Articles | Volume 12, issue 10
https://doi.org/10.5194/se-12-2387-2021
© Author(s) 2021. 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-12-2387-2021
© Author(s) 2021. This work is distributed under
the Creative Commons Attribution 4.0 License.
the Creative Commons Attribution 4.0 License.
Constraining 3D geometric gravity inversion with a 2D reflection seismic profile using a generalized level set approach: application to the eastern Yilgarn Craton
Mahtab Rashidifard
CORRESPONDING AUTHOR
Centre of Exploration Targeting (School of Earth Sciences), University
of Western Australia, 35 Stirling Highway, Crawley, WA 6009, Australia
Mineral Exploration Cooperative Research Centre, School of Earth
Sciences, University of Western Australia, 35 Stirling Highway, Crawley, WA
6009, Australia
Jérémie Giraud
Centre of Exploration Targeting (School of Earth Sciences), University
of Western Australia, 35 Stirling Highway, Crawley, WA 6009, Australia
RING Team, GeoRessources, Université de Lorraine/CNRS, 54000 Nancy, France
Mineral Exploration Cooperative Research Centre, School of Earth
Sciences, University of Western Australia, 35 Stirling Highway, Crawley, WA
6009, Australia
Mark Lindsay
Centre of Exploration Targeting (School of Earth Sciences), University
of Western Australia, 35 Stirling Highway, Crawley, WA 6009, Australia
CSIRO Mineral Resources, 26 Dick Perry Avenue, Kensington, WA 6151, Australia
Mineral Exploration Cooperative Research Centre, School of Earth
Sciences, University of Western Australia, 35 Stirling Highway, Crawley, WA
6009, Australia
Mark Jessell
Centre of Exploration Targeting (School of Earth Sciences), University
of Western Australia, 35 Stirling Highway, Crawley, WA 6009, Australia
Mineral Exploration Cooperative Research Centre, School of Earth
Sciences, University of Western Australia, 35 Stirling Highway, Crawley, WA
6009, Australia
Vitaliy Ogarko
Centre of Exploration Targeting (School of Earth Sciences), University
of Western Australia, 35 Stirling Highway, Crawley, WA 6009, Australia
Mineral Exploration Cooperative Research Centre, School of Earth
Sciences, University of Western Australia, 35 Stirling Highway, Crawley, WA
6009, Australia
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Geosci. Model Dev. Discuss., https://doi.org/10.5194/gmd-2024-154, https://doi.org/10.5194/gmd-2024-154, 2024
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To facilitate the exploration of alternative hydrogeological scenarios, we propose to approximate costly physical simulations of contaminant transport by more affordable shortest distances computations. It enables to accept or reject scenarios within a predefined confidence interval. In particular, it can allow to estimate the probability of a fault acting as a preferential path or a barrier.
Vitaliy Ogarko, Kim Frankcombe, Taige Liu, Jeremie Giraud, Roland Martin, and Mark Jessell
Geosci. Model Dev., 17, 2325–2345, https://doi.org/10.5194/gmd-17-2325-2024, https://doi.org/10.5194/gmd-17-2325-2024, 2024
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We present a major release of the Tomofast-x open-source gravity and magnetic inversion code that is enhancing its performance and applicability for both industrial and academic studies. We focus on real-world mineral exploration scenarios, while offering flexibility for applications at regional scale or for crustal studies. The optimisation work described in this paper is fundamental to allowing more complete descriptions of the controls on magnetisation, including remanence.
Jiateng Guo, Xuechuang Xu, Luyuan Wang, Xulei Wang, Lixin Wu, Mark Jessell, Vitaliy Ogarko, Zhibin Liu, and Yufei Zheng
Geosci. Model Dev., 17, 957–973, https://doi.org/10.5194/gmd-17-957-2024, https://doi.org/10.5194/gmd-17-957-2024, 2024
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This study proposes a semi-supervised learning algorithm using pseudo-labels for 3D geological modelling. We establish a 3D geological model using borehole data from a complex real urban local survey area in Shenyang and make an uncertainty analysis of this model. The method effectively expands the sample space, which is suitable for geomodelling and uncertainty analysis from boreholes. The modelling results perform well in terms of spatial morphology and geological semantics.
Jérémie Giraud, Guillaume Caumon, Lachlan Grose, Vitaliy Ogarko, and Paul Cupillard
Solid Earth, 15, 63–89, https://doi.org/10.5194/se-15-63-2024, https://doi.org/10.5194/se-15-63-2024, 2024
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We present and test an algorithm that integrates geological modelling into deterministic geophysical inversion. This is motivated by the need to model the Earth using all available data and to reconcile the different types of measurements. We introduce the methodology and test our algorithm using two idealised scenarios. Results suggest that the method we propose is effectively capable of improving the models recovered by geophysical inversion and may be applied in real-world scenarios.
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
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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
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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
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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
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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
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Lachlan Grose, Laurent Ailleres, Gautier Laurent, Guillaume Caumon, Mark Jessell, and Robin Armit
Geosci. Model Dev., 14, 6197–6213, https://doi.org/10.5194/gmd-14-6197-2021, https://doi.org/10.5194/gmd-14-6197-2021, 2021
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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.
Lachlan Grose, Laurent Ailleres, Gautier Laurent, and Mark Jessell
Geosci. Model Dev., 14, 3915–3937, https://doi.org/10.5194/gmd-14-3915-2021, https://doi.org/10.5194/gmd-14-3915-2021, 2021
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LoopStructural is an open-source 3D geological modelling library with a model design allowing for multiple different algorithms to be used for comparison for the same geology. Geological structures are modelled using structural geology concepts and techniques, allowing for complex structures such as overprinted folds and faults to be modelled. In the paper, we demonstrate automatically generating a 3-D model from map2loop-processed geological survey data of the Flinders Ranges, South Australia.
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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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
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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
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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
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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.
Xiaojun Feng, Enyuan Wang, Jérôme Ganne, Roland Martin, and Mark W. Jessell
Solid Earth Discuss., https://doi.org/10.5194/se-2017-142, https://doi.org/10.5194/se-2017-142, 2018
Preprint withdrawn
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.
Related subject area
Subject area: Crustal structure and composition | Editorial team: Geodesy, gravity, and geomagnetism | Discipline: Remote sensing
Sedimentary basins of the eastern Asia Arctic zone: new details on their structure revealed by decompensative gravity anomalies
Roman V. Sidorov, Mikhail K. Kaban, Anatoly A. Soloviev, Alexei G. Petrunin, Alexei D. Gvishiani, Alexei A. Oshchenko, Anton B. Popov, and Roman I. Krasnoperov
Solid Earth, 12, 2773–2788, https://doi.org/10.5194/se-12-2773-2021, https://doi.org/10.5194/se-12-2773-2021, 2021
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In the present study, the structure of sedimentary basins in the eastern Asia Arctic zone is analysed by employing the approach based on decompensative gravity anomalies. Two obtained models of thickness and density of sediments in the study area display significant changes in the thickness and distribution of sedimentary rocks revealed for some particular basins. The new results improve our knowledge about the region, providing a better understanding of the evolution of the sedimentary basins.
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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.
One motivation for this study is to develop a workflow that enables the integration of...