and insights gained from the feedback provided by experts in several regions of Europe: France, Portugal and Iceland. Exploration of the geophysical characteristics of these regions and analysis of additional ground motion records prompted recalibrations of the GMM logic tree and/or modifications to the proposed regionalisation. These modifications illustrate how the ESHM20 GMM logic tree can still be refined and adapted to different regions based on new ground motion data and/or expert judgement, without diverging from the proposed regionalised scaled-backbone GMM framework. In addition to the regions of crustal seismicity, the scaled-backbone approach needed to be adapted to earthquakes occurring in Europe's subduction zones and to the Vrancea deep seismogenic source region. Using a novel fuzzy methodology to classify earthquakes according to different seismic regimes within the subduction system, we compare ground motion records from non-crustal earthquakes to existing subduction GMMs and identify a suitable-backbone GMM for application to subduction and deep seismic sources in Europe. The observed ground motion records from moderate- and small-magnitude earthquakes allow us to calibrate the anelastic attenuation of the backbone GMM specifically for the eastern Mediterranean region. Epistemic uncertainty is then calibrated based on the global variability in source and attenuation characteristics of subduction GMMs. With the ESHM20 now completed, we reflect on the lessons learned from implementing this new approach in regional-scale PSHA and highlight where we hope to see new developments and improvements to the characterisation of ground motion in future generations of the European Seismic Hazard Model.
... Initially, the lithosphere's temperature has reached steady state and follows the continental geotherm T geoth ðzÞ = T 0 + 6:55z, which was modelled using a temperature-and pressure-dependent thermal conductivity and a heat production within the lower crustal rocks of 0.4 μW m −3 (ref. 11) to match the surface heat flux 45 mWm −2 suitable for the EE basins 63 . At t = 0 the temperature at the base of the lithosphere is increased by ΔT = T p i À T l (the plume excess temperature), where T p i is the plume temperature; two values of the plume temperature are considered, T p 1 = 1770 K and T p 2 = 1970 K (ref. ...
A strong negative anomaly of seismic wave velocities at the core-mantle boundary (the Perm Anomaly) beneath the East European platform is attributed to the remnant of a deep mantle upwelling. The interaction between the upwelling and the East European lithosphere in the geological past and its resulting surface manifestations are still poorly understood. Using mantle plume modelling and global plate motion reconstructions, we show here that the East European lithosphere is likely to have been situated over the weakening Perm Anomaly upwelling for about 150–200 million years. As the East European platform moved above the Perm Anomaly in post-Jurassic times, the vertical tectonic movements recorded in sedimentary hydrocarbon-rich basins show either hiatus/uplift or insignificant subsidence. Analytical modelling of heat conduction through the lithosphere demonstrates that the basins have been slowly heated for a long time by the Perm Anomaly upwelling, creating suitable conditions for hydrocarbon maturation. This suggests a profound relationship between mantle plume dynamics, basin evolution, and hydrocarbon generation.
... The study area benefits from high heat flow due to the Red Sea rifting at the divergent plate boundary (Girdler and Evans, 1977;Pollack et al., 1993;Rolandone et al., 2013;Limberger et al., 2018). The heat flux in the Red Sea basin ranges from 70-90 mW∕m 2 (Limberger et al., 2018;Lucazeau, 2019), with the Al-Wajj basin reaching up to 90 mW∕m 2 near the town of Umluj. Therefore, we limit our analysis to these syn-rift deposits, as they offer promising hydrothermal-reservoir-bearing strata for geothermal energy production. ...
... Additionally, observations are often concentrated in areas of economic interest or areas that are easily accessible . Therefore, Arctic heat flow observations are distributed very heterogeneously, with dense data coverage in regions around the mid-oceanic ridge, Scandinavia, and the north of Canada, while Siberia, Greenland, and the Arctic Ocean north of Alaska are poorly covered (Lucazeau, 2019;Fig. 2). ...
