Search

SUMMARY: For accurate modelling of groundwater flow and transport processes within an aquifer, precise knowledge about hydraulic conductivity K and its small-scale heterogeneities is fundamental. Methods based on pumping tests, such as hydraulic tomography (HT), allow for retrieving reliable K-estimates, but are limited in their ability to image structural features with high resolution, since the data from time-consuming hydraulic tests are commonly sparse. In contrast, geophysical methods like induced polarization (IP) can potentially yield structural images of much higher resolution, but depend on empirical petrophysical laws that may introduce significant uncertainties to the K-estimation. Therefore, this paper presents a joint inversion procedure for both HT and IP data, which allows for combining the complementary abilities of both methods. Within this approach, a traveltime inversion is applied to the HT data, while the IP inversion is based on a full-decay time-domain forward response, as well as a reparametrization of the Cole–Cole model to invert for K directly. The joint inversion is tested on a synthetic model mimicking horizontally layered sediments, and the results are compared with the individual HT and IP inversions. It is shown that jointly inverting both data sets consistently improves the results by combining the complementary sensitivities of the two methods, and that the inversion is more robust against changes in the experimental setups. Furthermore, we illustrate how a joint inversion approach can correct biases within the petrophysical laws by including reliable K-information from hydraulic tests and still preserving the high-resolution structural information from IP. The different inversion results are compared based on the structural similarity index (SSIM), which underlines the robustness of the joint inversion compared to using the data individually. Hence, the combined application of HT and IP within field surveys and a subsequent joint inversion of both data sets may improve our understanding of hydraulically relevant subsurface structures, and thus the reliability of groundwater modelling results. [ABSTRACT FROM AUTHOR]

Transient electromagnetic (TEM) is an efficient non-invasive method to map electrical conductivity distribution in the subsurface. This paper presents an inversion scheme for 3-D TEM time-lapse (TL) data using a generalized minimum support (MS) norm and its application to monitoring conductivity changes over time. In particular, two challenges for TL TEM applications are addressed: (i) the survey repetition with slightly different acquisition position, that is, because systems are not installed and (ii) non-optimal data coverage above the TL anomalies, for instance, due to the presence of infrastructure that limits the acquisition layout because of coupling. To address these issues, we developed a new TEM TL inversion scheme with the following features: (1) a multimesh approach for model definition and forward computations, which allows for seamless integration of data sets with different acquisition layouts; (2) 3-D sensitivity calculation during the inversion, which allows retrieving conductivity changes in-between TEM soundings and (3) simultaneous inversion of two data sets at once, imposing TL constraints defined in terms of a generalized MS norm, which ensures compact TL changes. We assess the relevance of our implementations through a synthetic example and a field example. In the synthetic example, we study the capability of the inversion scheme to retrieve compact time-lapse changes despite slight changes in the acquisition layout and the effect of data coverage on the retrieval of TL changes. Results from the synthetic tests are used for interpreting field data, which consists of two TEM data sets collected in 2019 and 2020 at the Nesjavellir high-temperature geothermal site (Iceland) within a monitoring project of H2S sequestration. Furthermore, the field example illustrates the effect of the trade-off between data misfit and TL constraints in the inversion objective function, using the tuning settings of the generalized MS norm. Based on the results from both the synthetic and field cases, we show that our implementation of 3-D TL inversion has a robust performance for TEM monitoring. [ABSTRACT FROM AUTHOR]

