Joint Inversion of Seismic and Audio Magnetotelluric Data with Structural Constraint for Metallic Deposit

2018 ◽  
Vol 23 (2) ◽  
pp. 159-169
Author(s):  
Xuan Feng ◽  
Enhedelihai Nilot ◽  
Cai Liu ◽  
Minghe Zhang ◽  
Hailong Yu ◽  
...  
Keyword(s):  
Partial Information ◽  
Joint Inversion ◽  
Waveform Inversion ◽  
Geophysical Methods ◽  
P Wave ◽  
Real Field ◽  
Sulfide Deposit ◽  
Inversion Algorithm ◽  
Data Types ◽  
Magnetotelluric Data

Audio magnetotelluric (AMT) and seismic methods are widely used to detect metallic deposits. However, each geophysical method only provides partial information of the underground target. Besides, individual methods have inherent limitations and ambiguity which leads to non-uniqueness when solving the inverse problem. To obtain a more robust and consistent ore deposit model, it is best to integrate different geophysical methods and data types. Towards this effort, we propose a joint inversion algorithm using cross-gradient constraint to build a connection between seismic and AMT data, and simultaneously invert for a resistivity and P-wave velocity model. Compared with separate AMT Gauss–Newton inversion and seismic Full waveform inversion (FWI) method, we can get more detailed and robust inversion results. In addition, frequency domain FWI with the Limited-Memory-Broyden–Fletcher–Goldfarb–Shanno (L-BFGS) algorithm provides an effective way to reduce computer memory usage and improve convergence speed. This joint inversion algorithm has been tested using simple synthetic models with two cross targets. The results obtained with separate inversions were compared with those obtained with joint inversion. Then, we applied the algorithm to geophysical models of the Jinchuan sulfide deposit. The AMT results obtained with joint inversion of seismic data were better than those obtained with separate AMT inversion. The joint inversion approach appears more robust than the traditional separate FWI inversion and it is recommended that the proposed algorithm be considered in future projects of real field data.

Joint inversion of full-waveform ground-penetrating radar and electrical resistivity data: Part 1

Geophysics ◽  
2020 ◽  
Vol 85 (6) ◽  
pp. H97-H113 ◽  
Author(s):  
Diego Domenzain ◽  
John Bradford ◽  
Jodi Mead
Keyword(s):  
Electrical Conductivity ◽  
Electrical Resistivity ◽  
Ground Penetrating Radar ◽  
Joint Inversion ◽  
Geophysical Methods ◽  
Data Types ◽  
Full Waveform ◽  
Electrical Permittivity ◽  
Ground Penetrating ◽  
Subsurface Geometry

We have developed an algorithm for joint inversion of full-waveform ground-penetrating radar (GPR) and electrical resistivity (ER) data. The GPR data are sensitive to electrical permittivity through reflectivity and velocity, and electrical conductivity through reflectivity and attenuation. The ER data are directly sensitive to the electrical conductivity. The two types of data are inherently linked through Maxwell’s equations, and we jointly invert them. Our results show that the two types of data work cooperatively to effectively regularize each other while honoring the physics of the geophysical methods. We first compute sensitivity updates separately for the GPR and ER data using the adjoint method, and then we sum these updates to account for both types of sensitivities. The sensitivities are added with the paradigm of letting both data types always contribute to our inversion in proportion to how well their respective objective functions are being resolved in each iteration. Our algorithm makes no assumptions of the subsurface geometry nor the structural similarities between the parameters with the caveat of needing a good initial model. We find that our joint inversion outperforms the GPR and ER separate inversions, and we determine that GPR effectively supports ER in regions of low conductivity, whereas ER supports GPR in regions with strong attenuation.

