Articles | Volume 16, issue 12
https://doi.org/10.5194/gmd-16-3565-2023
© 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/gmd-16-3565-2023
© Author(s) 2023. This work is distributed under
the Creative Commons Attribution 4.0 License.
the Creative Commons Attribution 4.0 License.
Development and technical paper
| 
28 Jun 2023
Development and technical paper |
| 28 Jun 2023
| 28 Jun 2023
PySubdiv 1.0: open-source geological modeling and reconstruction by non-manifold subdivision surfaces
Mohammad Moulaeifard
CORRESPONDING AUTHOR
Computational Geoscience and Reservoir Engineering
Department, RWTH Aachen University, 52062 Aachen, Germany
Simon Bernard
Computational Geoscience and Reservoir Engineering
Department, RWTH Aachen University, 52062 Aachen, Germany
Florian Wellmann
Computational Geoscience and Reservoir Engineering
Department, RWTH Aachen University, 52062 Aachen, Germany
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Denise Degen, Moritz Ziegler, Oliver Heidbach, Andreas Henk, Karsten Reiter, and Florian Wellmann
Solid Earth, 16, 477–502, https://doi.org/10.5194/se-16-477-2025, https://doi.org/10.5194/se-16-477-2025, 2025
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Obtaining reliable estimates of the subsurface state distributions is essential to determine the location of, e.g., potential nuclear waste disposal sites. However, providing these is challenging since it requires solving the problem numerous times, yielding high computational cost. To overcome this, we use a physics-based machine learning method to construct surrogate models. We demonstrate how it produces physics-preserving predictions, which differentiates it from purely data-driven approaches.
Denise Degen, Daniel Caviedes Voullième, Susanne Buiter, Harrie-Jan Hendricks Franssen, Harry Vereecken, Ana González-Nicolás, and Florian Wellmann
Geosci. Model Dev., 16, 7375–7409, https://doi.org/10.5194/gmd-16-7375-2023, https://doi.org/10.5194/gmd-16-7375-2023, 2023
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In geosciences, we often use simulations based on physical laws. These simulations can be computationally expensive, which is a problem if simulations must be performed many times (e.g., to add error bounds). We show how a novel machine learning method helps to reduce simulation time. In comparison to other approaches, which typically only look at the output of a simulation, the method considers physical laws in the simulation itself. The method provides reliable results faster than standard.
Michael Hillier, Florian Wellmann, Eric A. de Kemp, Boyan Brodaric, Ernst Schetselaar, and Karine Bédard
Geosci. Model Dev., 16, 6987–7012, https://doi.org/10.5194/gmd-16-6987-2023, https://doi.org/10.5194/gmd-16-6987-2023, 2023
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Neural networks can be used effectively to model three-dimensional geological structures from point data, sampling geological interfaces, units, and structural orientations. Existing neural network approaches for this type of modelling are advanced by the efficient incorporation of unconformities, new knowledge inputs, and improved data fitting techniques. These advances permit the modelling of more complex geology in diverse geological settings, different-sized areas, and various data regimes.
Michał P. Michalak, Lesław Teper, Florian Wellmann, Jerzy Żaba, Krzysztof Gaidzik, Marcin Kostur, Yuriy P. Maystrenko, and Paulina Leonowicz
Solid Earth, 13, 1697–1720, https://doi.org/10.5194/se-13-1697-2022, https://doi.org/10.5194/se-13-1697-2022, 2022
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When characterizing geological/geophysical surfaces, various geometric attributes are calculated, such as dip angle (1D) or dip direction (2D). However, the boundaries between specific values may be subjective and without optimization significance, resulting from using default color palletes. This study proposes minimizing cosine distance among within-cluster observations to detect 3D anomalies. Our results suggest that the method holds promise for identification of megacylinders or megacones.
Alexander Schaaf, Miguel de la Varga, Florian Wellmann, and Clare E. Bond
Geosci. Model Dev., 14, 3899–3913, https://doi.org/10.5194/gmd-14-3899-2021, https://doi.org/10.5194/gmd-14-3899-2021, 2021
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Uncertainty is an inherent property of any model of the subsurface. We show how geological topology information – how different regions of rocks in the subsurface are connected – can be used to train uncertain geological models to reduce uncertainty. More widely, the method demonstrates the use of probabilistic machine learning (Bayesian inference) to train structural geological models on auxiliary geological knowledge that can be encoded in graph structures.
Stephanie Thiesen, Diego M. Vieira, Mirko Mälicke, Ralf Loritz, J. Florian Wellmann, and Uwe Ehret
Hydrol. Earth Syst. Sci., 24, 4523–4540, https://doi.org/10.5194/hess-24-4523-2020, https://doi.org/10.5194/hess-24-4523-2020, 2020
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A spatial interpolator has been proposed for exploring the information content of the data in the light of geostatistics and information theory. It showed comparable results to traditional interpolators, with the advantage of presenting generalization properties. We discussed three different ways of combining distributions and their implications for the probabilistic results. By its construction, the method provides a suitable and flexible framework for uncertainty analysis and decision-making.
Fabian Antonio Stamm, Miguel de la Varga, and Florian Wellmann
Solid Earth, 10, 2015–2043, https://doi.org/10.5194/se-10-2015-2019, https://doi.org/10.5194/se-10-2015-2019, 2019
Miguel de la Varga, Alexander Schaaf, and Florian Wellmann
Geosci. Model Dev., 12, 1–32, https://doi.org/10.5194/gmd-12-1-2019, https://doi.org/10.5194/gmd-12-1-2019, 2019
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GemPy is an open-source Python-based 3-D structural geological modeling software, which allows the implicit (i.e. automatic) creation of complex geological models from interface and orientation data. GemPy is implemented in the programming language Python, making use of a highly efficient underlying library, Theano, for efficient code generation that performs automatic differentiation. This enables the link to probabilistic machine-learning and Bayesian inference frameworks.
Raphael Schneeberger, Miguel de La Varga, Daniel Egli, Alfons Berger, Florian Kober, Florian Wellmann, and Marco Herwegh
Solid Earth, 8, 987–1002, https://doi.org/10.5194/se-8-987-2017, https://doi.org/10.5194/se-8-987-2017, 2017
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Structural 3-D modelling has become a widely used technique within applied projects. We performed a typical modelling workflow for a study site with the occurrence of an underground facility. This exceptional setting enabled us to test the surface-based extrapolation of faults with the mapped faults underground. We estimated the extrapolation-related uncertainty with probabilistic 2-D interpolation. This research was conducted to improve structural 3-D modelling in less-constrained areas.
