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Статті в журналах з теми "Three-dimensional inversion"

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Автор: Grafiati

Опубліковано: 10 грудня 2022

Оновлено: 28 січня 2023

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1

Timor-Tritsch, Ilan E., Ana Monteagudo, Tanya Tsymbal, and Irina Strok. "Three-Dimensional Inversion Rendering." Journal of Ultrasound in Medicine 24, no. 5 (May 2005): 681–88. http://dx.doi.org/10.7863/jum.2005.24.5.681.

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2

Xiong, Zonghou, and Andreas Kirsch. "Three-dimensional earth conductivity inversion." Journal of Computational and Applied Mathematics 42, no. 1 (September 1992): 109–21. http://dx.doi.org/10.1016/0377-0427(92)90166-u.

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3

Cohen, Jack K., Frank G. Hagin, and Norman Bleistein. "Three‐dimensional Born inversion with an arbitrary reference." GEOPHYSICS 51, no. 8 (August 1986): 1552–58. http://dx.doi.org/10.1190/1.1442205.

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Анотація:

Recent work of G. Beylkin helped set the stage for very general seismic inversions. We have combined these broad concepts for inversion with classical high‐frequency asymptotics and perturbation methods to bring them closer to practically implementable algorithms. Applications include inversion schemes for both stacked and unstacked seismic data. Basic assumptions are that the data have relative true amplitude, and that a reasonably accurate background velocity c(x, y, z) is available. The perturbation from this background is then sought. Since high‐frequency approximations are used throughout, the resulting algorithms essentially locate discontinuities in velocity. An expression for a full 3-D velocity inversion can be derived for a general data surface. In this degree of generality the formula does not represent a computationally feasible algorithm, primarily because a key Jacobian determinant is not expressed in practical terms. In several important cases, however, this shortcoming can be overcome and expressions can be obtained that lead to feasible computing schemes. Zero‐offsets, common‐sources, and common‐receivers are examples of such cases. Implementation of the final algorithms involves, first, processing the data by applying the FFT, making an amplitude adjustment and filtering, and applying an inverse FFT. Then, for each output point, a summation is performed over that portion of the processed data influencing the output point. This last summation involves an amplitude and traveltime along connecting rays. The resulting algorithms are computationally competitive with analogous migration schemes.

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4

Avdeev, Dmitry B., and Anna D. Avdeeva. "A RIGOROUS THREE-DIMENSIONAL MAGNETOTELLURIC INVERSION." Progress In Electromagnetics Research 62 (2006): 41–48. http://dx.doi.org/10.2528/pier06041205.

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5

Sevink, Agur G. J., and Gérard C. Herman. "Three-dimensional, nonlinear, asymptotic seismic inversion." Inverse Problems 12, no. 5 (October 1, 1996): 757–77. http://dx.doi.org/10.1088/0266-5611/12/5/016.

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6

Zhdanov, Michael S., and Sheng Fang. "Three-dimensional quasi-linear electromagnetic inversion." Radio Science 31, no. 4 (July 1996): 741–54. http://dx.doi.org/10.1029/96rs00719.

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7

Tripp, A. C., and G. W. Hohmann. "Three-dimensional electromagnetic cross-well inversion." IEEE Transactions on Geoscience and Remote Sensing 31, no. 1 (1993): 121–26. http://dx.doi.org/10.1109/36.210452.

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8

Madden, T. M., and R. L. Mackie. "Three-dimensional magnetotelluric modelling and inversion." Proceedings of the IEEE 77, no. 2 (1989): 318–33. http://dx.doi.org/10.1109/5.18628.

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9

Keto, Eric, and William Jeffrey. "The three dimensional structure of astronomical sources through optimal inversion." International Astronomical Union Colloquium 131 (1991): 228–32. http://dx.doi.org/10.1017/s0252921100013361.

