BAYESIAN MAGNETOTELLURIC INVERSION USING METHYLENE BLUE STRUCTURAL PRIORS FOR IMAGING SHALLOW CONDUCTORS IN GEOTHERMAL FIELDS

Geophysics ◽  
2021 ◽  
pp. 1-66
Author(s):  
Alberto Ardid ◽  
David Dempsey ◽  
Edward Bertrand ◽  
Fabian Sepulveda ◽  
Flora Solon ◽  
...  
Keyword(s):  
Methylene Blue ◽  
Clay Content ◽  
3D Models ◽  
Bayesian Inversion ◽  
Inversion Method ◽  
Geothermal Fields ◽  
Geological Information ◽  
Resistivity Model ◽  
Irreducible Uncertainty ◽  
Clay Cap

In geothermal exploration, magnetotelluric (MT) data and inversion models are commonly used to image shallow conductors typically associated with the presence of an electrically conductive clay cap that overlies the main reservoir. However, these inversion models suffer from non-uniqueness and uncertainty, and the inclusion of useful geological information is still limited. We develop a Bayesian inversion method that integrates the electrical resistivity distribution from MT surveys with borehole methylene blue data (MeB), an indicator of conductive clay content. MeB data is used to inform structural priors for the MT Bayesian inversion that focus on inferring with uncertainty the shallow conductor boundary in geothermal fields. By incorporating borehole information, our inversion reduces non-uniqueness and then explicitly represents the irreducible uncertainty as estimated depth intervals for the conductor boundary. We use Markov chain Monte Carlo (McMC) and a one-dimensional three-layer resistivity model to accelerate the Bayesian inversion of the MT signal beneath each station. Then, inferred conductor boundary distributions are interpolated to construct pseudo-2D/3D models of the uncertain conductor geometry. We compared our approach against a deterministic MT inversion software on synthetic and field examples and showed good performance in estimating the depth to the bottom of the conductor, a valuable target in geothermal reservoir exploration.

scholarly journals Estimates of European emissions of methyl chloroform using a Bayesian inversion method

2014 ◽  
Vol 14 (18) ◽  
pp. 9755-9770 ◽  
Author(s):  
M. Maione ◽  
F. Graziosi ◽  
J. Arduini ◽  
F. Furlani ◽  
U. Giostra ◽  
...  
Keyword(s):  
Point Source ◽  
High Frequency ◽  
Stratospheric Ozone ◽  
Montreal Protocol ◽  
Source Analysis ◽  
Bayesian Inversion ◽  
Inversion Method ◽  
Data Set ◽  
Methyl Chloroform

Abstract. Methyl chloroform (MCF) is a man-made chlorinated solvent contributing to the destruction of stratospheric ozone and is controlled under the "Montreal Protocol on Substances that Deplete the Ozone Layer" and its amendments, which called for its phase-out in 1996 in developed countries and 2015 in developing countries. Long-term, high-frequency observations of MCF carried out at three European sites show a constant decline in the background mixing ratios of MCF. However, we observe persistent non-negligible mixing ratio enhancements of MCF in pollution episodes, suggesting unexpectedly high ongoing emissions in Europe. In order to identify the source regions and to give an estimate of the magnitude of such emissions, we have used a Bayesian inversion method and a point source analysis, based on high-frequency long-term observations at the three European sites. The inversion identified southeastern France (SEF) as a region with enhanced MCF emissions. This estimate was confirmed by the point source analysis. We performed this analysis using an 11-year data set, from January 2002 to December 2012. Overall, emissions estimated for the European study domain decreased nearly exponentially from 1.1 Gg yr−1 in 2002 to 0.32 Gg yr−1 in 2012, of which the estimated emissions from the SEF region accounted for 0.49 Gg yr−1 in 2002 and 0.20 Gg yr−1 in 2012. The European estimates are a significant fraction of the total semi-hemisphere (30–90° N) emissions, contributing a minimum of 9.8% in 2004 and a maximum of 33.7% in 2011, of which on average 50% are from the SEF region. On the global scale, the SEF region is thus responsible for a minimum of 2.6% (in 2003) and a maximum of 10.3% (in 2009) of the global MCF emissions.

