SM5.2

The hydraulic conductivity (K) is a relevant parameter in soil sciences as it is critical, e.g., for hydrological modeling or the characterization of groundwater flow and atmosphere-soil interactions. Field investigations allow for the direct assessment of K, yet the number and distribution of the sampling points limit the spatial resolution. To assess the spatial variability of K at the field scale, pedotransfer functions (PTFs) have been developed, which estimate K from soil parameters such as soil texture or bulk density. On the other hand, geophysical methods have also revealed their potential to quantify K in laboratory investigations, yet investigations at the field scale are still rare. In this study, we investigate the estimation of K through the simultaneous inversion of seismic and electrical data in an imaging framework. We use an open-source joint inversion framework, and adapt the underlying petrophysical model to take into account the (electrical) surface conductivity during parameter estimation. In particular, we invert resistivity data collected at a low and a high frequency, considering that the associated difference accounts for the (electrical) surface conductivity based on the frequency dependence of the observed electrical response. Accordingly, our joint inversion scheme solves, among other parameters, for water content, cation exchange capacity, polarization and porosity, which we use to quantify K through different models developed from laboratory investigations. Moreover, we investigate the possibility to enhance the quantification of K by adapting the joint inversion scheme to solve directly for the parameters required by the employed models. We illustrate our approach based on data collected at the Hydrological Open Air Laboratory (HOAL), a thoroughly investigated and monitored catchment located in Petzenkirchen (Lower Austria). We use available information about soil properties to calibrate our joint inversion scheme and evaluate the resolved K models based on K values obtained through direct investigations or the use of PTFs, respectively. Our approach contributes to the field-scale estimation of process-relevant subsurface properties at high spatial resolution by means of non-invasive geophysical imaging techniques – a key objective of the hydrogeophysical discipline.

How to cite: Steiner, M., Pavlin, L., Katona, T., Wagner, F. M., Roser, N., Strauss, P., Blöschl, G., and Flores Orozco, A.: Imaging of hydraulic conductivity from seismic and electrical data in a joint inversion framework, EGU General Assembly 2022, Vienna, Austria, 23–27 May 2022, EGU22-9493, https://doi.org/10.5194/egusphere-egu22-9493, 2022.

The rapid climatic changes and their impact in the regions where unique environmental balance is not polluted by human existence are strongly visible. One of those places, exposed to Arctic amplification, is the newly deglaciated areas of Southern Spitsbergen. One of the most important scientific aspects is understanding their response to climate and environmental changes. To do that, an extensive geophysical approach is required integrating results from multiple imaging techniques. To derive spatial information from complex geomorphological terrain, joint interpretation of three non-intrusive geophysical methods were applied: Electrical Resistivity Tomography, Ground Penetrating Radar, and time-lapse Seismic Tomography. These were used to identify subsurface structures in the forefield of the retreating Hansbreen glacier in SW Spitsbergen, Svalbard. As a result, the authors distinguish three main zones, with different responses to the freezing-thawing effect: outwash plain, terminal moraine at the last glacial maximum, and glacial forefield proximal to the glacier front. The obtained data allowed for differentiation between geological and periglacial structures, and seasonally changing effects. The estimation of the impact of the freezing-thawing effect based on the VP velocity change reveals, that changes are deeper than previously believed reaching down to 30 metres of flat terrain and even deeper to 40 metres at the slope area with the strong subsurface flow. The study provides a unique snapshot of the current situation on the forefield of retreating Hansbreen concerning the current climate state.

This research was funded by National Science Centre, Poland (NCN) Grant UMO-2016/21/B/ST10/02509 and, Poland (NCN) Grant 2020/37/N/ST10/01486.

How to cite: Majdański, M., Dobiński, W., Marciniak, A., Osuch, M., Wawrzyniak, T., Owoc, B., and Glazer, M.: The effect of subsurface freezing-thawing in the SW Svalbard on the newly deglaciated areas, EGU General Assembly 2022, Vienna, Austria, 23–27 May 2022, EGU22-2292, https://doi.org/10.5194/egusphere-egu22-2292, 2022.

Engineering-geophysical tasks in urban environments pose significant challenges for both the collection and interpretation of geophysical data. Typical problems that arise consist of background noise affecting seismic methods (i.e., moving cars or pedestrians), electromagnetic fields due to power lines and other infrastructure distorting electrical and electromagnetic methods and even traffic itself, requiring a thorough planning of fieldwork in order to minimize interruptions. To mitigate such limitations, commonly a combination of several geophysical methods is applied to counterbalance the caused distortions by a careful analysis of the data and combined modelling of the available information. Following this notion, we present a case study conducted in an urban setting in the first district of Vienna, a busy place in terms of both traffic and number of pedestrians. The objective was to delineate possible infiltration pathways of surface water or shallow subsurface water, infiltrating into an ancient cellar complex with a delay of two days after rainfall. The geophysical imaging included seismic refraction (RST) and multichannel analysis of surface waves (MASW), complex conductivity imaging (CCI) and ground-penetrating radar (GPR) measurements to characterize the subsurface architecture below the street (i.e., above the cellar) and CCI and GPR from within the cellar along the outer wall (i.e., below the street). Based on a combined analysis of the datasets from the street and the cellar itself, and incorporating 3D information from LiDAR within the cellar, we propose a model of infiltration pathways, as well as zones in the cellar wall possibly already strongly weakened by continuous high soil moisture.

