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Potential field data form an important frontline exploration tool thanks to the modern-day airborne platforms capable of collecting large amounts of data over large areas. Interpretation of these data using a 3D inversion is still a challenging problem due to the large amount of data and the need to discretize the inversion volume into a huge number of elements.

We have developed a multi-level parallel magnetotelluric (MT) integral equation based inversion program which uses variable sensitivity domain. The limited sensitivity of the data, which decreases with increasing frequency, is exploited by a receiver sensitivity domain, which also varies with frequency. We assess the effect of inverting principal, full impedance tensor, and full tensor with magnetovariational data (tipper). We first apply this method to several models and then invert the EarthScope MT data. We recover well the prominent features in the area including resistive structure associated with the Juan de Fuca slab subducting beneath the northwestern United States, the conductive zone of partially melted material above the subducting slab at the Cascade volcanic arc, conductive features in the Great Basin resulting from prior subduction and in the area of Yellowstone associated with the hot spot, and resistive areas to the east corresponding to the older and more stable cratons. Our results agree well with other publications which furthers the confidence in the inversion of the EarthScope MT project.

The ability to monitor reservoir behavior over the course of production is necessary for optimization of production performance and the development of production strategies. This goal can be achieved by geophysical monitoring of the fluid propagation within the reservoir. Electromagnetic methods represent an important technique for geophysical monitoring of reservoirs, because they can distinguish between hydrocarbons and saline water based on their differing resistivities. The induced polarization (IP) method can be used to detect additional electrical property contrasts between the fluids and thus can increase the method’s sensitivity to the differing fluids. This chapter considers an application of nanoparticles for reservoir monitoring in order to enhance the electrical conductivity contrast and the IP responses associated with the oil–water interface within the reservoir.

We consider an application of the ideas of electromagnetic (EM) holography/migration to the interpretation of a typical marine controlled-source EM (MCSEM) survey, which consists of a set of sea-bottom receivers and a moving electrical bipole transmitter. The three-dimensional interpretation of MCSEM data is a very challenging problem because of the enormous amount of computations required in the case of the multitransmitter and multireceiver data acquisition systems used in these surveys. At the same time, we show that the MCSEM surveys with their dense system of transmitters and receivers are extremely well suited for application of the holography/migration method. The combined EM signal in the receivers forms a broadband EM “hologram” of the sea-bottom geological target. As in optical and radiowave holography, we can reconstruct the volume image of the geological target by “illuminating” this EM hologram with the reference signal. The principles of holography/migration imaging formulated in this chapter are tested on typical models of a sea-bottom petroleum reservoir. We also apply this new technique to the interpretation of an MCSEM survey conducted in the Troll West gas province, offshore from Norway.

The 3D inversion of potential field data constitutes an increasingly important method of interpretation of geophysical data. A generalized inversion method first discretizes the 3D earth models into cells of constant density, susceptibility, or magnetization vector. In the case of continental-scale geophysical data collected by a combination of land, airborne and satellite measurements, the survey area may cover thousands and even millions of square kilometres, which makes the size of the inversion domain and the number of inverse model parameters extremely large. It is well known that for potential field data the computational complexity increases linearly with the size of the problem. Even a small-sized 3D inversion of huge amounts of data to 3D earth models with hundreds of thousands of cells can exceed the memory available on a desktop computer. In the case of several millions of discretization cells, the memory requirements may exceed the capacity even of the PC clusters. The second obstacle is the amount of CPU time required to apply a huge, dense matrix of the forward modelling operator to the data and model vectors, even using parallel computing.

This paper presents a fast and efficient large-scale anisotropic inversion technique for towed streamer electromagnetic (EM) data, which incorporates seismic constraints. The inversion algorithm is based on the 3D contraction integral equation method and utilizes a reweighted regularized conjugate gradient technique to minimize the objective functional (Zhdanov et al. 2014a, b). We have also introduced the concept of a moving sensitivity domain for seismically guided EM inversion, originally developed for airborne EM surveys (Zhdanov and Cox, 2013), which makes it possible to invert the entire large-scale towed streamer EM survey data while keeping the accuracy of the computation of the EM fields. The developed algorithm and software can take into account the constraints based on seismic and well-log data, and provide the inversion guided by these constraints. To demonstrate the practical effectiveness of this approach for large-scale inversion of marine EM data, as well as integration with seismic data, we apply the method to the inversion of about 2000 line-km of towed streamer EM data. The data form part of a larger survey in the Norwegian Barents Sea (McKay et al., 2016). We show that the technique produces a single resistivity model that is consistent with both the measured EM data and the main seismically defined structures. Thus, the resistivity model is ready to be interpreted and used in further quantitative interpretation studies.