2-D and 3-D resistivity image reconstruction using crosshole data

Geophysics ◽  
1992 ◽  
Vol 57 (10) ◽  
pp. 1270-1281 ◽  
Author(s):  
Hiromasa Shima
Keyword(s):  
Field Test ◽  
Numerical Models ◽  
Electrical Potential ◽  
Nonlinear Least Squares ◽  
Three Dimensions ◽  
Inversion Method ◽  
Good Resolution ◽  
Inversion Algorithm ◽  
Linear Inversion ◽  
Resistivity Model

Theoretical changes in the distribution of electrical potential near subsurface resistivity anomalies have been studied using two resistivity models. The results suggest that the greatest response from such anomalies can be observed with buried electrodes, and that the resistivity model of a volume between boreholes can be accurately reconstructed by using crosshole data. The distributive properties of crosshole electrical potential data obtained by the pole‐pole array method have also been examined using the calculated partial derivative of the observed apparent resistivity with respect to a small cell within a given volume. The results show that for optimum two‐dimensional (2-D) and three‐dimensional (3-D) target imaging, in‐line data and crossline data should be combined, and an area outside the zone of exploration should be included in the analysis. In this paper, the 2-D and 3-D resistivity images presented are reconstructed from crosshole data by the combination of two inversion algorithms. The first algorithm uses the alpha center method for forward modeling and reconstructs a resistivity model by a nonlinear least‐squares inversion. Alpha centers express a continuously varying resistivity model, and the distribution of the electrical potential from the model can be calculated quickly. An initial general model is determined by the resistivity backprojection technique (RBPT) prior to the first inversion step. The second process uses finite elements and a linear inversion algorithm to improve the resolution of the resistivity model created by the first step. Simple 2-D and 3-D numerical models are discussed to illustrate the inversion method used in processing. Data from several field studies are also presented to demonstrate the capabilities of using crosshole resistivity exploration techniques. The numerical experiments show that by using the combined reconstruction algorithm, thin conductive layers can be imaged with good resolution for 2-D and 3-D cases. The integration of finite‐element computations is shown to improve the image obtained by the alpha center inversion process for 3-D applications. The first field test uses horizontal galleries to evaluate complex 2-D features of a zinc mine. The second field test illustrates the use of three boreholes at a dam site to investigate base rock features and define the distribution of an altered zone in three dimensions.

scholarly journals Evaluation of a Straight-Ray Forward Model for Bayesian Inversion of Crosshole Ground Penetrating Radar Data

Electronics ◽  
2019 ◽  
Vol 8 (6) ◽  
pp. 630 ◽  
Author(s):  
Hui Qin ◽  
Xiongyao Xie ◽  
Yu Tang
Keyword(s):  
Ground Penetrating Radar ◽  
Computational Cost ◽  
Measurement Data ◽  
Forward Model ◽  
Bayesian Inversion ◽  
Inversion Method ◽  
Model Parameters ◽  
Model Structure ◽  
Modeling Error ◽  
Ground Penetrating

Bayesian inversion of crosshole ground penetrating radar (GPR) data is capable of characterizing the subsurface dielectric properties and qualifying the associated uncertainties. Markov chain Monte Carlo (MCMC) simulations within the Bayesian inversion usually require thousands to millions of forward model evaluations for the parameters to hit their posterior distributions. Therefore, the CPU cost of the forward model is a key issue that influences the efficiency of the Bayesian inversion method. In this paper we implement a widely used straight-ray forward model within our Bayesian inversion framework. Based on a synthetic unit square relative permittivity model, we simulate the crosshole GPR first-arrival traveltime data using the finite-difference time-domain (FDTD) and straight-ray solver, respectively, and find that the straight-ray simulator runs 450 times faster than its FDTD counterpart, yet suffers from a modeling error that is more than 7 times larger. We also perform a series of numerical experiments to evaluate the performance of the straight-ray model within the Bayesian inversion framework. With modeling error disregarded, the inverted posterior models fit the measurement data nicely, yet converge to the wrong set of parameters at the expense of unreasonably large number of iterations. When the modeling error is accounted for, with a quarter of the computational burden, the main features of the true model can be identified from the posterior realizations although there still exist some unwanted artifacts. Finally, a smooth constraint on the model structure improves the inversion results considerably, to the extent that it enhances the inversion accuracy approximating to those of the FDTD model, and further reduces the CPU demand. Our results demonstrate that the use of the straight-ray forward model in the Bayesian inversion saves computational cost tremendously, and the modeling error correction together with the model structure constraint are the necessary amendments that ensure that the model parameters converge correctly.

Transient electromagnetic search engine for real-time imaging

Geophysics ◽  
2017 ◽  
Vol 82 (5) ◽  
pp. E277-E285 ◽  
Author(s):  
Jide Nosakare Ogunbo ◽  
Jie Zhang ◽  
Xiong Zhang
Keyword(s):  
Real Time ◽  
Search Engine ◽  
Solution Space ◽  
Inversion Method ◽  
Model Parameters ◽  
Transient Electromagnetic ◽  
Model Solutions ◽  
Resistivity Model ◽  
2D Resistivity ◽  
Engine Method

To image the resistivity distribution of the subsurface, transient electromagnetic (TEM) surveying has been established as an effective geophysical method. Conventionally, an inversion method is applied to resolve the model parameters from the available measurements. However, significant time and effort are involved in preparing and executing an inversion and this prohibits its use as a real-time decision-making tool to optimize surveying in the field. We have developed a search engine method to find approximate 1D resistivity model solutions for circular central-loop configuration TEM data in real time. The search engine method is a concept used for query searches from large databases on the Internet. By extension, approximate solutions to any input TEM data can be found rapidly by searching a preestablished database. This database includes a large number of forward simulation results that represent the possible model solutions. The database size is optimized by the survey depth of investigation and the sensitivity analysis of the model layers. The fast-search speed is achieved by using the multiple randomized [Formula: see text]-dimensional tree method. In addition to its high speed in finding solutions, the search engine method provides a solution space that quantifies the resolutions and uncertainties of the results. We apply the search engine method to find 1D model solutions at different data points and then interpolate them to a pseudo-2D resistivity model. We tested the method with synthetic and real data.

