Articles | Volume 11, issue 3
https://doi.org/10.5194/se-11-1053-2020
© Author(s) 2020. 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-11-1053-2020
© Author(s) 2020. This work is distributed under
the Creative Commons Attribution 4.0 License.
the Creative Commons Attribution 4.0 License.
Mapping undercover: integrated geoscientific interpretation and 3D modelling of a Proterozoic basin
Mark D. Lindsay
CORRESPONDING AUTHOR
The Centre for Exploration Targeting, School of Earth Sciences, The
University of Western Australia, Crawley, Western Australia, 6009, Australia
Sandra Occhipinti
The Centre for Exploration Targeting, School of Earth Sciences, The
University of Western Australia, Crawley, Western Australia, 6009, Australia
Mineral Resources, Commonwealth Science and Industry Research
Organisation, Kensington, Western Australia, 6151, Australia
Crystal Laflamme
The Centre for Exploration Targeting, School of Earth Sciences, The
University of Western Australia, Crawley, Western Australia, 6009, Australia
Department of Geology and Geological Engineering, Laval University,
Québec City, Québec G1V 0A6, Canada
Alan Aitken
The Centre for Exploration Targeting, School of Earth Sciences, The
University of Western Australia, Crawley, Western Australia, 6009, Australia
Lara Ramos
The Centre for Exploration Targeting, School of Earth Sciences, The
University of Western Australia, Crawley, Western Australia, 6009, Australia
Related authors
Jérémie Giraud, Hoël Seillé, Mark D. Lindsay, Gerhard Visser, Vitaliy Ogarko, and Mark W. Jessell
Solid Earth, 14, 43–68, https://doi.org/10.5194/se-14-43-2023, https://doi.org/10.5194/se-14-43-2023, 2023
Short summary
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We propose and apply a workflow to combine the modelling and interpretation of magnetic anomalies and resistivity anomalies to better image the basement. We test the method on a synthetic case study and apply it to real world data from the Cloncurry area (Queensland, Australia), which is prospective for economic minerals. Results suggest a new interpretation of the composition and structure towards to east of the profile that we modelled.
Guillaume Pirot, Ranee Joshi, Jérémie Giraud, Mark Douglas Lindsay, and Mark Walter Jessell
Geosci. Model Dev., 15, 4689–4708, https://doi.org/10.5194/gmd-15-4689-2022, https://doi.org/10.5194/gmd-15-4689-2022, 2022
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Results of a survey launched among practitioners in the mineral industry show that despite recognising the importance of uncertainty quantification it is not very well performed due to lack of data, time requirements, poor tracking of interpretations and relative complexity of uncertainty quantification. To alleviate the latter, we provide an open-source set of local and global indicators to measure geological uncertainty among an ensemble of geological models.
Richard Scalzo, Mark Lindsay, Mark Jessell, Guillaume Pirot, Jeremie Giraud, Edward Cripps, and Sally Cripps
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Short summary
Short summary
This paper addresses numerical challenges in reasoning about geological models constrained by sensor data, especially models that describe the history of an area in terms of a sequence of events. Our method ensures that small changes in simulated geological features, such as the position of a boundary between two rock layers, do not result in unrealistically large changes to resulting sensor measurements, as occur presently using several popular modeling packages.
Mark Jessell, Jiateng Guo, Yunqiang Li, Mark Lindsay, Richard Scalzo, Jérémie Giraud, Guillaume Pirot, Ed Cripps, and Vitaliy Ogarko
Earth Syst. Sci. Data, 14, 381–392, https://doi.org/10.5194/essd-14-381-2022, https://doi.org/10.5194/essd-14-381-2022, 2022
Short summary
Short summary
To robustly train and test automated methods in the geosciences, we need to have access to large numbers of examples where we know
the answer. We present a suite of synthetic 3D geological models with their gravity and magnetic responses that allow researchers to test their methods on a whole range of geologically plausible models, thus overcoming one of the fundamental limitations of automation studies.
Ranee Joshi, Kavitha Madaiah, Mark Jessell, Mark Lindsay, and Guillaume Pirot
Geosci. Model Dev., 14, 6711–6740, https://doi.org/10.5194/gmd-14-6711-2021, https://doi.org/10.5194/gmd-14-6711-2021, 2021
Short summary
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We have developed a software that allows the user to extract and standardize drill hole information from legacy datasets and/or different drilling campaigns. It also provides functionality to upscale the lithological information. These functionalities were possible by developing thesauri to identify and group geological terminologies together.
