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NSG2020 26th European Meeting of Environmental and Engineering Geophysics
- Conference date: December 7-8, 2020
- Published: 07 December 2020
1 - 20 of 65 results
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Levee Characterization by Means of Geophysical and Geotechnical Data Fusion: Improvements in Methodology
Authors T. Dezert, S. Palma Lopes and Y. FargierSummaryLevee assessment recognized methodologies imply setting up investigation campaigns, including geophysical and geotechnical investigation methods. A major issue is to combine the geotechnical and geophysical data, taking into consideration their respective levels of uncertainties, inaccuracies and incompleteness as well as spatial distributions. In this work we propose the results of a fusion methodology based on the use of Belief Functions and two combination rules, to merge geotechnical (cone penetrometer and grain size distribution) and geophysical (electrical resistivity) data, acquired on a real fluvial levee. We display an enhancement of the results obtained in previous work, considering a new way of assigning geophysical belief masses, a different classification index for the penetrometer test data (Ic) and an additional combination rule (Proportional Conflict Rule n°6). We highlight the ability of this fusion methodology to discriminate the constitutive sets of geological materials inside an earthen levee with an associated confidence level. We also demonstrate the relevance of the improvements in the methodology comparatively with the past results.
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Laboratory Study of the Electrical Properties of Lutetian Limestones after Heating Up
Authors B. Souffaché and A. TabbaghSummaryLutetian limestones of the Paris Basin have been largely used in monument building during medieval and modern periods. Electrical properties of rocks samples, extracted in quarries from the same layers as those used for ancient monuments, are measured in the [100 Hz – 10 MHz] frequency range at ambient temperature and after heating at 300 °C and 600°C. The changes in the sample electrical properties are limited and it can be expected that it is the same for mechanical properties.
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Geochemistry of Soda-Type Groundwater in the Torey Lakes Region (Russia): Differences between Catchment Area and Beyond
By V. DrebotSummaryChemical groundwater composition analyses in the Torey Lakes case study area allowed identification of the difference between the chemical composition of groundwaters in the Torey Lakes catchment area and groundwaters beyond. Waters differed with respect to TDS content, pH, sodium, sulfate ion and chloride ion. The thermodynamic equilibrium of waters with calcite was calculated and analyzed. The study showed that the chemical composition formation of Na-HCO₃ (soda) waters in the area of the Torey lakes is due to a combination of factors: climatological conditions, hydrogeological conditions (catchment area and type of circulation) and time of interaction in the water-rock system.
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Monitoring a Drilling Trajectory by Using the Drill-Bit Signal as a Source
Authors J. Ridderbusch, M. Abbasian and A. KaslilarSummaryA deviation from the desired drilling trajectory creates problems and costs. Monitoring the drill-bit trajectory can help to take action in advance to adjust the drilling process to the desired trajectory. In this study we suggest a possible approach to detect the deviation of the drill-bit using seismic while drilling (SWD) methods. SWD allows seismic measurements without stopping the drilling process and will therefore enable near real-time corrections for the drilling trajectory. We use the drill-bit as a seismic source and an array of seismic receivers on the surface to record the drilling signals. Because the drill bit will create a noisy source signature we apply cross-coherence to retrieve the seismic signal as it would be emitted by a standard seismic borehole source. A cross-correlation between the records at a reference depth and recordings due to deeper source positions reveals a specific change in travel times, when the drill-bit source is located along a deviating drilling trajectory. By using 2D finite-difference modelling of wave propagation for a typical hard rock environment, we show that this method can deliver sufficient information about the deviation that a correction of the drilling process is possible.
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Novel Approach to Modelling the Elastic Waves in a Cluster of 3D Fractured Structures
Authors N. Khokhlov, P. Stognii and M. ZhdanovSummaryThis work presents the results of modelling the cluster of 3D vertical fractures in the heterogeneous medium based on the 3D SEG/EAGE Overthrust model. In the previous work, we considered the approach to modelling 2D fractures based on the model of a two-shore extremely thin fracture. The results showed the effectiveness of the developed method to modeling the elastic wave propagation in fractured geological media. In this work, a similar approach to modelling a cluster of 3D vertical fractures is presented. The wave fields and the synthetic seismograms for the models with and without fractured zone are analyzed. The results demonstrate the significant contribution of fractures into the observed wave field.