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.
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Empirical modeling of tropospheric delays with uncertainty
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NSOAS24: a new global marine gravity model derived from multi-satellite sea surface slopes
GEOMAPLEARN 1.2: detecting structures from geological maps with machine learning – the case of geological folds
Accelerated pseudo-transient method for elastic, viscoelastic, and coupled hydromechanical problems with applications
Reconciling surface deflections from simulations of global mantle convection
A Bayesian framework for inferring regional and global change from stratigraphic proxy records (StratMC v1.0)
Three-dimensional analytical solution of self-potential from regularly polarized bodies in a layered seafloor model
A fast surrogate model for 3D Earth glacial isostatic adjustment using Tensorflow (v2.8.0) artificial neural networks
ShellSet v1.1.0 parallel dynamic neotectonic modelling: a case study using Earth5-049
FastIsostasy v1.0 – a regional, accelerated 2D glacial isostatic adjustment (GIA) model accounting for the lateral variability of the solid Earth
Broken Terrains v. 1.0: A supervised detection of fault-related lineaments on geological terrains
Automatic adjoint-based inversion schemes for geodynamics: reconstructing the evolution of Earth's mantle in space and time
Benchmarking the accuracy of higher-order particle methods in geodynamic models of transient flow
REHEATFUNQ (REgional HEAT-Flow Uncertainty and aNomaly Quantification) 2.0.1: a model for regional aggregate heat flow distributions and anomaly quantification
A new temperature–photoperiod coupled phenology module in LPJ-GUESS model v4.1: optimizing estimation of terrestrial carbon and water processes
A dynamic informed deep learning method for future estimation of laboratory stick-slip
High-precision 1′ × 1′ bathymetric model of Philippine Sea inversed from marine gravity anomalies
Deciphering past earthquakes from the probabilistic modeling of paleoseismic records – the Paleoseismic EArthquake CHronologies code (PEACH, version 1)
Modelling detrital cosmogenic nuclide concentrations during landscape evolution in Cidre v2.0
IMEX_SfloW2D v2: a depth-averaged numerical flow model for volcanic gas–particle flows over complex topographies and water
Simulation of a fully coupled 3D glacial isostatic adjustment – ice sheet model for the Antarctic ice sheet over a glacial cycle
AdaHRBF v1.0: gradient-adaptive Hermite–Birkhoff radial basis function interpolants for three-dimensional stratigraphic implicit modeling
Reconstructing tephra fall deposits via ensemble-based data assimilation techniques
ClinoformNet-1.0: stratigraphic forward modeling and deep learning for seismic clinoform delineation
Addressing challenges in uncertainty quantification: the case of geohazard assessments
DeepISMNet: three-dimensional implicit structural modeling with convolutional neural network
Towards automatic finite-element methods for geodynamics via Firedrake
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A global, spherical finite-element model for post-seismic deformation using Abaqus
SMAUG v1.0 – a user-friendly muon simulator for the imaging of geological objects in 3-D
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Jungang Wang, Junping Chen, and Yize Zhang
Geosci. Model Dev., 18, 1487–1504, https://doi.org/10.5194/gmd-18-1487-2025, https://doi.org/10.5194/gmd-18-1487-2025, 2025
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The Global Navigation Satellite System (GNSS) is widely used for real-time monitoring and early warning of geohazards. Accurate modeling of tropospheric delays is critical to achieving high-precision GNSS solutions, and using external delays can improve real-time GNSS convergence times. Current empirical delay models only provide delay but not uncertainty. We propose a global empirical delay model with uncertainty and demonstrate its benefits in accelerating GNSS positioning convergence.
Tao Yuan, Shijie Zhong, and Geruo A
Geosci. Model Dev., 18, 1445–1461, https://doi.org/10.5194/gmd-18-1445-2025, https://doi.org/10.5194/gmd-18-1445-2025, 2025
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Earth and other planets deform under various forces. Numerical modeling is critical in understanding the nature of various dynamic deformation processes. This article introduces a newly developed open-source package, CitcomSVE-3.0, which efficiently solves the viscoelastic deformation of planetary bodies. We present benchmark results against a semi-analytical code. With its accuracy and efficiency, CitcomSVE-3.0 could advance research in planetary and climatic sciences.
Shengjun Zhang, Xu Chen, Runsheng Zhou, and Yongjun Jia
Geosci. Model Dev., 18, 1221–1239, https://doi.org/10.5194/gmd-18-1221-2025, https://doi.org/10.5194/gmd-18-1221-2025, 2025
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NSOAS24, a new global marine gravity model derived from multi-satellite altimetry missions, represents a significant advancement over its predecessor, NSOAS22. Through optimized processing procedures, NSOAS24 resolves previous issues and demonstrates improved accuracy. Compared to NSOAS22, NSOAS24 shows a reduction of approximately 0.7 mGal in standard deviation when validated against recent shipborne data. Notably, its accuracy now rivals internationally recognized models DTU21 and V32.1.
David Oakley, Christelle Loiselet, Thierry Coowar, Vincent Labbe, and Jean-Paul Callot
Geosci. Model Dev., 18, 939–960, https://doi.org/10.5194/gmd-18-939-2025, https://doi.org/10.5194/gmd-18-939-2025, 2025
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In this work, we develop two automated workflows for identifying fold structures on geological maps using machine learning. In one method, we identify map patterns suggestive of folding based on pre-defined rules and apply a clustering algorithm to group those from the same fold together. In the other, we train a convolutional neural network to identify folds based on a set of training examples. We apply both methods to a set of synthetic maps and to real-world maps from two locations in France.
Yury Alkhimenkov and Yury Y. Podladchikov
Geosci. Model Dev., 18, 563–583, https://doi.org/10.5194/gmd-18-563-2025, https://doi.org/10.5194/gmd-18-563-2025, 2025
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The accelerated pseudo-transient (APT) method is an efficient way to solve partial differential equations, particularly well-suited for parallel computing. This paper explores the APT method's effectiveness in solving elastic, viscoelastic, and hydromechanical problems, focusing on quasi-static conditions in 1D, 2D, and 3D. The study examines the best numerical settings for fast and accurate solutions. The paper shows how the APT method can handle complex problems in high-resolution models.