... Due to the geological similarity, we take the length scales calculated from the semivariogram for the heat flow in Scandinavia (Lucazeau, 2019). Here, we have a high data coverage so that estimates based on the semivariogram are appropriate (Fig. C1). ...
Geothermal heat flow is an important boundary condition for ice sheets, affecting, for example, basal melt rates, but for ice-covered regions, we only have sparse heat flow observations with partly high uncertainty of up to 30 m W m−2. In this study, we first investigate the agreement between such pointwise heat flow observations and solid Earth models, applying a 1D steady-state approach to perform a statistical analysis for the entire Arctic region. We find that most of the continental heat flow observations have a high reliability and agreement to solid Earth models, except a few data points, such as, for example, the NGRIP (North Greenland Ice Core Project) point in central Greenland. For further testing, we perform a conditional simulation with focus on Greenland in which the local characteristics of heat flow structures can be considered. Simple kriging shows that including or excluding the less reliable NGRIP point has a large influence on the surrounding heat flow. The geostatistical analysis with the conditional simulation supports the assumption that NGRIP might not only be problematic for representing a regional feature but likely is an outlier. Basal melt estimates show that such a local spot of high heat flow results in local high basal melt rates but leads to less variation than existing geophysical models.
... Some authors succeeded to complete this database with additional data from confidential oil exploration studies (e.g. Lucazeau, 2019). Heat flow data from boreholes and from marine probe instruments are obtained in very different depth intervals and are dealing with different types of perturbations from surface processes, but if proper corrections are applied both can be considered as an appropriate estimate of the amount of thermal energy that the Earth loses per unit surface area and time. ...
... Goutorbe et al. (2011) published a more integrating process using the stacking of a large number of geologic or geophysical proxies in order to get relevant information for better constraining the heat flow predictions. The predictive global mapping is computed with a purely statistical calculation: the similarity method (Lucazeau, 2019). This method is based on the evaluation at each grid location of the number of similarities with several heat flow proxies at all other locations of the grid where heat flow is known. ...
... Due to the improvement of acquisition techniques and signal treatments, geologic and geophysical global databases are constantly increasing in number, quality and resolution. The method was initially applied on a 1 • × 1 • global grid (Goutorbe et al., 2011), but it was recently upgraded to a 0.5 • × 0.5 • global prediction by Lucazeau (2019). ...
... E at alongaxis distance between 2650 and 5200 km) and the melt-rich central region (SWIR 52.5-70° E at along-axis distance between 5250 and 7700 km). The melt-poor eastern SWIR corresponds to a topographic low, an MBA high, a detachment-faulting-dominated seafloor morphology, and a relatively low heat flow, while the melt-rich central SWIR corresponds to a topographic high, an MBA low, a volcanic-dominated seafloor morphology, and a slightly high heat flow (Figure 9a-c and Figure S3) [14,39,41,42]. We find that both swarm-type and non-swarm-type earthquakes exhibit higher seismicity rates in the melt-poor eastern SWIR (Figure 9d,e). ...
... These two regions are the melt-poor eastern region (SWIR 32-52.5 • E at along-axis distance between 2650 and 5200 km) and the melt-rich central region (SWIR 52.5-70 • E at along-axis distance between 5250 and 7700 km). The melt-poor eastern SWIR corresponds to a topographic low, an MBA high, a detachment-faulting-dominated seafloor morphology, and a relatively low heat flow, while the melt-rich central SWIR corresponds to a topographic high, an MBA low, a volcanic-dominated seafloor morphology, and a slightly high heat flow (Figure 9a-c and Figure S3) [14,39,41,42]. We find that both swarm-type and non-swarm-type earthquakes exhibit higher seismicity rates in the melt-poor eastern SWIR (Figure 9d,e). ...
... Supplementary Materials: The following supporting information can be downloaded at: https: //www.mdpi.com/article/10.3390/jmse12040605/s1, Figure S1: Different search radii on earthquake density; Figure S2: Different search radii on earthquake moment release intensity; Figure S3: Heat flow [42] along the SWIR axis at distance between 2650 and 7000 km (SWIR 32-70 • E). ...