Jérémie Giraud, Vitaliy Ogarko, Roland Martin, Mark Jessell, and Mark Lindsay
Geosci. Model Dev., 14, 6681–6709, https://doi.org/10.5194/gmd-14-6681-2021, https://doi.org/10.5194/gmd-14-6681-2021, 2021
Short summary
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We review different techniques to model the Earth's subsurface from geophysical data (gravity field anomaly, magnetic field anomaly) using geological models and measurements of the rocks' properties. We show examples of application using idealised examples reproducing realistic features and provide theoretical details of the open-source algorithm we use.
Mahtab Rashidifard, Jérémie Giraud, Mark Lindsay, Mark Jessell, and Vitaliy Ogarko
Solid Earth, 12, 2387–2406, https://doi.org/10.5194/se-12-2387-2021, https://doi.org/10.5194/se-12-2387-2021, 2021
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One motivation for this study is to develop a workflow that enables the integration of geophysical datasets with different coverages that are quite common in exploration geophysics. We have utilized a level set approach to achieve this goal. The utilized technique parameterizes the subsurface in the same fashion as geological models. Our results indicate that the approach is capable of integrating information from seismic data in 2D to guide the 3D inversion results of the gravity data.
Mark Jessell, Vitaliy Ogarko, Yohan de Rose, Mark Lindsay, Ranee Joshi, Agnieszka Piechocka, Lachlan Grose, Miguel de la Varga, Laurent Ailleres, and Guillaume Pirot
Geosci. Model Dev., 14, 5063–5092, https://doi.org/10.5194/gmd-14-5063-2021, https://doi.org/10.5194/gmd-14-5063-2021, 2021
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We have developed software that allows the user to extract sufficient information from unmodified digital maps and associated datasets that we are able to use to automatically build 3D geological models. By automating the process we are able to remove human bias from the procedure, which makes the workflow reproducible.
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Solid Earth, 11, 419–436, https://doi.org/10.5194/se-11-419-2020, https://doi.org/10.5194/se-11-419-2020, 2020
Short summary
Short summary
We propose a methodology for the identification of rock types using geophysical and geological information. It relies on an algorithm used in machine learning called
self-organizing maps, to which we add plausibility filters to ensure that the results respect base geological rules and geophysical measurements. Application in the Yerrida Basin (Western Australia) reveals that the thinning of prospective greenstone belts at depth could be due to deep structures not seen from surface.
Evren Pakyuz-Charrier, Mark Jessell, Jérémie Giraud, Mark Lindsay, and Vitaliy Ogarko
Solid Earth, 10, 1663–1684, https://doi.org/10.5194/se-10-1663-2019, https://doi.org/10.5194/se-10-1663-2019, 2019
Short summary
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This paper improves the Monte Carlo simulation for uncertainty propagation (MCUP) method for 3-D geological modeling. Topological heterogeneity is observed in the model suite. The study demonstrates that such heterogeneity arises from piecewise nonlinearity inherent to 3-D geological models and contraindicates use of global uncertainty estimation methods. Topological-clustering-driven uncertainty estimation is proposed as a demonstrated alternative to address plausible model heterogeneity.
Jeremie Giraud, Mark Lindsay, Vitaliy Ogarko, Mark Jessell, Roland Martin, and Evren Pakyuz-Charrier
Solid Earth, 10, 193–210, https://doi.org/10.5194/se-10-193-2019, https://doi.org/10.5194/se-10-193-2019, 2019
Short summary
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We propose the quantitative integration of geology and geophysics in an algorithm integrating the probability of observation of rocks with gravity data to improve subsurface imaging. This allows geophysical modelling to adjust models preferentially in the least certain areas while honouring geological information and geophysical data. We validate our algorithm using an idealized case and apply it to the Yerrida Basin (Australia), where we can recover the geometry of buried greenstone belts.
Evren Pakyuz-Charrier, Mark Lindsay, Vitaliy Ogarko, Jeremie Giraud, and Mark Jessell
Solid Earth, 9, 385–402, https://doi.org/10.5194/se-9-385-2018, https://doi.org/10.5194/se-9-385-2018, 2018
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MCUE is a method that produces probabilistic 3-D geological models by sampling from distributions that represent the uncertainty of the initial input dataset. This process generates numerous plausible datasets used to produce a range of statistically plausible 3-D models which are combined into a single probabilistic model. In this paper, improvements to distribution selection and parameterization for input uncertainty are proposed.
