Geoelectric modeling of gold mineralization in a coarse topographic relief using structured and unstructured meshing

In controlled-source electromagnetic (CSEM) inversion with conventional regularization, the reconstructed conductivity image is usually blurry and only has limited resolution. To effectively obtain more compact conductivity models, we apply the concept of multinary transformation to CSEM inversion based on the finite-element method with an unstructured tetrahedral mesh. Within the framework of multinary inversion, the model conductivities are allowed to be clustered only within the designed values, which are usually obtained from other a priori information or from conventional inversion. Synthetic studies show that multinary inversion produces conductivity images with clearer model boundaries compared to the maximum smoothness inversion and the focusing inversion for realistic geoelectric models. We further apply the developed method to a land CSEM survey for mineral exploration. The multinary inversion results are closer to the ground truth compared to the conventional maximum smoothness inversion and the focusing inversion. The developed method and the numerical algorithm provide a new approach and workflow for CSEM inversion when the models need to have clear boundaries and clustering model values. Such geoelectric models could be very useful for geologic interpretation in oil and mineral exploration when a priori information (such as the estimated conductivity values) of the exploration targets is known.

Multi-objective unstructured triangular mesh generation for use in hydrological and land surface models

The stochastic gravity inversion on unstructured meshes is presented. The unstructured meshes are used because they provide the flexibility required to closely approximate complicated geological structures. Sharp topographic relief and geological bodies of complex shapes are usually more accurately described by unstructured meshes rather than with regular grids. The forward method has a closed form solution and gives accurate results. A geostatistical method is applied to invert the gravity data.

This study develops an unstructured mesh generation tool for land surface modeling using a multi‐scale hexagon discrete mesh. The tool can automatically determine the required mesh resolution for different regions based on multi‐objective criteria such as elevation, slope, land cover, and land use. The refined unstructured meshes demonstrate significant enhancement in the representation of spatial heterogeneity. The tool is coupled with the Common Land Model (CoLM) to enable land surface simulations using unstructured meshes. Evaluations focused on runoff, river discharge, and inundation indicate improved model performance compared to traditional structured mesh‐based CoLM simulations under the same computational cost constraints. This tool provides new capabilities for more efficiently capturing localized land surface processes and extreme events.

Land surface topography plays an essential role in flood plain inundation modeling. High-resolution digital surface models (DSMs) based on LiDAR surveys have become increasingly accessible in various geographical areas. Nevertheless, common practice involves filtering out land surface macrostructures, such as trees and buildings, by using obtained digital terrain models (DTMs) to represent the land surface hydraulic geometry. This is done by letting resistance coefficients represent the effects of both micro and macrostructures on surface flow propagation. In addition, significant information loss is observed when digital terrain models are coarsened for computational efficiency.In the present study, physically meaningful unstructured meshes are automatically extracted from high-resolution digital surface models to explicitly describe land surface macrostructures. This is achieved by extracting relevant ridges at a selected level of representation without applying any coarsening or depression filling pre-processing. The effects of these macrostructures on floodwater propagation are evaluated by comparing simulations obtained by using digital terrain models and related Manning coefficients, simulations obtained by using digital surface models representing land surface macrostructures and related Manning coefficients, and observations for a real flood inundation event occurred after a levee failure in the lowlands adjoining the Panaro River in Northern Italy in 2020.The explicit description of land surface macrostructures based on a 1-m digital surface model is found to yield a 42% improvement in the prediction of flooded area extent, a 36% improvement in the prediction of flooded areal position, and a 24% improvement in the prediction of flood plain inundation travel time with respect to the case in which resistance coefficients representing both land surface micro and macrostructures are used. Unstructured meshing of land surface macrostructures based on extracted ridge networks is essential for achieving a detailed description of land surface hydraulic geometry without altering the original topographic data, while also preserving computational efficiency. The obtained results highlight the role of natural and human-made macrotopographic structures in delineating flood plain inundation models and generating flood hazard mapping. These tools represent valuable assets in the context of Emergency Action Planning (EAP) and prevention strategies.

This study develops an unstructured mesh generation tool for land surface modeling using a multi-scale hexagon discrete grid. The tool can automatically determine the required grid resolution for different regions based on multi-objective criteria such as elevation, slope, land cover, and land use. The refined unstructured meshes demonstrate significant enhancement in the representation of spatial heterogeneity. The tool is coupled with the Common Land Model (CoLM) to enable land surface simulations using unstructured grids. Evaluations focused on runoff, river discharge, and inundation indicate improved model performance compared to traditional grid-based CoLM simulations under the same computational cost constraints. This tool provides new capabilities for more efficiently capturing localized land surface processes and extreme events.

