Efficient 3D large-scale forward modeling of gravity anomaly in space-wavenumber mixing domain

2019 ◽  
Author(s):  
Dongdong Zhao ◽  
Xiaoying Hu ◽  
Shikun Dai* ◽  
Deqiang Tao ◽  
Yinming Zhou ◽  
...  
Keyword(s):  
Gravity Anomaly ◽  
Large Scale ◽  
Forward Modeling

Vening Meinesz and the theory of Wegener

2010 ◽  
Vol 29 (2) ◽  
pp. 213-231
Author(s):  
Willemjan Barzilay
Keyword(s):  
Gravity Anomaly ◽  
Plate Tectonics ◽  
Large Scale ◽  
Scientific Work ◽  
History Of ◽  
Vening Meinesz

The Dutch geophysicist Felix Vening Meinesz is a familiar name in the history of plate tectonics, because of his discovery of the so-called Meinesz zone, a large-scale gravity anomaly in Indonesia. However, what is not familiar is how he himself viewed the theory of Wegener. This article traces how Vening Meinesz thought about Wegener's theory, how it related to his scientific work and how his view of it changed during his career. Vening Meinesz influenced how Dutch geologists thought about Wegener's theory.

The Deposit Features and Comprehensive Information Prospecting Model of Mengyejing Potash Deposits in Yunnan Province

2012 ◽  
Vol 588-589 ◽  
pp. 2136-2139
Author(s):  
Wei Hao Yue ◽  
Jian Guo Gao
Keyword(s):  
Remote Sensing ◽  
Gravity Anomaly ◽  
Large Scale ◽  
Yunnan Province ◽  
Foreland Basin ◽  
The Core ◽  
Geochemical Anomalies ◽  
Comprehensive Information ◽  
Integrated Study ◽  
Chemical Anomaly

Mengyejing potash deposit lies in brown-red and variedness salting-in nagelfluh formation of Cenozoic Mengyejing formation which is located at the back-foreland basin of Lanping-Simao bidirectional arc zone, and it is one of the few large-scale solid potash deposits in China. By integrated study systematically, Mengyejing Potash Deposit’s different scales of mineralization geological anomalies information:geological, geophysical, geochemical, and salt spring chemistry and remote sensing were extracted. A comprehensive information prospecting model of Mengyejing potash deposit is established. Tentatively identified deposits prospecting model of Mengyejing formation, negative gravity anomaly, salt spring chemical anomaly and geochemical anomalies as the core and is of a positive significance for this type of deposit’s prospecting.

scholarly journals 3D induced-polarization data inversion for complex resistivity

Geophysics ◽  
2011 ◽  
Vol 76 (3) ◽  
pp. F157-F171 ◽  
Author(s):  
Michael Commer ◽  
Gregory A. Newman ◽  
Kenneth H. Williams ◽  
Susan S. Hubbard
Keyword(s):  
Environmental Remediation ◽  
Large Scale ◽  
Forward Modeling ◽  
Induced Polarization ◽  
Inversion Method ◽  
Data Sets ◽  
Inversion Algorithm ◽  
Data Set ◽  
Complex Resistivity ◽  
Data Inversion

The conductive and capacitive material properties of the subsurface can be quantified through the frequency-dependent complex resistivity. However, the routine three-dimensional (3D) interpretation of voluminous induced polarization (IP) data sets still poses a challenge due to large computational demands and solution nonuniqueness. We have developed a flexible methodology for 3D (spectral) IP data inversion. Our inversion algorithm is adapted from a frequency-domain electromagnetic (EM) inversion method primarily developed for large-scale hydrocarbon and geothermal energy exploration purposes. The method has proven to be efficient by implementing the nonlinear conjugate gradient method with hierarchical parallelism and by using an optimal finite-difference forward modeling mesh design scheme. The method allows for a large range of survey scales, providing a tool for both exploration and environmental applications. We experimented with an image focusing technique to improve the poor depth resolution of surface data sets with small survey spreads. The algorithm’s underlying forward modeling operator properly accounts for EM coupling effects; thus, traditionally used EM coupling correction procedures are not needed. The methodology was applied to both synthetic and field data. We tested the benefit of directly inverting EM coupling contaminated data using a synthetic large-scale exploration data set. Afterward, we further tested the monitoring capability of our method by inverting time-lapse data from an environmental remediation experiment near Rifle, Colorado. Similar trends observed in both our solution and another 2D inversion were in accordance with previous findings about the IP effects due to subsurface microbial activity.

Evaluation of a rapid hybrid spectral-spatial domain 3D forward-modeling approach for loop-loop electromagnetic induction quadrature data acquired in low-induction-number environments

Geophysics ◽  
2016 ◽  
Vol 81 (6) ◽  
pp. E447-E458 ◽  
Author(s):  
Julien Guillemoteau ◽  
Jens Tronicke
Keyword(s):  
Electrical Conductivity ◽  
Large Scale ◽  
Structural Information ◽  
Forward Modeling ◽  
Spatial Domain ◽  
Near Surface ◽  
Homogeneous Half Space ◽  
Subsurface Environments ◽  
Em Induction ◽  
The Right

When exploring subsurface environments using electromagnetic (EM) induction (EMI) tools, approximate forward-modeling methods based on a homogeneous half-space kernel have been extensively evaluated in the past. For large-scale exploration methods, such as magnetotellurics, marine EM, airborne EM, transient EM, and large offset loop-loop harmonic EM, such forward-modeling approaches are limited because the kernel depends strongly on the subsurface distribution of electrical conductivity. However, the response of small portable EMI loop-loop sensors applied in a low-induction number (LIN) context are known to be more linearly related to the true distribution of electrical conductivity. Thus, data collected using such sensors are more adapted to an approximate forward-modeling with a conductivity-independent kernel. We have evaluated the bias of such an approximate modeling for the case of portable multiconfiguration system measurements in 1D, 2D, and 3D contexts. Our result shows that the approximate approach tends to underestimate the conductivity of more conductive targets but is able to reproduce the right structural information. Compared with previous algorithms presented in the literature, we solved the approximate forward-modeling problem in the hybrid spectral-spatial domain to speed up the computation. Considering the level of accuracy in structural modeling as well as the computational efficiency of our hybrid spectral-spatial approach, we conclude that this method is especially suitable for near-surface, large-scale mapping applications in LIN environments as typically encountered in soil sciences and archaeological studies. For such applications, our approach can be implemented in rapid multichannel deconvolution procedures.

Seismic and gravity anomaly evidence of large-scale compressional deformation off SW Portugal

2010 ◽  
Vol 293 (1-2) ◽  
pp. 171-179 ◽  
Author(s):  
T.A. Cunha ◽  
A.B. Watts ◽  
L.M. Pinheiro ◽  
R. Myklebust
Keyword(s):  
Gravity Anomaly ◽  
Large Scale ◽  
Compressional Deformation ◽  
Sw Portugal

Forward Modeling with Forced Neural Networks for Gravity Anomaly Profıle

2007 ◽  
Vol 39 (6) ◽  
pp. 593-605 ◽  
Author(s):  
Onur Osman ◽  
A. Muhittin Albora ◽  
Osman Nuri Ucan
Keyword(s):  
Neural Networks ◽  
Gravity Anomaly ◽  
Forward Modeling
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