J. Florian Wellmann, Sam T. Thiele, Mark D. Lindsay, and Mark W. Jessell
Geosci. Model Dev., 9, 1019–1035, https://doi.org/10.5194/gmd-9-1019-2016, https://doi.org/10.5194/gmd-9-1019-2016, 2016
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We often obtain knowledge about the subsurface in the form of structural geological models, as a basis for subsurface usage or resource extraction. Here, we provide a modelling code to construct such models on the basis of significant deformational events in geological history, encapsulated in kinematic equations. Our methods simplify complex dynamic processes, but enable us to evaluate how events interact, and finally how certain we are about predictions of structures in the subsurface.
Alan Robert Alexander Aitken, Ian Delaney, Guillaume Pirot, and Mauro A. Werder
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Understanding how glaciers generate sediment and transport it to the ocean is important for understanding ocean ecosystems and developing knowledge of the past cryosphere from marine sediments. This paper presents a new way to simulate sediment transport in rivers below ice sheets and glaciers and quantify volumes and characteristics of sediment that can be used to reveal the hidden record of the subglacial environment for both past and present glacial conditions.
Felicity S. McCormack, Jason L. Roberts, Bernd Kulessa, Alan Aitken, Christine F. Dow, Lawrence Bird, Benjamin K. Galton-Fenzi, Katharina Hochmuth, Richard S. Jones, Andrew N. Mackintosh, and Koi McArthur
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Changes in Antarctic surface elevation can cause changes in ice and basal water flow, impacting how much ice enters the ocean. We find that ice and basal water flow could divert from the Totten to the Vanderford Glacier, East Antarctica, under only small changes in the surface elevation, with implications for estimates of ice loss from this region. Further studies are needed to determine when this could occur and if similar diversions could occur elsewhere in Antarctica due to climate change.
Alice C. Frémand, Peter Fretwell, Julien A. Bodart, Hamish D. Pritchard, Alan Aitken, Jonathan L. Bamber, Robin Bell, Cesidio Bianchi, Robert G. Bingham, Donald D. Blankenship, Gino Casassa, Ginny Catania, Knut Christianson, Howard Conway, Hugh F. J. Corr, Xiangbin Cui, Detlef Damaske, Volkmar Damm, Reinhard Drews, Graeme Eagles, Olaf Eisen, Hannes Eisermann, Fausto Ferraccioli, Elena Field, René Forsberg, Steven Franke, Shuji Fujita, Yonggyu Gim, Vikram Goel, Siva Prasad Gogineni, Jamin Greenbaum, Benjamin Hills, Richard C. A. Hindmarsh, Andrew O. Hoffman, Per Holmlund, Nicholas Holschuh, John W. Holt, Annika N. Horlings, Angelika Humbert, Robert W. Jacobel, Daniela Jansen, Adrian Jenkins, Wilfried Jokat, Tom Jordan, Edward King, Jack Kohler, William Krabill, Mette Kusk Gillespie, Kirsty Langley, Joohan Lee, German Leitchenkov, Carlton Leuschen, Bruce Luyendyk, Joseph MacGregor, Emma MacKie, Kenichi Matsuoka, Mathieu Morlighem, Jérémie Mouginot, Frank O. Nitsche, Yoshifumi Nogi, Ole A. Nost, John Paden, Frank Pattyn, Sergey V. Popov, Eric Rignot, David M. Rippin, Andrés Rivera, Jason Roberts, Neil Ross, Anotonia Ruppel, Dustin M. Schroeder, Martin J. Siegert, Andrew M. Smith, Daniel Steinhage, Michael Studinger, Bo Sun, Ignazio Tabacco, Kirsty Tinto, Stefano Urbini, David Vaughan, Brian C. Welch, Douglas S. Wilson, Duncan A. Young, and Achille Zirizzotti
Earth Syst. Sci. Data, 15, 2695–2710, https://doi.org/10.5194/essd-15-2695-2023, https://doi.org/10.5194/essd-15-2695-2023, 2023
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This paper presents the release of over 60 years of ice thickness, bed elevation, and surface elevation data acquired over Antarctica by the international community. These data are a crucial component of the Antarctic Bedmap initiative which aims to produce a new map and datasets of Antarctic ice thickness and bed topography for the international glaciology and geophysical community.