Conor P. B. O'Malley, Gareth G. Roberts, James Panton, Fred D. Richards, J. Huw Davies, Victoria M. Fernandes, and Sia Ghelichkhan
Geosci. Model Dev., 17, 9023–9049, https://doi.org/10.5194/gmd-17-9023-2024, https://doi.org/10.5194/gmd-17-9023-2024, 2024
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We wish to understand how the history of flowing rock within Earth's interior impacts deflection of its surface. Observations exist to address this problem, and mathematics and different computing tools can be used to predict histories of flow. We explore how modeling choices impact calculated vertical deflections. The sensitivity of vertical motions at Earth's surface to deep flow is assessed, demonstrating how surface observations can enlighten flow histories.
Stacey Edmonsond and Blake Dyer
EGUsphere, https://doi.org/10.5194/egusphere-2024-2579, https://doi.org/10.5194/egusphere-2024-2579, 2024
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The chemistry of sedimentary rocks is used to reconstruct past changes in Earth’s climate and biogeochemical cycles. Reconstructing global change requires merging stratigraphic proxy records from many locations, each of which may be incomplete, time-uncertain, and influenced by both global and local processes. StratMC uses Bayesian modeling to see through this complexity, building more accurate and testable reconstructions of global change from stratigraphic data.
Pengfei Zhang, Yi-an Cui, Jing Xie, Youjun Guo, Jianxin Liu, and Jieran Liu
Geosci. Model Dev., 17, 8521–8533, https://doi.org/10.5194/gmd-17-8521-2024, https://doi.org/10.5194/gmd-17-8521-2024, 2024
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Our study proposes a three-dimensional analytical solution for the self-potential (SP) method to detect seafloor massive sulfide deposits. Using the mirror image method, we derived formulas for the SP generated by polarized bodies in layered media. We conducted experiments with a simulated environment and compared the results with our theoretical predictions. The findings confirmed a high degree of accuracy, demonstrating the reliability of our approach for faster and precise SP modeling.
Ryan Love, Glenn A. Milne, Parviz Ajourlou, Soran Parang, Lev Tarasov, and Konstantin Latychev
Geosci. Model Dev., 17, 8535–8551, https://doi.org/10.5194/gmd-17-8535-2024, https://doi.org/10.5194/gmd-17-8535-2024, 2024
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A relatively recent advance in glacial isostatic adjustment modeling has been the development of models that include 3D Earth structure, as opposed to 1D structure. However, a major limitation is the computational expense. We have developed a method using artificial neural networks to emulate the influence of 3D Earth models to affordably constrain the viscosity parameter space. Our results indicate that the misfits are of a scale such that useful predictions of relative sea level can be made.
Jon B. May, Peter Bird, and Michele M. C. Carafa
Geosci. Model Dev., 17, 6153–6171, https://doi.org/10.5194/gmd-17-6153-2024, https://doi.org/10.5194/gmd-17-6153-2024, 2024
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ShellSet is a combination of well-known geoscience software packages. It features a simple user interface and is optimised through the addition of a grid search input option (automatically searching for optimal models within a defined N-dimensional parameter space) and the ability to run multiple models in parallel. We show that for each number of models tested there is a performance benefit to parallel running, while two examples demonstrate a use case by improving an existing global model.
Jan Swierczek-Jereczek, Marisa Montoya, Konstantin Latychev, Alexander Robinson, Jorge Alvarez-Solas, and Jerry Mitrovica
Geosci. Model Dev., 17, 5263–5290, https://doi.org/10.5194/gmd-17-5263-2024, https://doi.org/10.5194/gmd-17-5263-2024, 2024
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Ice sheets present a thickness of a few kilometres, leading to a vertical deformation of the crust of up to a kilometre. This process depends on properties of the solid Earth, which can be regionally very different. We propose a model that accounts for this often-ignored heterogeneity and run 100 000 simulation years in minutes. Thus, the evolution of ice sheets is modeled with better accuracy, which is critical for a good mitigation of climate change and, in particular, sea-level rise.
Michał Michalak, Christian Gerhards, and Peter Menzel
EGUsphere, https://doi.org/10.5194/egusphere-2024-2004, https://doi.org/10.5194/egusphere-2024-2004, 2024
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This study presents a novel method for fault detection on geological terrains. Using synthetic models, we applied machine learning to classify terrain shape and nearby features. Testing on real borehole data validated its effectiveness across various fault orientations. The supervised approach represents a significant improvement over older methods that relied on simpler clustering techniques which were capable of identifying less orientations of faults.
Sia Ghelichkhan, Angus Gibson, D. Rhodri Davies, Stephan C. Kramer, and David A. Ham
Geosci. Model Dev., 17, 5057–5086, https://doi.org/10.5194/gmd-17-5057-2024, https://doi.org/10.5194/gmd-17-5057-2024, 2024
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We introduce the Geoscientific ADjoint Optimisation PlaTform (G-ADOPT), designed for inverse modelling of Earth system processes, with an initial focus on mantle dynamics. G-ADOPT is built upon Firedrake, Dolfin-Adjoint and the Rapid Optimisation Library, which work together to optimise models using an adjoint method, aligning them with seismic and geologic datasets. We demonstrate G-ADOPT's ability to reconstruct mantle evolution and thus be a powerful tool in geosciences.
Rene Gassmöller, Juliane Dannberg, Wolfgang Bangerth, Elbridge Gerry Puckett, and Cedric Thieulot
Geosci. Model Dev., 17, 4115–4134, https://doi.org/10.5194/gmd-17-4115-2024, https://doi.org/10.5194/gmd-17-4115-2024, 2024
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Numerical models that use simulated particles are a powerful tool for investigating flow in the interior of the Earth, but the accuracy of these models is not fully understood. Here we present two new benchmarks that allow measurement of model accuracy. We then document that better accuracy matters for applications like convection beneath an oceanic plate. Our benchmarks and methods are freely available to help the community develop better models.
Malte Jörn Ziebarth and Sebastian von Specht
Geosci. Model Dev., 17, 2783–2828, https://doi.org/10.5194/gmd-17-2783-2024, https://doi.org/10.5194/gmd-17-2783-2024, 2024
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Thermal energy from Earth’s active interior constantly dissipates through Earth’s surface. This heat flow is not spatially uniform, and its exact pattern is hard to predict since it depends on crustal and mantle properties, both varying across scales. Our new model REHEATFUNQ addresses this difficulty by treating the fluctuations of heat flow within a region statistically. REHEATFUNQ estimates the regional distribution of heat flow and quantifies known structural signals therein.
