Just-Accepted Journal Articles

Just-Accepted Articles are peer-reviewed, accepted manuscripts that have been assigned Digital Object Identifiers (DOIs) and undergo the normal publication process (copy editing, page composition, proofing by author, and finalization). A Just-Accepted article listing includes an abstract and the DOI (scroll).  The article is removed when the final version of the manuscript is ready and assigned to a Journal of Environmental & Engineering Geophysics (JEEG) issue, becoming the official version of the article. The Just Accepted article has the same DOI that appears on the official version of the article; therefore, citations made to an article during the Just-Accepted stage will continue to link to the article's official version.  EEGS Members can access the full, preliminary article via this "member-only" link:  Just-Accepted Articles with full article PDF

Electrical Resistivity Inversion Based on Symmetric Polynomial Constraint

Authors:
qikai sun; MAN LI; zhiyong zhang; yihao guo

DOI: 10.32389/JEEG23-028

ABSTRACT: 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.

Keywords: Electrical resistivity; Inversion; Symmetric polynomial; rock physical properties

Applying Particle Swarm Optimization on VES Data for Groundwater Evaluation

Authors:
Idrees Khan; CUI Yi-an; Warda Yousaf; Farid Ullah; Inayath Ur Rahman; Shafqat Hussain

DOI: 10.32389/JEEG24-003

ABSTRACT: 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.

Keywords: Vertical Electrical Sounding (VES); Inversion; Particle Swarm Optimization; Aquifer Geohydraulic Properties; Groundwater Evaluation

Development of An ANN-based Technique for Inversion of Seismic Refraction Travel Times

Authors:
Rashed Pourmirzaee; Shahab Hoseini

DOI: 10.32389/JEEG22-044

ABSTRACT: Non-uniqueness in inversion of seismic data can be considered as the main challenge for application of such data. To control this problem, prior information such as downhole data should be used. 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 artificial neural network (ANN) for 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) was trained by synthetic data; then, a layered earth model, i.e. 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, which was trained by the new synthetic samples, the final model for the observed data was estimated. The proposed method was also tested employing different synthetic data with and without noise. Moreover, the SMLP inversion technique was used in analyzing 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.

Keywords: Sequential multilayer perceptron; travel times; Inversion; prior information

Application of Geoelectrical Methods to Identify the Subsurface Layering Structure of Construction and Demolition Waste Depot

Authors:
Asgar Nasiri; Abolfazl Eslami; Ahmad Fahimifar; Davood Akbarimehr

DOI: 10.32389/JEEG22-025

ABSTRACT: 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 the layering structure and composition of these depots can be of great benefit to 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 the line 4 of 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 were 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 gain a better understanding of 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.

Keywords: Construction and demolition waste; Geoelectric; Schlumberger; Geotechnical properties; Electrical resistivity

Characterization of a small abandoned municipal solid waste scattered landfill combining remote sensing and near-surface geophysical investigations

Authors:
Grégory Bièvre; Stéphane Garambois

DOI: 10.32389/JEEG23-002

ABSTRACT: This study reports the combination of remote sensing and ground geophysical techniques to locate an abandoned and hidden municipal solid waste landfill located in a fluvial plain in the French Western Alps. Following earthworks and further floods that eroded into the river bank, wastes made of a mixture of plastic, metal and soil/earth, were uncovered and some of them flowed into the river. The existence of an abandoned landfill, several decades-old, was known, but the knowledge of its exact location was forgotten. Historic aerial photographs back to 1948 allowed delineation in space and time of the location of a platform that was used for landfill operations between around 1973 and 1983. A LiDAR DEM acquired in 2012 allowed was used to locate topographic depressions 0.1 to 0.4 m in depth, notably inside the platform. These depressions are interpreted as resulting from differential compaction originating from the presence of compressible wastes. Geophysical mapping techniques (magnetic and electromagnetic) confirmed the presence of anomalies inside the identified platform. Geophysical imaging techniques (ground-penetrating radar, electrical resistivity tomography) provided a quantitative evaluation of the width and depth of the individual pits. The combination of the different techniques allowed for estimating the first-order volume of waste. The methodology adopted in this work is applicable to detect landfills exhibiting differential compaction and physical contrasts.