How to cite: Gallistl, J., Bano, G., and Schlögel, I.: Detecting infiltration pathways by means of multi-method geophysical interpretation: an urban case study, EGU General Assembly 2022, Vienna, Austria, 23–27 May 2022, EGU22-6851, https://doi.org/10.5194/egusphere-egu22-6851, 2022.

The main objective of this study is to understand salt dynamics in the soda lakes of the Austrian National Park Neusiedlersee Seewinkel and the influence of climate change in these dynamics. To achieve this, we investigated the application of electrical and electromagnetical methods to quantify spatial and temporal variations in the salt and water content. Built on the link between electrical conductivity and salt content, we mainly present results obtained with low induction number electromagnetic (EMI). EMI data were collected with the CMD Explorer and CMD Mini Explorer (from GF Instruments). Our investigations present, on the one hand, mapping of four lakes, each related to a different degree of degradation, with the aim of understanding the general patterns of electrical conductivity and their link to vegetation and surface cover. On the other hand, we conducted measurements at different time-lapses to monitor changes in the electrical conductivity along three profiles. The monitoring datasets combined EMI and time-domain induced polarization (TDIP) imaging and were repeated every two weeks between April and October 2021 near the Wörthenlacken. Monitoring measurements were conducted with both horizontal and vertical coplanar configurations with 3 separate receiver coils, for a total of 12 measurements for each point with a maximal nominal depth up to 6.7 m. Mapping measurements were collected only with horizontal configurations with both instruments, for six measurements with the same nominal depth of investigation. The initial analysis of the raw data demonstrates changes in the electrical conductivity related to changes in vegetation. In a second step, we inverted the EMI data using the open-source application EMagPy to resolve vertical variations of electrical conductivity along the monitoring profiles. Based on these results we evaluated the variation in electrical conductivity and potential salinity accompanying seasonal variations. Our interpretation incorporates non-geophysical data (temperature, water level, and precipitation) collected in observation wells near the study area. Moreover, we compared EMI monitoring results with those obtained from the inversion of TDIP datasets.

How to cite: Hettegger, A., Aigner, L., Armas, M. A., Moser, C., Cimadom, A., and Flores-Orozco, A.: Application of electrical and electromagnetic methods to delineate changes in salt content of soda lakes, EGU General Assembly 2022, Vienna, Austria, 23–27 May 2022, EGU22-5554, https://doi.org/10.5194/egusphere-egu22-5554, 2022.

For the detection of contaminated zones based on geophysical surveys, we make numerical experiments since it is not easy to make or maintain contaminated test-beds for field surveys. In the numerical experiments, we numerically simulate and analyze the responses of geophysical surveys including electrical resistivity tomography (ERT), induced polarization (IP) and ground penetrating radar (GPR), for numerical models, each of which was constructed based on the results of field geophysical survey obtained from contaminated site. ERT, which can image electrical resistivity of subsurface, is one of the most common geophysical tools, while IP survey can provide additional electrical information of the subsurface. Besides GPR can suggest the structure of geology.

For each model, whose geological structure was composed as similar to that of the corresponding field-survey site, we first numerically simulated corresponding field surveys performed in the site and compare with field data to verify the properness of the model. For the verified models we performed numerical simulation of geophysical surveys about various scenario of contaminations (e.g., oil pollution, leachate, heavy metal, etc.), and analyzed resulting responses in order to make strategies for the detection of contaminated zones bases on geophysical surveys. Further, we considered time-lapse geophysical surveys for changing contamination scenarios with respect to time. In the case of models including clay media, the responses of IP were remarkable useful in locating the clay media when compared ERT-only survey.

This work was supported by the Energy Efficiency & Resources of the Korea Institute of Energy Technology Evaluation and Planning (KETEP) granted financial resource from the Ministry of Trade, Industry & Energy, Republic of Korea (No. 20194010201920) and Korea Ministry of Environment as "The SEM projects; 2018002440005"

How to cite: Yu, H., Kim, B., Cho, A., Joung, I. S., Jeong, J., Jang, H., Jang, S., and Nam, M. J.: Comparative analyses on geophysical survey responses for various numerical models constructed based on field data, EGU General Assembly 2022, Vienna, Austria, 23–27 May 2022, EGU22-10826, https://doi.org/10.5194/egusphere-egu22-10826, 2022.

