Conductivity-depth Imaging Research Articles

A novel trans-dimensional Bayesian inversion strategy for airborne time-domain electromagnetic data

The trans-dimensional Bayesian inversion method based on statistical theory regards the inversion parameters as random variable, it not only provides a reasonable inverse model based on the probability, but also offers the probability distribution and the uncertainty information of the inverse model parameters. However, for the conventional trans-dimensional Bayesian inversion, the model sampling efficiency and inversion convergence rate are influenced by several factors, and it requires sampling over a big model space, those limit the application of the trans-dimensional Bayesian inversion for airborne time-domain electromagnetic data. In this paper, we present a novel trans-dimensional Bayesian inversion strategy for airborne time-domain electromagnetic data, which uses a combining sampling update method to implement the model sampling. This method uses the block-wise updating method to run only one Markov chain with the initial state constructed by conductivity-depth imaging during the burn-in period, and adopts the component-wise updating method with an adaptive sampling step size to perform multiple Markov chains in parallel after the burn-in period ends. The effectiveness of the novel Bayesian inversion strategy was validated by both synthetic data and survey data. The experimental results showed that this inversion strategy can not only obtain better inversion results, but also shorten the burn-in period and reduce the total sampling times of the Markov chain.

(Quasi-)Real-Time Inversion of Airborne Time-Domain Electromagnetic Data via Artificial Neural Network

The possibility to have results very quickly after, or even during, the collection of electromagnetic data would be important, not only for quality check purposes, but also for adjusting the location of the proposed flight lines during an airborne time-domain acquisition. This kind of readiness could have a large impact in terms of optimization of the Value of Information of the measurements to be acquired. In addition, the importance of having fast tools for retrieving resistivity models from airborne time-domain data is demonstrated by the fact that Conductivity-Depth Imaging methodologies are still the standard in mineral exploration. In fact, they are extremely computationally efficient, and, at the same time, they preserve a very high lateral resolution. For these reasons, they are often preferred to inversion strategies even if the latter approaches are generally more accurate in terms of proper reconstruction of the depth of the targets and of reliable retrieval of true resistivity values of the subsurface. In this research, we discuss a novel approach, based on neural network techniques, capable of retrieving resistivity models with a quality comparable with the inversion strategy, but in a fraction of the time. We demonstrate the advantages of the proposed novel approach on synthetic and field datasets.

Fast imaging of time-domain airborne EM data using deep learning technology

Due to the huge amount of data generated by time-domain airborne electromagnetic (AEM) systems, conductivity depth imaging methods are widely used to help in the interpretation of these data because they can be generated quickly and easily. We have introduced a new imaging method generated using a deep neural network. The network structure combines four convolutional neural networks with a long short-term memory technique and adopts an error back-propagation scheme to update the parameters. A deep hierarchical structure is used to extract and store the complex nonlinear relationship between the model and electromagnetic (EM) responses, creating results close to 1D inversions. To check the effectiveness, we have examined our algorithm on synthetic and survey AEM data. The imaging result shows that this method, when using reasonable network parameters, can not only image well at high speed, but the method also is not very sensitive to noise. Another advantage of this method is that once the training is completed on a well-distributed training set, the network can be used without any changes to process other data sets from an identically configured AEM system.

Stripping induced polarization effects from airborne electromagnetics to improve 3D conductivity inversion of a narrow palaeovalley

The electrical conductivity distribution within wide palaeochannels is usually well-mapped from airborne electromagnetic data using stitched 1D algorithms. Such stitched 1D solutions are, however, inappropriate for narrow valleys. An alternative option is to consider 2D or 3D models to allow for finite lateral extent of conductors. In airborne electromagnetic data within the Musgrave block near the well-studied Valen conductor, strong induced polarization (IP) and superparamagnetic (SPM) effects make physical property and structure estimation even more uncertain for deep channel clays, particularly those whose channel widths are comparable to their depth of burial. We developed a recursive data fitting algorithm based on dispersive thin sheet responses. The separate IP and SPM components of the fit provide near-surface chargeability and SPM distributions, and the associated electromagnetic (EM) fit provides stripped data with monotonic decays compatible with a simple nondispersive conductivity model. The validity of this stripped data prediction was tested through a comparison of 1D conductivity-depth imaging and 3D inversion applied to the original data and the stripped data. Due to the forked geometry of the deep conductivity structure in the region we investigated, we successfully used 3D rather than 2D inversion to predict the conductivity distribution related to the EM data. We recovered from the stripped data a continuous conductivity structure consistent with a branching, clay-filled palaeovalley under cover.