Inversion of large-scale time-domain transient electromagnetic (TEM) surveys is computationally expensive and time-consuming. The calculation of partial derivatives for the Jacobian matrix is by far the most computationally intensive task, as this requires calculation of a significant number of forward responses. We propose to accelerate the inversion process by predicting partial derivatives using an artificial neural network. Network training data for resistivity models for a broad range of geological settings are generated by computing partial derivatives as symmetric differences between two forward responses. Given that certain applications have larger tolerances for modeling inaccuracy and varying degrees of flexibility throughout the different phases of interpretation, we present four inversion schemes that provide a tunable balance between computational time and inversion accuracy when modeling TEM datasets. We improve speed and maintain accuracy with a hybrid framework, where the neural network derivatives are used initially and switched to full numerical derivatives in the final iterations. We also present a full neural network solution where neural network forward and derivatives are used throughout the inversion. In a least-squares inversion framework, a speedup factor exceeding 70 is obtained on the calculation of derivatives, and the inversion process is expedited ~36 times when the full neural network solution is used. Field examples show that the full nonlinear inversion and the hybrid approach gives identical results, whereas the full neural network inversion results in higher deviation but provides a reasonable indication about the overall subsurface geology. [ABSTRACT FROM AUTHOR]

Worldwide, soil contamination due to industrial activities is a major issue. One method for remediation of contaminated sites is in situ chemical oxidation, where an oxidizing agent is injected into the contaminated soil. Normally, monitoring wells are established in the remediation area for tracking the oxidizing agent. However, wells only provide point information of the injectant spread. This issue can be addressed using cross‐borehole resistivity and induced polarization tomography, by mapping the electrical properties in the entire remediation volume and by deriving, through petrophysical relations, the hydraulic properties of the medium. Here we present a proof‐of‐concept study, performed over one year as part of a larger remediation project, where resistivity and time‐domain induced polarization data were acquired among 10 boreholes, before and after two rounds of injection of oxidizing agents. The time‐lapse resistivity models, obtained through a focusing inversion scheme that favours compact time‐lapse changes, clearly show the oxidizing agent spread as highly conductive anomalies and confirmed by water conductivity measurements in boreholes. The time‐lapse inversions also show spatial variability in the injectant spread, with some areas not reached. The induced polarization data quality decreased significantly just after the injection rounds, because of the decrease in resistivity and induced polarization signal level, so that induced polarization time‐lapse inversions were not feasible. However, the induced polarization data were used for background characterization and to estimate permeability. In particular, there is a good match between the imaged low‐permeability zones and the areas in which the injectant did not spread, identified by the time‐lapse resistivity inversions. Furthermore, geological samples confirm the presence of fine‐grained sediments in the estimated low‐permeability zones. While time‐lapse resistivity tomography may be used for documenting the injectant spread, induced polarization permeability estimates prior to injection can be used to better tailor the remediation in terms of dimension and location of injection filters. [ABSTRACT FROM AUTHOR]

With advances in data acquisition and processing methods, spectral inversion of time domain (TD) induced polarization (IP) data is becoming more common. Geological interpretation of inverted spectral parameters, for instance Cole–Cole parameters, often relies on results from systematic laboratory measurements. These are most often carried out with frequency domain (FD) systems on sandstone samples. However, the two different methods of measuring the spectral IP response differ in both measurement technique and scale. One of the main objectives of this study is, thus, to perform a direct comparison of inverted spectral parameters from TD IP field data with FD IP spectra from laboratory measurements. To achieve this, field measurements were carried out before a ∼50-m-long rock core was drilled down along one of the measurement lines. Solid parts of the core were vacuum-sealed in plastic bags to preserve the natural groundwater in the samples, after which the core samples were measured with FD spectral IP in laboratory. The results showed that the inverted Cole–Cole parameters closest to the borehole were comparable to the IP spectra measured at the core samples, despite differences in measurement techniques and scale. The field site chosen for the investigation was a limestone succession spanning over a well-known lithological boundary (the Cretaceous–Palaeogene boundary). Little is known in previous research about varying spectral IP responses in limestones, and an additional objective of this study was, therefore, to investigate possible sources of these variations in the laboratory. The IP spectra were interpreted in light of measured lithological and physicochemical properties. The carbonate texture differed strongly across the Cretaceous–Palaeogene boundary from fine-grained calcareous mudstone (Cretaceous) to more well-lithified and coarse-grained wackestone and packstone (Palaeogene). Both laboratory and field spectral IP results showed that these differences cause a large shift in measured bulk conductivity across the boundary. Furthermore, carbonate mound structures with limestone grains consisting mainly of cylindrical bryozoan fragments could be identified in the inverted Cole–Cole parameters as anomalies with high relaxation times. A general conclusion of this work is that limestones can give rise to a wide range of spectral responses. The carbonate texture and the dominant shape of the fossil grains seem to have important control over the electrical properties of the material. A main conclusion is that the inverted Cole–Cole parameters from the field scale TD IP tomography were comparable to the magnitude and shape of FD IP spectra at low frequencies. This opens up large interpretational possibilities, as the comprehensive knowledge about relationships between lithological properties and IP spectra from laboratory research can be used for field data interpretation. [ABSTRACT FROM AUTHOR]