Proper characterization of geologic structures that host geothermal systems is crucial for the efficiency and safety of their energy production. This includes estimating layer boundaries, complex geologic features, and lithology through means of inversion and its regularization. However, existing advanced regularization techniques (e.g., geostatistical regularization, minimum-gradient support, etc.) fail to capture the complexity of 3D geological models including fault networks, fault–surface interactions, unconformities, and dome structures. Förderer et al (2021) propose a solution by means of structure-based inversion, which implements implicit geological modeling and low-dimensional parametrization to produce sharp subsurface interfaces in 2D. This work aims to extend their approach to image realistic and complex geometries in 3D. We continue with the example of electrical resistivity tomography (ERT) and synthetic data; however, this approach is aimed towards independent and joint inversion of geophysical methods that are commonly used in geothermal exploration such as magnetotellurics, gravity, and seismic techniques.

The 3D geological model is created using GemPy, an open-source Python library, which constructs a structural geological model from interface points and orientations using an implicit approach based on co-kriging (de la Varga et al., 2019). Subsequently, the 3D model is discretized, and physical parameters are assigned using minimal pilot points that are then interpolated. We use pyGIMLi (Rücker et al., 2017), another open-source multi-method library for geophysical modelling and inversion, to perform a structure-based inversion, where we include the interface points in the primary model vector of the inversion to update these points iteratively to estimate a geological model in agreement with the geophysical observations.

In this work, special focus is placed on the sensitivity of each model parameter. To maintain low parametrization and account for the increase in computational power, the cumulative sensitivity is calculated and tested under criteria to optimize the model updates. This is relevant for geometries where the interface and pilot points are more influential in one dimension than others. The workflow has also been adapted to include more complex structures that can be defined in 3D, especially those that reflect geothermal systems. This work is part of the Innovative Training Network EASYGO (www.easygo-itn.eu), which aims to improve the efficiency and safety of geothermal operations but can be readily used in other applications.

References:

Förderer, A., Wellmann, F., and Wagner, F.: Geoelectrical imaging of subsurface discontinuities and heterogeneities using low-dimensional parameterizations, EGU General Assembly 2021, online, 19–30 Apr 2021, EGU21-10012, https://doi.org/10.5194/egusphere-egu21-10012, 2021.

de la Varga, M., Schaaf, A., and Wellmann, F., 2019. GemPy 1.0: open-source stochastic geological modeling and inversion, Geosci. Model Dev., 12, 1–32, doi:10.5194/gmd-12-1-2019.

Rücker, C., Günther, T., Wagner, F.M., 2017. pyGIMLi: An open-source library for modelling and inversion in geophysics, Computers and Geosciences, 109, 106-123, doi: 10.1016/j.cageo.2017.07.011.

How to cite: Balza Morales, A., Maurer, H., Wellmann, F., and Wagner, F. M.: Towards structure-based joint geological-geophysical inversion for improved characterization of geothermal reservoirs, EGU General Assembly 2022, Vienna, Austria, 23–27 May 2022, EGU22-8876, https://doi.org/10.5194/egusphere-egu22-8876, 2022.

There are two main drivers to integrate former metallurgical residues or mine waste into the circular economy through an efficient resource recovery. First, the economic driver, which considers land and resource recovery of high value elements such as critical raw materials. Secondly, the environmental and human health driver, as these types of residues might be a potential source of pollution. In both scenarios, there is a need to improve the characterization of past metallurgical sites and to locate and quantify materials of interest. To this aim, mostly geoelectric methods applied in the laboratory and/or in the field have been used and they are often complemented with geochemical or mineralogical studies. In this contribution, we present an approach that integrates a 3D Electrical Resistivity Tomography (ERT) and Induced Polarization (IP) acquisition in the field, lab measurements of ERT, IP and Spectral Induced Polarization (SIP) in several samples together with chemical analysis, to predict the metallic content in a slag heap from a former iron and steel factory located in Belgium. The samples were collected at locations targeting the observed geophysical anomalies. We first look for correlations between geophysical lab measurements and the chemical analysis to identify the variables which could potentially have a larger impact or control in the metallic content. Second, we use the geophysical lab measurements to improve the deterministic constrained inversion carried out for the 3D field data. Third, we use a supervised learning algorithm - Gaussian Process Classification (GPC)- to predict the metallic content of the slag heap from the 3D inverted resistivity/chargeability model. Overall, we found that variations in the chargeability are correlated with changes in iron, calcium and silicon content. Additionally, the GPC represents a suitable algorithm to integrate the uncertainty in the prediction results as well as the uncertainty that arises from the direct comparison of field and lab data. Finally, this methodology which integrates geophysical field data, targeted sampling, lab measurements and supervised learning can be applied in broader contexts where such data are available.

How to cite: Isunza Manrique, I., Caterina, D., Dumont, M., and Nguyen, F.: Integrated Approach to Identify Variables for the Prediction of Metallic Content in a Slag Heap using Time-Domain ERT and SIP Laboratory Measurements, EGU General Assembly 2022, Vienna, Austria, 23–27 May 2022, EGU22-10857, https://doi.org/10.5194/egusphere-egu22-10857, 2022.