Keywords: Municipal solid wastes; aerial photographs; LiDAR; near-surface geophysical methods

GPR with a Bench Model Experiment to Measure Bathymetry and Sediment Accumulation of Faylor Lake, PA

Authors:
Ahmed Lachhab; Trey Dupont-Andrew; Michael Shearer

DOI: 10.32389/JEEG22-033

ABSTRACT: Waterborne 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 collecting cores, which lead to rough estimates due to limited available physical data. The objective of this study is 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. Data has been used to generate contour maps and 3D models of the current bathymetry, as well as the original topography of the basin prior to the construction of the dam in 1983. During this study, the dielectric permittivity of the lacustrine deposit was directly measured using a laboratory bench experiment with a 1600 MHz GPR transceiver. The measured ε =51.69 has enabled the determination of accurate depth values and, subsequently, the sediment volume. The sediment volume was found to represent 20% of the entire lake, with a volume of 139,281 m3. Additionally, the water volume was determined with ε = 80, amounting to 663,659 m3. The 3D bathymetry map has also shown 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 1.63m.

Keywords: Bathymetry; GPR; Dielectric; sub-bottom profiling; Faylor Lake

Seismic swell effect correction using GVF-based guide-line

Authors:
Kyoungmin Lim; Jiho Ha; Jungkyun Shin; Sungryul Shin; Wookeen Chung

DOI: 10.32389/JEEG23-009

ABSTRACT: Swells in marine seismic data disrupt the continuity of the reflection events and makes 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, a number of mispick scenarios exist due to the characteristics of the data, and additional processes are needed. In this study, we propose a process for accurate detection of sea-bottom reflection signals using the guide-line. The errors are caused by mistaking other reflection events as sea-bottom signals. The guide-line can improve the accuracy of detection by providing rough event times of sea-bottom reflection. The guide-line was extracted from the gradient vector flow (GVF) technique, which is a segmentation method in the image processing field. In the GVF data, the seafloor signals are smoothed and the energy is focused on the sea-bottom. The threshold method was used to detect sea-bottom signals in the range after the guide-line. To attenuate the swell effect, the detected signals were shifted to estimated seafloor locations. The GVF-based guide-line (GVF-GL) method was applied in 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 on the section was improved.

Keywords: swell effect correction, sea-bottom detection, gradient vector flow (GVF), guide-line, threshold

Detect multiple-set fractures by crosshole seismic tomography for using in environmental and engineering geophysics

Authors:
YOUNGFO CHANG; Wei-Zhih Chang; Lun-Tao Tong

DOI: 10.32389/JEEG22-037

ABSTRACT: Crosshole seismic tomography (CST) could be used to reconstruct the velocity section of media between two holes. One of the commonly used attributes 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), which are extensions of isotropic ART and SIRT, are used 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 the numerical and physical modeling. Testing results show that the multiple-set fractures can be successfully detected by the proposed AART and ASIRT methods when the number of observed data exceeds the number of estimated parameters. However, in complexly anisotropic and heterogeneous media, if the number of estimated parameters is equal to or greater than the number of observed data, the estimation error will significantly increase for using these techniques.

Keywords: anisotropy; multiple-set fractures; crosshole seismic tomography

Shear Properties and Pore Characteristics of Soil-rock Mixture under Dry-wet cycling

