Improving Groundwater Flow Model Conceptualisation and Calibration with ERT and Self-potential Methods

Simulating solute transport in heterogeneous porous media poses computational challenges due to the high-resolution meshing required for traditional solvers. To overcome these challenges, this study explores a mesh-free method based on deep learning to accelerate solute transport simulation. We employ Physics-informed Neural Networks (PiNN) with a periodic activation function to solve solute transport problems in both homogeneous and heterogeneous porous media governed by the advection-dispersion equation. Unlike traditional neural networks that rely on large training datasets, PiNNs use strong-form mathematical models to constrain the network in the training phase and simultaneously solve for multiple dependent or independent field variables, such as pressure and solute concentration fields. To demonstrate the effectiveness of using PiNNs with a periodic activation function to resolve solute transport in porous media, we construct PiNNs using two activation functions, sin and tanh, for seven case studies, including 1D and 2D scenarios. The accuracy of the PiNNs’ predictions is then evaluated using absolute point error and mean square error metrics and compared to the ground truth solutions obtained analytically or numerically. Our results demonstrate that the PiNN with sin activation function, compared to tanh activation function, is up to two orders of magnitude more accurate and up to two times faster to train, especially in heterogeneous porous media. Moreover, PiNN’s simultaneous predictions of pressure and concentration fields can reduce computational expenses in terms of inference time by three orders of magnitude compared to FEM simulations for two-dimensional cases.

Coal seam fire and coal mine fire as well as fire in coal waste or storage piles are worldwide general phenomenon and pose a great threat to the national economy, environment, ecology and health of peoples living in its proximity. In 17th century the coal mining in India first started in Raniganj coalfield in an ill- planned way and some planned mining started in an about 1820. In early days, the collieries were owned by several small companies and owners. In 1971, the Indian coal industry was nationalized under Coal India (CIL) and Bharat Coking Coal Limited (BCCL) was formed as a subsidiary of CIL. The haphazard coal mining without suitable mine planning pose several paramount threats with environmental hazards. At present it is spread over more than 70 areas. The mapping and understanding of hidden subsurface coal fire is a challenging task. In view of this, the present study was attempted for Coal fire mapping and detection of previously burnt coal fire regions in East Basuria colliery, a part of the Jharia coal field, India. Magnetic and Self Potential (SP) methods of geophysical investigation have been used for coal fire mapping over parts of Jharia Coalfield, India mainly due to cost-effectiveness with good accuracy and faster data acquisition. SP study works based on redox potential generated by oxidation of coal and also on Thomson potential due to temperature gradient. Whereas, magnetic study allows to map the previously burned, currently burning and unburned locations based on the magnetic properties of the materials and their changes with temperatures above or below Curie temperature. SP data have been analysed using Particle Swarm Optimization (PSO) technique. Magnetic data have been corrected for diurnal variation followed by correction using reduced to magnetic pole (RTP). The corrected magnetic data further, enhanced using north-south and east-west horizontal derivatives, first vertical derivative, second vertical derivative, Total horizontal derivative, Analytical signal, Tilt Derivative and downward continuation techniques. Radially averaged power spectrum (RAPS) of magnetic data has been calculated to estimate the average depth to the top of different layers. Different sets of 3D Euler’s depth solutions have been estimated separately for each various source geometry (SI = 0, 0.5, 1.0, 1.5, 2, 2.5 and 3) to understand the possible source geometry of complex fire activities. PSO inversion of SP data reveals that the depth of the coal fire extends between 10 and 12 m below the surface. The study based on SP method over East Basuria reveals that the geometry of subsurface coal combustion is possibly similar to the inclined sheet with relatively large horizontal extension. The large variations in inclination angles of the causative sources may possibly indicate complex nature of fire propagation along different inclined fractured planes which are generated in multiphase coal seam combustion. It is observed that the total magnetic field intensity anomaly of the area varies approximately from 44,850 to 47,460 nT and the residual magnetic anomaly varies approximately from −1323 to 1253 nT. The range of the magnetic anomaly after RTP is approximately 1050–1450 nT. Twelve low (L1–L12) and nine high (H1–H9) RTP magnetic anomalies have been delineated from RTP of East Basuria Colliery for 2012. The average depth to the top of different layers estimated using radially averaged power spectrum (RAPS) over East Basuria colliery are (i) 10 m, (ii) 18 m and (iii) 38 m for 2012. It is observed that the average depth of the estimated Euler’s solution for different SI is varies from 10 to 26 m for 2012. Possible fire affected, non-fire and possible baked and cool areas have been delineated as (i) 21%, (ii) 36%, (iii) 42% for the years 2012 based on RTP anomaly distribution over East Basuria colliery. The results prove the efficacy of the SP and magnetic methods for characterization of causative sources associated with coal fires over East Basuria colliery, Jharia coalfield, India.