Fault zone head waves (FZHWs) generated by bimaterial interfaces are the first arriving seismic phases at near-fault stations on the slower side of the fault. Since FZHWs spend almost their entire path along the fault interface, imaging methods based on these phases can provide high-resolution information on fault structure at seismogenic depths. In Eastern Taiwan, many past catastrophic earthquakes highlight the need for an improved understanding of fault characteristics and mechanical properties in this tectonically active environment. Here we use FZHWs to examine the northern segment of the Longitudinal Valley (LV) fault system, a suture zone between the Eurasian Plate and the Philippine Sea plate. We focus on 44 stations within a 70 km by 28 km area located along the northern segment of the LV fault system and ~8800 small-to-moderate earthquake seismograms recorded between 2012 and 2018 by those stations. We apply a set of algorithms developed by Ross and Ben-Zion to automatically detect and pick direct P waves, S waves and potential head waves contained in the seismograms. We augment the detection using finite-difference simulations to study the effect of varying source mechanisms on the first motion polarity characteristics of the P wave and FZHW. The results indicate that head waves will be generated not only by a clean strike-slip fault but by a wider range of focal mechanisms. We discuss 414 robustly detected head waves excited by 204 events that are located within a thin volume along the west-dipping Central Range fault, which now suggests—for the first time—the existence of a consistent velocity contrast across that fault segment. We apply particle motion, polarization, and moveout analyses to confirm the robustness of our FZHW phase picks obtained with the automatic method. Most particle motion and polarization results show that the azimuths calculated from windows containing direct P waves do not consistently point to the epicentres. This variability in horizontal particle motion is likely associated with the complex structure beneath the receivers and changes in topography. To the first order, the moveout pattern of the P wave to FZHW time difference is constant. This indicates a shallow bimaterial interface along the fault that affects the wavefield near or below the stations. We fit the moveout and constant arrivals with two models to the differential P and head wave arrival times to explore possible local variations of the generally constant trend. The Akaike Information Criterion applied to the constant and the sloping moveout pattern suggests spatially complex significant results that together with the depth distribution of the involved events indicate a deeper-reaching bimaterial interface. For these configurations, the obtained average velocity contrast ranges from 0.75 to ~3 per cent.

How to cite: Lin, T.-C., Hillers, G., Lee, S.-J., and Hung, S.-H.: Seismic Velocity Contrast Along the Longitudinal Valley Fault System, Taiwan, from Analysis of Fault Zone Head Waves and Direct P Arrivals, EGU General Assembly 2022, Vienna, Austria, 23–27 May 2022, EGU22-8695, https://doi.org/10.5194/egusphere-egu22-8695, 2022.

Surface waves propagating from earthquakes, active sources or within the ambient noise wavefield are widely used to image Earth structure at various scales, from centimetres to hundreds of kilometres. The accuracy of surface-wave, phase-velocity measurements is essential for the accuracy of the Earth models they constrain. Here, we identify a finite-frequency phase shift in the phase travel time that causes systematic errors in time-domain, phase-velocity measurements. The phase shift arises from the approximation of monochromatic surface waves with narrow-band filtered surface waves. We derive an explicit formula of the finite-frequency phase shift and present a numerical method for its evaluation and for the correction of the measurements. Applications to high-frequency and long-period examples show that the phase shift is typically around π/60-π/16 for the common settings of ambient-noise imaging studies, which translates to 0.2-0.8% phase-velocity measurement errors. The finite-frequency phase shift depends on the (1) second derivative of the wavenumber with respect to frequency; (2) width of the narrow-band filter; (3) epicentral or interstation distance; (4) centre frequency of the filter. In conversion to phase velocity, the last two factors cancel out. Frequency-domain methods for phase-velocity measurements have the advantage of not producing the finite-frequency phase shift. Both time- and frequency-domain measurements, however, can be impacted by a break-down of the far-field approximation (near-field phase shift), which our calculations also show. Our method offers an effective means of improving the accuracy of the widely used time-domain, phase-velocity measurements via the evaluation of and corrections for the finite-frequency phase shift.

How to cite: Xu, Y., Lebedev, S., and Meier, T.: Improving the accuracy of time-domain surface-wave measurements: evaluation and correction of the finite-frequency phase shift, EGU General Assembly 2022, Vienna, Austria, 23–27 May 2022, EGU22-5753, https://doi.org/10.5194/egusphere-egu22-5753, 2022.

Charbaoui A.^(1*), Jaffal M.^(1,2), Kchikach A.^(1,2), Eljabbar B.⁽¹⁾, Bodinier J,L.^(1,3), Rochdane S.⁽¹⁾, Khadiri O.⁽⁴⁾, Jourani E.⁽⁴⁾

(1) Mohammed VI Polytechnic University, Geology and Sustainable Mining (GSM), Benguerir, Morocco

(2) Cadi Ayyad University, Georessources, Geoenvironment & Civil Engineering Laboratory, Marrakech, Morocco

(3) University of Montpellier & CNRS, Geosciences Montpellier, Montpellier, France.