Shouzhi Chen, Yongshuo H. Fu, Mingwei Li, Zitong Jia, Yishuo Cui, and Jing Tang
Geosci. Model Dev., 17, 2509–2523, https://doi.org/10.5194/gmd-17-2509-2024, https://doi.org/10.5194/gmd-17-2509-2024, 2024
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It is still a challenge to achieve an accurate simulation of vegetation phenology in the dynamic global vegetation models (DGVMs). We implemented and coupled the spring and autumn phenology models into one of the DGVMs, LPJ-GUESS, and substantially improved the accuracy in capturing the start and end dates of growing seasons. Our study highlights the importance of getting accurate phenology estimations to reduce the uncertainties in plant distribution and terrestrial carbon and water cycling.
Enjiang Yue, Mengjiao Qin, Linshu Hu, Sensen Wu, and Zhenhong Du
Geosci. Model Dev. Discuss., https://doi.org/10.5194/gmd-2024-46, https://doi.org/10.5194/gmd-2024-46, 2024
Revised manuscript accepted for GMD
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Laboratory earthquakes is important means to understand natural earthquakes while previous work focused on transient prediction, lacking future prediction capability. We propose a method and evaluate on data from lab experiments with different slip behaviors. It outperforms state-of-the-art methods in modeling slip moments, intervals and predictions beyond trained horizons especially for challenging slip scenarios, which is crucial for quasi-periodic geophysical process like seismicity.
Dechao An, Jinyun Guo, Xiaotao Chang, Zhenming Wang, Yongjun Jia, Xin Liu, Valery Bondur, and Heping Sun
Geosci. Model Dev., 17, 2039–2052, https://doi.org/10.5194/gmd-17-2039-2024, https://doi.org/10.5194/gmd-17-2039-2024, 2024
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Seafloor topography, as fundamental geoinformation in marine surveying and mapping, plays a crucial role in numerous scientific studies. In this paper, we focus on constructing a high-precision seafloor topography and bathymetry model for the Philippine Sea (5° N–35° N, 120° E–150° E), based on shipborne bathymetric data and marine gravity anomalies, and evaluate the reliability of the model's accuracy.
Octavi Gómez-Novell, Bruno Pace, Francesco Visini, Joanna Faure Walker, and Oona Scotti
Geosci. Model Dev., 16, 7339–7355, https://doi.org/10.5194/gmd-16-7339-2023, https://doi.org/10.5194/gmd-16-7339-2023, 2023
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Knowing the rate at which earthquakes happen along active faults is crucial to characterize the hazard that they pose. We present an approach (Paleoseismic EArthquake CHronologies, PEACH) to correlate and compute seismic histories using paleoseismic data, a type of data that characterizes past seismic activity from the geological record. Our approach reduces the uncertainties of the seismic histories and overall can improve the knowledge on fault rupture behavior for the seismic hazard.
Sébastien Carretier, Vincent Regard, Youssouf Abdelhafiz, and Bastien Plazolles
Geosci. Model Dev., 16, 6741–6755, https://doi.org/10.5194/gmd-16-6741-2023, https://doi.org/10.5194/gmd-16-6741-2023, 2023
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We present the development of a code to simulate simultaneously the dynamics of landscapes over geological time and the evolution of the concentration of cosmogenic isotopes in grains throughout their transport from the slopes to the river outlets. This new model makes it possible to study the relationship between the detrital signal of cosmogenic isotope concentration measured in sediment and the erosion--deposition processes in watersheds.
Mattia de' Michieli Vitturi, Tomaso Esposti Ongaro, and Samantha Engwell
Geosci. Model Dev., 16, 6309–6336, https://doi.org/10.5194/gmd-16-6309-2023, https://doi.org/10.5194/gmd-16-6309-2023, 2023
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We present version 2 of the numerical code IMEX-SfloW2D. With this version it is possible to simulate a wide range of volcanic mass flows (pyroclastic avalanches, lahars, pyroclastic surges), and here we present its application to transient dilute pyroclastic density currents (PDCs). A simulation of the 1883 Krakatau eruption demonstrates the capability of the numerical model to face a complex natural case involving the propagation of PDCs over the sea surface and across topographic obstacles.
Caroline J. van Calcar, Roderik S. W. van de Wal, Bas Blank, Bas de Boer, and Wouter van der Wal
Geosci. Model Dev., 16, 5473–5492, https://doi.org/10.5194/gmd-16-5473-2023, https://doi.org/10.5194/gmd-16-5473-2023, 2023
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The waxing and waning of the Antarctic ice sheet caused the Earth’s surface to deform, which is stabilizing the ice sheet and mainly determined by the spatially variable viscosity of the mantle. Including this feedback in model simulations led to significant differences in ice sheet extent and ice thickness over the last glacial cycle. The results underline and quantify the importance of including this local feedback effect in ice sheet models when simulating the Antarctic ice sheet evolution.
Baoyi Zhang, Linze Du, Umair Khan, Yongqiang Tong, Lifang Wang, and Hao Deng
Geosci. Model Dev., 16, 3651–3674, https://doi.org/10.5194/gmd-16-3651-2023, https://doi.org/10.5194/gmd-16-3651-2023, 2023
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We propose a Hermite–Birkhoff radial basis function (HRBF) formulation, AdaHRBF, with an adaptive gradient magnitude for continuous 3D stratigraphic potential field (SPF) modeling of multiple stratigraphic interfaces. In the linear system of HRBF interpolants constrained by the scattered on-contact attribute points and off-contact attitude points of a set of strata in 3D space, we add a novel optimization term to iteratively obtain the true gradient magnitude.
Leonardo Mingari, Antonio Costa, Giovanni Macedonio, and Arnau Folch
Geosci. Model Dev., 16, 3459–3478, https://doi.org/10.5194/gmd-16-3459-2023, https://doi.org/10.5194/gmd-16-3459-2023, 2023
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Two novel techniques for ensemble-based data assimilation, suitable for semi-positive-definite variables with highly skewed uncertainty distributions such as tephra deposit mass loading, are applied to reconstruct the tephra fallout deposit resulting from the 2015 Calbuco eruption in Chile. The deposit spatial distribution and the ashfall volume according to the analyses are in good agreement with estimations based on field measurements and isopach maps reported in previous studies.