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Drone-Borne Electromagnetic (DREM) Surveying in The Netherlands
Authors M. Karaoulis, I. Ritsema, C. Bremmer and M. De KleineSummaryIn the past decade drones have become available and affordable for civil applications, including monitoring with geophysical sensors. In 2017 and 2019 the feasibility of executing frequency domain electromagnetic (FDEM) method surveys using an off the shelf drone, was investigated at Deltares. This paper reports on the preparatory tests executed to determine the optimal configuration, processing and inversion scheme and on the field validation tests demonstrating the capability of the drone-borne electromagnetic survey.
One demonstration example shows how the system can efficiently map shallow groundwater and surface water salinity in areas where seepage of saline water occurs. The other demonstration example shows how the system can map shallow lithology as well as buried metal cables and pipelines.
The general findings are that the system provides for the flexibility to fly a combination of FDEM soundings, profiles or grid patterns and its ability and efficiently to fly over inaccessible areas and surface water. Compared to the HLEM surveys, the spatial resolution is much higher which allows for detailed 3D mapping of subsurface and the costs are, certainly for small study areas, relatively low, which also makes monitoring of changes by repeated drone-borne electromagnetic (DREM) surveys affordable.
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Combined Geophysical-Geotechnical Investigations Using Share Waves: A Case Study from Budapest
Authors A.C. Kovács, Z. Szilágyi, J. Stickel, M. Bauer, R. Csabafi and G. BernáthSummaryIn this paper a case study of a typical city-centre development project from Budapest, Hungary is presented, with focus on the thorough soil investigation program in the preliminary phase of construction projects. The aim of this study is to give an overview about the state-of-the-art geophysical soil investigation methods applied in Hungary and to show how findings obtained by regular geotechnical measurements can be supplemented and verified. Borehole geophysics, geophysical and seismic cone penetration test, surface seismic 2D share wave reflection and tomography, and downhole measurements were applied during the geophysical investigation. One of the main results was that the compression- and shear-wave velocity profiles measured with different in-situ methods were very similar.
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Addressing the Inherent Issues with the Deconvolution of Vibroseis Seismic Data in View of Near-Surface Exploration
Authors L. Gupta and N. VedantiSummaryNowadays, seismic exploration is the most commonly used method for near-surface exploration since it effectively delineates structures hosting mineral deposits and other natural resources in the shallow subsurface. One of the popular energy sources for the land seismic method is ‘Vibroseis’ which uses a baseplate mounted on a truck to emit a band-limited ‘sweep signal’ into the earth. In this paper, we discuss the two major issues inherently associated with Vibroseis seismic data: harmonics and phase, which arise due to the nature of the sweep signal. Both of these issues are usually ignored and conventional data processing is carried out similar to the case of the explosive source. With the help of a high-resolution seismic dataset, we show that these issues become significant for near-surface exploration due to their effect on high frequencies and hence cannot be ignored. We suggest using the pilot sweep for cross-correlation to reduce the harmonic noise, but to resolve shallow and near-surface structures accurately, we recommend Frequency Domain Sweep Deconvolution (FDSD) in lieu of conventional cross-correlation. We further recommend the application of predictive deconvolution in combination with FDSD to achieve an improved seismic image than the usual.
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An ERT Time-Lapse Method to Characterize Water Movements in a Karstic Medium
Authors C. Verdet, C. Sirieix, J. Riss and D. LacanetteSummaryGeophysical methods are currently used to give a better understanding of the karst system functioning. At the Lascaux site, the prehistorical painted cave faces conservation needs that can be partly linked to its karstic environment, and to a karstic spring present at its entrance. This paper deals with a six-years electrical resistivity tomography (ERT) monthly time-lapse to better acknowledge the cave upstream. We used a hierarchical method to interpret the ERT. A hierarchical ascending clustering was done on the 53 acquisition dates to forms four groups. Those groups vary accordingly to both the rain and the flow of the cave spring. The clustering of the resistivity blocks were aggregated to form seven classes. It revealed that a maximum time of 21 days was necessary for the water to pass from the superficial layers (0-2.5 m depth) to the depth (2.5-7.5 m depth). The resistivity block clustering seems to display a layer of contrast of permeability at about 185 mNGF.
