Littérature scientifique sur le sujet « Magnetotellurics, all-at-once, 3D inversion »

We evaluated a method for cooperatively inverting multiple electromagnetic (EM) data sets with bound constraints to produce a consistent 3D resistivity model with improved resolution. Field data from the Antonio gold deposit in Peru and synthetic data were used to demonstrate this technique. We first separately inverted field airborne time-domain EM (AEM), controlled-source audio-frequency magnetotellurics (CSAMT), and direct current resistivity measurements. Each individual inversion recovered a resistor related to gold-hosted silica alteration within a relatively conductive background. The outline of the resistor in each inversion was in reasonable agreement with the mapped extent of known near-surface silica alteration. Variations between resistor recoveries in each 3D inversion model motivated a subsequent cooperative method, in which AEM data were inverted sequentially with a combined CSAMT and DC data set. This cooperative approach was first applied to a synthetic inversion over an Antonio-like simulated resistivity model, and the inversion result was both qualitatively and quantitatively closer to the true synthetic model compared to individual inversions. Using the same cooperative method, field data were inverted to produce a model that defined the target resistor while agreeing with all data sets. To test the benefit of borehole constraints, synthetic boreholes were added to the inversion as upper and lower bounds at locations of existing boreholes. The ensuing cooperative constrained synthetic inversion model had the closest match to the true simulated resistivity distribution. Bound constraints from field boreholes were then calculated by a regression relationship among the total sulfur content, alteration type, and resistivity measurements from rock samples and incorporated into the inversion. The resulting cooperative constrained field inversion model clearly imaged the resistive silica zone, extended the area of interpreted alteration, and also highlighted conductive zones within the resistive region potentially linked to sulfide and gold mineralization.

Magnetotellurics (MT) is an important geophysical method for exploring geothermal systems, with the Earth resistivity obtained from the MT method proving to be useful for the hydrothermal imaging changes of the system. In this research, we applied the MT method to map the geothermal system of the Seulawah Agam volcano in northern Sumatra, a site intended for the construction of a geothermal power plant with an estimated energy of 230 Mwe. Herein, 3D MT measurements were carried out, covering the entire area of the volcano and the various intersecting local faults from the Seulimeum segment in the NW–SE direction. Based on Occam 2D inversion, a conductive anomaly (<10 ohm·m) near the surface was identified in response to specific manifestation areas, including the Heutsz crater on the northern side and the Cempaga crater on the southern side. A further conductive anomaly was also found at a depth of 1 km, which was presumably due to a clay cap layer covering the fluid in the reservoir layer below the surface, where the manifestation areas are formed at various locations (where faults and fractures are found) owing to the fluid in the reservoir rising to the surface. The MT modeling also revealed that the reservoir layer in Seulawah Agam lies at a depth of 2 km with a higher resistivity of 40–150 ohm·m, which is the main target of geothermal energy exploration. At the same time, the heat source zone where magma is located was estimated to lie in two locations, namely, on the northern side centering on the Heutsz crater area and the southern side in the Cempaga crater area. A clear 3D structure obtained via Occam inversion was also used to visualize the hydrothermal flow in the Seulawah Agam volcano that originates from two heat source zones, where one structure that was consistent across all models is the conductive zone that reaches a depth of 5 km in the south in response to the regional faulting of the Seulimeum segment. Based on the MT research, we concluded that the volcano has the geothermal potential to be tapped into power plant energy in the future.

The dominant salt body at Gemini Prospect, Gulf of Mexico, has been analyzed by seismic methods, revealing a complex 3D salt volume at depths 1 to 5 km beneath the mud line. Because of the high contrast in electrical conductivity between the salt and surrounding sediments, Gemini is an attractive target for electromagnetic interrogation. Using a broadband magnetotelluric (MT) sensor package developed at the Scripps Institution of Oceanography, data in the period band of 1 to 3000 s were collected at 42 sites in a series of profiles over Gemini, one of which was directly over a linear ridgelike salt feature striking roughly northwest–southeast and another orthogonal to it. These two profiles reveal that the strongest MT response arises when the electric field is oriented northeast–southwest. We test the suitability of 2D inversion of these data for recovering the true salt structure by examining inversions of both actual data and synthetic 3D MT responses derived from the seismically inferred salt volume. Occam inversions of the northeast–southwest component result in resistivity images that generally agree with the seismic data, whereas inversions of the complementary component yield significantly poorer fidelity. Disagreement is greatest (1–2 km) along the salt sides and base. Depth errors for top of salt are less than 500 m. Although thin, deep salt (<1 km thick at 5 km depth) is not well resolved, the inversions reveal a resistive basement and a shallow subseabed environment rich in electrical heterogeneity that is weakly, if at all, suggested by the seismic data. A notable exception is a correlation between a previously uninterpreted seismic reflector and the base of a shallow resistivity anomaly whose presence is consistent with gas accumulation near the hydrate stability zone.