This paper presents the results of airborne electromagnetic induced polarisation inversions using the Maximum Phase Angle (MPA) model for a helicopter time domain survey in the Quadrilátero Ferrífero area, Minas Gerais State (MG), Brazil. The inversions were conducted using a laterally constrained robust scheme, in order to decrease the difficulties to recover the multi-parametric model in a very ill-posed inverse problem, often found in induced polarisation studies. A set of six flight lines over the Lamego gold mine mineralised structure were inverted using the MPA re-parameterisation of the Cole–Cole model and also the classical resistivity-only parameterisation, in order to understand the implications of the induced polarisation effect in the data and, consequently, in the resistivity model. A synthetic study was also conducted, seeking to understand what to expect from the resistivity-only inversions in the real data. According to borehole lithological data and previous structural knowledge from the literature, the results from the Maximum Phase Angle approach indicate an important chargeable body that seems to be in good agreement with a sulfide enriched carbonaceous/graphite and altered mafic unities, which are important markers for the gold mineralisation. [ABSTRACT FROM AUTHOR]

An integral component of the surface nuclear magnetic resonance forward model involves predicting the magnitude of the transverse magnetization following excitation. To predict the transverse magnetization, the Bloch equation must be solved. Traditional surface NMR forward models solve a simplified version of the Bloch equation where the relaxation terms are neglected. A shortcoming of this approach is that it can struggle to accurately describe the impact of relaxation during pulse effects. To address this concern, an alternative forward model based on solution of the full-Bloch equation is proposed. The advantage of the proposed scheme is that it implicitly accounts for relaxation during pulse effects, increases the flexibility to implement alternative parametrizations of the inverse model, and can readily describe an arbitrary excitation protocol given that it no longer requires closed form expressions of the transverse magnetizations. To demonstrate the potential of the updated forward modelling scheme, a novel approach for the inversion of complex-valued free-induction decay (FID) data is presented. The inverse model is reparametrized in order to produce depth profiles of the water content, T2* and T2. This approach has great potential to enhance the ability of FID measurements to provide insights into pore size and permeability as it can provide direct sensitivity to T2. In contrast, traditional approaches that employ a forward model based on the simplified Bloch equation and estimate only T2* are plagued by uncertainty surrounding the link between T2* and pore size/permeability. Synthetic and field results are presented to demonstrate the feasibility of the proposed forward model and FID inversion framework. [ABSTRACT FROM AUTHOR]

The signal level and shape of induced polarization responses are significantly affected by the current pulse duration and waveform. If not accounted for, this data dependency on the current will propagate trough the inversion to results rendering unquantifiable subsurface models. While this problem has been addressed in full-response induced polarization modelling, questions remain as to how to accurately retrieve quantitative induced polarization inversion models from the types of apparent integral chargeability data often used in data interpretation. Although several methodologies have been proposed for handling and inverting apparent resistivity and integral chargeability, these cannot compensate for the data dependency on the current waveform and pulse duration. This paper presents a novel inversion method for such data. The method considers current waveform and receiver transfer functions for retrieving quantitative IP models unbiased by transmitter waveform. The method uses the constant phase angle model, expressed in terms of the medium resistivity and phase. Specifically, four field data sets for the same profile but with different 100 per cent duty cycle pulse durations (4, 2, 1 and 0.5 s) serve as examples of data sets giving models dependant on current waveform when inverted with standard approaches. The novel inversion method presented here gives quantifiable models independent on the current waveform and pulse duration. These results resemble models retrieved with existing, full-response induced polarization inversions. The results still contain some degree of uncertainty in relation to underlying assumptions and parametrizations. Managing this source of uncertainty is considered in terms of full-response induced polarization inversions with constant phase angle and maximum phase angle inversions. [ABSTRACT FROM AUTHOR]