(4) OCP Group, Casablanca, Morocco

*Email: anas.charbaoui@um6p.ma

Abstract

Seismic reflection is extensively used in petroleum exploration because it is recognized as an excellent tool of geological imaging, especially for sedimentary basins. In recent years, a variant of this method, namely the high-resolution seismic reflection (HRS) has experienced a rapid development due its implementation in many shallow geophysical investigations including studies in geotechnics, hydrogeology, structural geology, seismic hazard estimation, etc. This method can provide continuous coverage of the underground in two-dimensional 2-D, as well as in three-dimensional 3-D spaces. The HRS method has a lot of successful applications in shallow underground prospecting for various purposes (Tallini et al. 2020, Ahokangas et al. 2020).

The present project is concerned with the study of the Bahira basin, which hosts some of the most important phosphate deposits of Morocco. Its main objective is to provide a detailed seismic imaging of the phosphatic series, particularly in the area where it is hidden by a plio-quaternary cover. The Bahira phosphatic series is made of a Maastrichtian to Ypresian regular intercalation of phosphate beds and sterile layers.

The studies planned in order to reach this objective include first and foremost, the knowledge of the different terms of phosphatic series through (i) the analysis the available boreholes data, so as to gather information about the thickness of the layers, their lithological lateral change, etc., and (ii) the measurement of the rock properties necessary for the seismic modelling. The next step is to carry out numerical simulations that would help establish the expected seismic response of the phosphatic series. This also would aid to determine the appropriate parameters of the subsequent data acquisition. The third step is to perform HRS survey on the areas of interest. This will includes 2D surface seismic profiling and borehole vertical profiling (VSP). The projected studies also include performing measurements of Electrical Resistivity Tomography along the same survey profiles as the HRS. This would help realize a joint inversion of the two type of data and contribute to a better understanding the phosphatic series deep structure.

References:

[1] Tallini M., Spadi M., Cosentino D., Nocentini M., Cavuoto G., Di Fiore V., 2020. High-resolution seismic reflection exploration for evaluating the seismic hazard in a Plio-Quaternary intermontane basin (L'Aquila downtown, central Italy). Quaternary Iternational (In press)

[2] Ahokangas E., Mäkinen J., Artimo A., Pasanen A., Vanhala H., 2020. Reflection method with landstreamer in SW Finland, Journal of Applied Geophysics 177, 104014

Keywords: Phosphatic series, high-resolution seismic imaging, numerical simulations, Joint inversion, Bahira basin, Morocco.

How to cite: charbaoui, A.: High-resolution seismic investigation in phosphate mining, EGU General Assembly 2022, Vienna, Austria, 23–27 May 2022, EGU22-154, https://doi.org/10.5194/egusphere-egu22-154, 2022.

Preceding the seismic modelling of Campo de Dalías sedimentary basin by single-station ambient noise measurements, research focused on the reliability of the methodology employed, namely the microtremor horizontal-to-vertical spectral ratio (MHVSR), is conducted. It is known that MHVSR may present some dependence on weather and site-specific conditions as topographic effects, anthropogenic activities or the variability in the microtremor source distribution. In this context, the stationarity of MHVSR curves with their fundamental peaks below 1 Hz is studied after the installation of three long-term stations in rural sites and another one for a week in the urban area of El Ejido town.

The robustness of the MHVSR methodology is often assured by looking into the stationarity of mainly two peak parameters: frequency and amplitude. In this study, two new parameters are tested: the peak-width and the trough frequency. We have up to two years of microtremor and weather data that helped to track the variability of wind speed, atmospheric pressure, and temperature, as well as sea tide and aquifer levels compared to the peak shape of MHVSR curves.

Most weather variables only show short or punctual correlations with MHVSR parameters, which is the case of wind gusts above 10 m/s that totally blurred the MHVSR peak-shape for periods of a few days in the more poorly isolated station. The wind-speed time series collected in Campo de Dalías show high correlations with the total microtremor energy in the frequency band of secondary microseisms (0.3 - 1 Hz) with a clear seasonal behaviour. However, the MHVSR peaks studied in that band are uncorrelated with them. Our results show that the piezometric level maintains a moderate to high correlation with MHVSR peak-variability during a time span of 9 months. Campo de Dalías hosts a system of karst aquifers, which constitutes the main water supply for this semi-arid region. Modelling the groundwater flow in that kind of aquifers is a challenging field of research and monitoring it by means of investigation wells has a high cost. The results observed in this study widen the possibilities of MHVSR for being an aquifer-monitoring tool on time scales as short as a few days.

How to cite: García-Jerez, A., Seivane, H., Navarro, M., and Molina, L.: Capabilities for Aquifer Monitoring of long-term MHVSR Observations in Campo de Dalías (Almería, SE Spain), EGU General Assembly 2022, Vienna, Austria, 23–27 May 2022, EGU22-10210, https://doi.org/10.5194/egusphere-egu22-10210, 2022.

The densely populated Bangladesh occupies most of the part of the Bengal Basin; the basin is located just above the subduction margin extended with an N-S alignment between the Indian and the Burmese Plates. The subduction tectonics along this Indo-Burmese plate boundary has put this locality to high seismic risk, which is also supported by the historical earthquake records. Moreover, being in the foothill of the Himalayan Mountains and the Indo-Burmese Ranges, respectively, to the North and the East, this country has become extremely riverine to be filled by sediments. Soft sedimentary layers over geophysical bedrock, with shear-wave velocity, V_S > 760 m/s, can significantly amplify earthquake ground motion to cause damage to infrastructure. In addition, bedrock depth significantly controls the phenomena of soil-infrastructure vibration resonance. That is why, for seismic risk evaluation, it is essential to have adequate information on soft sediment thickness or depth to the sediment-bedrock interface.