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AbstractWe explore the application of optimal inversion techniques to astronomical data with a goal of developing a set of procedures for the determination of the three dimensional structure of astronomical sources. Astronomical data present a particularly difficult problem in inversion because: In any observation, 3 of 6 spatial and velocity dimensions are lost in projection onto the plane of the sky and the line of sight velocity. In any inversion, we would like to solve for a number of physical parameters. Generally, these parameters are closely related in their effect on the single observable, the sky brightness.The dimensional deficiency leaves us with an unavoidably large degree of ambiguity (non-uniqueness) in any solution, while the inter-related parameters lead to a high probability of correlated errors and hence instability in the presence of to noise.We show how constraints of symmetry and smoothness source allow us to handle an inversion with an insufficiently sampled data base and mutually dependent solution parameters (mathematically ill-posed and ill-conditioned). The constraints represent a priori information incorporated into the solution; thus very highly constrained inversions are similar to model fitting. In any case the inversion procedure provides us with quantitative statistics on the goodness of fit which may be used to assess the degree of ambiguity in a particular model, and the expected errors and cross-correlated errors on the parameters defining the source structure.We briefly discuss the background and motivation, and outline the procedure in general terms. We refer to papers published in the Ap. J. where different aspects of the inversion are applied to observational data bases collected at the VLA.

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10

Ma, Huan, Handong Tan, and Yue Guo. "Three-Dimensional Induced Polarization Parallel Inversion Using Nonlinear Conjugate Gradients Method." Mathematical Problems in Engineering 2015 (2015): 1–12. http://dx.doi.org/10.1155/2015/464793.

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Four kinds of array of induced polarization (IP) methods (surface, borehole-surface, surface-borehole, and borehole-borehole) are widely used in resource exploration. However, due to the presence of large amounts of the sources, it will take much time to complete the inversion. In the paper, a new parallel algorithm is described which uses message passing interface (MPI) and graphics processing unit (GPU) to accelerate 3D inversion of these four methods. The forward finite differential equation is solved by ILU0 preconditioner and the conjugate gradient (CG) solver. The inverse problem is solved by nonlinear conjugate gradients (NLCG) iteration which is used to calculate one forward and two “pseudo-forward” modelings and update the direction, space, and model in turn. Because each source is independent in forward and “pseudo-forward” modelings, multiprocess modes are opened by calling MPI library. The iterative matrix solver within CULA is called in each process. Some tables and synthetic data examples illustrate that this parallel inversion algorithm is effective. Furthermore, we demonstrate that the joint inversion of surface and borehole data produces resistivity and chargeability results are superior to those obtained from inversions of individual surface data.

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11

Siripunvaraporn, Weerachai, Makoto Uyeshima, and Gary Egbert. "Three-dimensional inversion for Network-Magnetotelluric data." Earth, Planets and Space 56, no. 9 (September 2004): 893–902. http://dx.doi.org/10.1186/bf03352536.

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12

Diaz, Derek D., and Valerie K. Sims. "Accidental Inversion during Three-Dimensional Orientational Control." Proceedings of the Human Factors and Ergonomics Society Annual Meeting 49, no. 13 (September 2005): 1248–50. http://dx.doi.org/10.1177/154193120504901307.

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This research investigates a type of operator error, referred to here as accidental inversion, which occurs during manipulation of the pitch and yaw of a real or simulated object in a three-dimensional environment. Specifically, we investigated whether accidental inversion is linked to a hypothetical individual difference variable referred to here as “axis-mapa“ expectation. Participants exhibited two distinct types of axis-map expectations to the exact same visual stimuli– matching and ambiguous. An important implication for person-machine systems is that one should expect naïve operators to already have a pre-conceived notion of how an interface for orientational control works and that different operators may have different, and possibly opposite, axis-map expectations

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13

Mackie, Randall L., and Theodore R. Madden. "Three-dimensional magnetotelluric inversion using conjugate gradients." Geophysical Journal International 115, no. 1 (October 1993): 215–29. http://dx.doi.org/10.1111/j.1365-246x.1993.tb05600.x.

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14

Siripunvaraporn, Weerachai, Gary Egbert, Yongwimon Lenbury, and Makoto Uyeshima. "Three-dimensional magnetotelluric inversion: data-space method." Physics of the Earth and Planetary Interiors 150, no. 1-3 (May 2005): 3–14. http://dx.doi.org/10.1016/j.pepi.2004.08.023.

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15

Lu, Libin, Kunpeng Wang, Handong Tan, and Qingkun Li. "Three-dimensional magnetotelluric inversion using L-BFGS." Acta Geophysica 68, no. 4 (June 30, 2020): 1049–66. http://dx.doi.org/10.1007/s11600-020-00456-7.