The DC resistivity method is a common tool in periglacial research because it can delineate zones of large resistivities, which are often associated with frozen water. The interpretation can be ambiguous, however, because large resistivities may also have other causes, like solid dry rock. One possibility to reduce the ambiguity is to measure the frequency-dependent resistivity. At low frequencies (< 100 Hz) the corresponding method is called induced polarization, which has also been used in periglacial environments. For the detection and possibly quantification of water ice, a higher frequency range, between 100 Hz and 100 kHz, may be particularly interesting because in that range, the electrical properties of water ice exhibit a characteristic behaviour. In addition, the large frequencies allow a capacitive coupling of the electrodes, which may have logistical advantages. The capacitively coupled resistivity (CCR) method tries to combine these logistical advantages with the potential scientific benefit of reduced ambiguity. In this paper, we discuss CCR data obtained at two field sites with cryospheric influence: the Schilthorn massif in the Swiss Alps and the frozen Lake Prestvannet in the northern part of Norway. One objective is to add examples to the literature where the method is assessed in different conditions. Our results agree reasonably well with known subsurface structure: at the Prestvannet site, the transition from a frozen lake to the land is clearly visible in the inversion results, whereas at the Schilthorn site, the boundary between a snow cover and the bedrock below can be nicely delineated. In both cases, the electrical parameters are consistent with those expected from literature. The second objective is to discuss useful methodological advancements: first, we investigate the effect of capacitive sensor height above the surface and corroborate the assumption that it is negligible for highly resistive conditions. For the inversion of the data, we modified an existing 2-D inversion code originally developed for low-frequency induced polarization data by including a parametrization of electrical permittivity. The new inversion code allows the extraction of electrical parameters that may be directly compared with literature values, which was previously not possible. [ABSTRACT FROM AUTHOR]

Contaminant mass discharge is a commonly applied tool to evaluate the environmental impact of contaminated sites on water resources. At large contaminated sites with heterogeneous sources, such as landfills, the number of wells available is often not sufficient, leading to a high uncertainty of mass discharge estimates. In this study, we tackle the uncertainty of the contaminant mass discharge due to low sampling densities by interpolating limited water‐sample data with the support of surface direct current resistivity and induced polarization geophysical data. The method relies on finding a conceptual link between the bulk conductivity imaged from geophysics and the contaminant concentrations. We investigate the link between (1) imaged bulk and electrical water conductivity, (2) water conductivity and conservative ionic species, (3) water conductivity and redox‐sensitive species, (4) water conductivity and semipersistent organic species, and (5) water conductivity and biodegradable organic compounds. The method successfully identify similarities between the distribution of the bulk conductivity and chloride and pharmaceutical compounds in a landfill leachate plume and between the bulk conductivity data and benzene and chlorinated ethenes for a contaminant plume from a former pharmaceutical factory. Contaminant concentrations were interpolated through regression kriging, using geophysical data as the dependent variable. The distribution of concentration determined with the novel method showed a lower mean relative estimation error than the traditional method of kriging only contaminant concentration data. At large sites, the method can improve contaminant mass discharge estimates, especially if surface geophysical measurements are integrated in the site investigation at an early stage. Key Points: Surface direct current resistivity and induced polarization geophysical data can improve the interpolation of contaminant concentration dataThe geophysics‐based method can improve estimation of contaminant mass discharge at large contaminated sites with low water‐sample densitiesSurface geophysical data are affected by changes in inorganic species arising from a contaminant source or generated during biodegradation [ABSTRACT FROM AUTHOR]