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In-Situ Stresses and Pore Pressure Prediction of a Well in an Iranian Southwest Oil Field
Authors M. Motahari and H. AmeriSummaryOne of the most important parts of wellbore stability research is in-situ stresses and pore pressure estimation. In this work, for well A in LI region of Gachsaran oil field, the in-situ stresses, pore pressure, and fracture pressure are computed by different equations. Moreover, the Leak off tests (LOT) and Repeat formation tests (RFT) data are used to validate their values. The analysis demonstrates that the best equation for the minimum and maximum horizontal stresses calculation are that has the best agreement to the RFT and LOT data. This study illustrates that the stress regime changes from slip-strike to reverse stress regime based on the in-situ stresses magnitude in some depths of the well. Besides, by comparison between the plotted stress profile and caliper log of well A, could be concluded that the collapse or breakout in some sections and depths has occurred in a well A. Finally, FMI image log data for the current well displays the direction of the minimum and maximum horizontal stresses that are N 120ᵒ E and N 30ᵒ E respectively. The results of this research could be used for future wellbore stability analysis and modelling in this region.
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A Convolutional Neural Network Approach to Electric Resistivity Tomography
Authors M. Aleardi, A. Vinciguerra and A. SalustiSummaryElectric resistivity tomography (ERT) is an ill-posed inverse problem commonly solved through deterministic gradient-based methods. Markov Chain Monte Carlo algorithms can be employed to cast this problem into a solid probabilistic Bayesian framework, but they remain a formidable computational task due to the expensive forward model evaluation. Here we explore the potential of convolutional neural networks (CNN) for ERT inversion. A large dataset is used to train the network to learn the relation between the observed data and the subsurface resistivity model, whereas a Discrete Cosine Transform reparameterization allows for a compression of the parameter space, thus reducing the ill-conditioning of the inverse problem. Once trained the network can be used to predict the subsurface model from the observed data in near real-time. We also implement a Monte Carlo inversion framework that propagates onto the estimated model the uncertainties related to both noise contamination and network approximation (the so-called modeling error). To draw general conclusions about the feasibility of the proposed approach, we focus the attention on synthetic inversion experiments. Our preliminary results confirm the feasibility of the CNN-ERT inversion, opening the possibility to estimate the subsurface resistivity distribution and the associated uncertainties in real-time.
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Using Convolutional Neural Networks to Expedite the Hamiltonian Monte Carlo Inversion of Rayleigh Wave Dispersion Curves
Authors A. Salusti and M. AleardiSummaryThe inversion of Rayleigh wave dispersion curves is a non-linear problem in which a numerical sampling of the posterior probability density function (pdf) is needed for accurate uncertainty appraisals. Hamiltonian Monte Carlo (HMC) algorithm is a very promising sampling method that guarantees rapid convergence toward the stationary regime while maintaining high acceptance ratios and independence between the sampled models. The main downside of HMC is that several forward evaluations per iteration are needed to compute the derivative information of the target pdf. This makes this approach inapplicable to problems with expensive forward calculations and many unknown parameters. Here, we replace the semi-analytical evaluation of the forward problem (i.e. the Haskell-Thomson method) with a convolutional neural network that, once trained, can be evaluated extremely fast. This introduces a modelings error that can also be reliably propagated into the posterior model. We validate our approach on synthetic inversions in which the observed dispersion curves have been extracted from seismic gathers computed on a schematic subsurface model. Our tests demonstrate that this strategy guarantees accurate model estimations and uncertainty evaluations while ensuring a very efficient sampling that is orders of magnitude less computationally expensive than a standard HMC based on the Haskell-Thomson method.
