scholarly journals Utilisation of probabilistic MT inversions to constrain magnetic data inversion: proof-of-concept and field application

2021 ◽  
Author(s):  
Jeremie Giraud ◽  
Hoël Seillé ◽  
Mark D. Lindsay ◽  
Gerhard Visser ◽  
Vitaliy Ogarko ◽  
...  
Keyword(s):  
Field Application ◽  
Magnetic Data ◽  
Structural Constraints ◽  
Proof Of Concept ◽  
Bound Constraints ◽  
Probabilistic Information ◽  
Data Inversion ◽  
Magnetic Inversion ◽  
Interval Bound ◽  
Spatially Varying

Abstract. We propose, test and apply a methodology integrating 1D magnetotelluric (MT) and magnetic data inversion, with a focus on the characterization of the cover-basement interface. It consists of a cooperative inversion workflow relying on standalone inversion codes. Probabilistic information about the presence of rock units is derived from MT and passed on to magnetic inversion through constraints combining such structural constraints with petrophysical prior information. First, we perform the 1D probabilistic inversion of MT data for all sites and recover the respective probabilities of observing the cover-basement interface, which we interpolate to the rest of the study area. We then calculate the probabilities of observing the different rock units and partition the model into domains defined by combinations of rock units with non-zero probabilities. Third, we combine such domains with petrophysical information to apply spatially-varying, disjoint interval bound constraints to least-squares magnetic data inversion. We demonstrate the proof-of-concept using a realistic synthetic model reproducing features from the Mansfield area (Victoria, Australia) using a series of uncertainty indicators. We then apply the workflow to field data from the prospective mining region of Cloncurry (Queensland, Australia). Results indicate that our integration methodology efficiently leverages the complementarity between separate MT and magnetic data modelling approaches and can improve our capability to image the cover-basement interface. In the field application case, our findings also suggest that the proposed workflow may be useful to refine existing geological interpretations and to infer lateral variations within the basement.

Gravity and magnetic inversion with minimization of a specific functional

Geophysics ◽  
1984 ◽  
Vol 49 (8) ◽  
pp. 1354-1360 ◽  
Author(s):  
A. Guillen ◽  
V. Menichetti
Keyword(s):  
Physical Properties ◽  
Magnetic Data ◽  
Constant Density ◽  
Minimum Volume ◽  
Data Inversion ◽  
Gravity And Magnetic ◽  
Magnetic Inversion ◽  
Line Passing ◽  
Susceptibility Contrast ◽  
The Moment

The nonuniqueness of gravity or magnetic data inversion is well known. In order to remove ambiguity, some authors have sought solutions minimizing a functional describing geometrical or physical properties. Last and Kubik (1983), in particular, developed a method explaining the observed anomaly by structures of minimum volume. In this method the domain where anomalous sources are searched is divided into elementary prisms of a constant density or susceptibility contrast. Each elementary contrast is allowed to vary individually. Thus a contrast distribution is computed. The search for this kind of solution leads in general to geologically more appropriate bodies, but exceptions do occur. In this paper, the technique is broadened to include the search for solutions minimizing the moment of inertia with respect to the center of gravity or with respect to a given dip line passing through it. The resulting structures are both deeper and more compact, precisely as is required in specific cases. Theoretical and actual examples illustrate this flexible inversion technique.

Magnetic inversion to recover the subsurface block structures based on L1 norm and total variation regularization

2021 ◽  
Author(s):  
Mitsuru Utsugi
Keyword(s):  
Total Variation ◽  
Magnetic Data ◽  
Preconditioned Conjugate Gradient ◽  
Inversion Method ◽  
Total Variation Regularization ◽  
Subsurface Structure ◽  
L1 Norm ◽  
Magnetic Inversion ◽  
Original Definition ◽  
Primal Dual

