Ground penetrating radar (GPR) has become an effective means for assessing deterioration in concrete bridge decks. While success has been demonstrated, the method is still not adopted widely. Constant technical development is making such high speed GPR mapping more affordable with systems more widely available and easier to deploy. The American Society for Testing and Materials (ASTM) has a standard procedure for performing bridge deck deterioration using GPR. The current standard, initially written for air-launched GPR devices and then modified to include ground-coupled GPRs, has many simplifying assumptions that could lead to fallacious evaluations. Both field experience and numerical simulations indicate that ground-coupled GPR systems are preferable to air-launched GPRs in this application, delivering larger signal-to-noise and higher spatial resolution data, which enhance extraction of both electromagnetic wave velocity and attenuation. We describe advances in analysis and interpretation that go beyond the current ASTM approach which ignores the impact of depth and other variables. We demonstrate these advances using a high speed, ground-coupled GPR system with examples of deck deterioration mapping. We describe the workflow for using GPR to evaluate the deterioration of concrete bridge decks, highlight the basic interpretation assumptions, demonstrate successful applications and discuss limitations with the methodology.
A hidden water-bearing collapse column (WBCC), directly exposed during coal mining, is a potential source of serious mine flooding. Presently, the transient electromagnetic method (TEM) is widely used, which shows good performance in detecting WBCCs in coal mines. However, traditional numerical simulation approaches have failed to be adapted to complicated underground environments affected by roadways, and the application of boundary conditions require a large grid. Considering this, the authors chose the convolutional perfectly matched layer (CPML) as a boundary condition, whose effects were found to be superior to the traditional Dirichlet boundary condition. Then, based on stratigraphic data related to coal measures located in North and Mid-eastern China, the whole-space geoelectric model was established. The whole space TEM response of the WBCC at different depths of the stope face floor and ahead of the driving face were also simulated by the finite-difference time-domain method. The numerical simulation results indicate that the underground roadway exerted a substantial influence in early periods, yet the effects became negligible with time, according to the inductive potential decline curve. In addition, the contour distribution of apparent resistivity for different geoelectrical models of the WBCC was consistent with the models. The closer the roof of the collapse column was to the coal seam floor, the lower the apparent resistivity. Moreover, TEM was applied to hidden water-bearing collapse column detection in real underground coal mines.
Large geophysical datasets are produced routinely during airborne surveys. The Spatially Constrained Inversion (SCI) is capable of inverting these datasets in an efficient and effective way by using a 1D forward modeling and, at the same time, enforcing smoothness constraints between the model parameters. The smoothness constraints act both vertically within each 1D model discretizing the investigated volume and laterally between the adjacent soundings. Even if the traditional, smooth SCI has been proven to be very successful in reconstructing complex structures, sometimes it generates results where the formation boundaries are blurred and poorly match the real, abrupt changes in the underlying geology. Recently, to overcome this problem, the original (smooth) SCI algorithm has been extended to include sharp boundary reconstruction capabilities based on the Minimum Support regularization. By means of minimization of the volume where, the spatial model variation is non-vanishing (i.e., the support of the variation), sharp-SCI promotes the reconstruction of blocky solutions. In this paper, we apply the novel sharp-SCI method to different types of airborne electromagnetic datasets and, by comparing the models against other geophysical and geological evidences, demonstrate the improved capabilities of in reconstructing sharp features.
This paper investigates the capability of the resistivity and induced polarization (IP) methods to delineate skarn alteration haloes within the Qale-Alimoradkhan skarn copper deposit. This deposit is located in the Sanandaj-Sirjan geological and structural zone, Hamedan province, Iran. It is understood that fresh limestone and metamorphosed limy units including skarns represent high resistivity anomalies whereas granodiorite intrusions represent medium to low resistivity responses. Four profiles were selected to explore the sulfide-rich zones within the deposit using the Combined Resistivity Sounding and Profiling (CRSP) array. After the appropriate selection of inversion parameters, the inverted models were in good agreement with the known geological features. The resistivity response of the intrusive rocks were found to be alteration dependent. Furthermore, IP targets likely represent sulfide-rich zones. Our study suggests that if preexisting knowledge regarding the geological setting is available, then resistivity and IP can be helpful in the exploration of skarn mineralization.
We present the results of an ultrasonic pulse-echo technique and its potential to classify iron meteorites into hexahedrites, octahedrites and ataxites by determining their acoustic impedance and phase velocity. Our technique has been adapted from those used in the field of ultrasonic non-destructive investigation of a variety of materials. The main advantage of our technique is that it does not need any preparation of the meteorites like cutting and etching and therefore is rapid, easy and non-destructive. In essence, a broadband acoustic transducer is used in a monostatic pulse-echo configuration which means that both the transducer and the meteorite sample are located in a water bath and adjusted in the way that the ultrasonic pulse shit the meteorite sample at normal incidence. Then the reflected pulses from the front and rear faces of the meteorite sample are measured with the emitting transducer, digitally recorded and processed to analyze the signal. After Fourier transforming the echoed pulses from the front and the rear face of the meteorite sample, the calculated reflection coefficients yield the phase velocity and the acoustic impedance. Our study investigates a variety of iron meteorites collected in Morocco and other countries and it helps to understand how the nickel content of these meteorites affects the acoustic impedance. It reveals that the acoustic impedance of iron meteorites increases with increasing nickel content, so that a further refinement of our technique might have the potential to classify iron meteorites directly and reliably into hexahedrites, octahedrites and ataxites without destroying them.
