Reduction of Noise in Induced Polarization Data using Full Time-Series Data

The induced polarization (IP) method is an established technique in mining geophysics. One of the major challenges facing mining geophysicists is the ability to differentiate between different lithologies based on geophysical data such as IP data. In this paper, we present a study that focuses on extracting useful information about lithology from the full waveform IP data acquired by Newmont Distributed IP Data Acquisition System (NEWDAS). We first invert the 4D IP data by performing a sequence of 3D inversions. We then propose a new 4D inversion algorithm with time regularization and time weighting function. Once the inversions are done, statistical analysis of these recovered chargeabilities on a regional basis reveals some important differences on how the chargeabilities of different lithologies decay with time, and consequently, helps differentiate between various rock types. We show in this paper that lithology differentiation based on IP data is possible by combining two components: advanced data acquisition system and powerful inversion algorithms.

In this study, we conducted an extensive geophysical survey to explore the potential of electrical resistivity methods in delineating deep ore deposits within between Koillismaa Intrusion and Näränkävaara intrusion, northeastern Finland. Preliminary investigations in 2022, including magnetic, gravity and audio-magnetotelluric (AMT) methods, along with drilling, uncovered significant anomalous structures in the survey area. Subsequent drilling of an exploration well provided positive lithological indications of a ultramafic igneous rock at more than 1.5 km depth, which are very likely of the same age as the layered intrusions in the area. Borehole data indeed revealed that the Archaean basement gneiss extends down to approximately 510 m, underlain by a granite dyke with interspersed thin layers of pyroxenite and peridotite. Notably, peridotite layers around 1500 m depth exhibited distinct magnetic and IP responses in core data.We employed electrical methods at the site, including electrical resistivity tomography (ERT) and induced polarization (IP). To cover a large-scale area, 25 transmitter dipoles, each 1 km long and using three different transmitter systems, were deployed and data were recorded at 119 receiver stations. This work presents the acquisition and preliminary results from the ERT-IP surveys. During the processing of ERT and IP data, we utilized full time-series data recorded across the four lowest main frequencies (from 0.0625 Hz to 8Hz) to capture voltage data in a steady state. Apparent resistivity data were derived from the stacked voltage data, while IP data were initially extracted from these decay curves of these stacked voltage data and subsequently processed in the frequency domain (outphasing). Analysis of the resistivity and IP responses revealed notable IP signals at depths exceeding 1.5 km. Meanwhile, the resistivity data indicated generally very high values, around 10,000 ohm-m, with complex variations observed near the surface. This study demonstrates the efficacy of ERT and IP methods in delineating deep-seated mineral deposits, with the deep-depths IP responses being particularly noteworthy.

Recreational fishing is increasingly recognised as an important source of mortality for marine fish populations. In the United States, estimates of marine recreational catch and effort were recently revised for the time period 1981 and beyond, and for many species, the revised estimates were substantially higher than the original values. Here, the proportion of total landings that came from the recreational sector in the Southeast US Atlantic was quantified. The proportions for 22 oceanic species and for all species combined were computed, using a full time series of landings (1981–2016) and a more recent time series (1999–2016). For the full and recent time series, landings of most species (15/22 and 17/22, respectively) were dominated by the recreational sector. For all species combined, 71% of landings in the full time series were from the recreational sector, and 76% in the recent time series. Trend analysis indicated that most species had a stable or increasing proportion of landings from the recreational sector. In addition, stock assessments were conducted on four species, and the catch revisions increased the estimated scale of abundance and, in some cases, affected stock or fishery status. This work underscores the importance of recreational fishing for marine resource management.