Geothermal energy accounts for 43% of the electricity expenditure of São Miguel Island, Azores Archipelago. All production comes from the Ribeira Grande (RG) high-enthalpy geothermal field. To meet the growing energy demand in the island, it is necessary to extend the exploration efforts to new areas. We evaluated the results of a broadband magnetotelluric reconnaissance survey conducted at Sete Cidades Volcano, placed only 30 km westward of the RG field. The resistivity structure of the Sete Cidades geothermal system was obtained through a simultaneous 3D inversion of the full impedance tensor and tipper. The bathymetry and the topography of the island were treated as fixed features in the model. The geothermal reservoir at Sete Cidades is outlined as a northwest–southeast elongated resistive anomaly, geologically controlled by the Terceira Rift fracture zone. We have also identified high-conductivity zones between 1000 and 4000 m below mean sea level, probably associated with clay cap rocks overlying the geothermal reservoir.

Frequency-domain methods, which are typically applied to 3D magnetotelluric (MT) modeling, require solving a system of linear equations for every frequency of interest. This is memory and computationally intensive. We developed a finite-difference time-domain algorithm to perform 3D MT modeling in a marine environment in which Maxwell’s equations are solved in a so-called fictitious-wave domain. Boundary conditions are efficiently treated via convolutional perfectly matched layers, for which we evaluated optimized parameter values obtained by testing over a large number of models. In comparison to the typically applied frequency-domain methods, two advantages of the finite-difference time-domain method are (1) that it is an explicit, low-memory method that entirely avoids the solution of systems of linear equations and (2) that it allows the computation of the electromagnetic field unknowns at all frequencies of interest in a single simulation. We derive a design criterion for vertical node spacing in a nonuniform grid using dispersion analysis as a starting point. Modeling results obtained using our finite-difference time-domain algorithm are compared with results obtained using an integral equation method. The agreement was found to be very good. We also discuss a real data inversion example in which MT modeling was done with our algorithm.

We present a general formulation for inverting frequency‐ or time‐domain electromagnetic data using an all‐at‐once approach. In this methodology, the forward modeling equations are incorporated as constraints and, thus, we need to solve a constrained optimization problem where the parameters are the electromagnetic fields, the conductivity model, and a set of Lagrange multipliers. This leads to a much larger problem than the traditional unconstrained formulation where only the conductivities are sought. Nevertheless, experience shows that the constrained problem can be solved faster than the unconstrained one. The primary reasons are that the forward problem does not have to be solved exactly until the very end of the optimization process, and that permitting the fields to be away from their constrained values in the initial stages introduces flexibility so that a stationary point of the objective function is found more quickly. In this paper, we outline the all‐at‐once approach and apply it to electromagnetic problems in both frequency and time domains. This is facilitated by a unified representation for forward modeling for these two types of data. The optimization problem is solved by finding a stationary point of the Lagrangian. Numerically, this leads to a nonlinear system that is solved iteratively using a Gauss‐Newton strategy. At each iteration, a large, indefinite matrix is inverted, and we discuss how this can be accomplished. As a test, we invert frequency‐domain synthetic data from a grounded electrode system that emulates a field CSAMT survey. For the time domain, we invert borehole data obtained from a current loop on thesurface.