Uranium exploration in the Athabasca Basin, Canada, relies heavily on ground-based transient electromagnetic (TEM) surveys to target thin, steeply dipping graphitic conductors that are often closely related to the uranium ore deposits. The interpretation of TEM data is important in identifying the locations and trends of conductors to guide subsequent drilling campaigns. We develop a trial-and-error modeling approach and demonstrate its application to the interpretation of a data set acquired at the Close Lake in the Athabasca Basin. The modeling process has two key tasks: building geoelectric models and computing their TEM responses. The modeling process is repeated with the geoelectric model being iteratively refined based on the match between three-component calculated and measured data from early to late times. To create geoelectric models, we first build a realistic geologic model and discretize it using an unstructured tetrahedral mesh, with each mesh cell populated with appropriate resistivities. To calculate the TEM responses of the geoelectric model, we use a 3D finite-volume time-domain algorithm. We construct our initial model based on existing geologic information and drilling data. We find that this modeling process is flexible and can easily handle thin, steeply dipping conductive graphitic fault models with variable resistivities in the fault and background and with topography. Our interpretation of the Close Lake data matches well with the trend and location of the main conductor as revealed by drilling data and also confirms the existence of a smaller conductor that only caused noticeable anomalous responses in early-time horizontal-component data. The smaller conductor was suggested by previous electromagnetic data but was missed in a recent interpretation based on the modeling of only late-time vertical-component data with plate-based approximate modeling methods.

This paper presents a parallel numerical technique for modelling wave propagation in 3-D heterogeneous anisotropic media. The scheme is developed by following a so-called 3-D grid method of the elastic-isotropic case. The proposed parallel algorithm needs small data exchanges between subdomains in contrast to that developed based on other numerical techniques; therefore, it is more suitable for a PC-Cluster. The algorithm is implemented on a mesh of mixed tetrahedrons and parallelepipedons, thus providing an accurate description of arbitrary 3-D surface and interface topographies and an easy generation of a non-uniform, unstructured mesh. The unstructured mesh means that the proposed algorithm can reduce the memory requirement by flexibly assigning small grid spacing in regions with low velocities and larger grid spacing in regions with higher velocities. Like the 3-D grid method, the resulting anisotropic scheme naturally satisfies the free-surface boundary conditions of arbitrary surface topography. As a result, the near-surface scattering effects can be more accurately modelled. The proposed scheme can handle a general anisotropy without any interpolations. In this paper, the transversely isotropic medium with a tilted symmetry axis, as typically caused by a system of parallel cracks or fine layers, is discussed in detail. A paraxial absorbing boundary condition in a 3-D general anisotropic case is also proposed. Comparisons with analytical solutions demonstrate the accuracy of the parallel algorithm. Computed 3-D radiation patterns illustrate shear-wave splitting, as predicted by the theory. We show the generality and flexibility of the algorithm by modelling wave propagation in an anisotropic half-space with a hemispherical crater on the surface and in mixed isotropic/anisotropic models with horizontal and inclined interfaces.

The marine controlled source electromagnetic method (MCSEM) is widely used in marine oil, gas exploration and deep structures investigation because of its low cost and high efficiency. In this paper, a high-precision forward algorithm for 3D modeling for MCSEM is proposed. Unstructured meshes are used to discretize the model domain, and local mesh refinement techniques are applied, which is conducive to simulating complex terrains and targets. The application of electric dipole discrete technology can load wire excitation sources with arbitrarily complex spatial shapes, which can simulate more realistic electromagnetic field distribution of marine controllable sources electromagnetic in actual exploration. Absorption boundary conditions based on real number and exponential stretching techniques are introduced to improve the numerical solution accuracy. To improve the efficiency of solving, the open-source massively parallel solver (MUMPS) based on the multifrontal algorithm is used to solve the finite element equations. Finally, some typical geoelectric models are designed to verify the correctness and effectiveness of the proposed algorithm. The calculation results show that higher order finite elements bring about higher accuracy. In addition, the loading of absorption boundary conditions is simple and effective than conventional Dirichlet boundary conditions.