Bayesian inversion of CSEM and magnetotelluric data

Geophysics ◽  
2012 ◽  
Vol 77 (1) ◽  
pp. E33-E42 ◽  
Author(s):  
Arild Buland ◽  
Odd Kolbjørnsen
Keyword(s):  
Prior Knowledge ◽  
Inversion Method ◽  
Earth Model ◽  
Magnetotelluric Data ◽  
Inversion Result ◽  
Electromagnetic Data ◽  
Magnetic Components ◽  
Resistivity Model ◽  
Frequency Components ◽  
Inversion Procedure

We have developed a Bayesian methodology for inversion of controlled source electromagnetic (CSEM) data and magnetotelluric (MT) data. The inversion method provided optimal solutions and also the associated uncertainty for any sets of electric and magnetic components and frequencies from CSEM and MT data. The method is based on a 1D forward modeling method for the electromagnetic (EM) response for a plane-layered anisotropic earth model. The inversion method was also designed to invert common midpoint (CMP)-sorted data along a 2D earth profile assuming locally horizontal models in each CMP position. The inversion procedure simulates from the posterior distribution using a Markov chain Monte Carlo (McMC) approach based on the Metropolis-Hastings algorithm. The method that we use integrates available geologic prior knowledge with the information in the electromagnetic data such that the prior model stabilizes and constrains the inversion according to the described knowledge. The synthetic examples demonstrated that inclusion of more data generally improves the inversion results. Compared to inversion of the inline electric component only, inclusion of broadside and magnetic components and an extended set of frequency components moderately decreased the uncertainty of the inversion. The results were strongly dependent on the prior knowledge imposed by the prior distribution. The prior knowledge about the background resistivity model surrounding the target was highly important for a successful and reliable inversion result.

scholarly journals European emissions of HCFC-22 based on eleven years of high frequency atmospheric measurements and a Bayesian inversion method

2015 ◽  
Vol 112 ◽  
pp. 196-207 ◽  
Author(s):  
F. Graziosi ◽  
J. Arduini ◽  
F. Furlani ◽  
U. Giostra ◽  
L.J.M. Kuijpers ◽  
...  
Keyword(s):  
High Frequency ◽  
Bayesian Inversion ◽  
Inversion Method ◽  
Atmospheric Measurements

First Results and Prospects of a New Approach to the Study of Active Geologic Processes by Space and Ground Instrumental Measurements (by the Example of Kamchatka and the Central Asian Orogenic Belt)

2021 ◽  
Vol 62 (1) ◽  
pp. 44-67
Author(s):  
N.L. Dobretsov ◽  
M.M. Buslov ◽  
A.N. Vasilevskiy ◽  
S.M. Zhmodik ◽  
A.V. Kotlyarov
Keyword(s):  
Satellite Images ◽  
Gravity Anomalies ◽  
3D Models ◽  
Tien Shan ◽  
Magma Chambers ◽  
Tectonic Structures ◽  
Central Asian ◽  
Geological Information ◽  
First Results ◽  
Geologic Processes

Abstract ––The use of satellite-geological information permits generalization of studies of various active geologic processes in a new way. As reference examples, we consider geologic regions extensively covered by research with our contribution. The joint use of satellite images, maps of gravity anomalies, and seismic-tomography data for Kamchatka made it possible to construct 3D models of surficial and deep-seated (depths from 10–50 to 650 km) volcanic structures. For young volcanosedimentary structures of Kamchatka, it is possible to trace the interaction of various processes, from crystallization of magmas in magma chambers to ore and oil formation in calderas. Ancient tectonic structures and superposed Cenozoic deformations in the Tien Shan, Altai, and Baikal regions are clearly displayed in satellite images and on maps of gravity anomalies. The long-range impact of the Indo-Eurasian collision on the Tien Shan, Altai, and Baikal regions was expressed as shearing, which resulted in the most contrasting structures in the zones of junction of regional faults and along the framing of cratonal structures. The active structures of Gorny Altai contain numerous travertines, whose abundance is correlated with seismic activity. The mass formation of methane and gas hydrates in Lake Baikal might be related to mantle plume fluids.

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