The major environmental and engineering applications of the self-potential method have been investigations of subsurface water movement. Specific uses have included mapping of seepage flow associated with dams, dikes, reservoir floors, and other containment structures; studies of general groundwater movement; and delineation of flow patterns in the vicinity of landslides, wells, faults, drainage structures, shafts, tunnels, and sinkholes. The method also has been used to a lesser extent for subsurface thermal investigations such as mapping of steam flood fronts and coal mine fires, and preliminary studies indicate that it could be used to help delineate chemical concentration gradients associated with subsurface contaminants. Self-potential anomaly amplitudes generated by such environmental and engineering sources tend to be lower than those seen in mineral and geothermal exploration, and spurious anomalies associated with the presence of man-made structures at most field sites often create very high noise levels. Therefore extreme care in the acquisition and reduction of field data, and recognition of characteristic fields associated with artificial and natural noise sources, are critical to the success of environmental self-potential investigations. Interpretation of self-potential data often is qualitative, using visual correlation between observed profile or contour patterns and known or suspected seepage flow paths or other sources. The use of available geometric source models, including charged points, lines, spheres, cylinders, and sheets, can provide useful first estimates of source depth and configuration. Computer programs based on analytical modeling techniques can be used to calculate self-potentials generated by subsurface gradients of pressure, temperature, or chemical concentration. If in-situ physical property parameters such as cross-coupling coefficients and hydraulic, thermal, and electrical conductivity are known or can be reasonably estimated, these techniques can provide useful information about the nature, location, and strength of self-potential sources.

Limestone covers about 4500 km2 in Romania, meaning about 2% from the country surface, being specific for the karst of the temperate zones due to its landforms, terrain diversity and the amplitude of the exo and endokarst particularities. Carbonate rocks are spread in the mountains and sub-mountains areas, with the most compact and the largest surface of this type of rocks in the Banat Mountains, more exactly in the Resiţa-Moldova Noua Synclinorium. The aim of this study to examine the use of the self-potential as geophysical method in detection of water flow and water resources in shallow karst depressions (sinkholes) in the Anina Karst Region, Banat Mountains, Romania. The self-potential (SP) method—also known as spontaneous potential—is founded on the measurements regarding the natural or spontaneous potentials that are forming in the ground. Our SP approach in several sinkholes in the Anina Karst Region shows that most of the anomalous zones with positive spontaneous electric potential are localized in the middle of the sinkholes, indicating the higher retention of water within the bottom part of the karst depressions. Also, the most of the values showing negative anomalies are situated in those parts where the karrens are developed. SP method applied in the Anina Karst Region, Banat Mountains, Romania, has shown the feasibility of this geophysical method in the study of water circulation in shallow karst environment. Since sinkholes are landforms that favor the fast circulation of the water from the surface into the underground, the SP approach could be a feasible method to study aquifers and the presence of contaminants in karst aquifers since water is a very important resource in karst areas. Moreover, SP method is reliable in characterization of shallow karst topography research and this geophysical method can be combined with other geophysical method in karst terrain analysis, methods like GPR and ERT.

A multidimensional streamline-based method to simulate reactive solute transport in heterogeneous porous media

The Red Hill area in Bangka Regency, one of the largest former mining sites on Bangka Island, remains largely unreclaimed, presenting opportunities for sustainable rehabilitation. This study utilizes the Self-Potential (SP) method to map groundwater flow patterns as a foundation for post-mining reclamation efforts. SP data were collected along eight survey lines, covering 150-250 meters each, in the Ampar Lake area. The analysis reveals SP anomalies ranging from -117 mV to 86,696 mV, indicating significant variations in electric potential linked to groundwater movement. High-potential zones were identified as recharge areas, while low-potential zones indicate discharge areas, suggesting a regional groundwater flow from northeast to southwest. These findings establish a preliminary understanding of groundwater behavior in the Red Hill area, providing a basis for targeted reclamation to support agricultural, educational, and ecotourism initiatives.