Magmatic and tectonic processes in the formation of oceanic lithosphere at slow–ultraslow-spreading mid-ocean ridges (MORs) are more complicated relative to faster-spreading ridges, as their melt flux is overall low, with highly spatial and temporal variations. Here, we use the teleseismic catalog of magnitudes over 4 between 1995 and 2020 from the International Seismological Center to investigate the characteristics of magmatic and tectonic activities at the ultraslow-spreading Southwest Indian Ridge and Arctic Gakkel Ridge and the slow-spreading North Mid-Atlantic Ridge and Carlsberg Ridge (total length of 14,300 km). Using the single-link cluster analysis technique, we identify 78 seismic swarms (≥8 events), 877 sequences (2–7 events), and 3543 single events. Seismic swarms often occur near the volcanic center of second-order segments, presumably relating to relatively robust magmatism. By comparing the patterns of seismicity between ultraslow- and slow-spreading ridges, and between melt-rich and melt-poor regions of the Southwest Indian Ridge with distinct seafloor morphologies, we demonstrate that a lower spreading rate and a lower melt supply correspond to a higher seismicity rate and a higher potential of large volcano-induced seismic swarms, probably due to a thicker and colder lithosphere with a higher degree of along-axis melt focusing there.
... Our results indicate high q s in West Antarctica, where heat supply into the base of the Antarctic Ice Sheet is estimated to vary between 60 and 130 mW m 2 , and is on average 97 ± 14 mW m 2 (median, and median absolute deviation, respectively). Such GHF values are significantly higher than the global continental average, q s = 67 ± 47 mW m 2 (as inferred from gravity-driven probe and borehole temperature-depth data), and are in fact intermediate between the former and the global average over continental rift zones, q s = 114 ± 94 mW m 2 (Lucazeau, 2019). This result is consistent with recent tectonic activity, evidence for Cenozoic magmatism, and inferences of a thermal anomaly beneath West Antarctica (Ball et al., 2021;Barletta et al., 2018;Hazzard et al., 2023). ...
... However, the distribution of inferred GHF is heavily skewed toward lower values, which is borne out in the spatial average 30 ± 8 mW m 2 . Such low values are consistent with globally averaged GHF estimates in continental regions of Archean age, q s = 46 ± 21 mW m 2 (Lucazeau, 2019). ...
Plain Language Summary
The future evolution of the Antarctic Ice Sheet depends on its stability, which describes how sensitive it is to environmental change. A key factor influencing ice sheet stability is how much thermal energy is transferred into its base from Earth's interior: a parameter called geothermal heat flow. If the level of heat supply is high, melting at the base of the ice sheet is encouraged, resulting in enhanced sliding toward outlet glaciers at the continental perimeter. Consequently, ice loss is accelerated, and the likelihood of glacial collapse is increased. Therefore, an accurate map of Antarctic geothermal heat flow, including how this parameter varies from region to region, is needed to produce high quality projections of Antarctic ice mass loss and therefore global sea level change. In this study, we use models of how seismic wave speed varies within Earth to estimate its three‐dimensional temperature structure, as well as its thermal conductivity. These data are used to infer a collection of best‐fitting models of Earth's thermal state, and hence estimate Antarctic geothermal heat flow.
... The amount of geotemperature data and the irregular state of the geothermal study still do not allow us to reveal the patterns of heat flow distribution and geothermal gradient with a high degree of detail in all Arctic seas of the Arctic Ocean. The insufficiency of geothermal data has a global character: only 2.7 (4.6% of the World Ocean surface) of the Earth's surface is covered by geothermal data [53]. ...
... High observed values in the Pacific Ocean could also be attributed to additional advective heat transport because they are located in an area of intense faulting (Marcaillou et al., 2006) close to the Panama Fracture Zone. Considering that the associated error in the heat flow data used in this analysis ranges between 10 % and 20 % (Lucazeau, 2019), it can be concluded that the model fits the regional trend except in those two areas previously mentioned. ...