Summary This paper presents a new sparse inversion method based on L1 norm regularization for 3D magnetic data. In isolation, L1 norm regularization yields model elements which are unconstrained by the input data to be exactly zero, leading to a sparse model with compact and focused structure. Here, we complement the L1 norm with a penalty minimizing total variation, the L1 norm of the model gradients; it is expected that the sharp boundaries of the subsurface structure are not compromised by incorporating this penalty. Although this penalty is widely used in the geophysical inversion studies, it is often replaced by an alternative quadratic penalty to ease solution of the penalized inversion problem; in this study, the original definition of the total variation, i.e., form of the L1 norm of the model gradients, is used. To solve the problem with this combined penalty of L1 norm and total variation, this study introduces alternative direction method of multipliers (ADMM), which is a primal-dual optimization algorithm that solves convex penalized problems based on the optimization of an augmented Lagrange function. To improve the computational efficiency of the algorithm to make this method applicable to large-scale magnetic inverse problems, this study applies matrix compression using the wavelet transform and the preconditioned conjugate gradient method. The inversion method is applied to both synthetic tests and real data, the synthetic tests demonstrate that, when subsurface structure is blocky, it can be reproduced almost perfectly.

scholarly journals Disjoint interval bound constraints using the alternating direction method of multipliers (ADMM) for geologically constrained inversion: Application to gravity data

Geophysics ◽  
2020 ◽  
pp. 1-45
Author(s):  
Vitaliy Ogarko ◽  
Jérémie Giraud ◽  
Roland Martin ◽  
Mark Jessell
Keyword(s):  
Gravity Data ◽  
Alternating Direction Method ◽  
Rock Properties ◽  
Model Parameters ◽  
Method Of Multipliers ◽  
Geological Modeling ◽  
Bound Constraints ◽  
Data Inversion ◽  
Alternating Direction ◽  
Geological Information

To reduce uncertainties in reconstructed images, geological information must be introduced in a numerically robust and stable way during the geophysical data inversion procedure. In the context of potential (gravity) data inversion, it is important to bound the physical properties by providing probabilistic information on the number of lithologies and ranges of values of possibly existing related rock properties (densities). For this purpose, we introduce a generalization of bounding constraints for geophysical inversion based on the alternating direction method of multipliers (ADMM). The flexibility of the proposed technique enables us to take into account petrophysical information as well as probabilistic geological modeling, when it is available. The algorithm introduces a priori knowledge in terms of physically acceptable bounds of model parameters based on the nature of the modeled lithofacies in the region under study. Instead of introducing only one interval of geologically acceptable values for each parameter representing a set of rock properties, we define sets of disjoint intervals using the available geological information. Different sets of intervals are tested, such as quasi-discrete (or narrow) intervals as well as wider intervals provided by geological information obtained from probabilistic geological modeling. Narrower intervals can be used as soft constraints encouraging quasi-discrete inversions. The algorithm is first applied to a synthetic 2D case for proof-of-concept validation and then to the 3D inversion of gravity data collected in the Yerrida basin (Western Australia). Numerical convergence tests show the robustness and stability of the bound constraints we apply, which is not always trivial for constrained inversions. This technique can be a more reliable uncertainty reduction method as well as an alternative to other petrophysically or geologically constrained inversions based on more classical “clustering” or Gaussian-mixture approaches.

Inversion of airborne geophysics over the DO-27/DO-18 kimberlites — Part 1: Potential fields

2017 ◽  
Vol 5 (3) ◽  
pp. T299-T311 ◽  
Author(s):  
Sarah G. R. Devriese ◽  
Kristofer Davis ◽  
Douglas W. Oldenburg
Keyword(s):  
Magnetic Data ◽  
Gravity Gradiometry ◽  
3D Inversion ◽  
Potential Field Data ◽  
Electromagnetic Data ◽  
Magnetic Inversion ◽  
Geophysical Surveys ◽  
Airborne Geophysics ◽  
Joint Interpretation ◽  
Geologic Model

The Tli Kwi Cho (TKC) kimberlite complex contains two pipes, called DO-27 and DO-18, which were discovered during the Canadian diamond exploration rush in the 1990s. The complex has been used as a testbed for ground and airborne geophysics, and an abundance of data currently exist over the area. We have evaluated the historical and geologic background of the complex, the physical properties of interest for kimberlite exploration, and the geophysical surveys. We have carried out 3D inversion and joint interpretation of the potential field data. The magnetic data indicate high susceptibility at DO-18, and the magnetic inversion maps the horizontal extent of the pipe. DO-27 is more complicated. The northern part is highly magnetic and is contaminated with remanent magnetization; other parts of DO-27 have a low susceptibility. Low densities, obtained from the gravity and gravity gradiometry data, map the horizontal extents of DO-27 and DO-18. We combine the 3D density contrast and susceptibility models into a single geologic model that identifies three distinct kimberlite rock units that agree with drilling data. In further research, our density and magnetic susceptibility models are combined with information from electromagnetic data to provide a multigeophysical interpretation of the TKC kimberlite complex.