Hui Gao, Xinming Wu, Jinyu Zhang, Xiaoming Sun, and Zhengfa Bi
Geosci. Model Dev., 16, 2495–2513, https://doi.org/10.5194/gmd-16-2495-2023, https://doi.org/10.5194/gmd-16-2495-2023, 2023
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We propose a workflow to automatically generate synthetic seismic data and corresponding stratigraphic labels (e.g., clinoform facies, relative geologic time, and synchronous horizons) by geological and geophysical forward modeling. Trained with only synthetic datasets, our network works well to accurately and efficiently predict clinoform facies in 2D and 3D field seismic data. Such a workflow can be easily extended for other geological and geophysical scenarios in the future.
Ibsen Chivata Cardenas, Terje Aven, and Roger Flage
Geosci. Model Dev., 16, 1601–1615, https://doi.org/10.5194/gmd-16-1601-2023, https://doi.org/10.5194/gmd-16-1601-2023, 2023
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We discuss challenges in uncertainty quantification for geohazard assessments. The challenges arise from limited data and the one-off nature of geohazard features. The challenges include the credibility of predictions, input uncertainty, and assumptions’ impact. Considerations to increase credibility of the quantification are provided. Crucial tasks in the quantification are the exhaustive scrutiny of the background knowledge coupled with the assessment of deviations of assumptions made.
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.
D. Rhodri Davies, Stephan C. Kramer, Sia Ghelichkhan, and Angus Gibson
Geosci. Model Dev., 15, 5127–5166, https://doi.org/10.5194/gmd-15-5127-2022, https://doi.org/10.5194/gmd-15-5127-2022, 2022
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Firedrake is a state-of-the-art system that automatically generates highly optimised code for simulating finite-element (FE) problems in geophysical fluid dynamics. It creates a separation of concerns between employing the FE method and implementing it. Here, we demonstrate the applicability and benefits of Firedrake for simulating geodynamical flows, with a focus on the slow creeping motion of Earth's mantle over geological timescales, which is ultimately the engine driving our dynamic Earth.
Federico Brogi, Simone Colucci, Jacopo Matrone, Chiara Paola Montagna, Mattia De' Michieli Vitturi, and Paolo Papale
Geosci. Model Dev., 15, 3773–3796, https://doi.org/10.5194/gmd-15-3773-2022, https://doi.org/10.5194/gmd-15-3773-2022, 2022
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Computer simulations play a fundamental role in understanding volcanic phenomena. The growing complexity of these simulations requires the development of flexible computational tools that can easily switch between sub-models and solution techniques as well as optimizations. MagmaFOAM is a newly developed library that allows for maximum flexibility for solving multiphase volcanic flows and promotes collaborative work for in-house and community model development, testing, and comparison.
Grace A. Nield, Matt A. King, Rebekka Steffen, and Bas Blank
Geosci. Model Dev., 15, 2489–2503, https://doi.org/10.5194/gmd-15-2489-2022, https://doi.org/10.5194/gmd-15-2489-2022, 2022
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We present a finite-element model of post-seismic solid Earth deformation built in the software package Abaqus for the purpose of calculating post-seismic deformation in the far field of major earthquakes. The model is benchmarked against an existing open-source post-seismic model demonstrating good agreement. The advantage over existing models is the potential for simple modification to include 3-D Earth structure, non-linear rheologies and alternative or multiple sources of stress change.
Alessandro Lechmann, David Mair, Akitaka Ariga, Tomoko Ariga, Antonio Ereditato, Ryuichi Nishiyama, Ciro Pistillo, Paola Scampoli, Mykhailo Vladymyrov, and Fritz Schlunegger
Geosci. Model Dev., 15, 2441–2473, https://doi.org/10.5194/gmd-15-2441-2022, https://doi.org/10.5194/gmd-15-2441-2022, 2022
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Muon tomography is a technology that is used often in geoscientific research. The know-how of data analysis is, however, still possessed by physicists who developed this technology. This article aims at providing geoscientists with the necessary tools to perform their own analyses. We hope that a lower threshold to enter the field of muon tomography will allow more geoscientists to engage with muon tomography. SMAUG is set up in a modular way to allow for its own modules to work in between.
Zuzanna M. Swirad and Adam P. Young
Geosci. Model Dev., 15, 1499–1512, https://doi.org/10.5194/gmd-15-1499-2022, https://doi.org/10.5194/gmd-15-1499-2022, 2022
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Cliff base and top lines that delimit coastal cliff faces are usually manually digitized based on maps, aerial photographs, terrain models, etc. However, manual mapping is time consuming and depends on the mapper's decisions and skills. To increase the objectivity and efficiency of cliff mapping, we developed CliffDelineaTool, an algorithm that identifies cliff base and top positions along cross-shore transects using elevation and slope characteristics.
Holly Kyeore Han, Natalya Gomez, and Jeannette Xiu Wen Wan
Geosci. Model Dev., 15, 1355–1373, https://doi.org/10.5194/gmd-15-1355-2022, https://doi.org/10.5194/gmd-15-1355-2022, 2022
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Interactions between ice sheets, sea level and the solid Earth occur over a range of timescales from years to tens of thousands of years. This requires coupled ice-sheet–sea-level models to exchange information frequently, leading to a quadratic increase in computation time with the number of model timesteps. We present a new sea-level model algorithm that allows coupled models to improve the computational feasibility and precisely capture short-term interactions within longer simulations.
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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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.
Eric A. de Kemp
Geosci. Model Dev., 14, 6661–6680, https://doi.org/10.5194/gmd-14-6661-2021, https://doi.org/10.5194/gmd-14-6661-2021, 2021
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This is a proof of concept and review paper of spatial agents, with initial research focusing on geomodelling. The results may be of interest to others working on complex regional geological modelling with sparse data. Structural agent-based swarming behaviour is key to advancing this field. The study provides groundwork for research in structural geology 3D modelling with spatial agents. This work was done with NetLogo, a free agent modelling platform used mostly for teaching complex systems.
