Inflows pose a serious concern to potash mining operations and often increase operating costs and production slow-downs. The mapping and understanding of water-bearing geohazards is vital in the potash mining industry. Critical to this effort is the development of geophysical tools to quantify the type and magnitude of these geohazards. In this paper, we propose using in-mine time-domain electromagnetics (TDEM) as a viable tool for investigating porous, water-bearing anomalies in geological layers more distant than has been done with electrical methods in the past. This work includes a TDEM survey to better delineate and quantify the properties of a suspected geohazard near a potash mine in southern Saskatchewan. Our investigations had two objectives: one was to confirm and define the extent of the conductive brine in the overlying lithology. The second was to determine the effectiveness of deploying TDEM in-mine where full-space effects and nearby machinery pose significant noise challenges to operation. Our results found a strong conductive EM signature to the suspected anomaly, suggesting there is high value in deploying TDEM underground. In addition, full-space EM computer modeling was performed in COMSOL Multiphysics using 2D-axisymmetric geometry to account for lithological changes both above and below our survey. We invert the survey data using a pair of different strategies. The results of which demonstrate that the anomalous EM response is caused by a conductive high in the Dawson Bay carbonate layers above the mine workings.
The first step in processing the determination of near-surface velocity structures is critical. In addition to improper static adjustments, a poor near-surface velocity model causes the rays predicted by the model to deviate from their actual ray paths. Due to the cumulative nature of this ray path deviation, even a small error in the near-surface velocity model can result in momentous errors in calculating the ray path and travel time. Furthermore, the deviation can notably degrade the seismic image at depth, particularly in regions with significant lateral velocity variations. A seismic model with significant lateral velocity variations and bare bedrock was built to perform theoretical calculations. The concept of first arrival tomographic static correction was also examined. Numerical simulation techniques were used to study the conditions and application consequences of the first arrival tomographic static correction, providing a reference for the static correction of challenging surface coal bed methane (CBM) seismic data. The findings demonstrate that tomographic static correction is better suited for processing complicated surface CBM seismic data and can effectively handle the problems of surface undulation and lateral velocity fluctuation, which are critical for improving the accuracy of CBM exploration.
Waterborne Ground Penetrating Radar (GPR) can be a powerful method for surveying bathymetry, water, and sedimentation volumes within water impoundments like Faylor Lake in Snyder County, Pennsylvania. Current methods for measuring sediment volume in water impoundments often involve invasive techniques, such as collecting cores, which lead to rough estimates due to limited available physical data. This study aims to utilize a custom-made GPR apparatus, which includes a 100 MHz transceiver, a GPR controller, and a GPS device, all mounted on a small 2-person crewed inflatable watercraft. Over 40,000 data points of depth locations spanning the entire lake were collected. The data has been used to generate contour maps and 3D models of the current bathymetry, as well as the original topography of the basin before the dam's construction in 1983. During this study, the lacustrine deposit's dielectric permittivity (<<) was directly measured using a laboratory bench experiment with a 1600 MHz GPR transceiver. The measured << = 51.69 has enabled the determination of accurate depth values and, subsequently, the sediment volume. The sediment volume represented 20% of the entire lake, with a volume of 139,281 m3. The water volume was also determined with << = 80, amounting to 663,659 m3. The 3D bathymetry map also shows the outlines of the old Middle Creek channel. The deepest part of the lake was identified on the southeast side, near the drop inlet of the dam, along the old Middle Creek channel, with an average depth of 1.63 m.
Metallic structures are a common noise source in Slingram electromagnetic surveys because they interact with the primary magnetic field generated by the transmitter coil and create a secondary magnetic field that distorts the apparent conductivity readings from a layered or homogeneous subsurface. The main challenge is understanding how their influence varies depending on the loop configuration and the distance at which the surface structure no longer distorts the apparent conductivity readings. We propose a methodology that integrates experimental techniques and numerical modeling to elucidate the distortions induced by a fence-like structure placed at varying distances from the coils of a low-induction conductivity meter. Additionally, we aim to evaluate the model responses using numerical simulations with electromagnetic systems operating at higher frequency ranges. To quantify the distortions in apparent conductivity, we conducted field measurements by keeping the electromagnetic coils in a fixed position while changing the placement of the conductive structure. The readings obtained before installing the conductive structure were used as the background reference response to accurately determine the distortions. The same experimental procedure was tested in terrains with different resistivities to evaluate the changes caused by the same structure in different backgrounds. Our results show that this approach allowed us to infer that the deviations in apparent conductivity caused by the presence of the fence are more noticeable where the background resistivity is higher. However, these deviations were observed only for short distances of about 1/5 to 1/2 of the coil separation for the evaluated targets. The integration between the experimental survey and the numerical modeling suggests that distortion increases when the instrument is operated at induction numbers higher than similar to 0.2. For all tested conductivity models and frequency ranges, minor distortions were observed with the vertical coplanar coil configuration compared to the horizontal coplanar configuration for the transmitter-receiver pair. Negligible distortions were observed for fences with unconnected wires, suggesting minor interference from loose metallic objects on the ground surface that do not form closed loops, favoring EM induction.