The induced polarization phenomenon, both in time domain and frequency domain, is often parameterised using the empirical Cole–Cole model. To improve the resolution of model parameters and to decrease the parameter correlations in the inversion process of induced polarization data, we suggest here three re‐parameterisations of the Cole–Cole model, namely the maximum phase angle Cole–Cole model, the maximum imaginary conductivity Cole–Cole model, and the minimum imaginary resistivity Cole–Cole model. The maximum phase angle Cole–Cole model uses the maximum phase φmax and the inverse of the phase peak frequency, τφ, instead of the intrinsic charge‐ability m0 and the time constant adopted in the classic Cole–Cole model. The maximum imaginary conductivity Cole–Cole model uses the maximum imaginary conductivity σmax′′ instead of m0 and the time constant τσ of the Cole–Cole model in its conductivity form. The minimum imaginary resistivity Cole–Cole model uses the minimum imaginary resistivity ρmin′′ instead of m0 and the time constant τρ of the Cole–Cole model in its resistivity form. The effects of the three re‐parameterisations have been tested on synthetic time‐domain and frequency‐domain data using a Markov chain Monte Carlo inversion method, which allows for easy quantification of parameter uncertainty, and on field data using 2D gradient‐based inversion. In comparison with the classic Cole–Cole model, it was found that for all the three re‐parameterisations, the model parameters are less correlated with each other and, consequently, better resolved for both time‐domain and frequency‐domain data. The increase in model resolution is particularly significant for models that are poorly resolved using the classic Cole–Cole parameterisation, for instance, for low values of the frequency exponent or with low signal‐to‐noise ratio. In general, this leads to a significantly deeper depth of investigation for the ϕmax, σmax′′, and ρmin′′ parameters, when compared with the classic m0 parameter, which is shown with a field example. We believe that the use of re‐parameterisations for inverting field data will contribute to narrow the gap between induced polarization theory, laboratory findings, and field applications. [ABSTRACT FROM AUTHOR]

The application of time-domain induced polarization (TDIP) is increasing with advances in acquisition techniques, data processing and spectral inversion schemes. An inversion of TDIP data for the spectral Cole–Cole parameters is a non-linear problem, but by applying a 1-D Markov Chain Monte Carlo (MCMC) inversion algorithm, a full non-linear uncertainty analysis of the parameters and the parameter correlations can be accessed. This is essential to understand to what degree the spectral Cole–Cole parameters can be resolved from TDIP data. MCMC inversions of synthetic TDIP data, which show bell-shaped probability distributions with a single maximum, show that the Cole–Cole parameters can be resolved from TDIP data if an acquisition range above two decades in time is applied. Linear correlations between the Cole–Cole parameters are observed and by decreasing the acquisitions ranges, the correlations increase and become non-linear. It is further investigated how waveform and parameter values influence the resolution of the Cole–Cole parameters. A limiting factor is the value of the frequency exponent, C. As C decreases, the resolution of all the Cole–Cole parameters decreases and the results become increasingly non-linear. While the values of the time constant, τ, must be in the acquisition range to resolve the parameters well, the choice between a 50 per cent and a 100 per cent duty cycle for the current injection does not have an influence on the parameter resolution. The limits of resolution and linearity are also studied in a comparison between the MCMC and a linearized gradient-based inversion approach. The two methods are consistent for resolved models, but the linearized approach tends to underestimate the uncertainties for poorly resolved parameters due to the corresponding non-linear features. Finally, an MCMC inversion of 1-D field data verifies that spectral Cole–Cole parameters can also be resolved from TD field measurements. [ABSTRACT FROM AUTHOR]