New regional stratigraphic insights from a 3D geological model of the Nasia sub-basin, Ghana, developed for hydrogeological purposes and based on reprocessed B-field data originally collected for mineral exploration

Abstract. Reprocessing of regional-scale airborne electromagnetic data is used to build a 3D geological model of the Nasia sub-basin, northern Ghana. The resulting 3D geological model consistently integrates all the prior pieces of information brought by electromagnetic data, lithologic logs, ground-based geophysical surveys, and geological knowledge of the terrain. The geo-modeling process is aimed at defining the lithostratigraphy of the area, chiefly to improve the stratigraphic definition of the area, and for hydrogeological purposes. The airborne electromagnetic measurements, consisting of GEOTEM B-field data, were originally collected for mineral exploration purposes. Thus, those B-field data had to be (re)processed and properly inverted as the original survey and data handling were designed for the detection of potential mineral targets and not for detailed geological mapping. These new geophysical inversion results, compared with the original conductivity–depth images, provided a significantly different picture of the subsurface. The new geophysical model led to new interpretations of the geological settings and to the construction of a comprehensive 3D geo-model of the basin. In this respect, the evidence of a hitherto unexposed system of paleovalleys could be inferred from the airborne data. The stratigraphic position of these paleovalleys suggests a distinctly different glaciation history from the known Marinoan events, commonly associated with the Kodjari formation of the Voltaian sedimentary basin. Indeed, the presence of the paleovalleys within the Panabako may be correlated with mountain glaciation within the Sturtian age, though no unequivocal glaciogenic strata have yet been identified. Pre-Marinoan glaciation is recorded in rocks of the Wassangara group of the Taoudéni Basin. The combination of the Marinoan and, possibly, Sturtian glaciation episodes, both of the Cryogenian period, can be an indication of a Neoproterozoic Snowball Earth. Hence, the occurrence of those geological features not only has important socioeconomic consequences – as the paleovalleys can act as reservoirs for groundwater – but also from a scientific point of view, they could be extremely relevant as their presence would require a revision of the present stratigraphy of the area.

High resolution conductivity-depth transformation of TEM data

Conductivity depth transformation of TEM data remains an important tool for preliminary interpretation, despite the increasing speed of 1D inversion. Conductivity-depth imaging (CDI) is very fast, does not require a starting model, and is an effective means for data quality assessment. Moreover, CDI sections can serve as starting models for inversion. This paper describes a high resolution enhancement of an existing CDI algorithm for TEM data. Conductivitydepth transformation is accomplished in two steps. Measured voltages or B-field at a given delay time are first transformed to apparent conductivity. For dB/dt data, the assigned depth, z(t), at each time is the depth of the electric field or current maximum (Emax depth) in a half-space with conductivity equal to the apparent conductivity. For B-field data, the depth to the halfspace B-field maximum (Bmax depth) is employed. CDI sections based on apparent conductivity provide a vertically smoothed representation of the true conductivity profile. The apparent conductivity at any time can be represented as an inner product of the true conductivity with the Frechet kernel. The Frechet kernel at time t can be approximated as a linear function, decreasing from its maximum value at the surface to zero at a depth d(t). Therefore, given apparent conductivities from the CDI algorithm, a sharper estimate of the true conductivity can be generated via solution of a simple integral equation. We solve the integral equation for a ?minimum structure? model using linear programming. The implementation of this high resolution CDI algorithm is illustrated on selected examples of synthetic and real airborne TEM data.