In large cities with a growing population, the expansion of construction and demolition (C&D) waste of buildings can lead to the annual production of millions of tons of waste. Any solution for inexpensive, rapid, and accurate identification of these depots' layering structure and composition can greatly benefit urban management. Geoelectric methods can serve as a simple, cost-effective, and sufficiently accurate means of identifying these materials. In this study, the layering structure of C&D waste buried in line 4 of the Hesar landfill in Karaj City, Iran, was determined using a geoelectric method involving the assessment of electrical resistivity variations in both vertical and horizontal directions. Wenner-Schlumberger array was utilized for the measurements, and 2,870 electrical resistivity points were collected. RES2D-INV software was utilized to interpret the data and plot geological sections. In addition, a series of laboratory tests, including Sieve analysis and water content, were performed on samples collected by continuous core boring to better understand the waste composition. According to the study results, compared to the field data, it was concluded that the ERT could accurately predict the changes in various soil layers, aggregate sizes, and water content. In addition, data from boreholes revealed that most of the materials buried in this depot are concrete. The results of this study can assist urban management in recycling C&D waste. Recycling C&D waste recovers some economic value from C&D waste, clearing out C&D waste depots and eliminating the environmental desirability issues that they can cause in surrounding areas.
Direct and indirect methods of detecting subsurface voids and cavities using seismic methods have proven to be a challenge for the better part of a century. There are several examples of resonance associated with shallow voids in the literature, but many of them are individual instances or do not include real data, leaving readers to wonder if it is an exploitable phenomenon that can be used at multiple sites, or if it requires a site-specific set of criteria to be generated. We present three examples of observed resonance that is coincident with the location of known voids at a range of depths to determine if the ringing effect is consistently recorded from one place to another. The data used were not collected specifically for this purpose, but were pulled from data sets acquired over known voids in Utah, Iraq, and Arizona. Additional data from a wider variety of geologic settings and void dimensions would help to determine if observations are consistent across a range of geologic environments and void characteristics.
As we seek to make geophysical models more consistent with geological models, more and more a priori information is incorporated into geophysical inverse problems. How we make the most use of a priori information is still a key issue in geophysical inversion, particularly for effectively representing such information in inversion problems. To address this problem, we propose a symmetric polynomial constrained inversion algorithm that can represent multiple known physical properties for the lithology. The electrical resistivity synthetic model tests show that the inversion results constrained with symmetric polynomials can make the model resistivity be in line with a priori information and obtain more realistic sharp boundaries. Finally, we give a practical verification of our inversion algorithm with field data.
This research addresses groundwater management challenges in southeastern Punjab Province, Pakistan, focusing on over-exploitation, contamination, and climate change impacts. Employing a multidisciplinary approach, it integrates hydro geology, ecology, economics, and policy studies. The study emphasizes particularly on vertical electrical sounding (VES) enhanced with Particle Swarm Optimization (PSO) algorithm and other advanced electrical geophysical techniques. This innovative method improves VES data inversion, vital for understanding aquifer characteristics and identifying salinity-free zones, supporting sustainable groundwater strategies. Covering 200 square kilometers in the Indus Plain, an area with alluvial deposits from the Ravi and Beas rivers, the research offers insight into complex groundwater dynamics. PSO's efficiency in generating accurate resistivity models is key for locating new wells, ensuring water availability and sustainable agriculture. The methodology includes aquifer parameters, borehole logs, and analysis of aquifer properties and salinity distribution, mapping crucial aquifer features to assess groundwater potential and contamination risks.
The occurrence of geothermal spring not only enhances human health, but also plays a crucial role in generating community’s revenue that boosts up the standard living of locals. An endeavor has been made to delineate the prospective areas of geothermal spring in Kon Tum province, Vietnam by the utilization of joint-geophysical techniques. The blended mode as mentioned is opted for its superiority in providing the rapidassesments of temperature in shallow temperature survey, comprehensive understanding the subsurface structure in electrical resistivity tomography in copporating with the validation in well log interpretation. The results found that the overlapping region of high temperature (35°C) region and low resistivity (200 Ωm) is observed in the east in the vicinity of Dlak Bla river, and it probably broadens to the west of the study area. The outcome of geophysical approaches strongly concur with the well log interpretation, revealing the presence of water-bearing zone encountered in fractured granite. The results also corroborated the existence of concealing fault F5 as a branch of the NE-SW fault F2 which is favorable for creating a route to form the geothermal spring. The output of this research could be considered as an intentive consultation for Kon Tum’s planners and makers on expanding the investigation and exploitation.