Electromagnetic (EM) exploration for base metals using the natural‐source audio‐magnetotelluric (AMT) technique has increased significantly during the last five years due to enhancements in all aspects of AMT and to the demand for imaging deeper than conventional controlled‐source EM methods. However, regional currents induced by natural sources can be problematic in certain situations, and the appropriate interpretational dimensionality must be known. Herein we demonstrate that a two‐dimensional (2D) interpretation is valid for a defined frequency band, but that the effects of large‐scale three‐dimensional (3D) structures must be considered at lower frequencies. Using an AMT dataset from an area located north of Voisey's Bay, Labrador, Canada, we analyse the responses to determine the appropriate dimensionality and to test them for internal consistency. Maps of the distortion‐corrected data identify the lateral extent of connected conducting mineralization intersected by a drilling program. One‐dimensional (1D) inversions of the corrected data from those sites on top of the mineralized zone show the resolution properties of the data. We constructed a pseudo‐3D model from 2D inversions of the data in the frequency band 1000–10~Hz from all profiles, and this model images the mineralized body sufficiently for exploration purposes. We suggest that the anomalous low‐frequency responses observed at sites close to the mineralized zone are possibly due to charges impinged on the mineralized body's boundaries by currents induced in the Atlantic Ocean some 50 km away. Although 3D numerical modeling studies exhibit some of the effects observed, we are unable to reproduce numerically the observed behavior.

In Sanfu, Qaidam basin, China, traditional geophysical methods have failed to find subtle hydrocarbon reservoirs. In an attempt to predict and delineate gas reservoirs, we used a type of magnetotelluric (MT) profiling called 3D continuous electromagnetic profiling (CEMP). Electric logs indicate that gas-bearing formations have high resistivity relative to nongas-bearing formations. Obvious resistivity anomalies derived from MT sounding curves are interpreted to come from gas-bearing formations; we observed no such anomalous resistivity away from gas-bearing reservoirs. For CEMP, five electric components were recorded at each station; the inline electric components of all stations were measured using dipoles placed end to end. Becausethe survey area was quite wide, we divided it into three rectangular blocks for data processing and inversion. After noise removal and static corrections, the data from each block were inverted with a 3D nonlinear conjugate-gradient inversion method to obtain the spatial distribution of resistivity. Using this resistivity, we created a 2D model, which we inverted to determine the induced polarization (IP) parameters. We found that a high-resistivity anomaly and high IP anomaly are two key indicators when predicting and delineating the location of gas-bearing reservoirs. In our case study, a known gas-bearing formation had a high-resistivity anomaly and a high IP anomaly. We identified two similar anomalous regions outside the known gas-bearing formations. As a result, two new prospects were determined as targets worth drilling.

Studying how injected [Formula: see text] affects the seismic response of reservoir rocks is important because it can improve subsurface characterization where [Formula: see text] injection is taking place. This study uses multicomponent data from a 3D vertical seismic profile (VSP) and well logs to model and invert probabilistically for the porosity and [Formula: see text] saturation at the Cranfield reservoir. The well logs were used to calibrate a rock-physics model. Once the accuracy of the model was verified, P-impedance and [Formula: see text]/[Formula: see text] from inverted multicomponent VSP data were used to estimate the porosity and fluid saturation. This inversion generated probabilistic estimates of porosity and fluid saturation for the area of the reservoir sampled by PP- and PS-waves. Inversion results using the measured well log data for calibration indicated that the model was able to estimate porosity with a relatively high degree of accuracy, with the root-mean-square (rms) error being less than 3% for all calibration tests. Pore-fluid composition was estimated, however, with reduced accuracy, with rms errors ranging from 6% to 22% depending on the composition of the calibration fluid. Results from integrating the multicomponent VSP data with the rock-physics model indicated that estimated reservoir porosities are quite close to measured values at an observation well. Pore-fluid composition estimates indicated that this method can differentiate between areas containing [Formula: see text] and those that do not.