The continuously subsiding Sylhet Basin (SB, Zone 1), being a sub-basin within the northern limit of the Bengal Basin, is the flexural depocenter in the northeastern Bangladesh with possibly the thickest (~ 25 km) sedimentary successions (Bürgi et. al. 2021). The active Dauki Fault demarcates the northern limit of the Sylhet Basin as well as the Bengal basin, along which the Shillong Plateau has been uplifted.

In this work, we present V_S velocity up to 3000 m beneath three seismic stations in the Sylhet Basin, namely JAML, SUST and JAFL, data of which are available in the Incorporated Research Institutes for Seismology (IRIS) website. Here, subsurface V_S profile is estimated by inversion of single-station horizontal-to-vertical (H/V) spectral ratio curve within 0.2 to 10 Hz. The H/V curves at three stations are obtained from 15 days continuous recordings of seismic ambient noise data. We use HV-Inv software (García-Jerez et. al. 2016) for the inversion, in which the H/V ratio is interpreted under the diffuse filed assumption (Sánchez-Sesma et. al. 2011) for full H/V inversion considering contribution from the full noise wavefield. The inversion process is constrained using the existing general lithological information as well as unpublishable V_P data from active seismic surveys of Bangladesh Petroleum Exploration Company Ltd. (BAPEX).

From this analysis, we find that geophysical bedrock depth is approximately at 180 m, 220 m and 160 m, respectively, below the stations JAML, SUST and JAFL. To the best of our knowledge, neither the current approach of V_S estimation was applied nor such high-resolution V_Sinformation of sedimentary successions was reported in the study area previously. The presented velocity information could be crucial for engineering development, seismic hazard mitigation, and exploration purpose in the Sylhet Basin. 

How to cite: Farazi, A. H., Hossain, Md. S., and Ito, Y.: Shear wave velocity estimation in the Sylhet Basin, Bangladesh by H/V analysis: implication for geophysical bedrock depth, EGU General Assembly 2022, Vienna, Austria, 23–27 May 2022, EGU22-905, https://doi.org/10.5194/egusphere-egu22-905, 2022.

This work allowed us to estimate the space-time variations of the apparent resistivity (AR) at the USME station of the Red Sismológica de la Universidad Nacional de Colombia (RSUNAL), located in the center of Colombia at the Eastern Cordillera, and correlate these changes with seismic activity within a radius of 500 km to the station.

This project used recorded time series of the natural earth’s electric and magnetic field, processed its data with a computational algorithm of our own (which follows the magnetotelluric (MT) method’s fundamentals), and yielded positive results for the 6.1 Mw earthquake of December 24th, 2019 in Mesetas (Meta - Colombia) with some anomalies registered 8 hours before the mainshock. Although there is just one abnormal behavior for 1 of 5 study cases, it is seen in a good way a possible relation between the magnitude of the event and the AR anomaly as an input to the study of seismic precursors.

How to cite: Gómez Camacho, J. S., Gómez Rodriguez, J. J., and Vargas Jiménez, C. A.: Temporal variation estimates of apparent resistivities associated with occurrence of seismic activity around Bogotá - Colombia using MT records from the RSUNAL seismic network, EGU General Assembly 2022, Vienna, Austria, 23–27 May 2022, EGU22-10854, https://doi.org/10.5194/egusphere-egu22-10854, 2022.

In (time-domain) Electromagnetic Induction (EMI) surveys, an image of the electrical conductivity of the subsurface is obtained non-invasively. The electrical conductivity serves as a proxy for salinity via petrophysical laws. The advantage of geophysical EMI surveys is their cost-effectiveness because it is a non-contacting method, one can easily walk with the device or mount it on a vehicle or a helicopter (AEM).

An accurate interpretation of the data is computationally expensive as it requires a full 3D simulation of the induced electric currents embedded within an iterative and ill-posed inverse problem. Therefore, this forward model is usually approximated with an 1D forward model which only considers horizontal layers, for which fast analytical forward models exist. Quasi-2/3D inversion allows for lateral variation in the subsurface models, but uses those 1D forward models to generate the data. The final inversion model usually fits the (potentially intrinsic 2/3D) data well up to noise level. But what with the discrepancy between the 1D and 2D data? The biased modelling error, introduced by using a 1D forward model in a 3D problem, is difficult to estimate. Does the inversion model that fits the data via 1D model also fit the data via a 3D model? This question has already been addressed in the literature about fault detection, but in a saltwater intrusion context, the lateral variation is expected to be much smoother. And the question remains to what extent multidimensional modelling is crucial.