Characterization of varying bedrock properties is a common need in various contexts, ranging from large infrastructure pre-investigations to environmental protection. A direct current resistivity and time domain induced polarization (IP) survey aiming to characterize properties of a Cretaceous limestone was carried out in the Kristianstad basin, Sweden. The time domain IP data was processed with a recently developed method in order to suppress noise from the challenging urban setting in the survey area. The processing also enabled extraction of early decay times resulting in broader spectra of the time decays and inversion for Cole-Cole parameters. The aims of this study is to investigate if large-scale geoelectrical variations as well as small-scale structural and compositional variations exist within the Kristianstad limestone, and to evaluate the usefulness of Cole-Cole inverted IP data in early time ranges for bedrock characterization. The inverted sections showed variations within the limestone that could be caused by variations in texture and composition. Samples from a deep drilling in the Kristianstad basin were investigated with scanning electron microscopy and energy dispersive X-ray spectroscopy, and the results showed that varying amounts of pyrite, glauconite and clay matrix were present at different levels in the limestone. The local high IP anomalies in the limestone could be caused by these minerals otherwise the IP responses were generally weak. There were also differences in the texture of the limestone at different levels, governed by fossil shapes and composition, proportions of calcareous cement and matrix as well as amount of silicate grains. Textural variations may have implications on the variation in Cole-Cole relaxation time and frequency factor. However, more research is needed in order to directly connect microgeometrical properties in limestone to spectral IP responses. The results from this study show that it is possible to recover useable spectral information from early decay times. We also show that under certain conditions (e.g. relatively short relaxation times in the subsurface), it is possible to extract spectral information from time domain IP data measured with on-off times as short as 1 s. [ABSTRACT FROM AUTHOR]

The extraction of spectral information in the inversion process of time-domain (TD) induced polarization (IP) data is changing the use of the TDIP method. Data interpretation is evolving from a qualitative description of the subsurface, able only to discriminate the presence of contrasts in chargeability parameters, towards a quantitative analysis of the investigated media, which allows for detailed soil- and rock-type characterization. Two major limitations restrict the extraction of the spectral information of TDIP data in the field: (i) the difficulty of acquiring reliable early-time measurements in the millisecond range and (ii) the self-potential background drift in the measured potentials distorting the shape of the late-time IP responses, in the second range. Recent developments in TDIP acquisition equipment have given access to full-waveform recordings of measured potentials and transmitted current, opening for a breakthrough in data processing. For measuring at early times, we developed a new method for removing the significant noise from power lines contained in the data through a modelbased approach, localizing the fundamental frequency of the power-line signal in the fullwaveform IP recordings. By this, we cancel both the fundamental signal and its harmonics. Furthermore, an efficient processing scheme for identifying and removing spikes in TDIP data was developed. The noise cancellation and the de-spiking allow the use of earlier and narrower gates, down to a few milliseconds after the current turn-off. In addition, tapered windows are used in the final gating of IP data, allowing the use of wider and overlapping gates for higher noise suppression with minimal distortion of the signal. For measuring at late times, we have developed an algorithm for removal of the self-potential drift. Usually constant or linear drift-removal algorithms are used, but these algorithms often fail in removing the background potentials present when the electrodes used for potential readings are previously used for current injection, also for simple contact resistance measurements. We developed a drift-removal scheme that models the polarization effect and efficiently allows for preserving the shape of the IP responses at late times. Uncertainty estimates are essential in the inversion of IP data. Therefore, in the final step of the data processing, we estimate the data standard deviation based on the data variability within the IP gates and themisfit of the background drift removalOverall, the removal of harmonic noise, spikes, self-potential drift, tapered windowing and the uncertainty estimation allows for doubling the usable range of TDIP data to almost four decades in time (corresponding to four decades in frequency), which will significantly advance the applicability of the IP method. [ABSTRACT FROM AUTHOR]

Surface nuclear magnetic resonance technique, also called magnetic resonance sounding (MRS), is an emerging geophysical method that can detect the presence and spatial variations of the subsurface water content directly. In this paper, we introduce the MRS central loop geometry, in which the receiver loop is smaller than the transmitter loop and placed in its centre. In addition, using a shielded receiver coil we show how this configuration greatly increases signal-to-noise ratio and improves the resolution of the subsurface layers compared to the typically used coincident loop configuration. We compare sensitivity kernels for different loop configurations and describe advantages of the MRS central loop geometry in terms of superior behaviour of the sensitivity function, increased sensitivity values, reduced noise level of the shielded receiver coil, improved resolution matrix and reduced instrument dead time. With no extra time and effort in the field, central-loop MRS makes it possible to reduce measurement time and to measure data in areas with high anthropogenic noise. The results of our field example agree well with the complementary data, namely airborne electromagnetics, borehole data, and the hydrologic model of the area. [ABSTRACT FROM AUTHOR]