The seismogenesis of rocks is mainly affected by their mineral composition and in situ conditions (temperature and state of stress). Diverse laboratory experiments have explored the frictional behaviour of the rocks and rock-forming minerals most common in the crust and uppermost mantle. However, it is debated how to “upscale” these results to the lithosphere. In particular, most earthquakes in the crust nucleate down to the crustal seismogenic depth (CSD), which is a proxy for the maximum depth of crustal earthquake ruptures in seismic hazard assessments. In this study we propose a workflow to upscale and validate those laboratory experiments to natural geological conditions relevant for crustal and upper-mantle rocks. We used the southern Caribbean and northwestern South America as a case study to explore the three-dimensional spatial variation of the CSD (mapped as D90, the 90 % percentile of hypocentral depths) and the temperatures at which crustal earthquakes likely occur. A 3D steady-state thermal field was computed for the region with a finite-element scheme using the software GOLEM, considering the uppermost 75 km of a previously published 3D data-integrative lithospheric configuration, lithology-constrained thermal parameters, and appropriate upper and lower boundary conditions. The model was validated using additional, independent measurements of downhole temperatures and heat flow. We found that the majority of crustal earthquakes nucleate at temperatures less than 350 ∘C, in agreement with frictional experiments of typical crustal rocks. A few outliers with larger hypocentral temperatures evidence nucleation conditions consistent with the seismogenic window of olivine-rich rocks, and can be due to either uncertainties in the Moho depths and/or in the earthquake hypocentres or the presence of ultramafic rocks within different crustal blocks and allochthonous terranes accreted to this complex margin. Moreover, the spatial distribution of crustal seismicity in the region correlates with the geothermal gradient, with no crustal earthquakes occurring in domains with low thermal gradient. Finally, we find that the largest earthquake recorded in the region (Mw=7.1, Murindó sequence, in 1992) nucleated close to the CSD, highlighting the importance of considering this lower-stability transition for seismogenesis when characterizing the depth of seismogenic sources in hazard assessments. The approach presented in this study goes beyond a statistical approach in that the local heterogeneity of physical properties is considered in our simulations and additionally validated by the observed depth distribution of earthquakes. The coherence of the calculated hypocentral temperatures with those expected from laboratory measurements provides additional support to our modelling workflow. This approach can be applied to other tectonic settings worldwide, and it could be further refined as new, high-quality hypocentral locations and heat flow and temperature observations become available.
... regional heat flow by interpolating a few measurement points (Lucazeau, 2019). It is suitable for large-scale predictions, such as Jiang et al. (2019) delineating several high-temperature geothermal areas based on China's interpolating heat flow map. ...
... Meanwhile, the DL strategy is widely used in heat flow prediction (Bai et al., 2022(Bai et al., , 2023Meng et al., 2011;Spichak et al., 2007), hydrothermal geochemical prediction (Haklidir Tut & Haklidir, 2020), and geothermal reservoir classification (Sean et al., 2021;Vesselinov et al., 2020). Rezvanbehbahani et al. (2017) combined the global heat flow data set with geological and geophysical features to reveal the heat flow distribution in Greenland using the random forest tree method, which can build a reasonable predictive model without explicit expressions and is highly reliable in insufficient heat information (Goutorbe et al., 2011;Lucazeau, 2019). He et al. (2022) obtained prediction heat flow in the Bohai basin based on generalized linear models and gradient regression trees. ...
Heat flow is a geothermal parameter for indicating the heat sources distribution and evaluating geothermal reservoirs. Only 1230 heat flow points are distributed unevenly in China, mainly concentrated in the high-temperature geothermal areas and the southeast regions. The Songliao Basin is a potential geothermal field in China. Still, only 20 measurement points are known, making it difficult to evaluate the geothermal genetic mechanism. Sparse data interpolation using deep learning methods have high accuracy and are 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 flow 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.