Electrical resistivity tomography (ERT) is one of the most effective geophysical methods used to acquire detailed pictures of subsurface conditions without drilling. Site investigation using two- and three-dimensional electrical resistivity imaging is now a fundamental step before the design and construction of campus buildings at the University of Sohag in Egypt. In this study, an ERT survey was implemented at two pre-defined sites with the aim of selecting the most favorable location for construction of a new educational building on the university campus. The resistivity results were confirmed with boreholes drilled at both sites. RES2DINV and RES3DINV software were used for data processing and interpretation. The results show that the near surface sedimentary succession beneath both sites consists of four geoelectrical and lithological units. From the surface to a depth of 20 m, these layers are: unit 1) unconsolidated boulders and gravels intercalated with percentages of sand and reddish clay; unit 2) fine crushed calcareous gravels and sands with clays intercalations; unit 3) dry sand and clayey sand; and unit 4) shale, at the base. According to an evaluation of the presence and abundance of shale and sand contents cracks, fissures and faults, the second site is identified as more suitable for construction.
In this research study, the landslide events of Huangshan City in China's Anhui Province were monitored through the integration of two geophysical techniques: the magnetic resonance sounding (MRS) and transient electromagnetic (TEM) methods. The JLMRS-III system was used to determine the distributions of the free water in the strata and the MiniTEM system was utilized to image the subsurface electrical resistivity structures. Data acquisition was carried out on two planned survey lines during a wet season. A set of 15 measurements were completed using MRS array detection; a set of 44 measurements were completed using TEM method. The monitoring activities were repeatedly implemented before and after rainfall occurred. The results of water content information, relaxation time, and resistivity distributions were determined through joint inversion. Plots of the results clearly show the aquifer and resistivity structure of the study area. The monitoring data of displacement, pore-water pressure, and rainfall was collected to help differentiate the slip blocks, slip beds, and slip belts in the accumulation bodies of the landslides. We have delineated the potential landslide area, and determined the sliding depth range at 4 to 8 m. We analyzed the stability of the landslide based on the comparison of water content distribution and the relevant geological information in the sliding body to reveal the possibility of future destruction. The results of this study demonstrated that the combined techniques of MRS and TEM have the capability to effectively monitor potential landslides for key parameters needed for risk assessment.
There are a significant number of bridges for which information regarding the foundation is missing or incomplete. It is extremely challenging to evaluate the performance of such unknown foundation bridges (UFB), particularly against scour or when their foundations are reused. For critical UFB, it is often necessary to estimate performance by developing an appropriate working model of subsurface foundation conditions. Typically, nondestructive testing (NDT) has served as the most viable alternative due to the costs and risk associated with excavation, coring, and probing. NDT can be quite difficult to perform and their results can contain significant uncertainty in highly urban settings. The primary objective of this study was therefore to compare performance of borehole NDT methods when evaluating the depth of two in-service unknown foundations (concrete-filled steel pipe piles and H-piles) in highly urban settings. The borehole magnetic, parallel seismic, borehole sonic, and borehole radar methods were implemented to determine the foundation bottom locations. Though uncertainty was present in all measurements, the borehole magnetometer and radar results proved the most conclusive. Parallel seismic testing did not yield any evidence of foundations due to issues with background noise and lack of direct access to the foundation. Likewise, borehole sonic testing was generally inconclusive due to issues with sensor directivity and attenuation. Borehole magnetometer estimated the depth to the foundation bottom as 8.6 m and 9.2 m at the two sites. Borehole radar estimates for the depth to foundation bottom compared favorably at 9.8 m and 8.0 m for the two sites. Given the borehole construction and depth to competent rock at the sites, these results for borehole magnetometer and radar were likely a minimum estimate for the location of the foundation bottoms. Such information can help evaluate long-term performance of this system as part of rehabilitation and reuse efforts.
Subsurface cavities occur naturally by dissolution of carbonates and evaporites or by human action, such as the construction of tunnels and tombs. They can be filled with air, water, sediments, or a combination. Gravity and ground penetrating radar (GPR) methods have been used widely to determine the location and size of subsurface cavities. The objective of this study is to present a quantitative approach to estimate the porosity and water saturation of cavity-filling materials from GPR and gravity measurements. The approach uses appropriate rock-physics models of the dielectric permittivity and density of a shallow cavity and estimates the porosity and water saturation inside the cavity by solving the two model equations simultaneously for these two variables. We test the proposed method using synthetic GPR and gravity data sets corresponding to three spherical-cavity models: air-filled, water-filled, and a partially-saturated sand filling. Results show that the method is accurate in retrieving the correct porosity within 0.76% error and water saturation within 2.4% error. We also apply the method on three published case studies over air-filled rectangular cavities. We found that the proposed method estimated the correct porosity and water saturation in one study but failed with the other studies. However, when the procedure was repeated with gravity values calculated from parameters reported in these studies, the proposed method estimated the correct porosity and water saturation accurately.