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16

Lin, Tzeu‐Lie. "Prestack traveltime inversion for three‐dimensional structure." GEOPHYSICS 54, no. 3 (March 1989): 359–67. http://dx.doi.org/10.1190/1.1442661.

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An iterative method for determining three‐dimensional (3-D) velocity fields is presented. The input data are offset‐dependent traveltimes for primary reflections. 3-D traveltime derivatives (the Frêchet derivatives) for the 3-D structure are derived. The algorithm simultaneously determines all of the model parameters and is exceedingly robust compared to layer‐stripping algorithms, even for inaccurate data.

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17

Pustisek, A. M. "Noniterative three‐dimensional inversion of magnetic data." GEOPHYSICS 55, no. 6 (June 1990): 782–85. http://dx.doi.org/10.1190/1.1442891.

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The interpretation of magnetic or aeromagnetic data often requires the inverse problem’s solution of the structure of the magnetization interface. This nonlinear inverse problem of mapping the basement topography from potential field data was first discussed by Peters (1949).

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18

Gündoğdu, N. Yıldırım, and Mehmet Emin Candansayar. "Three-dimensional regularized inversion of DC resistivity data with different stabilizing functionals." GEOPHYSICS 83, no. 6 (November 1, 2018): E399—E407. http://dx.doi.org/10.1190/geo2017-0558.1.

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A regularized inversion with a smoothing (SM) stabilizer is commonly used in 3D inversion of direct-current (DC) resistivity data. We have developed a new 3D inversion algorithm for DC resistivity data to investigate the efficiency of various stabilizing functionals. This algorithm is capable of incorporating 3D regularized inversion with [Formula: see text]-norm, [Formula: see text]-norm, SM, minimum support (MS), minimum gradient support (MGS), first-order minimum entropy, and total variation (TV) stabilizers. This is, to our knowledge, a comprehensive study of the effects of these seven different stabilizers on the inverse solution using synthetic and field data. As expected, the structure boundaries are found to be smooth when a SM stabilizer is used in the synthetic data examples. The upper bounds of the structures are recovered close to true model with [Formula: see text]-norm, [Formula: see text]-norm, first-order minimum entropy, and TV stabilizers, but the lower bounds cannot be recovered. Moreover, these stabilizers cannot completely resolve the resistivity of structures. The boundaries and resistivity of the structures are determined to be close to the true model with MS and MGS stabilizers. Similar results are obtained from inversions of field data collected in the Kültepe archaeological site (Kayseri, Turkey). A buried wall structure is correctly identified when the inversion used MS or MGS stabilizers. The archaeological structure found in the excavation studies reveals the success of the solution using MS and MGS stabilizers. These two stabilizers are recommended for an exploration of sharp boundaries structures.

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19

Li, Shiwen, and Yunhe Liu. "Wavelet-Based Three-Dimensional Inversion for Geomagnetic Depth Sounding." Magnetochemistry 8, no. 12 (December 12, 2022): 187. http://dx.doi.org/10.3390/magnetochemistry8120187.

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The complexity of Earth’s structure poses a challenge to the multiscale detection capability of geophysics. In this paper, we present a new wavelet-based three-dimensional inversion method for geomagnetic depth sounding. This method is based on wavelet functions to transfer model parameters in the space domain into the wavelet domain. The model is represented by wavelet coefficients containing both large- and fine-scale information, enabling wavelet-based inversion to describe multiscale anomalies. L1-norm measurement is applied to measure the model roughness to accomplish the sparsity constraint in the wavelet domain. Meanwhile, a staggered-grid finite difference method in a spherical coordinate system is used to calculate the forward responses, and the limited-memory quasi-Newton method is applied to seek the solution of the inversion objective function. Inversion tests of synthetic data for multiscale models show that wavelet-based inversion is stable and has multiresolution. Although higher-order wavelets can lead to finer results, our tests present that a db6 wavelet is suitable for geomagnetic depth sounding inversion. The db6 inversion results of responses at 129 geomagnetic observatories around the world reveal a higher-resolution image of the mantle.