Fast 3D magnetic inversion of a surface relief in the space domain

Geophysics ◽  
2019 ◽  
Vol 84 (5) ◽  
pp. J57-J67 ◽  
Author(s):  
Marlon C. Hidalgo-Gato ◽  
Valéria C. F. Barbosa
Keyword(s):  
Hessian Matrix ◽  
Computational Cost ◽  
Magnetization Vector ◽  
Forward Modeling ◽  
Magnetic Data ◽  
Total Field ◽  
Inversion Algorithm ◽  
Sensitivity Matrix ◽  
Magnetic Inversion ◽  
Magnetic Basement

We have developed a fast 3D regularized magnetic inversion algorithm for depth-to-basement estimation based on an efficient way to compute the total-field anomaly produced by an arbitrary interface separating nonmagnetic sediments from a magnetic basement. We approximate the basement layer by a grid of 3D vertical prisms juxtaposed in the horizontal directions, in which the prisms’ tops represent the depths to the magnetic basement. To compute the total-field anomaly produced by the basement relief, the 3D integral of the total-field anomaly of a prism is simplified by a 1D integral along the prism thickness, which in turn is multiplied by the horizontal area of the prism. The 1D integral is calculated numerically using the Gauss-Legendre quadrature produced by dipoles located along the vertical axis passing through the prism center. This new magnetic forward modeling overcomes one of the main drawbacks of the nonlinear inverse problem for estimating the basement depths from magnetic data: the intense computational cost to calculate the total-field anomaly of prisms. The new sensitivity matrix is simpler and computationally faster than the one using classic magnetic forward modeling based on the 3D integrals of a set of prisms that parameterize the earth’s subsurface. To speed up the inversion at each iteration, we used the Gauss-Newton approximation for the Hessian matrix keeping the main diagonal only and adding the first-order Tikhonov regularization function. The large sparseness of the Hessian matrix allows us to construct and solve a linear system iteratively that is faster and demands less memory than the classic nonlinear inversion with prism-based modeling using 3D integrals. We successfully inverted the total-field anomaly of a simulated smoothing basement relief with a constant magnetization vector. Tests on field data from a portion of the Pará-Maranhão Basin, Brazil, retrieved a first depth-to-basement estimate that was geologically plausible.

Inversion of magnetic and frequency-domain electromagnetic data for investigating lithologies associated with gold mineralization in the Canadian Malartic area, Québec, Canada

2020 ◽  
pp. 1-20
Author(s):  
Mehrdad Darijani ◽  
Colin G. Farquharson
Keyword(s):  
Frequency Domain ◽  
Gold Mineralization ◽  
Volcanic Rocks ◽  
Tetrahedral Mesh ◽  
Iron Formation ◽  
Magnetic Data ◽  
Low Grade ◽  
Metasedimentary Rocks ◽  
Magnetic Inversion ◽  
Northern Edge

Canadian Malartic is an Archean low-grade bulk tonnage native gold deposit. The deposit is mostly located in altered clastic metasedimentary rocks, mafic–ultramafic dykes, and monzodioritic porphyry intrusions. Airborne magnetic and frequency-domain electromagnetic (EM) data were inverted to reconstruct the geological units associated with the mineralization, especially the intrusive masses. The 3-D inversion of magnetic data, which used a tetrahedral mesh to a depth of 2.4 km, shows that mafic volcanic rocks and iron formation rocks extend to depth in the area, more so than diabase dykes. The magnetic inversion also shows that the diorite and monzodiorite rocks of the Lac Fournière A pluton are dipping toward the south on its northern edge at the contact with the metasedimentary rocks. The 1-D inversion of the frequency-domain EM data, for both electrical conductivity and magnetic susceptibility, is able to reconstruct geological structures to a depth of approximately 100 m, providing more details and information about these features. The intrusive masses such as diabase dykes, diorite and monzodiorite rocks, and mafic volcanic rocks are reconstructed as electrically conductive structures in the inversion results. The metasedimentary rocks are resistive, and the overburden is conductive in most of the area. The geophysical data and inversion results suggest the presence of some features (such as diabase dykes and monzodiorite rocks) that are not yet present on some parts of the geology map. A comparison of the EM-derived susceptibility and the magnetic-derived susceptibility over the iron formations can reveal the effect of remanent magnetization.