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Discrete Cosine Transform for Parameter Space Reduction in Bayesian ERT Inversion
Authors A. Vinciguerra, M. Aleardi, A. Hojat and E. StucchiSummaryMarkov Chain Monte Carlo (MCMC) algorithms are employed for accurate uncertainty assessments in non-linear geophysical inverse problems. However, one of their main drawbacks is the considerable number of sampled models needed to attain stable posterior estimations, especially in high-dimensional parameter spaces. We use the Discrete Cosine Transform (DCT) to reparametrize a Bayesian Electrical Resistivity Tomography (ERT) inversion solved through an MCMC sampling. In this framework, the unknown parameters become the series of coefficients associated with the retained DCT base functions. We employ the Differential Evolution Markov Chain (DEMC) algorithm that guarantees a more accurate and rapid sampling of the posterior density than more standard MCMC algorithms (such as the random walk Metropolis). To draw essential conclusions about the reliability of the implemented algorithm, we focus on inversions of a synthetic subsurface block model. We assess the benefits provided by the DCT compression of the model space by comparing the outcomes of the implemented inversion approach with those provided by a DEMC algorithm running in the full, un-reduced model space. Although preliminary, our results are promising and prove that the implemented inversion approach guarantees rapid convergence toward the stationary regime, thereby preserving an accurate sampling of the posterior model.
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Coastal Soil Characterization Using Remote Sensing, Geoelectrical and Borehole Data: Insights from Nile Delta Coast, Egypt
Authors M. Attwa, A. El Mahmoudi, A. Altahrany and A. ElshennaweySummaryCostal soil characterization has a great significance in environmental and engineering studies. The present work is a proposed protocol using remote sensing (RS), direct current resistivity (DCR) and time-domain induced polarization (TDIP) data for characterizing the coastal soil on the Nile Delta coast. The land use-land cover (LU-LC) is introduced to get the changes in land degradation over the selected analysis period. Considering RS data analysis, geoelectrical measurements are carried out. Regarding to the saltwater intrusion and other heavy anthropogenic activities along the coastal zones, it can be noticed that the lateral heterogeneities within the near-surface coastal soil cannot be characterized using individual DCR data. The 2D resistivity profiles show limitations in mapping the high conductive layers of smearing and amplification of the conductive layer boundaries. On the other hand, the 2D-TDIP images can differentiate between the high conductive layer and saltwater intrusion calibrating with the nearby borehole data. Interestingly, negative chargeability data has been reported for coastal clays. Finally, the electric cone penetration test (CPT) with pore pressure measurements is carried out to confirm and calibrate the geophysical inversion results. The success of the proposed approach supports further studies into understating the geotechnical properties in such coastal areas.
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Defect Detection in Embankment Dams Using Artificial Neural Networks, Electrical Resistivity Tomography and Seepage Numerical Model
Authors R. Norooz and R. GhiassiSummaryIn this paper, Artificial Neural Networks (ANNs), Electrical Resistivity Tomography (ERT) and seepage models were used to detect the defect in the embankment dams. ANNs were established based on the human brain structure and are using in many complicated problems such as pattern recognition, etc. In this study, several models of embankment dams with different heights and defects at different depths were made using Geostudio software to extract hydraulic head. For collecting synthetic ERT data, it was assumed that electrodes were installed on the top of the crest in the center and left side. An anomaly with the resistivity of 5Ωm at different depths of the core was considered too. The resistivity values in the core, embankment and bedrock were considered to be about 20, 20000 and 10000, respectively. The 2D synthetic data was generated by RES2DMOD using finite element forward modelling and Wenner array. RES2DINV software was applied for inverting synthetic data. Qnet software was used for making ANNs. The data type effect was investigated and inverted resistivity, dimensionless water head and dimensionless depth as inputs and true resistivity as output had acceptable results. The results showed that ANNs are able to help in locating defects in embankment dams.
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Joined Migrations in GPR Prospecting: An Example in the Field
Authors R. Persico and G. MorelliSummaryIn this contribution we propose a joined migration of a GPR datum, where essentially two migration algorithms are applied on the same datum and then the two results are combined in order to provide a better focused image. We have applied this idea on real data gathered from a previous commitment assigned to the company Geostudi Astier. For sake of space, we will show the procedure applied on a single Bscan, but we have applied it to several GPR data within this case history.
The proposed joined migration can be useful when there are horizontal variations of the propagation velocity of the electromagnetic wave from point to point within the GPR measurement line. In such a situation, a single value might be optimal for part of the buried target, whereas another value might be better suited for other targets. A joined migration mitigated this problem allowing to choose more values for the migration result and combining them so to focus at best all the targets.