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20

Xu, Yikang, Zhaohua Sun, Wei Gu, Wangping Qian, Qiangru Shen, and Jian Gong. "Three-dimensional inversion analysis of transient electromagnetic response signals of water-bearing abnormal bodies in tunnels based on numerical characteristic parameters." Mathematical Biosciences and Engineering 20, no. 1 (2022): 1106–21. http://dx.doi.org/10.3934/mbe.2023051.

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<abstract> <p>The transient electromagnetic inversion of detection signals mainly depends on fast inversion in the half-space state. However, the interpretation results have a certain degree of uncertainty and blindness, so the accuracy and applicability of the three-dimensional full-space inversion need to be investigated. Two different three-dimensional full-space inversions were carried out. First, the numerical characteristic parameters of the response signals were extracted. Then, the correlations between the numerical characteristic parameters and physical parameters of the water-bearing abnormal bodies were judged, and the judgment criterion of the iterative direction was proposed. Finally, the inversion methods of the iterative algorithm and the BP neural network were utilized based on the virtual example samples. The results illustrate that the proposed numerical characteristic parameters can accurately reflect the response curve of the full-space surrounding rock. The difference in the numerical characteristic parameters was used to determine the update direction and correction value. Both inversion methods have their advantages and disadvantages. A single inversion method cannot realize the three-dimensional inversion of the physical parameters of water-bearing abnormal bodies quickly, effectively and intelligently. Therefore, the benefits of different inversion methods need to be considered to comprehensively select a reasonable inversion method. The results can provide essential ideas for the subsequent interpretation of the three-dimensional spatial response signals of water-bearing abnormal bodies.</p> </abstract>

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21

Pafeng, Josiane, Subhashis Mallick, and Hema Sharma. "Prestack waveform inversion of three-dimensional seismic data — An example from the Rock Springs Uplift, Wyoming, USA." GEOPHYSICS 82, no. 1 (January 1, 2017): B1—B12. http://dx.doi.org/10.1190/geo2016-0079.1.

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Applying seismic inversion to estimate subsurface elastic earth properties for reservoir characterization is a challenge in exploration seismology. In recent years, waveform-based seismic inversions have gained popularity, but due to high computational costs, their applications are limited, and amplitude-variation-with-offset/angle inversion is still the current state-of-the-art. We have developed a genetic-algorithm-based prestack seismic waveform inversion methodology. By parallelizing at multiple levels and assuming a locally 1D structure such that forward computation of wave equation synthetics is computationally efficient, this method is capable of inverting 3D prestack seismic data on parallel computers. Applying this inversion to a real prestack seismic data volume from the Rock Springs Uplift (RSU) located in Wyoming, USA, we determined that our method is capable of inverting the data in a reasonable runtime and producing much higher quality results than amplitude-variation-with-offset/angle inversion. Because the primary purpose for seismic data acquisition at the RSU was to characterize the subsurface for potential targets for carbon dioxide sequestration, we also identified and analyzed some potential primary and secondary storage formations and their associated sealing lithologies from our inversion results.

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22

Luan, Xiaodong, Qingyun Di, Guoqing Xue, and Bin Chen. "Ground-wire Source TEM 3D Full Time Multinary Inversion Using Adaptive Regulation." Journal of Environmental and Engineering Geophysics 25, no. 3 (September 2020): 403–13. http://dx.doi.org/10.32389/jeeg19-037.

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Ground-wire source transient electromagnetic method (GTEM) provides better investigation ability than loop source TEM at a given noise level and decay time. However, at the present time, the method still stays in the one-dimensional inversion interpretation stage. Since actual geological structures are three-dimensionally distributed, the three-dimensional electromagnetic forward and inversion are crucial for understanding the electromagnetic responses of complex geological structures. Moreover, the traditional 3D smooth inversions of geophysical data have been found to inaccurately reflect small-scale and isolated anomalies. In this study, a multinary inversion method was introduced and applied to GTEM inversions. It was found that the proposed method had the ability to enable GTEM to more accurately delineate anomalous bodies when applied to detect high-resistivity target. Then, for the purpose of avoiding the need for multiple inversion tests to determine the regularization factors, a self-adaptive scheme was proposed based on the differences between the data fitting functional and the model functional during each iteration step. It was observed that by introducing the multinary inversion with adaptive regulation, more stable and accurate inversion results were obtained. In the current study, the numerical simulation results had successfully verified that the proposed multinary inversion method had provided better resolution than the traditional inversion methods.