Modeling the electrical conductivity of hydrogeological strata using joint-inversion of loop-loop electromagnetic data

Geophysics ◽  
2012 ◽  
Vol 77 (4) ◽  
pp. WB99-WB107 ◽  
Author(s):  
J. Triantafilis ◽  
V. Wong ◽  
F. A. Monteiro Santos ◽  
D. Page ◽  
R. Wege
Keyword(s):  
Electrical Conductivity ◽  
Water Table ◽  
Saline Water ◽  
Joint Inversion ◽  
Geophysical Methods ◽  
Agricultural Landscapes ◽  
Estuarine Sediments ◽  
North Coast ◽  
Inversion Algorithm ◽  
Text Data

In coastal-estuarine agricultural landscapes that are inherently rich in sulfidic sediments and saline water-tables, natural resource management data need to be collected to describe the heterogeneous nature of the soil, underlying regolith, and interactions with groundwater. Geophysical methods, such as electromagnetic (EM) induction instruments, are increasingly being used. This is because they measure apparent soil electrical conductivity [Formula: see text], which has previously been successfully used to map the areal distribution of soil (e.g., salinity) and hydrological (e.g., water-table depth) properties. We explored the potential of a next-generation DUALEM-421 and EM34 to be used independently and in conjunction with each other to provide information we can use to represent the pedological and hydrogeological setting of alluvial and estuarine sediments. A 1D laterally constrained joint-inversion algorithm can account for the nonlinearity of large [Formula: see text] (i.e., [Formula: see text]). We applied this algorithm to develop 2D cross sections of electrical conductivity ([Formula: see text]) from DUALEM-421 and EM34 [Formula: see text] data acquired across an estuarine landscape and situated within Quaternary fluvial sediments adjacent to Rocky Mouth Creek on the far north coast of New South Wales, Australia. We compared this joint-inversion model with inversions of the DUALEM-421 and EM34 [Formula: see text] data independently of each other. For the most part, the general patterns of the inverted models of [Formula: see text] compare favorably with existing pedological and hydrogeological interpretations, based on results achieved during a previous geoelectrical survey. However, the joint-inversion provides a more realistic model of the location and extent of a saline water-table and associated with the location of sulfidic sediments.

Structural joint inversion on irregular meshes

2019 ◽  
Vol 220 (3) ◽  
pp. 1995-2008 ◽  
Author(s):  
C Jordi ◽  
J Doetsch ◽  
T Günther ◽  
C Schmelzbach ◽  
H Maurer ◽  
...  
Keyword(s):  
Electrical Resistivity ◽  
Joint Inversion ◽  
A Priori ◽  
Structural Similarity ◽  
P Wave ◽  
Parameter Distribution ◽  
Data Sets ◽  
Inversion Algorithm ◽  
Structural Joint ◽  
Irregular Meshes

SUMMARY Structural joint inversion of several data sets on an irregular mesh requires appropriate coupling operators. To date, joint inversion algorithms are primarily designed for the use on regular rectilinear grids and impose structural similarity in the direct neighbourhood of a cell only. We introduce a novel scheme for calculating cross-gradient operators based on a correlation model that allows to define the operator size by imposing physical length scales. We demonstrate that the proposed cross-gradient operators are largely decoupled from the discretization of the modelling domain, which is particularly important for irregular meshes where cell sizes vary. Our structural joint inversion algorithm is applied to a synthetic electrical resistivity tomography and ground penetrating radar 3-D cross-well experiment aiming at imaging two anomalous bodies and extracting the parameter distribution of the geostatistical background models. For both tasks, joint inversion produced superior results compared with individual inversions of the two data sets. Finally, we applied structural joint inversion to two field data sets recorded over a karstified limestone area. By including geological a priori information via the correlation-based operators into the joint inversion, we find P-wave velocity and electrical resistivity tomograms that are in accordance with the expected subsurface geology.

IGMAS+ – a tool for interdisciplinary 3D potential field modelling of complex geological structures.

2020 ◽  
Author(s):  
Sabine Schmidt ◽  
Denis Anikiev ◽  
Hans-Jürgen Götze ◽  
Àngela Gomez Garcia ◽  
Maria Laura Gomez Dacal ◽  
...  
Keyword(s):  
Joint Inversion ◽  
Waveform Inversion ◽  
Geophysical Methods ◽  
Research Centre ◽  
Nazca Plate ◽  
Salt Domes ◽  
The North ◽  
Gravity And Magnetic ◽  
Interactive 3D ◽  
3D Thermal Modeling