Jérémie Giraud, Hoël Seillé, Mark D. Lindsay, Gerhard Visser, Vitaliy Ogarko, and Mark W. Jessell
Solid Earth, 14, 43–68, https://doi.org/10.5194/se-14-43-2023, https://doi.org/10.5194/se-14-43-2023, 2023
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We propose and apply a workflow to combine the modelling and interpretation of magnetic anomalies and resistivity anomalies to better image the basement. We test the method on a synthetic case study and apply it to real world data from the Cloncurry area (Queensland, Australia), which is prospective for economic minerals. Results suggest a new interpretation of the composition and structure towards to east of the profile that we modelled.
Guillaume Pirot, Ranee Joshi, Jérémie Giraud, Mark Douglas Lindsay, and Mark Walter Jessell
Geosci. Model Dev., 15, 4689–4708, https://doi.org/10.5194/gmd-15-4689-2022, https://doi.org/10.5194/gmd-15-4689-2022, 2022
Short summary
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Results of a survey launched among practitioners in the mineral industry show that despite recognising the importance of uncertainty quantification it is not very well performed due to lack of data, time requirements, poor tracking of interpretations and relative complexity of uncertainty quantification. To alleviate the latter, we provide an open-source set of local and global indicators to measure geological uncertainty among an ensemble of geological models.
Richard Scalzo, Mark Lindsay, Mark Jessell, Guillaume Pirot, Jeremie Giraud, Edward Cripps, and Sally Cripps
Geosci. Model Dev., 15, 3641–3662, https://doi.org/10.5194/gmd-15-3641-2022, https://doi.org/10.5194/gmd-15-3641-2022, 2022
Short summary
Short summary
This paper addresses numerical challenges in reasoning about geological models constrained by sensor data, especially models that describe the history of an area in terms of a sequence of events. Our method ensures that small changes in simulated geological features, such as the position of a boundary between two rock layers, do not result in unrealistically large changes to resulting sensor measurements, as occur presently using several popular modeling packages.
Mark Jessell, Jiateng Guo, Yunqiang Li, Mark Lindsay, Richard Scalzo, Jérémie Giraud, Guillaume Pirot, Ed Cripps, and Vitaliy Ogarko
Earth Syst. Sci. Data, 14, 381–392, https://doi.org/10.5194/essd-14-381-2022, https://doi.org/10.5194/essd-14-381-2022, 2022
Short summary
Short summary
To robustly train and test automated methods in the geosciences, we need to have access to large numbers of examples where we know
the answer. We present a suite of synthetic 3D geological models with their gravity and magnetic responses that allow researchers to test their methods on a whole range of geologically plausible models, thus overcoming one of the fundamental limitations of automation studies.
Ranee Joshi, Kavitha Madaiah, Mark Jessell, Mark Lindsay, and Guillaume Pirot
Geosci. Model Dev., 14, 6711–6740, https://doi.org/10.5194/gmd-14-6711-2021, https://doi.org/10.5194/gmd-14-6711-2021, 2021
Short summary
Short summary
We have developed a software that allows the user to extract and standardize drill hole information from legacy datasets and/or different drilling campaigns. It also provides functionality to upscale the lithological information. These functionalities were possible by developing thesauri to identify and group geological terminologies together.
Jérémie Giraud, Vitaliy Ogarko, Roland Martin, Mark Jessell, and Mark Lindsay
Geosci. Model Dev., 14, 6681–6709, https://doi.org/10.5194/gmd-14-6681-2021, https://doi.org/10.5194/gmd-14-6681-2021, 2021
Short summary
Short summary
We review different techniques to model the Earth's subsurface from geophysical data (gravity field anomaly, magnetic field anomaly) using geological models and measurements of the rocks' properties. We show examples of application using idealised examples reproducing realistic features and provide theoretical details of the open-source algorithm we use.
Mahtab Rashidifard, Jérémie Giraud, Mark Lindsay, Mark Jessell, and Vitaliy Ogarko
Solid Earth, 12, 2387–2406, https://doi.org/10.5194/se-12-2387-2021, https://doi.org/10.5194/se-12-2387-2021, 2021
Short summary
Short summary
One motivation for this study is to develop a workflow that enables the integration of geophysical datasets with different coverages that are quite common in exploration geophysics. We have utilized a level set approach to achieve this goal. The utilized technique parameterizes the subsurface in the same fashion as geological models. Our results indicate that the approach is capable of integrating information from seismic data in 2D to guide the 3D inversion results of the gravity data.