A combining regularization strategy for the inversion of airborne time-domain electromagnetic data

Airborne time-domain electromagnetic data are usually over-sampled along the flight line. As the footprint of the ATEM method is larger than the interval between two soundings, inversion results cannot vary sharply in the lateral direction. The results of traditional one-dimensional inversion may be discontinuous. Although the popular lateral and spatial constraint inversion method can obtain a continuous quasi-2D and quasi-3D model respectively, these methods need to consider several soundings simultaneously, and their computational cost is relatively high, in comparison to inversion with only one sounding, for large ATEM data sets.To enhance the smoothness and continuity of the inversion result in the vertical and lateral directions, and simultaneously reduce the computation cost, we present a combining regularization strategy that can invert all ATEM soundings independently. The inversion strategy applies three regularization terms simultaneously. First, the inversion results of the previous sounding are used as a lateral constraint to strengthen continuity in the lateral direction. Second, the vertical model roughness is used to guarantee smoothness in the vertical direction. Finally, the results of conductivity-depth imaging are taken as a reference model to improve the inversion convergence rate.The combining regularization strategy was tested on synthetic data to analyze the influence of the first and second derivatives of vertical model roughness and that of the weight factors of the three regularization terms. The experimental results on synthetic data showed that the smoothness of the inversion result in the vertical direction is better with the second derivative of vertical model roughness than with the first derivative, and the proposed combining regularization strategy can effectively improve the continuity and smoothness of the inversion result in the horizontal and vertical directions, which is better than separately applying each regularization technique. Meanwhile, the combined scheme using conductivity-depth imaging results as reference model can not only obtain the inversion results close to the real distribution of media, but also improve the computational efficiency. In addition, the inversion results on field data acquired from Leach Lake Basin, Fort Irwin, California, verify the practicability of the proposed inversion strategy.

Conductivity-depth Imaging of Large Loop TEM Sounding Data Acquired using Central loop Configuration

Conductivity-depth Imaging of Large Loop TEM Sounding Data Acquired using Central loop Configuration

Review on airborne electromagnetic inverse theory and applications

Airborne electromagnetic (AEM) data processing and inversion has progressed from the early conductivity-depth imaging, to 1D inversion for a layered earth model, and most recently to 2D/3D inversions. The new processes have used methods for searching for solutions, applying constraints, and focusing images, such as Occam’s, laterally constrained, and holistic inversions. For airborne data imaging and 1D inversion, some algorithms are fast, whereas others have control over data misfit and the vertical or lateral smoothness. Beyond 1D algorithms, 2D/3D inversions are based on currently used methods such as isolated conductor models (which are good for highly conductive orebodies in resistive background) and techniques that discretized regions that are used for more complex structures and backgrounds. In the latter case, the computations are slow, so research is focusing on time-efficient computer algorithms for solving the equations such as Gauss-Newton, quasi-Newton, and nonlinear conjugate gradient algorithms. For the electromagnetic (EM) problem, the solution can be obtained in a more practical time frame if material that has minimal impact is ignored. Two approaches can be used to speedup the EM inversion process — the moving footprint and direct solver methods. We hope our work will to some extent help stimulate and focus the research in AEM inversion.

Rapid approximate inversion of airborne TEM

Rapid interpretation of large airborne transient electromagnetic (ATEM) datasets is highly desirable for timely decision-making in exploration. Full solution 3D inversion of entire airborne electromagnetic (AEM) surveys is often still not feasible on current day PCs. Therefore, two algorithms to perform rapid approximate 3D interpretation of AEM have been developed. The loss of rigour may be of little consequence if the objective of the AEM survey is regional reconnaissance. Data coverage is often quasi-2D rather than truly 3D in such cases, belying the need for ‘exact’ 3D inversion.Incorporation of geological constraints reduces the non-uniqueness of 3D AEM inversion. Integrated interpretation can be achieved most readily when inversion is applied to a geological model, attributed with lithology as well as conductivity. Geological models also offer several practical advantages over pure property models during inversion. In particular, they permit adjustment of geological boundaries. In addition, optimal conductivities can be determined for homogeneous units. Both algorithms described here can operate on geological models; however, they can also perform ‘unconstrained’ inversion if the geological context is unknown.VPem1D performs 1D inversion at each ATEM data location above a 3D model. Interpretation of cover thickness is a natural application; this is illustrated via application to Spectrem data from central Australia. VPem3D performs 3D inversion on time-integrated (resistive limit) data. Conversion to resistive limits delivers a massive increase in speed since the TEM inverse problem reduces to a quasi-magnetic problem. The time evolution of the decay is lost during the conversion, but the information can be largely recovered by constructing a starting model from conductivity depth images (CDIs) or 1D inversions combined with geological constraints if available. The efficacy of the approach is demonstrated on Spectrem data from Brazil.Both separately and in combination, these programs provide new options to exploration and mining companies for rapid interpretation of ATEM surveys.