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23

Hu, Xun Yang, Luckshi Rajendran, Emmanuelle Lapointe, Roger Tam, David Li, Anthony Traboulsee, and Alexander Rauscher. "Three-dimensional MRI sequences in MS diagnosis and research." Multiple Sclerosis Journal 25, no. 13 (May 22, 2019): 1700–1709. http://dx.doi.org/10.1177/1352458519848100.

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The most recent guidelines for magnetic resonance imaging (MRI) in multiple sclerosis (MS) recommend three-dimensional (3D) MRI sequences over their two-dimensional (2D) counterparts. This development has been made possible by advances in MRI scanner hardware and software. In this article, we review the 3D versions of conventional sequences, including T1-weighted, T2-weighted and fluid-attenuated inversion recovery (FLAIR), as well as more advanced scans, including double inversion recovery (DIR), FLAIR2, FLAIR*, phase-sensitive inversion recovery, and susceptibility weighted imaging (SWI).

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24

Su, Yang, Changchun Yin, Yunhe Liu, Xiuyan Ren, Bo Zhang, and Bin Xiong. "Three-Dimensional Anisotropic Inversions for Time-Domain Airborne Electromagnetic Data." Minerals 11, no. 2 (February 20, 2021): 218. http://dx.doi.org/10.3390/min11020218.

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Rocks and ores in nature usually appear macro-anisotropic, especially in sedimentary areas with strong layering. This anisotropy will lead to false interpretation of electromagnetic (EM) data when inverted under the assumption of an isotropic earth. However, the time-domain (TD) airborne EM (AEM) inversion for an anisotropic model has not attracted much attention. To get reasonable inversion results from TD AEM data, we present in this paper the forward modeling and inversion methods based on a triaxial anisotropic model. We apply three-dimensional (3D) finite-difference on the secondary scattered electric field equation to calculate the frequency-domain (FD) EM responses, then we use the inverse Fourier transform and waveform convolution to obtain TD responses. For the regularized inversion, we calculate directly the sensitivities with respect to three diagonal conductivities and then use the Gauss–Newton (GN) optimization scheme to recover model parameters. To speed up the computation and to reduce the memory requirement, we adopt the moving footprint concept and separate the whole model into a series of small sub-models for the inversion. Finally, we compare our anisotropic inversion scheme with the isotropic one using both synthetic and field data. Numerical experiments show that the anisotropic inversion has inherent advantages over the isotropic ones, we can get more reasonable results for the anisotropic earth structures.

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25

ZHOU, Qi You, Jun SHIMADA, and Akira SATO. "Three-Dimensional Soil Resistivity Inversion Using Patching Method." Journal of the Japan Society of Engineering Geology 39, no. 6 (1999): 524–32. http://dx.doi.org/10.5110/jjseg.39.524.

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26

Siripunvaraporn, Weerachai, Gary Egbert, and Mokoto Uyeshima. "Data Space Occam’s Inversion: Three-Dimensional Magnetotelluric Case." ASEG Extended Abstracts 2003, no. 1 (April 2003): 1–3. http://dx.doi.org/10.1071/aseg2003_3demab017.

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27

Sasaki, Yutaka. "Three-dimensional inversion of static-shifted magnetotelluric data." Earth, Planets and Space 56, no. 2 (February 2004): 239–48. http://dx.doi.org/10.1186/bf03353406.

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28

Sabbagh, H., and L. Sabbagh. "An eddy-current model for three-dimensional inversion." IEEE Transactions on Magnetics 22, no. 4 (July 1986): 282–91. http://dx.doi.org/10.1109/tmag.1986.1064305.

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29

Zhdanov, Michael S., Masashi Endo, Leif H. Cox, Martin Čuma, Johnathan Linfoot, Chris Anderson, Noel Black, and Alexander V. Gribenko. "Three-dimensional inversion of towed streamer electromagnetic data." Geophysical Prospecting 62, no. 3 (January 10, 2014): 552–72. http://dx.doi.org/10.1111/1365-2478.12097.

