Articles | Volume 14, issue 12
https://doi.org/10.5194/se-14-1289-2023
© Author(s) 2023. This work is distributed under
the Creative Commons Attribution 4.0 License.
the Creative Commons Attribution 4.0 License.
https://doi.org/10.5194/se-14-1289-2023
© Author(s) 2023. This work is distributed under
the Creative Commons Attribution 4.0 License.
the Creative Commons Attribution 4.0 License.
The crustal structure of the Longmenshan fault zone and its implications for seismogenesis: new insight from aeromagnetic and gravity data
Hai Yang
CORRESPONDING AUTHOR
China Aero Geophysical Survey and Remote Sensing Center for Natural Resources, Beijing, 100083, China
State Key Laboratory of Lithospheric Evolution, Institute of Geology and Geophysics, Chinese Academy of Sciences, Beijing, 100029, China
Key Laboratory of Airborne Geophysics and Remote Sensing Geology, Ministry of Natural Resources, Beijing, 100083, China
Shengqing Xiong
CORRESPONDING AUTHOR
China Aero Geophysical Survey and Remote Sensing Center for Natural Resources, Beijing, 100083, China
Key Laboratory of Airborne Geophysics and Remote Sensing Geology, Ministry of Natural Resources, Beijing, 100083, China
Qiankun Liu
China Aero Geophysical Survey and Remote Sensing Center for Natural Resources, Beijing, 100083, China
Fang Li
China Aero Geophysical Survey and Remote Sensing Center for Natural Resources, Beijing, 100083, China
Zhiye Jia
China Aero Geophysical Survey and Remote Sensing Center for Natural Resources, Beijing, 100083, China
Xue Yang
China Aero Geophysical Survey and Remote Sensing Center for Natural Resources, Beijing, 100083, China
Haofei Yan
China Aero Geophysical Survey and Remote Sensing Center for Natural Resources, Beijing, 100083, China
Zhaoliang Li
China Aero Geophysical Survey and Remote Sensing Center for Natural Resources, Beijing, 100083, China
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Zhengfa Bi, Xinming Wu, Zhaoliang Li, Dekuan Chang, and Xueshan Yong
Geosci. Model Dev., 15, 6841–6861, https://doi.org/10.5194/gmd-15-6841-2022, https://doi.org/10.5194/gmd-15-6841-2022, 2022
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We present an implicit modeling method based on deep learning to produce a geologically valid and structurally compatible model from unevenly sampled structural data. Trained with automatically generated synthetic data with realistic features, our network can efficiently model geological structures without the need to solve large systems of mathematical equations, opening new opportunities for further leveraging deep learning to improve modeling capacity in many Earth science applications.
Related subject area
Subject area: Crustal structure and composition | Editorial team: Geodesy, gravity, and geomagnetism | Discipline: Geodynamics
Magmatic underplating associated with Proterozoic basin formation: insights from gravity study over the southern margin of the Bundelkhand Craton, India
Crustal structure of the Volgo–Uralian subcraton revealed by inverse and forward gravity modelling
Interpolation of magnetic anomalies over an oceanic ridge region using an equivalent source technique and crust age model constraint
Gravity modeling of the Alpine lithosphere affected by magmatism based on seismic tomography
The preserved plume of the Caribbean Large Igneous Plateau revealed by 3D data-integrative models
Mapping undercover: integrated geoscientific interpretation and 3D modelling of a Proterozoic basin
Density distribution across the Alpine lithosphere constrained by 3-D gravity modelling and relation to seismicity and deformation
3-D crustal density model of the Sea of Marmara
A high-resolution lithospheric magnetic field model over southern Africa based on a joint inversion of CHAMP, Swarm, WDMAM, and ground magnetic field data
Density structure and isostasy of the lithosphere in Egypt and their relation to seismicity
Ananya Parthapradip Mukherjee and Animesh Mandal
Solid Earth, 15, 711–729, https://doi.org/10.5194/se-15-711-2024, https://doi.org/10.5194/se-15-711-2024, 2024
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Global gravity data are used to develop 2D models and a Moho depth map from 3D inversion, depicting the crustal structure below the region covered by Proterozoic sedimentary basins, south of the Bundelkhand Craton in central India. The observed thick mafic underplated layer above the Moho indicates Proterozoic plume activity. Thus, the study offers insights into the crustal configuration of this region, illustrating the geodynamic processes that led to the formation of the basins.
Igor Ognev, Jörg Ebbing, and Peter Haas
Solid Earth, 13, 431–448, https://doi.org/10.5194/se-13-431-2022, https://doi.org/10.5194/se-13-431-2022, 2022
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We present a new 3D crustal model of Volgo–Uralia, an eastern segment of the East European craton. We built this model by processing the satellite gravity data and using prior crustal thickness estimation from regional seismic studies to constrain the results. The modelling revealed a high-density body on the top of the mantle and otherwise reflected the main known features of the Volgo–Uralian crustal architecture. We plan to use the obtained model for further geothermal analysis of the region.