Authors:
Siwei Wang; Guinan Wang; Shuyi Li

DOI: 10.32389/JEEG22-041

ABSTRACT: The mechanical properties of soil-rock mixtures can deform significantly under the influence of dry-wet cycles, affecting the safety of high-fill projects. A drying device was developed to perform direct shear tests on the soil-rock mixture (S-RM). Large-scale direct shear tests were carried out under the action of dry-wet cycling to study the effect of dry-wet cycling on the mechanical properties of S-RM. Image J software was used to identify the number and area of pores in the binary image, and the pore characteristics of S-RM under dry-wet cycles were analyzed. The results show that the section of post-peak in the shear stress-strain curve is softening under the natural state (no dry- wet cycles), but it is plasticizening under application of the dry-wet cycles. The cohesion of the S-RM particles is affected by the dry-wet cycling and decreases greatly under the first dry-wet cycle, and then decreases gradually for each successive cycle, after which it stabilizes during the fifth dry-wet cycle. The internal friction angle is not affected to a large degree. The effect of a dry wet cycle on pores with different areas is significantly different. The pores with initial sizes of 0.5–10 mm2 decrease, while pores with other initial sizes are hardly affected by the dry-wet cycling. This paper quantitatively analyzed the relationship between the surface two-dimensional porosity and the cohesion and peak strain of S-RM.

Keywords: Soil-rock mixture (S-RM); Dry-wet cycle; Shear behavior; Porosity; Quantitative analysis

Field evaluation of two impulsive downhole seismic sources in crosswell and reverse VSP geometries and high-resolution characterization of near-surface Texas Gulf Coast sediments

Authors:
Zohreh Souri; Robert R. Stewart; Yingcai Zheng

DOI: 10.32389/JEEG22-048

ABSTRACT: 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 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 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. A Vp-Vs plot also fits reasonably to the Mudrock Line. Both sources can excite repeatable seismic signals up to 150m away and be useful in many geotechnical settings.

Keywords: Borehole Seismic Sources, Crosswell Seimic, Reverse VSP, Seismic Tomography, Seismic Velocity

Validation and Potential Improvement of Soil Survey Maps Using Proximal Soil Sensing

Authors:  Felippe Hoffmann Silva Karp; Viacheslav I. Adamchuk; Alex Melnitchouck; Barry Allred; Pierre Dutilleul; Luis R. Martinez

DOI: 10.32389/JEEG22-018

ABSTRACT: There is potential use of proximal soil sensors (PSS) to contribute to soil surveys and improve their results, and this study focused on the evaluation of this potential. An analysis using a high-resolution soil survey (1:5000), terrain data, and an ensemble of PSS (gamma ray emission, ground penetrating radar – GPR, apparent electrical conductivity from electromagnetic induction, and galvanic contact) was conducted. First, a geostatistical analysis was performed to characterize the spatial variability of each variable for each sensor and interpolate the data to a common support. The GPR data presented well-delineated groups of depths with similar spatial structure. These groups matched the field soil horizon depths, thus representing the potential for this sensor in soil characterization. A significant correlation was found between most of the variables from each sensor. However, no complete agreement was observed among the data from different PSS. In addition, a visual comparison of the maps showed that each PSS captured the soil spatial variability of the field and delineated regions distinctively. To validate the soil separation provided by the high-resolution soil survey and evaluate the capability of the PSS to distinguish the different soils, an analysis of variance was performed. Although none of the sensors could differentiate all the soils in the field, maps containing an overlay between sensors and soil models provided an important insight: overall, the soils were located correctly but the boundaries needed to be adjusted. Spatial clustering was used to perform a multivariate analysis of the data. A final map containing well-delimited homogenous PSS-based zones was obtained. Accordingly, it is possible to conclude that this approach and the resulting maps can be used to improve the delineation of boundaries between different soil types.

Keywords: soil types; data fusion; spatial cluster

Influence of Radiative Components and Meteorological Conditions on Simulation of Slope-Specific Heat Balance
Authors:  Mito Nishioka; Megumi Yamashita; Hirotaka Saito