Application of high resolution airborne geophysical data in geological modelling of Mohar Cauldron Complex, Bundelkhand Massif, central India: implications for uranium exploration

The Mohar cauldron, located near Mohar village, Shivpuri District, Madhya Pradesh, India, represents an explosive felsic volcanic event. The Mohar Cauldron Complex (MCC) is an important target area for uranium exploration as collapse breccias associated with extensional tectonics are traditionally important for multi-metal deposits, including uranium. Advanced processing and interpretation of the high resolution airborne electromagnetic (AEM), magnetic and radiometric data acquired over the Mohar cauldron and the surrounding environs by Fugro Airborne surveys, successfully mapped the major geological domains in the area based on their distinct geophysical characteristics. Interpretation of the data indicated the presence of three felsic intrusive bodies, only one of which, the MCC, reached the surface and collapsed. Variation in the geophysical characteristics of the three bodies is attributed to variations in hydrothermal alteration. Magnetic signature and radiometric response of the MCC and surrounding area also show signs of intense alteration. AEM data has allowed the boundary of the sediments within the MCC to be mapped accurately, along with the surrounding brecciated zone. Conductivity depth imaging calculated to a depth of 500 m clearly indicated the geometry and disposition of different layers of MCC. 3D voxel modelling of the MCC also allowed for the identification of the different lithologies that constitute the cauldron structure. 3D conductivity isosurfaces provided a thorough understanding of the subsurface distribution of conductivities.

Mapping subsurface geological structure using TEMPEST data, McArthur Basin, Northern Territory

The airborne TEMPEST electromagnetic (EM) and magnetic survey is a proven tool for mapping geological structure for exploration. This technique was applied at the Bulman project area in the McArthur Basin to identify the geological environment of stratabound carbonate-hosted Pb-Zn mineralisation. The Late Palaeoproterozoic to Early Mesoproterozoic sedimentary fill of the McArthur Basin in the Bulman project area consists of the Dook Creek and Limmen Formations. They are intruded by Early Mesoproterozoic dolerite sills and dykes. The location of the intrusive rocks was mapped using magnetic data while their depth was estimated from EM data. To find the top of the intrusives, depth to resistive basement was mapped using Conductivity Depth Images (CDIs) generated from the TEMPEST B-field Z-component data. Additionally, a voxel model was constructed from the CDIs to show the conductivity distribution in three dimensions. The conductivity pattern indicates that the dolomite sandstone and siltstone of the Dook Creek Formation are more conductive than the overlying coarse sandstone of the Limmen Formation. A disconformable boundary between the formations is shown as a distinct interface in the EM data. There is no marked conductivity contrast between intrusives and other rocks making up the resistive basement. As a result, the picked depth to resistive basement horizon corresponds to the bottom of a surface conductive unit that is interpreted to be the base of the Cenozoic unconsolidated deposits or part of the Dook Creek Formation. In places, the base of a sub-surface conductive zone is interpreted to be the top of the intrusives. The thickness of sediments above the resistive basement is variable, reaching up to 170 metres in the central - eastern part of the study area. Additionally, a 3D geological model has been constructed to image the distribution of the interpreted geological units and the tectonic pattern.

Bigger, better, smarter: High performance computing applied to government geophysics

Government Geological Surveys study the Earth at the regional, province or national scale, and acquire vast volumes of technically complex data. These data must be high quality, fit for purpose, durable, and readily accessible and usable by industry. Increasingly, users require the geological information contained within the data as well as the data itself. High performance computers facilitate a step-change in advanced processing and modelling of large, complex data, and will help Government deliver more sophisticated products to industry. Data enhancement and manipulation are no-longer limited by the computational effort required, and there are no artificial limits to the size of the data or model, or the data resolution that can be processed. Geoscience Australia is collaborating with the National Computational Infrastructure facility (NCI) at the Australian National University to develop advanced methods for extracting the maximum geological information from large data volumes. The new methods include: Modelling of potential-field data in spherical coordinates to create continental-scale reference models of density and magnetic susceptibility; Inversion of magnetotelluric tensor data to a full 3D mesh of resistivities, and; Monte Carlo inversions of AEM responses to assess the reliability and sensitivity of conductivity-depth images. These algorithms are being implemented in a new Virtual Geophysical Laboratory where Government data and advanced processing methods are brought together in a single high performance computer environment.