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Effect of Data Normalization on Neural Networks for the Forward Modelling of Transient Electromagnetic Data
Authors M.R. Asif, T.S. Bording, A.S. Barfod, E. Auken and J.J. LarsenSummaryInversion of geophysical data is often challenging and time-consuming, particularly for large scale surveys. The solution of the inverse problem requires numerous calculations of the forward problem, especially when calculating partial derivatives required for most linearized inversion schemes. The forward model is usually calculated numerically using accurate equations, but often less accurate and faster equations are used. In recent years, neural networks have become increasingly popular to replace the numerical forward modelling, as this may lead to a significant speed-up. Data normalization, prior to the training of neural networks, is crucial to obtain good results and faster convergence rate. This is especially true for geophysical data, as numerical data values may span over several orders of magnitude. In this abstract, we investigate several normalization approaches for TEM data, with a special focus on towed TEM data. Through extensive experimentations, we show that data normalization substantially affects the performance of neural networks when surrogating forward models. We also demonstrate the effect of normalized data variation on neural network’s performance and provide insights into which normalization approaches may be better than others. A significant improvement in performance accuracy is achieved when the appropriate data normalization technique is employed.
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Parallelized Hybrid Bloch Solver for Surface Nuclear Magnetic Resonance
Authors M. Griffiths, D. Grombacher and J.J. LarsenSummarySurface nuclear magnetic resonance (sNMR) is unique among non-invasive geophysical methods in that it is directly sensitive to water content. Computational intensity of modelling the forward response is one of the current limitations of the method. Consequently, common practice is to use many approximations and simplifications. These include neglecting relaxation during pulse effects, linearizing the tip angle as a function of excitation strength, and assuming equality of T1 and T2 to reduce the model space dimensionality. Here we show that these simplifications are no longer necessary, that the full solution can be obtained through the use of highly parallelized computation on a Graphics Processing Unit (GPU) combined with a hybrid solver. Our solver uses a 4th order Runge-Kutta numerical solution during excitation, but switches to the analytical solution during free precession. In this way arbitrarily long off-time responses can be obtained in a single step. This permits the expansion of the fast-mapping dimensionality to include T1 in the forward model. Serial implementations of the forward response on a CPU require 57 hours to cover the range of physically significant models. Our hybrid solver on a 4352 core GPU reduces this calculation to 4.7 minutes.
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The Added Value of Combining VES and TEM Data Focusing on Macro-Anisotropy
Authors J.A. Meekes and J. GunninkSummaryIn the Netherlands thousands of Vertical Electrical Soundings (VES) have been acquired in the second half of the last century. The VES-measurements still represent valuable information about the subsurface, especially of a deeper part (say > 60 m) of the subsurface, for which borehole information is less abundant. In the past decades airborne Time Domain Electromagnetic Methods data were acquired in selected part of the Netherlands. The objective of this presentation is to demonstrate the kind of added value brought by combining the VES and TEM datasets, focusing on macro-anisotropy. On several VES-locations analyses of the combined datasets were performed, showing locations with more and less fine layering and locations where the VES-model fitted the SkyTEM data well without any macro-anisotropy; the analysis of the data on one location is detailed in the paper. It is concluded that using the combination of VES data and SkyTEM data an identification of layers of macro-anisotropy can be obtained, as well as indication of the degree of thin clay sublayers in a mostly sand macro-layer.
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A Geophysical Study at an Anthropogenic Created Coastal Area of Thorikos, Attica, Greece
Authors S. Karizonis, G. Apostolopoulos and G. AmolochitisSummaryA geophysical study (EM, GPR, ERT, Seismic) at an anthropogenic created coastal area of Thorikos, Attica, Greece, has detected anthropogenic structures, as well as the paleo-coast line, the nature of the sediments and the bedrock top relief. Directionality of measurements as well as the salt water intrusion and its pathways greatly influences the measurements. The later can be used by electrical and electromagnetic methods in combination of the sediments distribution (possibly affected by anthropogenic structures) and their character (lithological, anthropogenic or geomorphological, grain size). Seismic method can give additional geotechnical information, been influenced differently by the previous factors.
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