The time-domain AEM field data from the salinization map of the region of Flanders, Belgium is used as the case study (Flanders environment agency published the map in 2019). A specific flight line is selected for which validation data is available that shows a 2D (lateral) variation. Both results from the quasi-2D and stitched inversion with a traditional smoothing regularization is presented. An accurate 3D forward modelling is performed on both inversion models via the SimPEG package. The results of the simulations are compared with the actual field data and help us to answer the question of whether multidimensional modelling is crucial in geophysical inversion at the AEM scales and a saltwater intrusion context.

How to cite: Deleersnyder, W., Hermans, T., and Dudal, D.: Multidimensional forward modelling of EM induction data within a salinization context – is it worth the extra cost?, EGU General Assembly 2022, Vienna, Austria, 23–27 May 2022, EGU22-657, https://doi.org/10.5194/egusphere-egu22-657, 2022.

GPR data sometimes present subsampling problems that prevent an effective study about the existence of buried structures in an archaeological site. This is a frequent problem, related with the profile spacing used in the survey, when this is performed in parallel profiles to construct a 3D dataset. This difficulty can be lessened by decreasing the profile spacing, but that increases the survey time, or can be experimented in the data processing. INT-FFT algorithm is GPR data densification approach, complementary to the other standard operations, that allows to reconstruct missing data from the combined use of mathematical transforms and predictive filters. To calculate the missing signal, two requirements must be checked: (1) the data in the frequency domain must be limited in a range of values; and (2) must be able to be represented by a distribution of Fourier coefficients. Both conditions are verified in GPR data. Based on seismic trace interpolation, INT-FFT algorithm uses an open access routine (Suinterp, from Seismic Unix package) to interpolate the GPR profiles, that makes use of automatic event identification routines, through the calculation of spatial derivatives, to identify discontinuities in space from the detection very subtle changes in the signal, thus allowing for more efficient interpolation without artifacts or signal deterioration. The approach was successfully tested using GPR datasets from the archaeological site of Roman Villa of Horta da Torre (Fronteira, Portugal). The results show that there was an increase of the geometric sharpness of the GPR planimetry and has not produced any numerical artefacts. The tests performed to apply the methodology to GPR-3D data allowed to assess the interpolation efficiency, the level of recovery of missing data and the level of information lost when one chooses to increase the distance between profiles in the acquisition stage of the data.

Acknowledgment: The work was supported by the Portuguese Foundation for Science and Technology (FCT) project UIDB/04683/2020 - ICT (Institute of Earth Sciences) and by the INTERREG 2014-2020 Program, through the "Innovación abierta e inteligente en la EUROACE" Project, with the reference 0049_INNOACE_4_E.

How to cite: Oliveira, R. J., Caldeira, B., Teixidó, T., and Borges, J. F.: Interpolation of GPR profiles (in 3D datasets) through Fourier Interpolation. Application to the case study of Roman Villa of Horta da Torre (Fronteira, Portugal), EGU General Assembly 2022, Vienna, Austria, 23–27 May 2022, EGU22-4241, https://doi.org/10.5194/egusphere-egu22-4241, 2022.

Investigating soil, roots and their interaction is important to optimize agricultural practices like irrigation and fertilization and therefore increase the sustainability and productivity of crop production. In this study, we are combining two methods to examine non-invasively, characterize and monitor the soil-root zone throughout crop growing seasons: crosshole ground penetrating radar (GPR) and root-images within horizontal mini-rhizotrons. Over three maize crop growing seasons, we acquired in-situ time-lapse crosshole ground penetrating radar data and time-lapse root images, at two mini-rhizotron facilities in Selhausen, Germany. These facilities allow to horizontally measure data at six different depths, ranging between 0.1 m - 1.2 m and below three different plots with varying agricultural treatments, such as irrigation, sowing density, sowing date and cultivars. The GPR measurements result in the dielectric permittivity slices by applying standard ray-based analysis to zero-offset measurements along a pair of rhizotubes. Such horizontal permittivity slices can be linked to soil water content using petro‑physical relationships. Additionally, the root images provide a root fraction per image, which is derived by using a workflow combining state-of-the-art software tools, deep neural networks and automated feature extraction. The dielectric permittivity slices suggest a permittivity variation along the horizontal and vertical axes, depending on atmospheric conditions, soil properties, and root architecture. To quantify the influence of the roots on the spatial and temporal distribution of dielectric permittivity, we used statistical methods to reduce the impacting factors like soil heterogeneity, tube deviations and changing atmospheric conditions, which results in the spatial and temporal variability. For verification these permittivity variabilities are compared to the root fraction values. In general, using the spatial and temporal permittivity variations, we can detect the presence of roots and additionally recognize a varying influence of the roots over the duration of the crop growing season. Using these first results, we demonstrate that GPR can be applied to improve the characterization of the root-soil system related to maize plants. This could be the first step towards developing proxies e.g. for irrigation and fertilization applications using this non-invasive method.

How to cite: Lärm, L., Bauer, F., van der Kruk, J., Vanderborght, J., Vereecken, H., Schnepf, A., and Klotzsche, A.: Estimating the effect of maize crops on time-lapse horizontal crosshole GPR data, EGU General Assembly 2022, Vienna, Austria, 23–27 May 2022, EGU22-9632, https://doi.org/10.5194/egusphere-egu22-9632, 2022.