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30

Kubota, Ryuji, and Akinori Uchiyama. "Three-dimensional magnetization vector inversion of a seamount." Earth, Planets and Space 57, no. 8 (August 2005): 691–99. http://dx.doi.org/10.1186/bf03351849.

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31

Patro, P. K., M. Uyeshima, and W. Siripunvaraporn. "Three-dimensional inversion of magnetotelluric phase tensor data." Geophysical Journal International 192, no. 1 (November 9, 2012): 58–66. http://dx.doi.org/10.1093/gji/ggs014.

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32

Haber, Eldad, Douglas W. Oldenburg, and R. Shekhtman. "Inversion of time domain three-dimensional electromagnetic data." Geophysical Journal International 171, no. 2 (November 2007): 550–64. http://dx.doi.org/10.1111/j.1365-246x.2007.03365.x.

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33

Newman, G. A., and D. L. Alumbaugh. "Three-dimensional massively parallel electromagnetic inversion-I. Theory." Geophysical Journal International 128, no. 2 (February 1997): 345–54. http://dx.doi.org/10.1111/j.1365-246x.1997.tb01559.x.

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34

Newman, Gregory A., and Michael Commer. "New advances in three dimensional transient electromagnetic inversion." Geophysical Journal International 160, no. 1 (December 21, 2004): 5–32. http://dx.doi.org/10.1111/j.1365-246x.2004.02468.x.

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35

Tanimoto, Toshiro. "Waveform inversion for three-dimensional density andSwave structure." Journal of Geophysical Research 96, B5 (1991): 8167. http://dx.doi.org/10.1029/91jb00196.

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36

Jackiewicz, J., A. C. Birch, L. Gizon, S. M. Hanasoge, T. Hohage, J. B. Ruffio, and M. Švanda. "Multichannel Three-Dimensional SOLA Inversion for Local Helioseismology." Solar Physics 276, no. 1-2 (November 15, 2011): 19–33. http://dx.doi.org/10.1007/s11207-011-9873-8.

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37

Jaffe, Jules S. "Three-Dimensional Probability Density Functions via Tomographic Inversion." SIAM Journal on Applied Mathematics 65, no. 5 (January 2005): 1506–25. http://dx.doi.org/10.1137/s003613990342390x.

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38

Sharma, B. D. "Three-dimensional periodicity and inversion axes in crystals." Journal of Applied Crystallography 28, no. 2 (April 1, 1995): 223. http://dx.doi.org/10.1107/s0021889894010137.

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39

Papadopoulos, Nikos G., Gregory N. Tsokas, Michel Dabas, Myeong-Jong Yi, Jung-Ho Kim, and Panagiotis Tsourlos. "Three-dimensional inversion of automatic resistivity profiling data." Archaeological Prospection 16, no. 4 (October 2009): 267–78. http://dx.doi.org/10.1002/arp.361.

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40

Zhang, Ye, Juraj Irsa, and Jianying Jiao. "Three-dimensional aquifer inversion under unknown boundary conditions." Journal of Hydrology 509 (February 2014): 416–29. http://dx.doi.org/10.1016/j.jhydrol.2013.11.024.

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41

Raga, F., F. Bonilla, M. Sanz-Cortés, and F. Bonilla-Musoles. "Three-dimensional inversion mode rendering in molar pregnancy." Ultrasound in Obstetrics and Gynecology 31, no. 3 (2008): 362–63. http://dx.doi.org/10.1002/uog.5216.

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42

Pauly, John M., Bob S. Hu, Samuel J. Wang, Dwight G. Nishimura, and Albert Macovski. "A three-dimensional spin-echo or inversion pulse." Magnetic Resonance in Medicine 29, no. 1 (January 1993): 2–6. http://dx.doi.org/10.1002/mrm.1910290103.

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43

Plessix, René-Édouard. "Three-dimensional frequency-domain full-waveform inversion with an iterative solver." GEOPHYSICS 74, no. 6 (November 2009): WCC149—WCC157. http://dx.doi.org/10.1190/1.3211198.