Application of induced polarization imaging across different scales to understand surface and groundwater flow at the Hofermuehle landslide

We analyze the relationship between induced polarization (IP) parameters and the specific surface area normalized to the pore volume (Spor) for an extensive sample database. We find that a single linear imaginary conductivity-Spor relation holds across a range of single-frequency IP data sets composed of sandstones and unconsolidated sediments that lack an appreciable metallic mineral content. We also apply a recent approach defined as Debye decomposition (DD) to determine normalized chargeability (mn), a global estimate of polarization magnitude from available spectral IP (SIP) data sets. A strong linear relationship between mn and Spor is also found across multiple data sets. However, SIP model parameters determined for samples containing metallic minerals are approximately two orders of magnitude greater than for the model parameters estimated for the nonmetallic sample database. We propose a concept of “polarizability of the mineral-fluid interface per unit Spor” to explain this difference, which is supported by the observed dependence of IP parameters on fluid conductivity between sample types. We suggest that this linear IP-Spor relation can be considered the IP equivalent of the classical Archie empirical relation. Whereas the Archie relation describes a power-law relation between electrical conductivity due to electrolytic conduction through the available interconnected pore volume, the IP-Spor relation is an equivalent relation between mineral-fluid interfacial polarization and available pore surface area.

Recent studies have shown that induced polarization (IP) coupled with electrical resistivity surveys can be used for in situ lithological and hydrologic discrimination of the subsurface; yet the driving factors behind the effects of water content dynamics on IP are relatively understudied. We sought to improve the understanding of the relationship of IP on variations in water saturation degree for an undisturbed agricultural soil. Our experiment consisted of collecting IP measurements concurrently with hydraulic data during multistep outflow experiments. We determined the hydraulic properties of the undisturbed soil samples and correlated saturation degree with IP data. Due to an increase in pore fluid conductivity in the column pore water with decreasing saturation degree, we found that imaginary conductivity (σ″) may offer distinct advantages for determining water content over real conductivity (σ′) measurements. Although σ″ exhibits a weaker dependence on saturation degree compared to σ′, the relative insensitivity of σ″ to pore fluid conductivity results in a simpler dependence on saturation change in the presence of varying salinities. As changes in pore fluid conductivity are likely to occur in the field simultaneously with water content variations, we suggest that although IP has mostly been used to discriminate lithology, time lapse IP measurements may additionally provide a robust indicator of changes in saturation degree.

ABSTRACTThe problem of discrimination between a valid induced polarization (IP) response and electromagnetic (EM) coupling effects is considered and an effective solution is provided. First, a finite dimensional approximation to the Cole‐Cole model is investigated. Using the least‐squares approach, the parameters of the approximate model are obtained. Next, based on the analysis of overvoltage, a finite dimensional structure of the IP model is produced. Using this overvoltage‐based structure, a specific finite dimensional approximation of the Cole‐Cole model is proposed. Summarizing the analysis of the finite dimensional IP model, it is concluded that the proposed IP model, which fits the field data much better than the traditional Cole‐Cole model, is essentially an RC‐circuit. From a circuit‐analysis point of view, it is well known that an electromagnetic effect can be described by an RL‐circuit. The simulation results on experimental data support this conception. According to this observation, a new method to discriminate between a valid IP response and EM coupling effects is proposed as follows: (i) use a special finite dimensional model for IP–EM systems; (ii) obtain the parameters for the model using a least‐squares approach; (iii) separate RC‐type terms and RL‐type terms – the first models the IP behaviour, the latter represents the EM part. Simulation on experimental data shows that the method is very simple and effective.

In recent years, several traditional mining exploration methods have been successfully modified for use in the environmental geophysics field. In these cases, "successfully modified" refers primarily to acquiring data fast enough, and therefore economically efficient enough, to accommodate the relatively small budgets that are available in most environmental studies.For example, transient electromagnetics (TEM) methods have been increasingly applied to environmental problems, particularly in unexploded ordnance (UXO), underground storage tank (UST) and utilities detection. Small, in-loop, cart-mounted TEM measurements are excellent for these deep metal detection applications. A major research effort is now underway to use, among other methods, multi-component, multi-time-gate mobile TEM systems (measuring Hx and Hy, as well as the standard Hz) in order to discriminate targets of interest (UXO, for example) from non-UXO objects such as metallic debris.A second good example is the induced polarization (IP) method. Although resistivity has been used extensively in shallow environmental applications, IP data acquisition has always been too slow, and therefore too expensive, for most environmental targets. Multichannel receivers, multiplexers, and laptop computers now allow us to acquire IP data at rates of 2500 to 3000 data points per day (in the dipole-dipole configuration, for example), providing low cost, high density data. IP data have been shown to be particularly useful in delineating buried waste, such as at old landfills. In numerous surveys, resistivity data have provided useful information on buried, back-filled pits and trenches, while IP data have been used to discriminate which of the pits and trenches located with resistivity actually contain waste material.