In both seismic and electromagnetic imaging the diffracted wavefield has gained importance in recent years. While seismic data is often acquired for a large range of different source-receiver offsets, ground-penetrating radar (GPR) acquisitions are mostly (near-) zero-offset. This characteristic inhibits the use of reflected waves for the estimation of depth velocities, which in turn increases the importance of a reliable imaging and characterization of the diffracted wavefield. In this study, we adapt a coherence-based workflow originally designed for seismic wavefields to ground-penetrating radar (GPR) data, which often exhibit similar wave propagation phenomena. The first step of the proposed workflow is the coherence-based imaging of the often predominant reflected wavefield, which in the second step is adaptively subtracted from the original data, resulting in an approximation of the diffracted wavefield. In the third step, we characterize the previously revealed diffracted wavefield by means of wavefront attributes, namely slopes and curvatures. In the fourth and final step, these wavefront attributes can be used for the estimation of depth velocities by means of wavefront tomography, an inversion scheme that provides both the localization of scatterers and a smooth velocity model of the subsurface. We demonstrate the wide applicability of the suggested workflow on two GPR field data examples provided by the USGS – one recorded in the aftermath of Hurricane Sandy on the shores of Long Beach Island, New Jersey, the other capturing the internal structure of Wolverine Glacier, Alaska.

How to cite: Bauer, A., Schwarz, B., and Gajewski, D.: Coherence-based GPR diffraction imaging and inversion, EGU General Assembly 2022, Vienna, Austria, 23–27 May 2022, EGU22-5953, https://doi.org/10.5194/egusphere-egu22-5953, 2022.

Subsurface cavities are mainly responsible for ground subsidence in and around coal mines. There is need to use an advanced high-resolution three-dimensional (3D) Electrical Resistivity Tomography (ERT) technique to detect anomalies and map subsurface precisely. The present study demonstrated the numerical evaluation of 2D and 3D-ERT for air-filled and water-filled cavities. Models simulated with reasonable resistivity values for voids and formations by considering bord and pillar mining environments in multilayer earth. Wenner, Wenner-Schlumberger, and Dipole-dipole arrays incorporated with and without a barrier to getting the best possible output. We used the Res2dinv and Res3dinv programs for data processing. 3D Dipole-dipole inverted geo-electrical section better showed the subsurface cavities signature than the results obtained from other applied arrays. The sensitivity section corresponding to used electrode configurations gives a more detailed picture of the subsurface for better interpretation. The 3D volume of the subsurface overcomes the limitations of 2D ERT to detect cavities within the coal seam.

How to cite: Rupesh, R., Tiwari, P., and Sharma, S. P.: Numerical study of 2D & 3D ERT with sensitivity analysis for subsidence in the coal mining area, EGU General Assembly 2022, Vienna, Austria, 23–27 May 2022, EGU22-10871, https://doi.org/10.5194/egusphere-egu22-10871, 2022.

Induced polarization (IP) methods can be classified into time domain IP (TDIP), complex resistivity (CR), and Spectral IP (SIP) surveys based on measurement method. In field surveys, TDIP measurements are the most widely performed thanks to the easier and less time-consuming acquisition than SIP. In the meantime, SIP measurements are preferred over TDIP for the analysis on dispersion characteristics of CRs of cores in laboratory experiments based on Cole-Cole parameters. Theoretically, the dispersion characteristics should be common in SIP and TDIP measurements if the nature of used sources in both measurements is the same. However, in real situations, ranges of time and frequency are limited due to limitations of equipment resulting in dissimilarities between SIP and TDIP. Despite the dissimilarities, it is attempted to mutual interpretation between TDIP and SIP data sets in recent researches. We analyze spectral dispersions of CRs from laboratory measurements data of SIP to estimate SIP parameters based on the Cole-Cole model. Using the dispersion characteristics, numerical models with IP anomalies are constructed for numerical simulation of not only SIP but also TDIP surveys. Through inversion of resulting SIP and TDIP synthetic data, we estimate Cole-Cole parameters from inverted SIP anomalies and chargeability decay curves of the inverted anomalies from TDIP. Based on the numerical experiments, we make further numerical tests considering field scale mining and contamination surveys.

This work was supported by the Energy Efficiency & Resources of the Korea Institute of Energy Technology Evaluation and Planning (KETEP) granted financial resource from the Ministry of Trade, Industry & Energy, Republic of Korea (No. 20194010201920) and Korea Ministry of Environment as "The SEM projects; 2018002440005"

How to cite: Jeong, J., Kim, B., Caesary, D., Mun, Y., Won, D., and Nam, M. J.: Numerical analysis for dispersion characteristic from time domain induced polarization based on laboratory measurement data of complex resistivity, EGU General Assembly 2022, Vienna, Austria, 23–27 May 2022, EGU22-10964, https://doi.org/10.5194/egusphere-egu22-10964, 2022.