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With the acquisition of wide-aperture seismic data sets, full-waveform inversion is an attractive method for deriving velocity models. Three-dimensional implementations require an efficient solver for the wave equation. Computing 3D time-harmonic responses with a frequency-domain solver is complicated because a large linear system with negative and positive eigenvalues must be solved. Time-domain schemes are an alternative. Nevertheless, existing frequency-domain iterative solvers with an efficient preconditioner are a viable option when full-waveform inversion is formulated in the frequency domain. An iterative solver with a multigrid preconditioner is competitive because of a high-order spatial discretization. Numerical examples illustrated the efficiency of the iterative solvers. Three dimensional full-waveform inversion was then studied in the context of deep-water ocean-bottom seismometer acquisition. Three dimensional synthetic data inversion results showed the behavior of full-waveform inversion with respect to the initial model and the minimum frequency available in the data set. Results on a 3D real ocean-bottom seismometer data set demonstrated the relevance of full-waveform inversion, especially to image the shallow part of the model.

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44

Asensio Ramos, A., and C. J. Díaz Baso. "Stokes inversion based on convolutional neural networks." Astronomy & Astrophysics 626 (June 2019): A102. http://dx.doi.org/10.1051/0004-6361/201935628.

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Context. Spectropolarimetric inversions are routinely used in the field of solar physics for the extraction of physical information from observations. The application to two-dimensional fields of view often requires the use of supercomputers with parallelized inversion codes. Even in this case, the computing time spent on the process is still very large. Aims. Our aim is to develop a new inversion code based on the application of convolutional neural networks that can quickly provide a three-dimensional cube of thermodynamical and magnetic properties from the interpreation of two-dimensional maps of Stokes profiles. Methods. We trained two different architectures of fully convolutional neural networks. To this end, we used the synthetic Stokes profiles obtained from two snapshots of three-dimensional magneto-hydrodynamic numerical simulations of different structures of the solar atmosphere. Results. We provide an extensive analysis of the new inversion technique, showing that it infers the thermodynamical and magnetic properties with a precision comparable to that of standard inversion techniques. However, it provides several key improvements: our method is around one million times faster, it returns a three-dimensional view of the physical properties of the region of interest in geometrical height, it provides quantities that cannot be obtained otherwise (pressure and Wilson depression) and the inferred properties are decontaminated from the blurring effect of instrumental point spread functions for free. The code, models, and data are all open source and available for free, to allow both evaluation and training.

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45

Chenot, D., and N. Debeglia. "Three‐dimensional gravity or magnetic constrained depth inversion with lateral and vertical variation of contrast." GEOPHYSICS 55, no. 3 (March 1990): 327–35. http://dx.doi.org/10.1190/1.1442840.

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Depth‐mapping inversion of gravity or magnetic fields generally assumes that anomalies originate from a main density or magnetization contrast interface. This particular inversion takes into account inhomogeneous density or magnetization distributions reflecting sediment compaction and basement heterogeneities: above the interface, the density can be approximated by an exponential function, and below it, an intrabasement contrast map can be used. The inversion also integrates local depth constraints from wells or seismic data, as well as general constraints set on the geometry and the contrast of the interface. After field transformations, spectral analysis and constraints help to define a starting model characterized mainly by the interface mean depth and the mean parameter contrast between the two media. The depth adjustment is completed iteratively under constraints using a space‐domain formulation derived from the Bouguer‐slab approximation. The interface model effect is computed in the wavenumber domain. A model data example shows the accuracy of the inversion and illustrates the role of the constraints. In a field example of a basin area where constraints can be derived from numerous well data, successive inversions of gravity data result in an isodepth map of the basement. The compatibility of the map with local depth constraints from wells is obtained by taking into account density heterogeneities related to known lithologic variations in the basement.

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46

Ma, De Xi, and Rui Qing Du. "Three-Dimensional Inversion and Visual Expression of Two-Dimensional Data in High Density Resistivity Method." Applied Mechanics and Materials 644-650 (September 2014): 1377–81. http://dx.doi.org/10.4028/www.scientific.net/amm.644-650.1377.

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High density resistivity method have integrated resistivity method and induced polarization method. It is widely used in exploring metallic deposits, especially metallic sulfide deposits. The aim of this article is to study three-dimensional inversion and visual expression of two-dimensional profile survey data in high density resistivity. After testing computing capability and application effect of three-dimensional inversion, the results show that the change rules of resistivity can be seen more clearly. And the visual expression after three-dimensional inversion is able to help us observe the distribution characteristics of resistivity with various perspectives. These results are helpful for us to deduce distribution characteristics and special locations of geological structures. They are also helpful to do some effective geological explaining works for spatial distributions and changing rules of ore deposits.

