25 research outputs found
Three-dimensional inversion of transient-electromagnetic data: A comparative study
Inversion of transient-electromagnetic (TEM) data arising from galvanic types of sources is approached by two different methods. Both methods reconstruct the subsurface three-dimensional (3D) electrical conductivity properties directly in the time-domain. A principal difference is given by the scale of the inversion problems to be solved. The first approach represents a small-scale 3D inversion and is based upon well-known tools. It uses a stabilized unconstrained least-squares inversion algorithm in combination with an existing 3D forward modeling solver and is customized to invert for 3D earth models with a limited model complexity. The limitation to only as many model unknowns as typical for classical least-squares problems involves arbitrary and rather unconventional types of model parameters. The inversion scheme has mainly been developed for the purpose of refining a priori known 3D underground structures by means of an inversion. Therefore, a priori information is an important requirement to design a model such that its limited degrees of freedom describe the structures of interest. The inversion is successfully applied to data from a long-offset TEM survey at the active volcano Merapi in Central Java (Indonesia). Despite the restriction of a low model complexity, the scheme offers some versatility as it can be adapted easily to various kinds of model structures. The interpretation of the resistivity images obtained by the inversion have substantially advanced the structural knowledge about the volcano. The second part of this work presents a theoretically more elaborate scheme. It employs imaging techniques originally developed for seismic wavefields. Large-scale 3D problems arising from the inversion for finely parameterized and arbitrarily complicated earth models are addressed by the method. The algorithm uses a conjugate-gradient search for the minimum of an error functional, where the gradient information is obtained via migration or backpropagation of the differences between the data observations and predictions back into the model in reverse time. Treatment for electric field and time derivative of the magnetic field data is given for the specification of the cost functional gradients. The inversion algorithm is successfully applied to a synthetic TEM data set over a conductive anomaly embedded in a half-space. The example involves a total number of more than 376000 model unknowns. The realization of migration techniques for diffusive EM fields involves the backpropagation of a residual field. The residual field excitation originates from the actual receiver positions and is continued during the simulated time range of the measurements. An explicit finite-difference time-stepping scheme is developed in advance of the imaging scheme in order to accomplish both the forward simulation and backpropagation of 3D EM fields. The solution uses a staggered grid and a modified version of the DuFort-Frankel stabilization method and is capable of simulating non-causal fields due to galvanic types of sources. Its parallel implementation allows for reasonable computation times, which are inherently high for explicit time-stepping schemes
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A Parallel Finite-Difference Approach for Three-Dimensional Transient Electromagnetic Modeling With Galvanic Sources
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New advances in three dimensional transient electromagnetic inversion
Inversion of transient electromagnetic (TEM) data sets to image the subsurface three-dimensional (3-D) electrical conductivity and magnetic permeability properties can be done directly in the time domain. The technique, first introduced by Wang et al. (1994) for causal and diffusive electromagnetic fields and subsequently implemented by Zhdanov and Portniaguine (1997) in the framework of iterative migration, is based upon imaging methods originally developed for seismic wavefields (Claerbout, 1971; Tarantola, 1984). In this paper we advance the original derivations of Wang et al. (1994) and Zhdanov and Portniaguine (1997) to treat non-causal TEM fields, as well as correct a flaw in the theory for treatment of magnetic field data. Our 3D imaging scheme is based on a conjugate-gradient search for the minimum of an error functional involving EM measurements governed by Maxwell's equations without displacement currents. Treatment for magnetic field, voltage (time derivative of the magnetic field) and electric field data are given. The functional can be computed by propagating the data errors back into the model in reverse time along with a DC field, sourced by the integrated data errors over the measurement time range. By correlating these fields, including the time-integrated back-propagated fields, with the corresponding incident field and its initial value at each image point, efficient computational forms for the gradients are developed. The forms of the gradients allow for additional efficiencies when voltage and electric field data are inverted. In such instances the combined data errors can be back-propagated jointly, significantly reducing the computation time required to solve the inverse problem. The inversion algorithm is applied to the long offset transient electromagnetic measurement (LOTEM) configuration thereby demonstrating its capability in inverting non-causal field measurements of electric field and voltage, sourced by a grounded wire, over complex structures. Findings also show that migration, without iteration or preconditioning, is not an effective imaging strategy; reconstructions at the first inversion iteration bear little resemblance to simple or complex test models
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New advances in three-dimensional controlled-source electromagnetic inversion
New techniques for improving both the computational and imaging performance of the three dimensional (3D) electromagnetic inverse problem are presented. A non-linear conjugate gradient algorithm is the framework of the inversion scheme. Full wave equation modelling for controlled sources is utilized for data simulation along with an efficient gradient computation approach for the model update. Improving the modelling efficiency of the 3D finite difference method involves the separation of the potentially large modelling mesh, defining the set of model parameters, from the computational finite difference meshes used for field simulation. Grid spacings and thus overall grid sizes can be reduced and optimized according to source frequencies and source-receiver offsets of a given input data set. Further computational efficiency is obtained by combining different levels of parallelization. While the parallel scheme allows for an arbitrarily large number of parallel tasks, the relative amount of message passing is kept constant. Image enhancement is achieved by model parameter transformation functions, which enforce bounded conductivity parameters and thus prevent parameter overshoots. Further, a remedy for treating distorted data within the inversion process is presented. Data distortions simulated here include positioning errors and a highly conductive overburden, hiding the desired target signal. The methods are demonstrated using both synthetic and field data
3D induced-polarization data inversion for complex resistivity
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
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Improved geophysical monitoring of carbon sequestration through parameter linkage to reservoir modeling
Predictive reservoir modeling, even if present in the form of only basic hydrogeological model assumptions, is expected to accompany the majority of carbon capture and sequestration monitoring activities. It thus represents a source of prior information about the migration of injected fluids that can benefit geophysical survey planning and ensuing monitoring. Constraining the imaging of geophysical monitoring data with reservoir modeling is preferable over standalone geophysical imaging because of additional complementary hydrogeological information. However, fully coupled hydrogeophysical data inversion for flow-modeling parameters that control saturation predictions is an involved process. Within the context of three-dimensional electromagnetic (EM) inversion of data from borehole-to-surface layouts, we employ a "poor people's" alternative. The approach constrains geophysical inversion parameters through saturation predictions. The coupling is realized through spatially variable lower and upper parameter bounds that scale with gas saturation magnitudes, the latter provided by reservoir modeling. Enhancement of three-dimensional time-lapse plume EM imaging is demonstrated for simulated sequestration into a depleted gas reservoir