<p>Reduction to pole and other transformations of total field magnetic intensity data are often challenging to perform at low magnetic latitudes, when remanence exists, and when large topographic relief exists. Several studies have suggested use of inversion-based equivalent source methods for performing such transformations under those complicating factors. However, there has been little assessment of the importance of erroneous edge effects that occur when fundamental assumptions underlying the transformation procedures are broken. In this work we propose a transformation procedure that utilizes magnetization vector inversion, inversion-based regional field separation, and equivalent source inversion on unstructured meshes. We investigated whether edge effects in transformations could be reduced by performing a regional separation procedure prior to equivalent source inversion. We applied our proposed procedure to the transformation of total field magnetic intensity to magnetic amplitude data, using a complicated synthetic example based on a real geological scenario from mineral exploration. While the procedure performed acceptably on this test example, the results could be improved. We pose many questions regarding the various choices and control parameters used throughout the procedure, but we leave the investigation of those questions to future work.</p>

ABSTRACTReduction to pole and other transformations of total field magnetic intensity data are often challenging to perform at low magnetic latitudes, when remanent magnetization exists, and when large topographic relief exists. Several studies have suggested the use of inversion‐based equivalent source methods for performing such transformations under those complicating factors. However, there has been little assessment of the importance of erroneous edge effects that occur when fundamental assumptions underlying the transformation procedures are broken. In this work we propose a transformation procedure that utilizes magnetization vector inversion, inversion‐based regional field separation and equivalent source inversion on unstructured meshes. We investigated whether edge effects in transformations could be reduced by performing a regional separation procedure prior to equivalent source inversion. We applied our proposed procedure to the transformation of total field magnetic intensity to all three Cartesian magnetic field components using a complicated synthetic example based on a real geological scenario from mineral exploration. While the procedure performed acceptably on this test example, the results could be improved. We pose many questions regarding the various choices and control parameters used throughout the procedure, but we leave the investigation of those questions to future work.

Meteorological forcing plays a critical role in accurately simulating the watershed hydrological cycle. With the advancement of high-performance computing and the development of integrated watershed models, simulating the watershed hydrological cycle at high temporal (hourly to daily) and spatial resolution (10s of meters) has become efficient and computationally affordable. These hyperresolution watershed models require high resolution of meteorological forcing as model input to ensure the fidelity and accuracy of simulated responses. In this study, we utilized the Advanced Terrestrial Simulator (ATS), an integrated watershed model, to simulate surface and subsurface flow and land surface processes using unstructured meshes at the Coal Creek Watershed near Crested Butte (Colorado). We compared simulated watershed hydrologic responses including streamflow, and distributed variables such as evapotranspiration, snow water equivalent (SWE), and groundwater table drivenby three publicly available, gridded meteorological forcing (GMF) – Daily Surface Weather and Climatological Summaries (Daymet), Parameter-elevation Regressions on Independent Slopes Model (PRISM), and North American Land Data Assimilation System (NLDAS). By comparing various spatial resolutions (ranging from 400 m to 4 km) of PRISM, the simulated streamflow only becomes marginally worse when spatial resolution of meteorological forcing is coarsened to 4 km (or 30 % of the watershed area). However, the 4 km resolution has much worse performance than finer resolution in spatially distributedvariables such as SWE. By comparing models forced by different temporal resolutions of NLDAS (hourly to daily), GMF in sub-daily resolution preserves the dynamic watershed responses (e.g., diurnal fluctuation of streamflow) that are absent in results forced by daily resolution. Conversely, the simulated streamflow shows better performance using daily resolution compared to that using sub-daily resolution. Our findings suggest that the choice of GMF and its spatiotemporal resolution depends on the quantity of interest and its spatial and temporal scale, which may have important implications on model calibration and watershed management decisions.

Meteorological forcing plays a critical role in accurately simulating the watershed hydrological cycle. With the advancement of high-performance computing and the development of integrated watershed models, simulating the watershed hydrological cycle at high temporal (hourly to daily) and spatial resolution (10s of meters) has become efficient and computationally affordable. These hyperresolution watershed models require high resolution of meteorological forcing as model input to ensure the fidelity and accuracy of simulated responses. In this study, we utilized the Advanced Terrestrial Simulator (ATS), an integrated watershed model, to simulate surface and subsurface flow and land surface processes using unstructured meshes at the Coal Creek Watershed near Crested Butte (Colorado). We compared simulated watershed hydrologic responses including streamflow, and distributed variables such as evapotranspiration, snow water equivalent (SWE), and groundwater table drivenby three publicly available, gridded meteorological forcing (GMF) – Daily Surface Weather and Climatological Summaries (Daymet), Parameter-elevation Regressions on Independent Slopes Model (PRISM), and North American Land Data Assimilation System (NLDAS). By comparing various spatial resolutions (ranging from 400 m to 4 km) of PRISM, the simulated streamflow only becomes marginally worse when spatial resolution of meteorological forcing is coarsened to 4 km (or 30 % of the watershed area). However, the 4 km resolution has much worse performance than finer resolution in spatially distributedvariables such as SWE. By comparing models forced by different temporal resolutions of NLDAS (hourly to daily), GMF in sub-daily resolution preserves the dynamic watershed responses (e.g., diurnal fluctuation of streamflow) that are absent in results forced by daily resolution. Conversely, the simulated streamflow shows better performance using daily resolution compared to that using sub-daily resolution. Our findings suggest that the choice of GMF and its spatiotemporal resolution depends on the quantity of interest and its spatial and temporal scale, which may have important implications on model calibration and watershed management decisions.