<p>We introduce a new approach for 3D joint inversion of potential fields and its derivatives under the condition of constraining data and information. The interactive 3D gravity and magnetic application IGMAS (Interactive Gravity and Magnetic Application System) has been around for more than 30 years, initially developed on a mainframe and then transferred to the first DOS PCs, before it was adapted to Linux in the ’90s and finally implemented as a cross-platform Java application with GUI called IGMAS+. The software has proven to be very fast, accurate and easy to use once a model has been established. Since 2019 IGMAS+ has been maintained and developed in the Helmholtz Centre Potsdam – GFZ German Research Centre by the staff of Section 4.5 – Basin Modelling and ID2 – eScience Centre.</p><p>The analytical solution of the volume integral for the gravity and magnetic effect of a homogeneous body is based on the reduction of the three-folded integral to an integral over the bounding polyhedrons (in IGMAS polyhedrons are built by triangles). Later the algorithm has been extended to cover all elements of the gravity tensor as well. Optimized storage enables very fast inversion of densities and changes to the model geometry and this flexibility makes geometry changes easy. The geometry is updated and the gravity is recalculated immediately after each change. Because of the triangular model structure, IGMAS can handle complex structures (multi Z surfaces) like the overhangs of salt domes very well. Geophysical investigations may cover huge areas of several thousand square kilometers but also models of Applied Geophysics at a meter scale. Due to the curvature of the Earth, the use of spherical geometries and calculations is necessary.</p><p>The model technique is user-friendly because it is highly interactive, operates ideally in real-time whilst conserving topology and can be used for both flat (regional) and spherical models (global) in 3D. Modeling is constrained by seismic and structural input from independent data sources and is essential toward true integration of 3D thermal modeling or even Full Waveform Inversion. We are close to the demand for treating all geophysical methods in a single model of the subsurface and aim of fulfilling most of the constraints: measurements and geological plausibility.</p><p>We demonstrate the flexibility of the software by modeling: (1) the southern segment of the Central Andes which is designed to assess the relationship between the characteristics of the overriding plate and the deformation and dynamics of the subduction system; (2) the South Caribbean margin which defines the two flat-slab subductions of the Nazca Plate and the Caribbean Plate, with variable mantle density distribution implemented by voxels; (3) the North Patagonian Massif Plateau in Argentina which provides insight into the main height differences between the plateau and the surroundings; and (4) an Alpine model which interrogates the strength of the lithosphere at different locations through the Alps and their forelands.</p>

scholarly journals Quantifying the basal conditions of a mountain glacier using a targeted full-waveform inversion: Bench Glacier, Alaska, USA

2014 ◽  
Vol 60 (224) ◽  
pp. 1221-1231 ◽  
Author(s):  
E. Babcock ◽  
J. Bradford
Keyword(s):  
Thin Layer ◽  
Waveform Inversion ◽  
Basal Layer ◽  
P Wave ◽  
Full Waveform Inversion ◽  
Inversion Algorithm ◽  
Mean Velocity ◽  
Mountain Glacier ◽  
Full Waveform ◽  
Seismic Quality Factor

AbstractGlacier dynamics are inextricably linked to the basal conditions of glaciers. Seismic reflection methods can image the glacier bed under certain conditions. However, where a seismically thin layer of material is present at the bed, traditional analyses may fail to fully characterize bed properties. We use a targeted full-waveform inversion algorithm to quantify the basal-layer parameters of a mountain glacier: thickness (d), P-wave velocity (α) and density (ρ). We simultaneously invert for the seismic quality factor (Q) of the bulk glacier ice. The inversion seeks to minimize the difference between the data and a one-dimensional reflectivity algorithm using a gradient-based search with starting values initialized from a Monte Carlo scheme. We test the inversion algorithm on four basal layer synthetic data traces with 5% added Gaussian noise. The inversion retrieved thin-layer parameters within 10% of synthetic test parameters with the exception of seismic Q. For the seismic dataset from Bench Glacier, Alaska, USA, inversion results indicate a thin basal layer of debris-rich ice within the study area having mean velocity 4000 ± 700 m s–1, density 1900 ± 200 kg m–3 and thickness 6 ± 1.5 m.