We have demonstrated that the induced polarization effect in the airborne electromagnetic (AEM) data can be represented well using the generalized effective-medium theory of induced polarization (GEMTIP) model. We have also developed a novel method for 3D inversion of the airborne spectral induced polarization (SIP) data into the volume distribution of the parameters of the GEMTIP model. The results show that the SIP effect can be observed by a typical AEM system. The AEM data collected by the standard systems can be used not only for producing resistivity models of the subsurface formations, but for recovering the chargeability and other GEMTIP model parameters which can be subsequently used for mineral exploration and possibly mineral discrimination.

Mechanistic induced polarization (IP) models describe the relationships between the physical properties of geomaterials and their frequency-dependent complex conductivity. However, practitioners rarely use mechanistic models to interpret the IP data because the uncertainties associated with estimating petrophysical properties from complex conductivity spectra are still poorly understood. We propose a framework for critically assessing any IP model’s sensitivity and parameter estimation limitations. The framework consists of a conditional variational autoencoder (CVAE), an unsupervised Bayesian neural network specializing in data dimension reduction and generative modeling. We apply the framework in a case study of the “perfectly polarized interfacial polarization” model by training the CVAE on the IP signatures of synthetic mixtures of metallic mineral inclusions hosted in electrolyte-filled geomaterials. First, the CVAE’s Jacobian reveals the relative importance of each petrophysical property for generating the spectral IP data. The most critical parameters are the conductivity of the host, the volume fraction of the inclusions, the characteristic length of the inclusions, and the permittivity of the host. Contrastingly, the inclusions’ diffusion coefficient, permittivity, and conductivity, as well as the host’s diffusion coefficient, have marginal importance. A parameter estimation experiment using various model constraints yields the standardized accuracy of petrophysical properties and corroborates the sensitivity analysis results. Finally, we visualize the effects of data transformations and model constraints on the petrophysical parameter space. We conclude that a common logarithm data transformation yields optimal parameter estimation results and that constraining the electrochemical properties of a geomaterial improves the estimates of the size of its metallic inclusions and vice versa.

Hydraulic conductivity estimation from induced polarisation data at the field scale — the Krauthausen case history

In recent decades, shrubs dominated by the genus Caragana have expanded in a large area in Xilin Gol grassland, Inner Mongolia, China. This study comprehensively evaluated the performances of multiple factors for mapping shrub coverage across the Xilin Gol grassland based on the spectral and temporal signatures of Sentinel-2 imagery, and for the first time produced a large-scale shrub coverage mapping result in this region. Considering the regional differences and gradients in the types and sizes of shrub in the study area, the study area was divided into three subregions based on precipitation data, i.e., west, middle and east regions. The shrub coverage estimation accuracy from dry- and wet-year data, different types of vegetation indices (VIs) and multiple regression methods were compared in each subregion, and the key phenological periods were selected. We also compared the accuracy of four mapping strategies, which were pairwise combinations of zoning (i.e., subregions divided by precipitation) and non-zoning, and full time series of VIs and key phenological period. Results show that the mapping accuracy in a dry year (2017) is higher than that in a wet year (2018). The optimal VIs and key phenological periods show high spatial variability. In terms of mapping strategies, the accuracy of zoning is higher than that of non-zoning. The root mean square error (RMSE), overall accuracy (OA) and recall for ‘zoning + full time series (or + key phenological period)’ strategy were 0.052 (0.055), 76.4% (79.7%) and 91.7% (94.6%), respectively, while for ‘non-zoning + full time series (or + key phenological period)’ strategy were 0.057 (0.060), 75.5% (74.6%) and 91.7% (88.6%), respectively. The mapping using VIs in key phenological periods is better than that of using full time series in the low-value prediction of shrub cover. Based on the strategy of ‘zoning + key phenological period’, the shrub coverage map of the whole region was generated with a RMSE of 0.055, OA of 80% and recall of 95%. This study not only provides the first large-scale mapping data of shrub coverage, but also provides reference for shrub dynamic monitoring in this area.