Modeling non-Darcian flow and solute transport in porous media with the Caputo–Fabrizio derivative

Groundwater resources, which are exposed to overexploitation and pollution at regional and local levels, may take benefit from fast, nonintrusive, and inexpensive monitoring methods based on electromagnetic techniques. In fact, the available technologies can help to improve management and protection of the aquifers. This chapter deals with the role of electromagnetic sensing techniques in water monitoring with a specific focus to pollution surveys in groundwater bodies. Being sensitive to the presence of water in the subsoil and its electrical conductivity, which in turn depends on the ionic content, the electromagnetic sensing techniques are useful tools for groundwater identification and soil quality assessment. In fact, these sensing techniques offer advantages such as quickness, nonintrusivity, and the possibility of investigating large areas at reasonable costs. However, the appropriate use of these techniques implies an adequate knowledge of their working principles as well as of their on field application procedures, which mainly depend on the survey aim and the geological and logistic conditions of the site. This chapter also discusses the uncertainty in the interpretation of results, which is due to the fact that the electromagnetic sensing techniques are based on indirect inspections. Several strategies can be exploited to reduce ambiguity of results, such as the integration of different electromagnetic techniques and the comparison between field data and those provided by laboratory experiments. These issues are herein addressed through practical examples concerning two study cases, one referred to a site located in Serbia-Herzegovina and one located in Italy. In particular, we illustrate the physical concepts, the operative aspects, the data processing, and the integration of results concerning the following measurement techniques: electrical resistivity tomography (ERT), ground-penetrating radar (GPR), time-domain-induced polarization (time domain IP), and self-potential method (SP). The two study cases concerns an industrial site and a large waste dump structure. These sites represent specific examples of soil monitoring and have been selected in order to evaluate the performance of the proposed techniques. For each site, we provide a description of the survey results accounting for geological evidences, logistic constraints, and physical limitation of the used techniques. Finally, we highlight the advantages offered by a cooperative use of different techniques and suggest strategies to overcome intrinsic limitations of each one of the considered survey methods.KeywordsElectromagnetic sensing techniquesWater monitoringElectrical resistivity tomographyGround-penetrating radarInduced polarizationSelf-potential

Self potential (SP) and electrical resistivity tomography (ERT) methods are used together with the results of groundwater samples hydrogeochemical analysis to assess the impact of the water leak from the landfill garbage site at NamSon located in Northern Hanoi on causing pollution to the surrounding environment and affecting geological structure. Selected survey area covers an area of 180 × 300 m lying in the low land of the NamSon site with a slope ranging about 8 m in direction NW–SE. There are three geophysical measurements lines denoted as T1, T2 and T3. Processing 180 SP data points has allowed to draw maps of equipotential epoch in the two periods in 2015 and 2016. The maps show four zones of SP positive anomalies with maximum amplitudes of about +20 mV where the groundwater flow direction is downward and five zones of SP negative anomalies with minimum values in a range from −180 to −260 mV where the groundwater flow direction is upward. Resistivity values of the subsurface layers of soils and rocks have been aquired from 2D inverse model for measuring ERT in March 2015 and March 2016. The results of the ERT allowed to define the low resistivity in the range 15–20 Ωm related to leachate plume from NamSon landfill site. Results of the physico-chemical analysis of groundwater samples from the existing six boreholes show increases in concentration of the measured pollutant parameters indicating contamination of the groundwater as a result of solid waste leachate accumulation. This result is affirmative evidence for the survey results by geophysical technique. The rapid decrease in quality of groundwater over the last year is probably due to the influence of the leachate from the NamSon landfill site.

In this work, the influence of pore space geometry on solute transport in porous media is investigated performing computational fluid dynamics pore-scale simulations of fluid flow and solute transport. The three-dimensional periodic domains are obtained from three different pore structure configurations, namely, face-centered-cubic (fcc), body-centered-cubic (bcc), and sphere-in-cube (sic) arrangements of spherical grains. Although transport simulations are performed with media having the same grain size and the same porosity (in fcc and bcc configurations), the resulting breakthrough curves present noteworthy differences, such as enhanced tailing. The cause of such differences is ascribed to the presence of recirculation zones, even at low Reynolds numbers. Various methods to readily identify recirculation zones and quantify their magnitude using pore-scale data are proposed. The information gained from this analysis is then used to define macroscale models able to provide an appropriate description of the observed anomalous transport. A mass transfer model is applied to estimate relevant macroscale parameters (hydrodynamic dispersion above all) and their spatial variation in the medium; a functional relation describing the spatial variation of such macroscale parameters is then proposed.

Scale dependence of dispersion coefficient (D) in the advection-dispersion equation (ADE) for solute transport in porous media was investigated by a series of experiments using image analysis. A hexahedral plexiglass box sized 200×8×1.5 cm (L×W×H) was set and packed with glass beads as porous media. The solute transport under different conditions was simulated by changing the particle size of glass beads, flow rate, and detection scale using Bright Blue as tracer. The image analysis method was used to dynamically monitor and identify the spatiotemporal variation of solute concentration distribution. The results showed that image analysis can effectively monitor and identify the solute concentration in porous media, as indicated by an R2 value of 0.9890. There is an obvious linear relationship between hydraulic gradient (J) and velocity (v) in porous media under different experimental conditions. The ADE model is suitable for solute breakthrough curve (BTC) with good fitting accuracy, and can effectively reflect the concentration variation during solute transport. The key parameters controlling the solute transport were analyzed. D has abnormal diffusion (i.e., non-Fickian phenomenon) and scale dependence, and BTCs had a long tail, which becomes more obvious with the increase of flow rate, medium particle size, and transport scale.