Summary Airborne electromagnetic (AEM) methods are widely used for mineral exploration. However, until recently AEM data acquired for geophysical exploration have been interpreted using 1D layered-earth models calculated for each transmitter-receiver pairs. These 1D resistivity models are often stitched or interpolated in order to produce a pseudo- 3D model over the survey area. However, the geological structures of particular interest, such as mineral deposits, are poorly resolved with these various 1D methods. Exploiting the fact that an AEM system’s sensitivity domain is significantly smaller than the area of an AEM survey, we have developed a practical 3D inversion methodology based on the moving sensitivity domain approach. This approach has resulted in a paradigm change for AEM data interpretation by making it possible to invert entire AEM surveys with no approximations into high-resolution 3D geoelectrical earth models.

Conventional 3D magnetic inversion methods are based on the assumption that there is no remanent magnetization, and the inversion is run for magnetic susceptibility only. However, this approach ignores the situation where the direction of magnetization of the rocks is different from the direction of the induced magnetic field. This situation happens in a case of remanent magnetization, typical for geological structures such as kimberlites, dykes, iron-rich ultramafic pegmatitoids (IRUP), platinum group element (PGE) reefs, and banded iron formations (BIF). This paper presents a novel method of inversion of magnetic data for the scalar components of the magnetization vector. The method is based on a new magnetic forward modeling algorithm, which uses triangular prisms of arbitrary shape in order to achieve a more accurate approximation of the topography and complex geological structures. The inversion also includes Gramian constraints in order to obtain a robust solution of otherwise ill-posed magnetic inverse problems. The method was successfully tested on a number of synthetic models of the magnetized bodies. The results of inversion of airborne TMI data demonstrate how inversion for the magnetization vector with Gramian constraints can improve the subsurface imaging of kimberlites.

Airborne gravity or gravity gradiometry surveys typically contain hundreds to thousands of line kilometers of data with measurement locations every few meters. The goal of 3D inversion of airborne gravity and/or gravity gradiometry (AGG) data is to recover the density distribution in a 3D earth model at an appropriate level of resolution and detail for subsequent use in geological interpretation. This is a challenging problem for a number of reasons. First, as mentioned, airborne surveys are characterized by very large data volumes. Second, the 3D modeling of large-scale surveys is a computationally challenging problem. In this paper, we discuss how these difficulties can be overcome by using a number of innovations, more specifically, the moving sensitivity domain approach, focusing regularization, and massively parallel computer implementation. We illustrate our method with an example of 3D inversion of AGG data collected by Bell Geospace over the Bathurst Mining Camp in New Brunswick, Canada.

The thermal discrete dipole approximation (T-DDA) is a numerical approach for modeling near-field radiative heat transfer in complex three-dimensional geometries. In this work, the convergence of the T-DDA is investigated by comparison against the exact results for two spheres separated by a vacuum gap. The error associated with the T-DDA is reported for various sphere sizes, refractive indices and vacuum gap thicknesses. The results reveal that for a fixed number of subvolumes, the accuracy of the T-DDA degrades as the refractive index and the sphere diameter to gap ratio increase. A converging trend is observed as the number of subvolumes increases. The large computational requirements associated with increasing the number of subvolumes, and the shape error induced by large sphere diameter to gap ratios, are mitigated by using a nonuniform discretization scheme. Nonuniform discretization is shown to significantly accelerate the convergence of the T-DDA, and is thus recommended for near-field thermal radiation simulations. Errors less than 5% are obtained in 74% of the cases studied by using up to 82712 subvolumes. Additionally, the convergence analysis demonstrates that the T-DDA is very accurate when dealing with surface polariton resonant modes dominating radiative heat transfer in the near field., 46 pages, 12 figures, 3 tables

This paper presents a parallelized version of the edge-based finite element method with a novel post-processing approach for numerical modeling of an electromagnetic field in complex media. The method uses an unstructured tetrahedral mesh which can reduce the number of degrees of freedom significantly. The linear system of finite element equations is solved using parallel direct solvers which are robust for ill-conditioned systems and efficient for multiple source electromagnetic (EM) modeling. We also introduce a novel approach to compute the scalar components of the electric field from the tangential components along each edge based on field redatuming. The method can produce a more accurate result as compared to conventional approach. We have applied the developed algorithm to compute the EM response for a typical 3D anisotropic geoelectrical model of the off-shore HC reservoir with complex seafloor bathymetry. The numerical study demonstrates that the modeling algorithm is capable of simulating the complex topography and bathymetry that is commonly encountered in controlled source electromagnetic problems.