José M. Bastías Espejo, Andy Wilkins, Gabriel C. Rau, and Philipp Blum
Geosci. Model Dev., 14, 6257–6272, https://doi.org/10.5194/gmd-14-6257-2021, https://doi.org/10.5194/gmd-14-6257-2021, 2021
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The hydraulic and mechanical properties of the subsurface are inherently heterogeneous. RHEA is a simulator that can perform couple hydro-geomechanical processes in heterogeneous porous media with steep gradients. RHEA is able to fully integrate spatial heterogeneity, allowing allocation of distributed hydraulic and geomechanical properties at mesh element level. RHEA is a valuable tool that can simulate problems considering realistic heterogeneity inherent to geologic formations.
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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Fault discontinuities in rock packages represent the plane where two blocks of rock have moved. They are challenging to incorporate into geological models because the geometry of the faulted rock units are defined by not only the location of the discontinuity but also the kinematics of the fault. In this paper, we outline a structural geology framework for incorporating faults into geological models by directly incorporating kinematics into the mathematical framework of the model.
Florence Colleoni, Laura De Santis, Enrico Pochini, Edy Forlin, Riccardo Geletti, Giuseppe Brancatelli, Magdala Tesauro, Martina Busetti, and Carla Braitenberg
Geosci. Model Dev., 14, 5285–5305, https://doi.org/10.5194/gmd-14-5285-2021, https://doi.org/10.5194/gmd-14-5285-2021, 2021
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PALEOSTRIP has been developed in the framework of past Antarctic ice sheet reconstructions for periods when bathymetry around Antarctica differed substantially from today. It has been designed for users with no knowledge of numerical modelling and allows users to switch on and off the processes involved in backtracking and backstripping. Applications are broad, and it can be used to restore any continental margin bathymetry or sediment thickness and to perform basin analysis.
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.
Zhenjiao Jiang, Dirk Mallants, Lei Gao, Tim Munday, Gregoire Mariethoz, and Luk Peeters
Geosci. Model Dev., 14, 3421–3435, https://doi.org/10.5194/gmd-14-3421-2021, https://doi.org/10.5194/gmd-14-3421-2021, 2021
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Fast and reliable tools are required to extract hidden information from big geophysical and remote sensing data. A deep-learning model in 3D image construction from 2D image(s) is here developed for paleovalley mapping from globally available digital elevation data. The outstanding performance for 3D subsurface imaging gives confidence that this generic novel tool will make better use of existing geophysical and remote sensing data for improved management of limited earth resources.
Stephan C. Kramer, D. Rhodri Davies, and Cian R. Wilson
Geosci. Model Dev., 14, 1899–1919, https://doi.org/10.5194/gmd-14-1899-2021, https://doi.org/10.5194/gmd-14-1899-2021, 2021
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Computational models of Earth's mantle require rigorous verification and validation. Analytical solutions of the underlying Stokes equations provide a method to verify that these equations are accurately solved for. However, their derivation in spherical and cylindrical shell domains with physically relevant boundary conditions is involved. This paper provides a number of solutions. They are provided in a Python package (Assess) and their use is demonstrated in a convergence study with Fluidity.
Bastian van den Bout, Theo van Asch, Wei Hu, Chenxiao X. Tang, Olga Mavrouli, Victor G. Jetten, and Cees J. van Westen
Geosci. Model Dev., 14, 1841–1864, https://doi.org/10.5194/gmd-14-1841-2021, https://doi.org/10.5194/gmd-14-1841-2021, 2021
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Landslides, debris flows and other types of dense gravity-driven flows threaten livelihoods around the globe. Understanding the mechanics of these flows can be crucial for predicting their behaviour and reducing disaster risk. Numerical models assume that the solids and fluids of the flow are unstructured. The newly presented model captures the internal structure during movement. This important step can lead to more accurate predictions of landslide movement.
Andrzej Górszczyk and Stéphane Operto
Geosci. Model Dev., 14, 1773–1799, https://doi.org/10.5194/gmd-14-1773-2021, https://doi.org/10.5194/gmd-14-1773-2021, 2021
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We present the 3D multi-parameter synthetic geomodel of the subduction zone, as well as the workflow designed to implement all of its components. The model contains different geological structures of various scales and complexities. It is intended to serve as a tool for the geophysical community to validate imaging approaches, design acquisition techniques, estimate uncertainties, benchmark computing approaches, etc.
Mattia de' Michieli Vitturi and Federica Pardini
Geosci. Model Dev., 14, 1345–1377, https://doi.org/10.5194/gmd-14-1345-2021, https://doi.org/10.5194/gmd-14-1345-2021, 2021
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Here, we present PLUME-MoM-TSM, a volcanic plume model that allows us to quantify the formation of aggregates during the rise of the plume, model the phase change of water, and include the possibility to simulate the initial spreading of the tephra umbrella cloud intruding from the volcanic column into the atmosphere. The model is first applied to the 2015 Calbuco eruption (Chile) and provides an analytical relationship between the upwind spreading and some characteristic of the volcanic column.
Zhikui Guo, Lars Rüpke, and Chunhui Tao
Geosci. Model Dev., 13, 6547–6565, https://doi.org/10.5194/gmd-13-6547-2020, https://doi.org/10.5194/gmd-13-6547-2020, 2020
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We present the 3-D hydro-thermo-transport model HydrothermalFoam v1.0, which we designed to provide the marine geosciences community with an easy-to-use and state-of-the-art tool for simulating mass and energy transport in submarine hydrothermal systems. HydrothermalFoam is based on the popular open-source platform OpenFOAM, comes with a number of tutorials, and is published under the GNU General Public License v3.0.
Marisol Monterrubio-Velasco, F. Ramón Zúñiga, Quetzalcoatl Rodríguez-Pérez, Otilio Rojas, Armando Aguilar-Meléndez, and Josep de la Puente
Geosci. Model Dev., 13, 6361–6381, https://doi.org/10.5194/gmd-13-6361-2020, https://doi.org/10.5194/gmd-13-6361-2020, 2020
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The Mexican subduction zone along the Pacific coast is one of the most active seismic zones in the world, where every year larger-magnitude earthquakes shake huge inland cities such as Mexico City. In this work, we use TREMOL (sThochastic Rupture Earthquake ModeL) to simulate the seismicity observed in this zone. Our numerical results reinforce the hypothesis that in some subduction regions single asperities are responsible for producing the observed seismicity.