<strong class="journal-contentHeaderColor">Abstract.</strong> Meteorological forcing plays a critical role in accurately simulating the watershed hydrological cycle. With the advancement of high-performance computing and the development of integrated watershed models, simulating the watershed hydrological cycle at high temporal (hourly to daily) and spatial resolution (tens of meters) has become efficient and computationally affordable. These hyperresolution watershed models require high resolution of meteorological forcing as model input to ensure the fidelity and accuracy of simulated responses. In this study, we utilized the Advanced Terrestrial Simulator (ATS), an integrated watershed model, to simulate surface and subsurface flow and land surface processes using unstructured meshes at the Coal Creek Watershed near Crested Butte (Colorado). We compared simulated watershed hydrologic responses including streamflow and distributed variables such as evapotranspiration, snow water equivalent (SWE), and groundwater table driven by three publicly available, gridded meteorological forcings (GMFs) – Daily Surface Weather and Climatological Summaries (Daymet), the Parameter-elevation Regressions on Independent Slopes Model (PRISM), and the North American Land Data Assimilation System (NLDAS). By comparing various spatial resolutions (ranging from 400 m to 4 km) of PRISM, the simulated streamflow only becomes marginally worse when spatial resolution of meteorological forcing is coarsened to 4 km (or 30 % of the watershed area). However, the 4 km-resolution has much worse performance than finer resolution in spatially distributed variables such as SWE. Using the temporally disaggregated PRISM, we compared models forced by different temporal resolutions (hourly to daily), and sub-daily resolution preserves the dynamic watershed responses (e.g., diurnal fluctuation of streamflow) that are absent in results forced by daily resolution. Conversely, the simulated streamflow shows better performance using daily resolution compared to that using sub-daily resolution. Our findings suggest that the choice of GMF and its spatiotemporal resolution depends on the quantity of interest and its spatial and temporal scale, which may have important implications for model calibration and watershed management decisions.

Meteorological forcing plays a critical role in accurately simulating the watershed hydrological cycle. With the advancement of high-performance computing and the development of integrated watershed models, simulating the watershed hydrological cycle at high temporal (hourly to daily) and spatial resolution (10s of meters) has become efficient and computationally affordable. These hyperresolution watershed models require high resolution of meteorological forcing as model input to ensure the fidelity and accuracy of simulated responses. In this study, we utilized the Advanced Terrestrial Simulator (ATS), an integrated watershed model, to simulate surface and subsurface flow and land surface processes using unstructured meshes at the Coal Creek Watershed near Crested Butte (Colorado). We compared simulated watershed hydrologic responses including streamflow, and distributed variables such as evapotranspiration, snow water equivalent (SWE), and groundwater table drivenby three publicly available, gridded meteorological forcing (GMF) – Daily Surface Weather and Climatological Summaries (Daymet), Parameter-elevation Regressions on Independent Slopes Model (PRISM), and North American Land Data Assimilation System (NLDAS). By comparing various spatial resolutions (ranging from 400 m to 4 km) of PRISM, the simulated streamflow only becomes marginally worse when spatial resolution of meteorological forcing is coarsened to 4 km (or 30 % of the watershed area). However, the 4 km resolution has much worse performance than finer resolution in spatially distributedvariables such as SWE. By comparing models forced by different temporal resolutions of NLDAS (hourly to daily), GMF in sub-daily resolution preserves the dynamic watershed responses (e.g., diurnal fluctuation of streamflow) that are absent in results forced by daily resolution. Conversely, the simulated streamflow shows better performance using daily resolution compared to that using sub-daily resolution. Our findings suggest that the choice of GMF and its spatiotemporal resolution depends on the quantity of interest and its spatial and temporal scale, which may have important implications on model calibration and watershed management decisions.