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47

Zhdanov, Michael S., Robert Ellis, and Souvik Mukherjee. "Three‐dimensional regularized focusing inversion of gravity gradient tensor component data." GEOPHYSICS 69, no. 4 (July 2004): 925–37. http://dx.doi.org/10.1190/1.1778236.

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We develop a new method for interpretation of tensor gravity field component data, based on regularized focusing inversion. The focusing inversion makes its possible to reconstruct a sharper image of the geological target than conventional maximum smoothness inversion. This new technique can be efficiently applied for the interpretation of gravity gradiometer data, which are sensitive to local density anomalies. The numerical modeling and inversion results show that the resolution of the gravity method can be improved significantly if we use tensor gravity data for interpretation. We also apply our method for inversion of the gradient gravity data collected by BHP Billiton over the Cannington Ag‐Pb‐Zn orebody in Queensland, Australia. The comparison with the drilling results demonstrates a remarkable correlation between the density anomaly reconstructed by the gravity gradient data and the true structure of the orebody. This result indicates that the emerging new geophysical technology of the airborne gravity gradient observations can improve significantly the practical effectiveness of the gravity method in mineral exploration.

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Pace, Francesca, Anna Martí, Pilar Queralt, Alessandro Santilano, Adele Manzella, Juanjo Ledo, and Alberto Godio. "Three-Dimensional Magnetotelluric Characterization of the Travale Geothermal Field (Italy)." Remote Sensing 14, no. 3 (January 24, 2022): 542. http://dx.doi.org/10.3390/rs14030542.

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The geoelectrical features of the Travale geothermal field (Italy), one of the most productive geothermal fields in the world, have been investigated by means of three-dimensional (3D) magnetotelluric (MT) data inversion. This study presents the first resistivity model of the Travale geothermal field derived from derivative-based 3D MT inversion. We analyzed MT data that have been acquired in Travale over the past decades in order to determine its geoelectrical dimensionality, directionality, and phase tensor properties. We selected data from 51 MT sites for 3D inversion. We carried out a number of 3D MT inversion tests by changing the type of data to be inverted, the inclusion of static-shift correction at some sites where new time-domain electromagnetic soundings (TDEM) were acquired, the grid rotation, as well as the starting model in order to assess the connection between the inversion model and the geology. The final 3D model herein presents deep elongated resistive bodies between the depths of 1.5 and 8 km. They are transverse to the Apennine structures and suggest a correlation with the strike-slip tectonics. Comparison with a seismic velocity model and well log data suggests a highly-fractured volume of rocks with vapor-dominated circulation. The outcome of this study provides new insights into the complex geothermal system of Travale.

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49

Wang, X., and R. O. Hansen. "Inversion for magnetic anomalies of arbitrary three‐dimensional bodies." GEOPHYSICS 55, no. 10 (October 1990): 1321–26. http://dx.doi.org/10.1190/1.1442779.

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Two‐dimensional (profile) inversion techniques for magnetic anomalies are widely used in exploration geophysics: but, until now, the three‐dimensional (3-D) methods available have been restricted in their geologic applicability, dependent upon good initial values or limited by the capabilities of existing computers. We have developed a fully 3-D inversion algorithm intended for routine application to large data sets. The algorithm based on a Fourier transform expression for the magnetic field of homogeneous polyhedral bodies (Hansen and Wang, 1998), is a 3-D generalization of CompuDepth (O’Brien, 1972). Like CompuDepth, the new inversion algorithm employs thespatial equivalent of frequency‐domain autoregression to determine a series of coefficients from which the depths and locations of polyhedral vertices are calculated by solving complex polynomials. These vertices are used to build a 3-D geologic model. Application to the Medicine Lake Volcano aeromagnetic anomaly resulted in a geologically reasonable model of the source.

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50

Günther, Thomas, Carsten Rücker, and Klaus Spitzer. "Three-dimensional modelling and inversion of dc resistivity data incorporating topography - II. Inversion." Geophysical Journal International 166, no. 2 (August 2006): 506–17. http://dx.doi.org/10.1111/j.1365-246x.2006.03011.x.

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