Thomas Zwinger, Grace A. Nield, Juha Ruokolainen, and Matt A. King
Geosci. Model Dev., 13, 1155–1164, https://doi.org/10.5194/gmd-13-1155-2020, https://doi.org/10.5194/gmd-13-1155-2020, 2020
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We present a newly developed flat-earth model, Elmer/Earth, for viscoelastic treatment of solid earth deformation under ice loads. Unlike many previous approaches with proprietary software, this model is based on the open-source FEM code Elmer, with the advantage for scientists to apply and alter the model without license constraints. The new-generation full-stress ice-sheet model Elmer/Ice shares the same code base, enabling future coupled ice-sheet–glacial-isostatic-adjustment simulations.
Swarup Chauhan, Kathleen Sell, Wolfram Rühaak, Thorsten Wille, and Ingo Sass
Geosci. Model Dev., 13, 315–334, https://doi.org/10.5194/gmd-13-315-2020, https://doi.org/10.5194/gmd-13-315-2020, 2020
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We present CobWeb 1.0, a graphical user interface for analysing tomographic images of geomaterials. CobWeb offers different machine learning techniques for accurate multiphase image segmentation and visualizing material specific parameters such as pore size distribution, relative porosity and volume fraction. We demonstrate a novel approach of dual filtration and dual segmentation to eliminate edge enhancement artefact in synchrotron-tomographic datasets and provide the computational code.
Loïc Huder, Nicolas Gillet, and Franck Thollard
Geosci. Model Dev., 12, 3795–3803, https://doi.org/10.5194/gmd-12-3795-2019, https://doi.org/10.5194/gmd-12-3795-2019, 2019
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The pygeodyn package is a geomagnetic data assimilation tool written in Python. It gives access to the Earth's core flow dynamics, controlled by geomagnetic observations, by means of a reduced numerical model anchored to geodynamo simulation statistics. It aims to provide the community with a user-friendly and tunable data assimilation algorithm. It can be used for education, geomagnetic model production or tests in conjunction with webgeodyn, a set of visualization tools for geomagnetic models.
Mattia de' Michieli Vitturi, Tomaso Esposti Ongaro, Giacomo Lari, and Alvaro Aravena
Geosci. Model Dev., 12, 581–595, https://doi.org/10.5194/gmd-12-581-2019, https://doi.org/10.5194/gmd-12-581-2019, 2019
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Pyroclastic avalanches are a type of granular flow generated at active volcanoes by different mechanisms, including the collapse of steep pyroclastic deposits (e.g., scoria and ash cones) and fountaining during moderately explosive eruptions. We present IMEX_SfloW2D, a depth-averaged flow model describing the granular mixture as a single-phase granular fluid. Benchmark cases and preliminary application to the simulation of the 11 February pyroclastic avalanche at Mt. Etna (Italy) are shown.
Cited articles
Börner, J. H., Bär, M., and Spitzer, K.: Electromagnetic methods
for exploration and monitoring of enhanced geothermal systems – a virtual
experiment, Geothermics, 55, 78–87, https://doi.org/10.1016/j.geothermics.2015.01.011, 2015.
Botsch, M., Kobbelt, L., Pauly, M., Alliez, P., and Lévy, B.: Polygon
mesh processing, CRC press, https://doi.org/10.1201/b10688,
2010.
Cashman, T. J.: NURBS-compatible subdivision surfaces, BCS Learning & Development Limited, ISBN 1906124825, 9781906124823,
2010.
Caumon, G., Collon-Drouaillet, P., Le Carlier de Veslud, C., Viseur, S., and
Sausse, J.: Surface-based 3D modeling of geological structures, Math.
Geosci., 41, 927–945, https://doi.org/10.1007/s11004-009-9244-2, 2009.
De Kemp, E. A.: Visualization of complex geological structures using 3-D
Bézier construction tools, Comput. Geosci., 25, 581–597,
https://doi.org/10.1016/S0098-3004(98)00159-9, 1999.
de la Varga, M., Schaaf, A., and Wellmann, F.: GemPy 1.0: open-source stochastic geological modeling and inversion, Geosci. Model Dev., 12, 1–32, https://doi.org/10.5194/gmd-12-1-2019, 2019.
De Paor, D. G.: Bézier curves and geological design, in: Computer
methods in the geosciences, Elsevier, 389–417, https://doi.org/10.1016/S1874-561X(96)80031-9, 1996.
DeRose, T., Kass, M., and Truong, T.: Subdivision surfaces in character
animation, Proceedings of the 25th annual conference on Computer graphics
and interactive techniques, 19–24 July 1998, Orlando, Florida, United States of America, 85–94, https://doi.org/10.1145/280814.280826, 1998.
Farin, G. and Hamann, B.: Current trends in geometric modeling and selected
computational applications, J. Comput. Phys., 138, 1–15,
https://doi.org/10.1006/jcph.1996.5621, 1997.
Freymark, J., Scheck-Wenderoth, M., Bär, K., Stiller, M., Fritsche,
J.-G., Kracht, M., and Gomez Dacal, M. L.: 3D-URG: 3D gravity constrained
structural model of the Upper Rhine Graben, GFZ Data Services [data set], https://doi.org/10.5880/GFZ.4.5.2020.004, 2020.
Halstead, M., Kass, M., and DeRose, T.: Efficient, fair interpolation using
Catmull-Clark surfaces, Proceedings of the 20th annual conference on
Computer graphics and interactive techniques, 1–6 August 1993, Anaheim, California, United States of America, 35–44, https://doi.org/10.1145/166117.166121, 1993.
Hoppe, H., DeRose, T., Duchamp, T., Halstead, M., Jin, H., McDonald, J.,
Schweitzer, J., and Stuetzle, W.: Piecewise smooth surface reconstruction,
Proceedings of the 21st annual conference on Computer graphics and
interactive techniques, 24–29 July 1994, Orlando, Florida, United States of America, 295–302, https://doi.org/10.1145/192161.192233, 1994.
Jacquemyn, C., Jackson, M. D., and Hampson, G. J.: Surface-based geological
reservoir modelling using grid-free NURBS curves and surfaces, Math.
Geosci., 51, 1–28, https://doi.org/10.1007/s11004-018-9764-8, 2019.
Kälberer, F., Nieser, M., and Polthier, K.: Quadcover-surface
parameterization using branched coverings, Computer graphics forum, 26, 375–384,
https://doi.org/10.1111/j.1467-8659.2007.01060.x, 2007.