The transport properties of porous rocks and soils are of broad interest to many<br>disciplines. An elusive goal in rock physics has been to develop a method of estimating<br>permeability in-situ, and various models have been developed. These existing models characterize<br>the porous media with parameters including porosity, hydraulic radius, grain packing, tortuosity,<br>specific surface area, fractal surface dimension, grain size and grain size distribution. Induced<br>polarization (IP) measurements are sensitive to many of the same variables associated with<br>hydraulic permeability as well as with the pore fluid chemistry, and may be able to measure the<br>parameters which make up the permeability models.<br>A series of experiments were performed on five different sandstones. Hydraulic<br>permeability and broadband (spectral) induced polarization measurements were made on several<br>sandstone samples both parallel and perpendicular to bedding. lnteresting relationships are shown<br>for the anisotropy data as a function of frequency. Porosity values were also determined for all of<br>the sandstones. Permeability model parameters, including formation factor, porosity, specific<br>surface area and surface fractal dimension were calculated using the IP data. Empirical models<br>which relate the polarization/capacitance of the sample to the grain size, surface fractal dimension<br>and the specific surface area were investigated. The results indicate that the surface fractal<br>dimension is the key component of the model, and that the values determined from our<br>experiments align extremely well with previously published data. Further investigation is being<br>pursued in efforts to determine the fractal dimension solely from electrical measurements.

Two-stage synthesis problems simultaneously consider here-and-now decisions (e.g., optimal investment) and wait-and-see decisions (e.g., optimal operation). The optimal synthesis of energy systems reveals such a two-stage character. The synthesis of energy systems involves multiple large time series such as energy demands and energy prices. Since problem size increases with the size of the time series, synthesis of energy systems leads to complex optimization problems. To reduce the problem size without loosing solution quality, we propose a method for time-series aggregation to identify typical periods. Typical periods retain the chronology of time steps which enables modeling of energy systems, e.g., with storage units or start-up cost. The aim of the proposed method is to obtain few typical periods with few time steps per period, while accurately representing the objective function of the full time series, e.g. cost. Thus, we determine the error of time-series aggregation as the cost difference between operating the optimal design for the aggregated time series and for the full time series. Thereby, we rigorously bound the maximum performance loss of the optimal energy system design. In an initial step, the proposed method identifies the best length of typical periods by autocorrelation analysis. Subsequently, an adaptive procedure determines aggregated typical periods employing the clustering algorithm $k$-medoids which groups similar periods into clusters and selects one representative period per cluster. Moreover, the number of time steps per period is aggregated by a novel clustering algorithm maintaining chronology of the time steps in the periods. The method is iteratively repeated until the error falls below a treshold value. A case study based on a real-world synthesis problem of an energy system shows that time-series aggregation from 8760 time steps to 2 typical periods with each 2 time steps results in an error smaller than the optimality gap of of the synthesis problem (2%). This corresponds to a reduction of the number time steps and thus a reduction of the size of the synthesis problem by a factor of 1000 with excellent accuracy in cost estimation. Thus, the proposed method enables an efficient and accurate synthesis of energy systems.

Our studies have determined that both gradient and dipole-dipole arrays may produce a rather strong electromagnetic (EM) coupling effect under certain conditions. Variations in these apparent effects are closely correlated with changes of surface current density and also influenced by topographic relief. The dipole-dipole array can provide EM coupling anomalies with the same sign and shape as bona fide induced-polarization (IP) anomalies.It has been shown by theoretical calculations and model studies that response curves of frequency effects of EM coupling in logarithmic coordinates have distinctive features of sectional linearization. This can provide a basic method to correct approximately EM coupling. Compared with methods being used inside and outside China, the suggested correction method has the advantage of wide application. This has been already proven by a few field examples.