scholarly journals Three-Dimensional Magnetic Inversion Based on an Adaptive Quadtree Data Compression

2020 ◽  
Vol 10 (21) ◽  
pp. 7636
Author(s):  
Dandan Jiang ◽  
Zhaofa Zeng ◽  
Shuai Zhou ◽  
Yanwu Guan ◽  
Tao Lin ◽  
...  
Keyword(s):  
Data Compression ◽  
Large Scale ◽  
Mineral Exploration ◽  
Three Dimensional ◽  
Original Data ◽  
Magnetic Data ◽  
The Best Approximation ◽  
Magnetic Inversion ◽  
Iterative Inversion ◽  
Computationally Intensive

Three-dimensional magnetic inversion allows the distribution of magnetic parameters to be obtained, and it is an important tool for geological exploration and interpretation. However, because of the redundancy of the data obtained from large-scale investigations or high-density sampling, it is very computationally intensive to use these data for iterative inversion calculations. In this paper, we propose a method for compressing magnetic data by using an adaptive quadtree decomposition method, which divides the two-dimensional data region into four quadrants and progressively subdivides them by recursion until the data in each quadrant meets the regional consistency criterion. The method allows for dense sampling at the abnormal boundaries with large amplitude changes and sparse sampling at regions with small amplitude changes, and achieves the best approximation to the original data with the least amount of data, thus retaining more anomalous information while achieving the purpose of data compression. In addition, assigning values to the data in the quadrants using the averaging method is essentially equivalent to average filtering, which reduces the noise of the magnetic data. Testing the synthetic model and applying the method to mineral exploration a prove that it can effectively compress the magnetic data and greatly improve the computational efficiency.

Stepped inversion of magnetic data

Geophysics ◽  
2007 ◽  
Vol 72 (3) ◽  
pp. L21-L30 ◽  
Author(s):  
Soraya Lozada Tuma ◽  
Carlos Alberto Mendonça
Keyword(s):  
Magnetic Anomaly ◽  
Shape Function ◽  
Source Parameters ◽  
Real Data ◽  
Magnetic Data ◽  
Total Field ◽  
Magnetization Direction ◽  
Magnetization Intensity ◽  
Magnetic Inversion ◽  
Total Gradient

We present a three-step magnetic inversion procedure in which invariant quantities with respect to source parameters are inverted sequentially to give (1) shape cross section, (2) magnetization intensity, and (3) magnetization direction for a 2D (elongated) magnetic source. The quantity first inverted (called here the shape function) is obtained from the ratio of the gradient intensity of the total-field anomaly to the intensity of the anomalous vector field. For homogenous sources, the shape function is invariant with source magnetization and allows reconstruction of the source geometry by attributing an arbitrary magnetization to trial solutions. Once determined, the source shape is fixed and magnetization intensity is estimated by fitting the total gradient of the total-field anomaly (equivalent to the amplitude of the analytic signal of magnetic anomaly). Finally, the source shape and magnetization intensity are fixed and the magnetization direction is determined by fitting the magnetic anomaly. As suggested by numerical modeling and real data application, stepped inversion allows checking whether causative sources are homogeneous. This is possible because the shape function from inhomogeneous sources can be fitted by homogeneous models, but a model obtained in this way fits neither the total gradient of the magnetic anomaly nor the magnetic anomaly itself. Such a criterion seems effective in recognizing strongly inhomogeneous sources. Stepped inversion is tested with numerical experiments, and is used to model a magnetic anomaly from intrusive basic rocks from the Paraná Basin, Brazil.

GMINV: A computer program for gravity or magnetic data inversion

1995 ◽  
Vol 21 (2) ◽  
pp. 301-319 ◽  
Author(s):  
B.Narasimha Rao ◽  
P. Ramakrishna ◽  
A. Markandeyulu
Keyword(s):  
Computer Program ◽  
Magnetic Data ◽  
Data Inversion
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