Kennedy, J. and Eberhart, R.: Particle swarm optimization, Proceedings of
ICNN'95-international conference on neural networks, 27 November–1 December 1995, Perth, WA, Australia, 1942–1948, https://doi.org/10.1109/ICNN.1995.488968, 1995.
Lavoué, G., Dupont, F., and Baskurt, A.: A framework for quad/triangle
subdivision surface fitting: Application to mechanical objects, Computer
Graphics Forum, 26, 1–14, https://doi.org/10.1111/j.1467-8659.2007.00930.x, 2007.
Lévy, B. and Mallet, J.-L.: Discrete smooth interpolation: Constrained
discrete fairing for arbitrary meshes, ACM Transactions on Graphics, 8, 121–144, https://doi.org/10.1145/62054.62057, 1999.
Loop, C.: Smooth subdivision surfaces based on triangles, Department of Mathematics, University of Utah, 1987.
Ma, X., Keates, S., Jiang, Y., and Kosinka, J.: Subdivision surface fitting
to a dense mesh using ridges and umbilics, Comput. Aided Geom. D.,
32, 5–21, https://doi.org/10.1016/j.cagd.2014.10.001, 2015.
Mallet, J.-L.: Geomodeling, Oxford University Press, Oxford University Press Inc, ISBN-10 0195144600, ISBN-13 978-0195144604, 2002.
Marinov, M. and Kobbelt, L.: Optimization methods for scattered data
approximation with subdivision surfaces, Graphical Models, 67, 452-473,
https://doi.org/10.1016/j.gmod.2005.01.003, 2005.
Miranda, L. J.: PySwarms: a research toolkit for Particle Swarm Optimization
in Python, J. Open Source Softw., 3, 433, https://doi.org/10.21105/joss.00433, 2018.
Moulaeifard, M., Wellmann, F., Bernard, S., de la Varga, M., and Bommes, D.:
Subdivide and Conquer: Adapting Non-Manifold Subdivision Surfaces to
Surface-Based Representation and Reconstruction of Complex Geological
Structures, Math. Geosci., 55, 81–111, https://doi.org/10.1007/s11004-022-10017-x, 2023.
Paluszny, A., Matthäi, S. K., and Hohmeyer, M.: Hybrid finite
element–finite volume discretization of complex geologic structures and a
new simulation workflow demonstrated on fractured rocks, Geofluids, 7,
186–208, https://doi.org/10.1111/j.1468-8123.2007.00180.x,
2007.
Peters, J.: Point-augmented biquadratic C1 subdivision surfaces, Graphical
models, 77, 18–26, https://doi.org/10.1016/j.gmod.2014.10.003,
2015.
Powell, M. J.: An efficient method for finding the minimum of a function of
several variables without calculating derivatives, Computer J., 7,
155–162, https://doi.org/10.1093/comjnl/7.2.155, 1964.
Reif, U.: A unified approach to subdivision algorithms near extraordinary
vertices, Comput. Aided Geom. D., 12, 153–174, https://doi.org/10.1016/0167-8396(94)00007-F, 1995.
Rossignac, J. and Cardoze, D.: Matchmaker: Manifold Breps for non-manifold
r-sets, Proceedings of the fifth ACM symposium on Solid modeling and
applications, 1 June 1999, Ann Arbor Michigan USA, 31–41, https://doi.org/10.1145/304012.304016, 1999.
Sederberg, T. W., Finnigan, G. T., Li, X., Lin, H., and Ipson, H.:
Watertight trimmed NURBS, ACM Transactions on Graphics (TOG), 27, 1–8,
https://doi.org/10.1145/1360612.1360678 2008.
SimBe-hub and MohammadCGRE:SimBe-hub/PySubdiv: PySubdiv (v1.0.0), Zenodo [code and data set], https://doi.org/10.5281/zenodo.6878051, 2022.
Stam, J.: Evaluation of loop subdivision surfaces, SIGGRAPH'98 CDROM
Proceedings, 19–24 July 1998, Orlando, Florida, United States of America, Corpus ID: 8420692, 85–94, 1998.
Sullivan, C. and Kaszynski, A.: PyVista: 3D plotting and mesh analysis
through a streamlined interface for the Visualization Toolkit (VTK), J. Open Source Softw., 4, 1450, https://doi.org/10.21105/joss.01450, 2019.
Suzuki, H., Takeuchi, S., and Kanai, T.: Subdivision surface fitting to a
range of points, Proceedings. Seventh Pacific Conference on Computer
Graphics and Applications (Cat. No. PR00293), 158–167, https://doi.org/10.1109/PCCGA.1999.803359, 1999.
Van Der Walt, S., Colbert, S. C., and Varoquaux, G.: The NumPy array: a
structure for efficient numerical computation, Comput. Sci.
Eng., 13, 22–30, https://doi.org/10.1109/MCSE.2011.37,
2011.
Virtanen, P., Gommers, R., Oliphant, T. E., Haberland, M., Reddy, T.,
Cournapeau, D., Burovski, E., Peterson, P., Weckesser, W., and Bright, J.:
SciPy 1.0: fundamental algorithms for scientific computing in Python, Nature
Methods, 17, 261–272, https://doi.org/10.1038/s41592-019-0686-2, 2020.
Wellmann, F. and Caumon, G.: 3-D Structural geological models: Concepts,
methods, and uncertainties, Adv. Geophys., 59, 1–121,
https://doi.org/10.1016/bs.agph.2018.09.001, 2018.
Wu, X., Zheng, J., Cai, Y., and Li, H.: Variational reconstruction using
subdivision surfaces with continuous sharpness control, Computational Visual
Media, 3, 217–228, https://doi.org/10.1007/s41095-017-0088-2, 2017.
Ying, L. and Zorin, D.: Nonmanifold subdivision, Proceedings Visualization,
VIS'01, 21–26 October 2001, San Diego California, 325–569, https://doi.org/10.1109/VISUAL.2001.964528,
2001.
Short summary
In this work, we propose a flexible framework to generate and interact with geological models using explicit surface representations. The essence of the work lies in the determination of the flexible control mesh, topologically similar to the main geological structure, watertight and controllable with few control points, to manage the geological structures. We exploited the subdivision surface method in our work, which is commonly used in the animation and gaming industry.
In this work, we propose a flexible framework to generate and interact with geological models...