Deep seismic reflection surveys in north Queensland that were collected in 2006 and 2007 discovered a previously unknown sedimentary basin, now named the Millungera Basin, which is completely covered by a thin succession of sediments of the Jurassic–Cretaceous, Eromanga-Carpentaria Basin. Interpretation of regional aeromagnetic data suggests that the basin could have areal dimensions of up to 280 km by 95 km. Apart from regional geophysical data, virtually no confirmed geological information exists on the basin. To complement the seismic data, new magnetotelluric data have been acquired on several lines across the basin. An angular unconformity between the Eromanga and Millungera basins indicates that the upper part of the Millungera Basin was eroded prior to deposition of the Eromanga-Carpentaria Basin. Both the western and eastern margins of the Millungera Basin are truncated by thrust faults, with well-developed hangingwall anticlines occurring above the thrusts at the eastern margin. The basin thickens slightly to the east, to a maximum preserved subsurface depth of ˜3,370 m. Using sequence stratigraphic principles, three discrete sequences have been mapped. The geometry of the stratigraphic sequences, the post-depositional thrust margins, and the erosional unconformity at the top of the succession all indicate that the original succession across much of the basin was thicker–by up to at least 1,500 m–than preserved today. The age of the Millungera Basin is unknown, but petroleum systems modelling has been carried out using two scenarios, that is, that the sediment fill is equivalent in age to (1) the Neoproterozoic-Devonian Georgina Basin, or (2) the Permian–Triassic Lovelle Depression of the Galilee Basin. Using the Georgina Basin analogue, potential Cambrian source rocks are likely to be mature over most of the Millungera Basin, with significant generation and expulsion of hydrocarbons occurring in two phases, in response to Ordovician and Cretaceous sediment loading. For the Galilee Basin analogue, potential Permian source rocks are likely to be oil mature in the central Millungera Basin, but immature on the basin margins. Significant oil generation and expulsion probably occurred during the Triassic, in response to late Permian to Early Triassic sediment loading. Based on the seismic and potential field data, several granites are interpreted to occur immediately below the Millungera Basin, raising the possibility of hot rock geothermal plays. Depending on its composition, the Millungera Basin could provide a thermal blanket to trap any heat which is generated. 3D inversion of potential field data suggests that the inferred granites range from being magnetic to nonmagnetic, and felsic (less dense) to more mafic. They may be part of the Williams Supersuite, which is enriched in uranium, thorium and potassium, and exposed just to the west, in the Mount Isa Province. 3D gravity modelling suggests that the inferred granites have a possible maximum thickness of up to 5.5 km. Therefore, if granites with the composition of the Williams Supersuite occur beneath the Millungera Basin, in the volumes indicated by gravity inversions, then, based on the forward temperature modelling, there is a good probability that the basin is prospective for geothermal energy.

A three-dimensional inversion was implemented for magnetotellurics, which is a passive electromagnetic method in geophysics. It exploits natural electromagnetic fields of the Earth, which function as sources. Their interaction with the conductive parts of the subsurface are registered when components of the electric and the magnetic field are measured and evaluated. The all-at-once approach is an inversion scheme that is relatively new to geophysics. In this approach, the objective function – the basis of each inversion – is called the Lagrangian. It consists of three parts: (i) the data residual norm, (ii) the regularisation part, and (iii) the forward problem. The latter is the significant difference to conventional inversion approaches that are built up of a forward calculation part and an inversion part. In the case of all-at-once, the forward problem is incorporated in the objective function and is therefore already taken into account in each inversion iteration. Thus, an explicit forward calculation is obsolete. As an objective function, the Lagrangian shall reach a minimum and therefore its first and second derivatives are evaluated. Hence, the gradient of the Lagrangian and its Hessian are constituent parts of the KKT system – the Newton-type system that is set up in the all-at-once inversion. Conventional inversion approaches avoid the Hessian because it is a large, dense, not positive definite matrix that is challenging to handle. However, it provides additional information to the inversion, which raises hope for a high quality inversion result. As a first step, the inversion was programmed for the more straightforward one-dimensional magnetotelluric case. This was particularly suitable to become familiar with sQMR – a Krylov subspace method which is essential for the three-dimensional case to be able to work with the Hessian and the resulting KKT system. After the implementation and validation of the one-dimensional forward operator, the Lagrangian and its derivatives were set up to complete the inversion, which successfully solved the KKT system. Accordingly, the three-dimensional forward operator also needed to be implemented and validated, which was done using published data from the 3D-2 COMMEMI model. To realise the inversion, the Lagrangian was assembled and its first and second derivatives were validated with a test that exploits the Taylor expansion. Then, the inversion was initially programmed for the Gauss-Newton approximation where second order information is neglected. Since the system matrix of the Gauss-Newton approximation is positive definite, the solution of this system of equations could be carried out by the conventional solver pcg. Based on that, the complete KKT system (Newton\\\'s method) was set up and preconditioned sQMR solved this system of equations.