Joint electromagnetic and seismic inversion using structural constraints

Geophysics ◽  
2009 ◽  
Vol 74 (6) ◽  
pp. R99-R109 ◽  
Author(s):  
Wenyi Hu ◽  
Aria Abubakar ◽  
Tarek M. Habashy
Keyword(s):  
Seismic Data ◽  
Joint Inversion ◽  
Monitoring And Evaluation ◽  
Structural Similarity ◽  
Compressional Wave ◽  
Seismic Inversion ◽  
P Wave ◽  
Optimization Approach ◽  
Structural Constraints ◽  
Inversion Algorithm

We have developed a frequency-domain joint electromagnetic (EM) and seismic inversion algorithm for reservoir evaluation and exploration applications. EM and seismic data are jointly inverted using a cross-gradient constraint that enforces structural similarity between the conductivity image and the compressional wave (P-wave) velocity image. The inversion algorithm is based on a Gauss-Newton optimization approach. Because of the ill-posed nature of the inverse problem, regularization is used to constrain the solution. The multiplicative regularization technique selects the regularization parameters automatically, improving the robustness of the algorithm. A multifrequency data-weighting scheme prevents the high-frequency data from dominating the inversion process. When the joint-inversion algorithm is applied in integrating marine controlled-source electromagnetic data with surface seismic data for subsea reservoir exploration applications and in integrating crosswell EM and sonic data for reservoir monitoring and evaluation applications, results improve significantly over those obtained from separate EM or seismic inversions.

scholarly journals Pareto Joint Inversion of 2D magnetometric and gravity data- synthetic study

2019 ◽  
Vol 133 ◽  
pp. 01009
Author(s):  
Tomasz Danek ◽  
Andrzej Leśniak ◽  
Katarzyna Miernik ◽  
Elżbieta Śledź
Keyword(s):  
Pareto Front ◽  
Joint Inversion ◽  
Gravity Data ◽  
Group Analysis ◽  
Geophysical Methods ◽  
Model Parameters ◽  
Data Sets ◽  
Inversion Algorithm ◽  
Promising Tool ◽  
Real Model

Pareto joint inversion for two or more data sets is an attractive and promising tool which eliminates target functions weighing and scaling, providing a set of acceptable solutions composing a Pareto front. In former author’s study MARIA (Modular Approach Robust Inversion Algorithm) was created as a flexible software based on global optimization engine (PSO) to obtain model parameters in process of Pareto joint inversion of two geophysical data sets. 2D magnetotelluric and gravity data were used for preliminary tests, but the software is ready to handle data from more than two geophysical methods. In this contribution, the authors’ magnetometric forward solver was implemented and integrated with MARIA. The gravity and magnetometry forward solver was verified on synthetic models. The tests were performed for different models of a dyke and showed, that even when the starting model is a homogeneous area without anomaly, it is possible to recover the shape of a small detail of the real model. Results showed that the group analysis of models on the Pareto front gives more information than the single best model. The final stage of interpretation is the raster map of Pareto front solutions analysis.

Joint acoustic full-waveform inversion of crosshole seismic and ground-penetrating radar data in the frequency domain

Geophysics ◽  
2017 ◽  
Vol 82 (6) ◽  
pp. H41-H56 ◽  
Author(s):  
Xuan Feng ◽  
Qianci Ren ◽  
Cai Liu ◽  
Xuebing Zhang
Keyword(s):  
Frequency Domain ◽  
Ground Penetrating Radar ◽  
Joint Inversion ◽  
Waveform Inversion ◽  
Structural Similarity ◽  
P Wave ◽  
Full Waveform Inversion ◽  
Full Waveform ◽  
Frequency Domain Methods ◽  
Ground Penetrating

Integrating crosshole ground-penetrating radar (GPR) with seismic methods is an efficient way to reduce the uncertainty and ambiguity of data interpretation in shallow geophysical investigations. We have developed a new approach for joint full-waveform inversion (FWI) of crosshole seismic and GPR data in the frequency domain to improve the inversion results of both FWI methods. In a joint objective function, three geophysical parameters (P-wave velocity, permittivity, and conductivity) are effectively connected by three weighted cross-gradient terms that enforce the structural similarity between parameter models. Simulation of acoustic seismic and scalar electromagnetic problems is implemented using 2D finite-difference frequency-domain methods, and the inverse problems of seismic FWI and GPR FWI are solved using a matrix-free truncated Newton algorithm. The joint inversion procedure is performed in several hierarchical frequencies, and the three parameter models are sequentially inverted at each frequency. The joint FWI approach is illustrated using three numerical examples. The results indicate that the joint FWI approach can effectively enhance the structural similarity among the models, modify the structure of each model, and improve the accuracy of inversion results compared with those of individual FWI approaches. Moreover, joint inversion can reduce the trade-off between permittivity and conductivity in GPR FWI, leading to an improved conductivity model in which artifacts are significantly decreased.