Non-uniqueness in the inversion of seismic data can be considered the main challenge for the application of such data. Prior information, such as downhole data, can be used to control this problem. However, in most cases, prior information is not available; accordingly, geophysicists/analysts have to suppose a primary model for the observed data and then find the final adequate layered earth model through trial and error. In this study, a new technique was developed based on the artificial neural network (ANN) for the inversion of seismic refraction data in the absence of prior information. In this regard, a sequential multilayer perceptron (SMLP) was proposed, which integrates the sequential information of the model parameters to predict a reasonable layered earth model. In fact, at first, a multilayer perceptron (MLP) (First-MLP) was trained by synthetic data; then, a layered earth model, i.e., the primary model, was predicted for the observed data. Next, using the primary model, a range for each of the model parameters, i.e., thickness and P-wave velocity, for each layer was defined. Subsequently, new synthetic samples were generated based on the determined ranges. Finally, using another MLP (Second-MLP), which was trained by the new synthetic samples, the final model for the observed data was estimated. The proposed method was also tested by employing different synthetic data with and without noise. Moreover, the SMLP inversion technique was used to analyze the experimental seismic refraction dataset at a dam construction site. The results for both synthetic and experimental data confirmed the reliability of the proposed SMLP inversion technique.
Crosshole seismic tomography (CST) could be used to reconstruct the velocity section of media between two holes. One commonly used attribute of fractures reflected in seismic waves is the anisotropy of velocity. Therefore, in this study, the multiple symmetry axes of anisotropic media are utilized to simulate the multiple-set fractures in strata. The anisotropic algebraic reconstruction technique (AART) and anisotropic simultaneous iterative reconstruction technique (ASIRT), extensions of isotropic ART and SIRT, are developed to detect the medium with multiple symmetry axes and strong anisotropy. Full coverage of ray paths in azimuth is needed for these techniques. The performances of these techniques are tested by numerical and physical modeling. Testing results show that the proposed AART and ASIRT methods can successfully detect the multiple-set fractures when the observed data exceeds the estimated parameters. However, in complexly anisotropic and heterogeneous media, the estimation error will significantly increase when using these techniques if the number of estimated parameters is equal to or greater than the number of observed data.
Swells in marine seismic data disrupt the continuity of the reflection events and make interpretation difficult. The swell effect removal process consists of sea-bottom detection and correction, which removes the swell effect by shifting the detected sea-bottom signal to the known or estimated seafloor location. The quality of correction depends on the accuracy of the sea-bottom detection. Since general sea-bottom signal detection techniques have been applied directly after pre-processing, many mispick scenarios exist due to the characteristics of the data, and additional processes are needed. This study proposes a method for accurately detecting sea-bottom reflection signals using the guideline. The errors are caused by mistaking other reflection events as sea-bottom signals. The guideline can improve detection accuracy by providing rough event times of sea-bottom reflection. The guideline was extracted from the gradient vector flow (GVF) technique, a segmentation method in image processing. In the GVF data, the seafloor signals are smoothed, and the energy is focused on the sea bottom. The threshold method detected sea-bottom signals in the range after the guideline. The detected signals were shifted to estimated seafloor locations to attenuate the swell effect. The GVF-based guideline (GVF-GL) method was applied to field data acquired by the airgun and chirp sources with different frequencies. The sea-bottom location was successfully detected, and the continuity of the sea-bottom and subsurface signals in the section was improved.
Borehole seismic methods have been widely used for characterizing the shallow subsurface. Accurate analysis of their data is aided by a solid understanding of the borehole sources' characteristics. This study presents a field evaluation of two impulsive borehole seismic sources (Trident's Scorpion sparker and RT Clark's Ballard weight drop) in crosswell and reverse vertical seismic profile (RVSP) geometries at a Gulf of Mexico coastal site with two shallow vertical wells. The acquired data is then utilized to characterize the near-surface coastal sediments. The Scorpion source generated P-wave dominant frequencies that were recorded as 650 Hz and 250 Hz in the crosswell and RVSP geometries, respectively. For the Ballard source in the two geometries, the P-wave dominant frequencies were 1100 Hz and 250 Hz. We were also able to pick direct S-wave arrivals with the Ballard source, and their dominant frequencies were 100 Hz and 40 Hz for in situ and surface recordings, respectively. The average signal-to-noise ratio (SNR) recorded with the Scorpion data for the crosswell geometry and RVSP, respectively, is 13 and 6, and for the Ballard source, 62 and 30. We also investigated the source radiation patterns and signature wavelets. Seismic tomography was performed for the area between the two wells. Low P-wave and S-wave velocities correspond to three fresh water-saturated sand zones identified from drilling cuttings and previous well log data. Also, the plot of velocity of P-wave (Vp) versus S-wave (Vs) fits reasonably to the Mudrock Line. Both sources can excite repeatable energetic seismic signals up to 150 m away and could be useful in many geotechnical settings and even single-well imaging.