3D VTEM inversion for delineating sub-vertical shear zones in the West African gold belt

SUMMARY Accurately delineating sub-vertical graphitic thrust faults and shear systems is one of the major strategies followed in West African gold exploration. Due to the dense vegetation and limited outcrops, airborne electromagnetic (AEM) surveys have been routinely flown for geological mapping. We present a case study for practical 3D inversion of VTEM data acquired in Ghana. The geology is very complex, and consists of carbonaceous shear zones containing multiple thrust faults. Certain types of gold mineralization are directly associated with the shear zones which manifest themselves as sub-vertical conductors. We compare results from 3D AEM inversion to those obtained from traditional AEM interpretation methods, including conductivity depth imaging, decay constant analysis, profile anomaly picking, Fraser filtering, and plate modelling. We show that even with no a priori information, 3D AEM inversion accurately delineates the sub-vertical conductors, and recovers the most accurate representation of the geology. Interpretations based on CDIs are shown to be unreliable.

Airborne time‐domain electromagnetics, electrical resistivity and seismic reflection for regional three‐dimensional mapping and characterization of the Spiritwood Valley Aquifer, Manitoba, Canada

The Geological Survey of Canada commissioned a helicopter‐borne time‐domain electromagnetic (HTEM) survey over a 1062 km2 area of the Spiritwood Valley in southern Manitoba in order to test the effectiveness of airborne time‐domain electromagnetics for mapping and characterizing buried valley aquifers in the Canadian Prairies. The data exhibit rich information content and clearly indicate the broader Spiritwood Valley in addition to a continuous incised valley along the broader valley bottom. We detect complex valley morphology with nested scales of valleys including at least three distinct valley features and multiple possible tributaries. Conductivity‐depth images (CDI) derived from the HTEM decays indicate that the fill materials within the incised valleys are more resistive than the broader valley fill, consistent with an interpretation of sand and gravel. Comparison of ground‐based electrical resistivity and seismic reflection data allow for the evaluation of CDI models. Lateral spatial information is in excellent agreement between data sets. However, CDI results tend to underestimate the dynamic range of electrical conductivity while overestimating depths to valley bottoms; these issues may be associated with system limitations, algorithm limitations or differences between data types. The integrated data sets illustrate that HTEM surveys have the potential to map complicated buried valley aquifers at a level of detail required for groundwater prospecting, modelling and management.

High resolution conductivity-depth transformation of TEM data

SummaryConductivity depth transformation of TEM data remains an important tool for preliminary interpretation, despite the increasing speed of 1D inversion. Conductivity-depth imaging (CDI) is very fast, does not require a starting model, and is an effective means for data quality assessment. Moreover, CDI sections can serve as starting models for inversion.This paper describes a high resolution enhancement of an existing CDI algorithm for TEM data. Conductivitydepth transformation is accomplished in two steps. Measured voltages or B-field at a given delay time are first transformed to apparent conductivity. For dB/dt data, the assigned depth, z(t), at each time is the depth of the electric field or current maximum (Emax depth) in a half-space with conductivity equal to the apparent conductivity. For B-field data, the depth to the halfspace B-field maximum (Bmax depth) is employed.CDI sections based on apparent conductivity provide a vertically smoothed representation of the true conductivity profile. The apparent conductivity at any time can be represented as an inner product of the true conductivity with the Frechet kernel. The Frechet kernel at time t can be approximated as a linear function, decreasing from its maximum value at the surface to zero at a depth d(t). Therefore, given apparent conductivities from the CDI algorithm, a sharper estimate of the true conductivity can be generated via solution of a simple integral equation. We solve the integral equation for a “minimum structure” model using linear programming.The implementation of this high resolution CDI algorithm is illustrated on selected examples of synthetic and real airborne TEM data.