Resolving the spatial distribution of the true electrical conductivity with depth using EM38 and EM31 signal data and a laterally constrained inversion model

Soil Research ◽  
2010 ◽  
Vol 48 (5) ◽  
pp. 434 ◽  
Author(s):  
J. Triantafilis ◽  
F. A. Monteiro Santos
Keyword(s):  
Electrical Conductivity ◽  
Spatial Distribution ◽  
Vadose Zone ◽  
Root Zone ◽  
Joint Inversion ◽  
Geophysical Methods ◽  
Exchange Capacity ◽  
Saturated Soil ◽  
Cotton Field ◽  
Inversion Algorithm

The ability to map the spatial distribution of average soil property values using geophysical methods at the field and district level has been well described. This includes the use of electromagnetic (EM) instruments which measure bulk soil electrical conductivity (σa). However, soil is a 3-dimensional medium. In order to better represent the spatial distribution of soil properties with depth, various methods of inverting EM instrument data have been attempted and include Tikhonov regularisation and layered earth models. In this paper we employ a 1-D inversion algorithm with 2-D smoothness constraints to predict the true electrical conductivity (σ) using σa data collected along a transect in an irrigated cotton field in the lower Namoi valley. The primary σa data include the root-zone measuring EM38 and the vadose-zone sensing EM31, in the vertical (v) and horizontal (h) dipole modes and at heights of 0.2 and 1.0 m, respectively. In addition, we collected σa with the EM38 at heights of 0.4 and 0.6 m. In order to compare and contrast the value of the various σa data we carry out individual inversions of EM38v and EM38h collected at heights of 0.2, 0.4, and 0.6 m, and EM31v and EM31h at 1.0 m. In addition, we conduct joint inversions of various combinations of EM38 σa data available at various heights (e.g. 0.2 and 0.4 m). Last we conduct joint inversions of the EM38v and EM38h σa data at 0.2, 0.4, and 0.6 m with the EM31v and EM31h at 1.0 m. We find that the values of σ achieved along the transect studied represent the duplex nature of the soil. In general, the EM38v and EM38h collected at a height of 0.2, 0.4, and 0.6 m assist in resolving solum and root-zone variability of the cation exchange capacity (cmol(+)/kg of soil solids) and the electrical conductivity of a saturated soil paste extract (ECe, dS/m), while the use of the EM31v and EM31h at 1.0 m assists in characterising the vadose zone and the likely location of a shallow perched-water table. In terms of identifying an optimal set of EM σa data for inversion we found that a joint inversion of the EM38 at a height of 0.6 m and EM31 signal data provided the best correlation with electrical conductivity of a saturated soil paste (ECp, dS/m) and ECe (respectively, 0.81 and 0.77) closely followed by a joint inversion of all the EM38 and EM31 σa data available (0.77 and 0.56).

Seismic imaging of the Naga thrust using multiscale waveform inversion

Geophysics ◽  
2009 ◽  
Vol 74 (6) ◽  
pp. WCC129-WCC140 ◽  
Author(s):  
Priyank Jaiswal ◽  
Colin A. Zelt ◽  
Rahul Dasgupta ◽  
Kulendra K. Nath
Keyword(s):  
Joint Inversion ◽  
Waveform Inversion ◽  
Physical Property ◽  
Velocity Model ◽  
Structural Features ◽  
Northeast India ◽  
P Wave ◽  
Fault System ◽  
Depth Migration ◽  
Structural Image

This case study images the structural features related to the Naga thrust fault (northeast India) using a combination of multiscale waveform inversion and prestack depth migration (PSDM). The waveform model and the PSDM image complement each other: the former provides a physical-property map (P-wave velocity model) and the latter provides a structural image. The velocity model encompassing the starting model for waveform inversion is constructed using joint inversion of first and reflected traveltimes. The [Formula: see text] data are inverted consecutively in [Formula: see text] bandwidths to yield the final waveform model, which in turn is used for PSDM. The PSDM image and the waveform model are consistent with the lithological interpretation of an inline exploratory well. When interpreted jointly, the PSDM image and the waveform model reveal the presence of a conjugate fault system in the Naga thrust and fold belt.

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