Duan Li, Jinsong Du, Chao Chen, Qing Liang, and Shida Sun
Solid Earth Discuss., https://doi.org/10.5194/se-2021-117, https://doi.org/10.5194/se-2021-117, 2021
Revised manuscript not accepted
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Oceanic magnetic anomalies are generally carried out using only few survey lines and thus there are many areas with data gaps. Traditional interpolation methods based on the morphological characteristics of data are not suitable for data with large gaps. The use of dual-layer equivalent-source techniques may improve the interpolation of magnetic anomaly fields in areas with sparse data which gives a good consideration to the extension of the magnetic lineation feature.
Davide Tadiello and Carla Braitenberg
Solid Earth, 12, 539–561, https://doi.org/10.5194/se-12-539-2021, https://doi.org/10.5194/se-12-539-2021, 2021
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We present an innovative approach to estimate a lithosphere density distribution model based on seismic tomography and gravity data. In the studied area, the model shows that magmatic events have increased density in the middle to lower crust, which explains the observed positive gravity anomaly. We interpret the densification through crustal intrusion and magmatic underplating. The proposed method has been tested in the Alps but can be applied to other geological contexts.
Ángela María Gómez-García, Eline Le Breton, Magdalena Scheck-Wenderoth, Gaspar Monsalve, and Denis Anikiev
Solid Earth, 12, 275–298, https://doi.org/10.5194/se-12-275-2021, https://doi.org/10.5194/se-12-275-2021, 2021
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The Earth’s crust beneath the Caribbean Sea formed at about 90 Ma due to large magmatic activity of a mantle plume, which brought molten material up from the deep Earth. By integrating diverse geophysical datasets, we image for the first time two fossil magmatic conduits beneath the Caribbean. The location of these conduits at 90 Ma does not correspond with the present-day Galápagos plume. Either this mantle plume migrated in time or these conduits were formed above another unknown plume.
Mark D. Lindsay, Sandra Occhipinti, Crystal Laflamme, Alan Aitken, and Lara Ramos
Solid Earth, 11, 1053–1077, https://doi.org/10.5194/se-11-1053-2020, https://doi.org/10.5194/se-11-1053-2020, 2020
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Integrated interpretation of multiple datasets is a key skill required for better understanding the composition and configuration of the Earth's crust. Geophysical and 3D geological modelling are used here to aid the interpretation process in investigating anomalous and cryptic geophysical signatures which suggest a more complex structure and history of a Palaeoproterozoic basin in Western Australia.
Cameron Spooner, Magdalena Scheck-Wenderoth, Hans-Jürgen Götze, Jörg Ebbing, György Hetényi, and the AlpArray Working Group
Solid Earth, 10, 2073–2088, https://doi.org/10.5194/se-10-2073-2019, https://doi.org/10.5194/se-10-2073-2019, 2019
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By utilising both the observed gravity field of the Alps and their forelands and indications from deep seismic surveys, we were able to produce a 3-D structural model of the region that indicates the distribution of densities within the lithosphere. We found that the present-day Adriatic crust is both thinner and denser than the European crust and that the properties of Alpine crust are strongly linked to their provenance.
Ershad Gholamrezaie, Magdalena Scheck-Wenderoth, Judith Bott, Oliver Heidbach, and Manfred R. Strecker
Solid Earth, 10, 785–807, https://doi.org/10.5194/se-10-785-2019, https://doi.org/10.5194/se-10-785-2019, 2019
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Based on geophysical data integration and 3-D gravity modeling, we show that significant density heterogeneities are expressed as two large high-density bodies in the crust below the Sea of Marmara. The location of these bodies correlates spatially with the bends of the main Marmara fault, indicating that rheological contrasts in the crust may influence the fault kinematics. Our findings may have implications for seismic hazard and risk assessments in the Marmara region.
Foteini Vervelidou, Erwan Thébault, and Monika Korte
Solid Earth, 9, 897–910, https://doi.org/10.5194/se-9-897-2018, https://doi.org/10.5194/se-9-897-2018, 2018
Mikhail K. Kaban, Sami El Khrepy, and Nassir Al-Arifi
Solid Earth, 9, 833–846, https://doi.org/10.5194/se-9-833-2018, https://doi.org/10.5194/se-9-833-2018, 2018
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We present an integrative model of the crust and upper mantle of Egypt based on an analysis of gravity, seismic, and geological data. These results are essential for deciphering the link between the dynamic processes in the Earth system and near-surface processes (particularly earthquakes) that influence human habitat. We identified the distinct fragmentation of the lithosphere of Egypt in several blocks. This division is closely related to the seismicity patterns in this region.
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Short summary
The Wenchuan (Ms 8.0) and Lushan (Ms 7.0) earthquakes show different geodynamic features and form a 40–60 km area void of aftershocks for both earthquakes. The inverse models suggest that the downward-subducted basement of the Sichuan Basin is irregular in shape and heterogeneous in magnetism and density. The different focal mechanisms of the two earthquakes and the genesis of the seismic gap may be closely related to the differential thrusting mechanism caused by basement heterogeneity.
The Wenchuan (Ms 8.0) and Lushan (Ms 7.0) earthquakes show different geodynamic features and...