Breaks in lithology: Interpretation problems when handling 2D structures with a 1D approximation

Most airborne electromagnetic (AEM) data are processed using successive 1D approximations to produce stitched conductivity-depth sections. Because the current induced in the near surface by an AEM system preferentially circulates at some radial distance from a horizontal loop transmitter (sometimes called the footprint), the section plotted directly below a concentric transmitter-receiver system actually arises from currents induced in the vicinity rather than directly underneath. Detection of paleochannels as conduits for groundwater flow is a common geophysical exploration goal, where locally 2D approximations may be valid for an extinct riverbed or filled valley. Separate from effects of salinity, these paleochannels may be conductive if clay filled or resistive if sand filled and incised into a clay host. Because of the wide system footprint, using stitched 1D approximations or inversions may lead to misleading conductivity-depth images or sections. Near abrupt edges of an extensive conductive layer, the lateral falloff in AEM amplitudes tends to produce a drooping tail in a conductivity section, sometimes coupled with alocal peak where the AEM system is maximally coupled to currents constrained to flow near the conductor edge. Once the width of a conductive ribbon model is less than the system footprint, small amplitudes result, and the source is imaged too deeply in the stitched 1D section. On the other hand, a narrow resistive gap in a conductive layer is incorrectly imaged as a drooping region within the layered conductor; below, the image falsely contains a blocklike poor conductor extending to depth. Additionally, edge-effect responses often are imaged as deep conductors with an inverted horseshoe shape. Incorporating lateral constraints in 1D AEM inversion (LCI) software, designed to improve resolution of continuous layers, more accurately recovers the depth to extensive conductors. The LCI, however, as with any AEM modeling methodology based on 1D forward responses, has limitations in detecting and imaging in the presence of strong 3D lateral discontinuities of dimensions smaller than the annulus of resolution. The isotropic, horizontally slowly varying layered-earth assumption devalues and limits AEM’s 3D detection capabilities. The need for smart, fast algorithms that account for 3D varying electrical properties remains.

Analysis of numerical differentiation methods applied to time domain electromagnetic (TDEM) geophysical data in the S-layer differential transform

The S-layer differential transform produces subsurface conductivity-depth images from Time Domain Electromagnetic (TDEM) data. It is a very fast method, but suffers from high noise levels due to the implementation of two consecutive numerical differentiations that are performed in the algorithm. In this paper, twelve numerical differentiation strategies are compared in order to find the most efficient differentiation scheme, specifically for TDEM data and the S-layer differential transform. The twelve strategies are made up through combinations of three differentiation methods, optional smoothing of data and optional resampling of data to equally spaced intervals. Comparisons are made on analytical, synthetic and field data.

Investigation on the groundwater resources of the South Eyre Peninsula, South Australia, determined from laterally constrained inversion of tempest data

Groundwater in the Eyre Peninsula of South Australia is scarce with potable resources limited to the western coastal margin and the southern tip of the peninsula. Consequently an understanding of their extent has become increasingly important particularly with demand being close to current extraction limits. In September 2006, about 1000 line km of TEMPEST AEM data were acquired over the Southern Eyre Peninsula, in order to assist in the definition of freshwater lens systems and in particular aquifer bounds associated with them as part of a resource definition project. Following their acquisition, the TEMPEST data set was analysed for data quality and then transformed into conductivity depth images (CDI) using EMFLOW and subsequently using a smooth model inversion (see Fitzpatrick and Munday, 2007). In an effort to better define to better define the geometry of specific bounding surfaces of hydrogeological relevance the TEMPEST data were inverted through the application of the laterally constrained inversion (LCI) technique. This paper describes the initial results from the first application of the LCI to data from a fixed wing AEM system.

Conductivity-depth imaging of helicopter-borne TEM data based on a pseudolayer half-space model

Helicopter-borne time-domain electromagnetic (HTEM) systems with a concentric horizontal coil configuration have been used increasingly in mineral exploration. Conductivity-depth imaging (CDI) is a useful tool for mapping the distribution of geologic conductivity and for identifying conductive targets. A CDI algorithm for HTEM systems with a concentric coil configuration is developed based on the pseudolayer half-space model. Primary advantages of this model are immunity to altimeter errors and better resolution of conductive layers than other half-space models. Effective depth is derived empirically from the diffusion depth and apparent thickness of the pseudolayer. A table lookup procedure is established based on the analytic solution of a half-space model to speed up processing. This efficiency makes generation of real-time conductivity-depth images possible. Tests on synthetic data demonstrate that the pseudolayer conductivity-depth-imaging algorithm maps a wider range of conduc-tivities and does a better job of resolving highly conductive layers, compared with that of the homogeneous half-space model. Effective depths are close to true depths in many circumstances. Field examples show stable and geologically meaningful conductivity-depth images.