Mark Jessell, Vitaliy Ogarko, Yohan de Rose, Mark Lindsay, Ranee Joshi, Agnieszka Piechocka, Lachlan Grose, Miguel de la Varga, Laurent Ailleres, and Guillaume Pirot
Geosci. Model Dev., 14, 5063–5092, https://doi.org/10.5194/gmd-14-5063-2021, https://doi.org/10.5194/gmd-14-5063-2021, 2021
Short summary
Short summary
We have developed software that allows the user to extract sufficient information from unmodified digital maps and associated datasets that we are able to use to automatically build 3D geological models. By automating the process we are able to remove human bias from the procedure, which makes the workflow reproducible.
Jérémie Giraud, Mark Lindsay, Mark Jessell, and Vitaliy Ogarko
Solid Earth, 11, 419–436, https://doi.org/10.5194/se-11-419-2020, https://doi.org/10.5194/se-11-419-2020, 2020
Short summary
Short summary
We propose a methodology for the identification of rock types using geophysical and geological information. It relies on an algorithm used in machine learning called
self-organizing maps, to which we add plausibility filters to ensure that the results respect base geological rules and geophysical measurements. Application in the Yerrida Basin (Western Australia) reveals that the thinning of prospective greenstone belts at depth could be due to deep structures not seen from surface.
Evren Pakyuz-Charrier, Mark Jessell, Jérémie Giraud, Mark Lindsay, and Vitaliy Ogarko
Solid Earth, 10, 1663–1684, https://doi.org/10.5194/se-10-1663-2019, https://doi.org/10.5194/se-10-1663-2019, 2019
Short summary
Short summary
This paper improves the Monte Carlo simulation for uncertainty propagation (MCUP) method for 3-D geological modeling. Topological heterogeneity is observed in the model suite. The study demonstrates that such heterogeneity arises from piecewise nonlinearity inherent to 3-D geological models and contraindicates use of global uncertainty estimation methods. Topological-clustering-driven uncertainty estimation is proposed as a demonstrated alternative to address plausible model heterogeneity.
Jeremie Giraud, Mark Lindsay, Vitaliy Ogarko, Mark Jessell, Roland Martin, and Evren Pakyuz-Charrier
Solid Earth, 10, 193–210, https://doi.org/10.5194/se-10-193-2019, https://doi.org/10.5194/se-10-193-2019, 2019
Short summary
Short summary
We propose the quantitative integration of geology and geophysics in an algorithm integrating the probability of observation of rocks with gravity data to improve subsurface imaging. This allows geophysical modelling to adjust models preferentially in the least certain areas while honouring geological information and geophysical data. We validate our algorithm using an idealized case and apply it to the Yerrida Basin (Australia), where we can recover the geometry of buried greenstone belts.
Evren Pakyuz-Charrier, Mark Lindsay, Vitaliy Ogarko, Jeremie Giraud, and Mark Jessell
Solid Earth, 9, 385–402, https://doi.org/10.5194/se-9-385-2018, https://doi.org/10.5194/se-9-385-2018, 2018
Short summary
Short summary
MCUE is a method that produces probabilistic 3-D geological models by sampling from distributions that represent the uncertainty of the initial input dataset. This process generates numerous plausible datasets used to produce a range of statistically plausible 3-D models which are combined into a single probabilistic model. In this paper, improvements to distribution selection and parameterization for input uncertainty are proposed.
J. Florian Wellmann, Sam T. Thiele, Mark D. Lindsay, and Mark W. Jessell
Geosci. Model Dev., 9, 1019–1035, https://doi.org/10.5194/gmd-9-1019-2016, https://doi.org/10.5194/gmd-9-1019-2016, 2016
Short summary
Short summary
We often obtain knowledge about the subsurface in the form of structural geological models, as a basis for subsurface usage or resource extraction. Here, we provide a modelling code to construct such models on the basis of significant deformational events in geological history, encapsulated in kinematic equations. Our methods simplify complex dynamic processes, but enable us to evaluate how events interact, and finally how certain we are about predictions of structures in the subsurface.
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
The crustal structure of the Longmenshan fault zone and its implications for seismogenesis: new insight from aeromagnetic and gravity data
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
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
Short summary
Short summary
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.
Hai Yang, Shengqing Xiong, Qiankun Liu, Fang Li, Zhiye Jia, Xue Yang, Haofei Yan, and Zhaoliang Li
Solid Earth, 14, 1289–1308, https://doi.org/10.5194/se-14-1289-2023, https://doi.org/10.5194/se-14-1289-2023, 2023
Short summary
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.
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
Short summary
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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
Short summary
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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.
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.
Cited articles
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Short summary
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.
Integrated interpretation of multiple datasets is a key skill required for better understanding...