DOI: 10.32389/JEEG22-011

ABSTRACT:  Fields have uneven surfaces, such as ridges, and the shortwave radiation of fields differs depending on the orientation of the slope of the unevenness, resulting in variations in the distribution of moisture on the ground surface. Therefore, it is necessary to estimate the heat and water balances spatially, taking into account the variation of the moisture distribution on the ground surface. Previously, one-dimensional simulations have been used to estimate the heat and water balance of non-sloping surfaces. To estimate the heat and water balance spatially while taking into account ground surface roughness, it is necessary to first estimate the heat and water balance of the ground surface on the basis of slope orientation. The purpose of this study was to clarify those factors, in addition to shortwave radiation, that affect the heat balance of a bare sloping surface at different orientations. To achieve this, the heat balance calculated using observational data of bare ground, including unevenness, was compared with the heat balance estimated by HYDRUS-1D simulation for each slope orientation. Additionally, the brightness index of RGB images was calculated and compared with the relative ground surface brightness and the estimated heat balance for each slope orientation. The estimated results at night and at sunrise/sunset were extremely small in comparison with the calculated results, and the heat balance simulation in the absence of shortwave radiation remained an issue. The relationship between ground surface brightness and ground conduction heat was completely different depending on slope direction, suggesting that ground surface heat transfer is affected substantially by factors other than shortwave radiation related to slope orientation. The findings indicate that it is necessary to examine the effects of heat transfer in detail to estimate the heat balance related to slope orientation.

Keywords: Heat balance; Net radiation; Slope orientation; Monitoring; HYDRUS-1D

Research on Time-domain Airborne EM Full-field Apparent Resistivity Imaging Method for Arbitrary Transmitting Waveform

Authors:  Jianbo Zheng; Yanfu Qi

DOI: 10.32389/JEEG22-023

ABSTRACT:  The time-domain airborne electromagnetic (AEM) system can do fast EM surveys over mountainous areas by carrying its detection equipment on an airplane. Due to the dense sampling of AEM method, it generates a huge amount of data. As a result, the resistivity imaging methods have become the first choice for data interpretation because they are fast. However, the traditional imaging methods do not fully consider the influence of the transmitting waveform. When they are used to deal with the AEM data with complex current waveform, the imaging results are seriously affected. Therefore, we develop a universal full-field apparent resistivity imaging method for AEM data with arbitrary transmitting waveform. Firstly, we calculate the convolution of time derivative of the current waveform and step response to obtain the time-domain AEM response of the arbitrary transmitting waveform. Then the full-field apparent resistivity imaging method based on the inverse function theorem is used to complete the rapid imaging of AEM data with complex waveform. Finally, we apply our imaging codes to both synthetic and field data to verify its correctness.

Keywords: Time-domain; Airborne EM; Transmitting waveform; Full-field apparent resistivity.

Noise Reduction of Aeromagnetic Data Using Artificial Neural Network

Authors: Osama Elghrabawy

DOI: 10.32389/JEEG22-013

ABSTRACT: The high frequency content of high-resolution aeromagnetic data is of particular interest to geophysicists to identify mineral deposits, shallow faults, and dikes. However high resolution aeromagnetic data contaminated by cultural noise generated from aircraft and man-made features. The culture noise must be removed before starting the interpretation process. Manual techniques are more selective of the noise, however slower and more expensive because they require considerable hands-on interaction. The present study develops a novel method for detecting and removing the culture noise from aeromagnetic data based on an artificial neural network (ANN) in automatic way, and comparing the results with conventional algorithm using the non-linear filter. The proposed method is tested using a theoretical example that combine a magnetic anomaly due to a dyke with three sources of cultural noise, besides using a practical example to increase the number of a training pattern. The network is trained based on the backpropagation training function, where the algorithm updates the weight and bias states as per the Levenberg–Marquardt optimization. The optimization is reached during the training and validation process after 3,000 iterations. The correlation coefficient () is utilized along with the mean squared error (MSE) as performance indices of the ANN. The ANN demonstrates the capability to detect the spiky data based on the optimal weights, thus allowing for removing and replacing them with clean data using the piecewise cubic Hermite interpolating polynomial (PCHIP) function. The practical utility of the two-method is discussed using high-resolution aeromagnetic data from the Tushka area located in the southwestern desert of Egypt. Comparing the denoising results using the two methods shows that the current approach is more effective in processing and more closely recovering the original magnetic data.

Keywords: aeromagnetic data processing; noise reduction; artificial neural network