184 research outputs found
Synthetic geophysical survey using geological modelling from the Yerrida Basin (Western Australia)
No full textThis is a companion dataset to the manuscript:
"Towards geologically reasonable lithological classification from integrated geophysical inverse modelling", by J. Giraud, M. Lindsay, M. Jessell, and V. Ogarko.
This dataset contains the true model, the geological uncertainty volume constraining inversion, the starting model for inversion, and the inverted model. It also contains the inverted geophysical data. The inverted data were generated using geological modelling from the area and prior petrophysical information (more information in the above-mentioned document). For standalone usage of this dataset, the inversion parameters can be found in the following publication:
Giraud, J., M. Lindsay, V. Ogarko, M. Jessell, R. Martin, and E. Pakyuz-Charrier, 2019a, Integration of geoscientific uncertainty into geophysical inversion by means of local gradient regularization: Solid Earth, 10, 193–210
Evolution of model and geological inconsistencies during inversion
No full textSupplementary material to:
Giraud, J., Caumon, G., Grose, L., Ogarko, V., and Cupillard, P.: Integration of automatic implicit geological modelling in deterministic geophysical inversion, EGUsphere [preprint], https://doi.org/10.5194/egusphere-2023-129, 2023
The GIF shows a 3D view of the inverted model and its geological inconsistencies during inversion when geological correction is applied at each iteration
Trans-dimensional 3D geometrical inversion: basics and field application example
No full text<p>This document is the PDF document of the presentation that was delivered by Jeremie Giraud for the following conference abstract: <br><br>Jeremie Giraud, Guillaume Caumon, Lachlan Grose, Vitaliy Ogarko, Julien Herrero, and Radu Stoica [2023], Trans-dimensional 3D geometrical inversion: proof of concept and field application using gravity data from the Boulia region (Queensland, Australia), Abstract S1214, in proceedings of the 22nd Annual Conference of the International Association for Mathematical Geosciences, Trondheim (Norway): https://www.iamgconferences.org/iamg2023/shortAbstractsIAMG2023.pdf</p><p>It presents essential elements of a new 3D trans-dimensional gravity data inversion algorithm and shows a field application in the Boulian region (Queensland, Australia).</p><p>The original presentation has been modified prior to being saved in PDF format; a couple of minor typographic alterations have been made for accuracy. <br> </p>
3-D geological and petrophysical models with synthetic geophysics based on data from the Hamersley region (Western Australia)
No full text3-D geological and petrophysical models with synthetic geophysics based on data from the Hamersley region (Western Australia)
M. Jessell 1,2, J. Giraud 1,2, M. Lindsay 1,2
1 Centre for Exploration Targeting (School of Earth Sciences), University of Western Australia, 35 Stirling Highway, 6009 Crawley, Australia
2 Mineral Exploration Cooperative Research Centre, School of Earth Sciences, University of Western Australia, 35 Stirling Highway, WA Crawley 6009, Australia
Contact author: Jeremie Giraud ([email protected])
Companion dataset to the paper:
Structural, petrophysical and geological constraints in potential field inversion using the Tomofast-x open-source code, J. Giraud, V. Ogarko, R. Martin, M. Lindsay, M. Jessell, Geoscientific Model Development Discussions.
This dataset contains models and data shown in the paper, in both 2D and 3D:
1. Geological model
Reference lithology voxet:
The reference geological model was obtained using public data from the Geological Survey of Western Australia and modified subsequently (stretched vertically and flattened at surface level) for the purpose of this study.
Probability voxet
The lithology probability voxet was derived using Monte Carlo simulations for uncertainty estimation as mentioned in the paper.
2. True and inverted models for density and magnetic susceptibility
Derivation is detailed in the paper; it uses fictitious density and magnetic susceptibility values.
3. Bouguer and total magnetic field anomaly
Calculation is detailed in the paper.
The authors are supported, in part, by Loop – Enabling Stochastic 3D Geological Modelling (LP170100985) and the Mineral Exploration Cooperative Research Centre (MinEx CRC) whose activities are funded by the Australian Government's Cooperative Research Centre Program. This is MinEx CRC Document 2021/3. Mark Lindsay acknowledges funding from the ARC and DECRA DE190100431.
It is a companion dataset to:
Vitaliy Ogarko, Jeremie Giraud, & Roland. (2021, February 5). Tomofast-x v1.0 source code (Version 1.0). Zenodo. http://doi.org/10.5281/zenodo.445262
Input and output datasets for the testing of joint inversion code(s) and sensitivity analysis.
No full text<p>Dataset associated to the paper: "Sensitivity of constrained joint inversions to geological and petrophysical input data uncertainties with posterior geological analysis" by Giraud J., Ogarko V., Pakyuz-Charrier E., Jessell M., Lindsay M., and Martin R. <br><br>This paper is under review for publication in Geophysical Journal International. The complete reference will be updated upon publication.</p><p>This dataset comprises:<br>- petrophysical model (x3)<br>- reference models for density contrast and magnetic susceptibility <br>- density contrast and magnetic susceptibility starting models (x3)<br>- inverted density contrast and magnetic susceptibility models (x3)<br>- three probabilistic geological models (x3)</p>Content made available to ensure reproducibility of work presented in the associated paper and in anticipation of the release of the inversion platform's source code
Input geophysical and geological data for "Geologically constrained geometry inversion and null-space navigation to explore alternative geological scenarios: a case study in the Western Pyrenees"
No full text<p>This is a companion dataset to the manuscript: <br><br>Geologically constrained geometry inversion and null-space navigation to explore alternative geological scenarios: a case study in the Western Pyrenees,</p><p>by: Jeremie Giraud , Mary Ford, Guillaume Caumon, Lachlan Grose, Vitaliy Ogarko, Roland Martin, and Paul Cupillard.<br><br>This dataset contains the input data used in the inversion, in terms of the gravity data and the geological data used in the inversion.<br><br>The *.txt file contains the gravity data as inverted in the manuscript: X, Y, Z, Value.<br>The *.csv file contains the geological data: location of the contacts and orientation data.</p>
Synthetic dataset for the testing of local conditioning of regularization function using geological uncertainty.
No full textThis companion datasets relates to the model shown supplementary information to the manuscript "Integration of geological uncertainty into geophysical inversion by means of local gradient regularization", by J. Giraud, M. Lindsay, V. Ogarko, M. Jessell, R. Martin and E. Pakyuz-Charrier, submitted to Solid Earth. The archive contains the input and output geophysical data, starting and inverted models, probabilistic geological model and conditioning volume derived from the calculation of Shannon's entropy
Tomofast-x v1.0 source code
No full textInternational audienceSource code of the geophysical inversion platform Tomofast-x. It is a companion software to the publication: "Structural, petrophysical and geological constraints in potential field inversion using the Tomofast-x open-source code" by: J. Giraud1,2, V. Ogarko3,4,†, R. Martin5, M. Jessell1,2, M. Lindsay1,2 1 Centre for Exploration Targeting (School of Earth Sciences), University of Western Australia, 35 Stirling Highway, 6009 Crawley, Australia. 2 Mineral Exploration Cooperative Research Centre, School of Earth Sciences, University of Western Australia, 35 Stirling Highway, WA Crawley 6009, Australia. 3 The International Centre for Radio Astronomy Research, University of Western Australia, 7 Fairway, WA Crawley 6009, Australia. 4ARC Centre of Excellence for All Sky Astrophysics in 3 Dimensions (ASTRO 3D) 5 Laboratoire de Géosciences Environnement Toulouse GET, CNRS UMR 5563, Observatoire Midi-Pyrénées, Université Paul Sabatier, 14 avenue Edouard Belin, 31400 Toulouse, France. †Formerly at Centre for Exploration Targeting (School of Earth Sciences), University of Western Australia, 35 Stirling Highway, 6009 Crawley, Australia Published in: Geoscientific Model Development. The companion dataset to this software and journal article is: Mark Jessell, Jeremie Giraud, Mark Lindsay. (2021). 3-D geological and petrophysical models with synthetic geophysics based on data from the Hamersley region (Western Australia). (Version version 1.0) [Data set]. Zenodo. http://doi.org/10.5281/10.5281/zenodo.443179
Mansfield (Victoria, Australia) area original GeoModeller model and relevant MCUE outputs
No full textCompanion dataset to the paper:

Monte Carlo Simulations for Uncertainty Estimation in 3D Geological Modeling, A Guide for Disturbance Distribution Selection and Parameterization, Evren Pakyuz-Charrier, Mark Lindsay, Vitaliy Ogarko, Jeremie Giraud, Mark Jessell

This dataset contains three archives pertaining to Monte Carlo Uncertainty Estimation (MCUE) in implicit 3D geological models:

1. Mansfield_Base.7z is a GeoModeller three dimensional model of the Mansfield syncline area (Victoria, Australia). This model is natively available in every GeoModeller install under the name of "Tutorial case study H".
2. MCUE_Mansfield_nopoletransform.7z is the MCUE output for non pole transfomed foliations.
3. MCUE_Mansfield_poletransform.7z is the MCUE output for non transfomed foliations.

In the output archive files:

- xml files are the GeoModeller project saves, these can be opened with Intrepid's free viewer for GeoModeller 3.3 3.4 (available @: http://www.intrepid-geophysics.com/ig/index.php?page=geomodeller-update)
- .vo, .isi and .vop1 files are the lithological voxet exports in binary GOCAD format, these can be opened with the aforementionned viewer or Geocando (available @: https://sourceforge.net/projects/geocando)
- .vtk files are the MCUE uncertainty indexes outputs, these can be opened with Paraview (available @:https://www.paraview.org/download)
- .csv file is the MCUE probabilistic model output, it can be opened with any text editor /spreadsheet
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