Global sensitivity analysis and Bayesian parameter inference for solute transport in porous media colonized by biofilms

We demonstrate that electrical resistivity imaging can be combined with self-potential and induced polarization to produce 3D images of the Darcy-velocity field in the subsurface of the Earth. We first review the basic concept behind this new appraoch and then, we apply it to two case studies associated with leakage in dams and enbankments. The dam of Lampy (Black Mountain, Aude, France) is considered as one of the oldest dams in France. A geophysical survey is performed to better understand the pattern of groundwater flow downstream of this dam in the granitic substratum. Induced polarization is first used to image both electrical conductivity and normalized chargeability. 8 core samples of granite from this site are measured and analyzed in the laboratory. Their electrical conductivity and normalized chargeability are expressed as a function of the porosity and Cation Exchange Capacity (CEC). The field data and the petrophysical results are used to image the water content, the CEC, and the permeability distribution of the substratum. Then, self-potential is used as a complementary passive geophysical technique, which, in absence of metallic bodies, is directly sensitive to groundwater flow through the so-called streaming potential effect. Indeed, the excess of electrical charges in the vicinity of the solid grains, in the so-called double layer, is dragged by the ground water flow generating in turn an electrical (streaming) current and therefore an electrical field. A map of the resulting self-potential signals is done over the area covered by the induced polarization profiles. This map shows a large positive anomaly with an amplitude of ~80 mV possibly associated with upwelling groundwater in an area where the soil is water-saturated. A groundwater flow simulation is performed to model this anomaly. This is done in two steps. A preliminary groundwater flow model is built using the permeability and water content distributions obtained from the induced polarization data. Then, this groundwater flow model is updated using the information contained in the self-potential data including the electrical conductivity distribution obtained through resistivity tomography. The algorithm for the inversion of the self-potential data is validated through a 2D numerical test. This analysis yields a groundwater flow model with the flow being focused through a high permeability zone. A similar appraoch is then apply to a leakage through a small dam in Easter France. We also provide a synthetic case study to demonstrate the value of our approach. This study shows how three geoelectrical methods (self-potential, induced polarization and electrical resistivity) can be efficiently combined to image groundwater flow in the vicinity of a dam or an embankment. We are currebtly working on using this approach on landslides. 

Views Icon Views Article contents Figures & tables Video Audio Supplementary Data Peer Review Share Icon Share Twitter Facebook Reddit LinkedIn Tools Icon Tools Reprints and Permissions Cite Icon Cite Search Site Citation Mochamad Khoirul Rifai, Eny Latifah, Yoyok Adisetio Laksono; Identification of landslide collapse (depression) using electrical resistivity tomography method as a preventive step of damaged infrastructure of the road. AIP Conference Proceedings 24 January 2023; 2634 (1): 020031. https://doi.org/10.1063/5.0112975 Download citation file: Ris (Zotero) Reference Manager EasyBib Bookends Mendeley Papers EndNote RefWorks BibTex toolbar search Search Dropdown Menu toolbar search search input Search input auto suggest filter your search All ContentAIP Publishing PortfolioAIP Conference Proceedings Search Advanced Search |Citation Search

Electrical resistivity tomography (ERT) method is often used to solve problems related to chemical pollution of the hydrogeological environment. The source of such contamination can be, e.g. industrial heaps, tailings ponds and municipal landfills. The contaminants spreading often takes the form of a (3D) pollution tongue. In this case, the standard interpretation of 2D ERT surveys may be difficult. Numerical modeling was carried out in order to show the specificity of pollutants propagation. Both 2D and 3D models were analysed. Those refer to the real geological situation - vicinity of Nowa Huta (Krakow, Poland) - where heaps and tailings ponds of the metallurgical plant are present. An appropriate geoelectrical model referring to the above situation was prepared. It was assumed that highly mineralized waters in the form of a contamination tongue are spreading within the aquifer. Resulting interpreted resistivity distributions for 2D and 3D variant of ERT method were analysed. It has been shown that the method is promising in terms of the ability to detect and assess the nature of the transitional zone between clean and contaminated waters. Additionally, it has been shown that 3D modeling can be a useful, complementary element in interpreting the results of DC-resistivity methods.