Precise information about the spatial distribution of hydraulic conductivity (K) in an aquifer is essential for the reliable modeling of groundwater flow and transport processes. In this study, we present results of a new inversion procedure for induced polarization (IP) data that incorporates petrophysical relations between electrical and hydraulic parameters, and therefore allows for the direct computation of K. This novel approach was successfully implemented for the Bolstern aquifer analog by performing synthetic IP experiments with a combined surface and cross-borehole setup. From these data, the distribution of K was retrieved with high accuracy and resolution, showing a similar quality compared to images achieved by hydraulic tomography. To further improve the quantitative estimates of K , we use synthetic pumping test data to inform two novel calibration strategies for the IP inversion results. Both calibrations are especially helpful for correcting a possible bias of the IP inversion, e.g., due to resolution limitations and/or to bias in the underlying petrophysical relations. The simulation of tracer experiments on the retrieved tomograms highlights the accuracy of the inversion results, as well as the significant role of the proposed calibrations. • New IP inversion procedure for direct computation of hydraulic conductivity. • IP inversion results have similar quality as hydraulic tomography. • Hydraulic calibration of IP results to improve transport simulations. [ABSTRACT FROM AUTHOR]

Often in geophysical monitoring experiments time-lapse inversion models vary too smoothly with time, owing to the strong imprint of regularization. Several methods have been proposed for focusing the spatiotemporal changes of the model parameters. In this study, we present two generalizations of the minimum support norm, which favour compact time-lapse changes and can be adapted to the specific problem requirements. Inversion results from synthetic direct current resistivity models that mimic developing plumes show that the focusing scheme significantly improves size, shape and magnitude estimates of the time-lapse changes. Inversions of the synthetic data also illustrate that the focused inversion gives robust results and that the focusing settings are easily chosen. Inversions of full-decay time-domain induced polarization (IP) field data from a CO2 monitoring injection experiment show that the focusing scheme performs well for field data and inversions for all four Cole-Cole polarization parameters. Our tests show that the generalized minimum support norms react in an intuitive and predictable way to the norm settings, implying that they can be used in time-lapse experiments for obtaining reliable and robust results. [ABSTRACT FROM AUTHOR]

We present an overview of a mature, robust and general algorithm providing a single framework for the inversion of most electromagnetic and electrical data types and instrument geometries. The implementation mainly uses a 1D earth formulation for electromagnetics and magnetic resonance sounding (MRS) responses, while the geoelectric responses are both 1D and 2D and the sheet's response models a 3D conductive sheet in a conductive host with an overburden of varying thickness and resistivity. In all cases, the focus is placed on delivering full system forward modelling across all supported types of data. Our implementation is modular, meaning that the bulk of the algorithm is independent of data type, making it easy to add support for new types. Having implemented forward response routines and file I/O for a given data type provides access to a robust and general inversion engine. This engine includes support for mixed data types, arbitrary model parameter constraints, integration of prior information and calculation of both model parameter sensitivity analysis and depth of investigation. We present a review of our implementation and methodology and show four different examples illustrating the versatility of the algorithm. The first example is a laterally constrained joint inversion (LCI) of surface time domain induced polarisation (TDIP) data and borehole TDIP data. The second example shows a spatially constrained inversion (SCI) of airborne transient electromagnetic (AEM) data. The third example is an inversion and sensitivity analysis of MRS data, where the electrical structure is constrained with AEM data. The fourth example is an inversion of AEM data, where the model is described by a 3D sheet in a layered conductive host. [ABSTRACT FROM AUTHOR]