Dynamic interactions between rivers and aquifers are controlled by the underlying hydrogeologic environment, as well as the type of hydrologic connection between the riverbed and saturated zone. The Arkansas River supplies groundwater to a heavily exploited region of the Ogallala Aquifer across Western Kansas. Site characterizations of this region using existing well and borehole data reveal large scale geologic features that significantly impact recharge processes, such as the Bear Creek fault. However, the existing hydrogeologic data do not provide the level of detail needed to fully understand the contribution of the losing river system to Arkansas Alluvial aquifer recharge. Knowledge about riverbed hydrogeology is acquirable using electrical resistivity imaging (ERI) surveys. ERI surveys and soil sample analysis were conducted at three sites along the Arkansas River to characterize the hydrogeologic environment within the Arkansas River Alluvial aquifer, which overlies the Ogallala aquifer. Temporal changes in electrical resistivity served as an indicator of the hydrologic response of the alluvial sediments to changes in river discharge as different patterns of water movement from the Arkansas River to Arkansas River Alluvial aquifer were observed. The ERI surveys revealed both fully connected and disconnected regions between the riverbed and groundwater table. The results supplement the existing geologic characterization of this region, and provide a more spatially detailed view of the hydrogeologic environment that has a direct causative effect on groundwater surface water interactions. Understanding the behavior of river-aquifer interactions is vital to the ability to predict the future holds of this important groundwater system.
Robust in situ power harvesting underlies the realization of embedded wireless sensors for monitoring the physicochemical state of subsurface engineered structures and environments. The use of electromagnetic (EM) contrast agents in hydraulically fractured reservoirs, in coordination with completion design of wells, offers a way to transmit energy to remotely charge distributed sensors and interrogate fracture width, extent, and fracture-stage cross-communication. The quantification of available power in fracture networks due to energized steel-cased wells is crucial for such sensor designs; however, this has not been clarified via numerical modeling in the limit of Direct Current (DC). This paper presents a numerical modeling study to determine the EM characteristics of a subsurface system that is based on a highly instrumented field observatory. We use those realistic field scenarios incorporating geometry and material properties of contrast agents, the wellbore, and the surrounding geologic environment to estimate volumetric power density near the wellbore and within hydraulic fractures. The numerical modeling results indicate that the highest power densities are mainly focused around the wellbore excited by a point current source and the fracture boundary. Using DC excitation, the highest power density in the fracture is at the fracture tip. The relatively high-power density on the order of tens of mW/m(3) at the vicinity of the wellbore and at fracture tips suggests that remote charging of sensor devices may be readily possible. Simulation results also show that the region of the highest power density can be significantly increased when the EM source is located inside a conductive fracture, which may lead to a promising deployment strategy for embedded micro-sensors in geologic formations.
A good understanding of the subsurface geological conditions at proposed construction sites is a fundamental requirement to design appropriate building foundations. In this study, the 2D electrical resistivity tomography (ERT) method was used to characterize the subsurface geology at three active construction sites located on or near exposed bedrock in northeast Thailand. The resistivity tomograms proved useful for determining the thickness of intact bedrock overlying a potentially weaker weathered rock of variable saturation. The wide-area information provided by the ERT method should be helpful to foundation design engineers assuming they have confidence in the geophysical results. Geophysics was also useful to guide suitable locations for ongoing geotechnical tests at a given construction site especially if difficult ground conditions exist.
Mined-out areas, caves, voids and cavities usually appear as diffracted waves on ground penetrating radar (GPR) profiles. Therefore, the complete extraction of diffracted waves forms the foundation of the efficient usage of the GPR technique in geological surveys. We propose a method of enhancing GPR diffracted waves via singular value decomposition (SVD) filtering and establish an effective GPR data processing flowchart. First, the shallow and deep signal energies were controlled within a certain dynamic range by energy scaling in the traces. Next, the SVD filtering process was employed to suppress air waves and multiples with better transverse coherence and to extract GPR diffracted waves. Third, background noise was suppressed via band-pass filtering to further improve the signal-to-noise ratio (SNR) of the GPR data. Finally, fitting a diffraction time-distance hyperbola allow us to obtain a diffraction velocity. Constant velocity migration processing for the diffracted waves was based on the Kirchhoff migration technique. The feasibility and effectiveness of this GPR processing technique were verified with the discovery of geological flaws beneath the Mengshan Giant Buddha in China during a cavity survey. Our proposed flowchart efficiently extracts GPR diffracted waves and increases the data SNR. The resulting images are more readily interpreted within the local geological context.
The unstructured finite-element method has been widely used in 3D time-domain electromagnetic (EM) modeling due to its flexibility for modeling rugged topography and complex underground structures. However, how to generate high-quality grids becomes the key to high-accuracy EM responses. We have developed a weighted goal-oriented adaptive finite-element method based on hybrid posterior error estimation in combination with unstructured vector finite-element method and Backward Euler scheme to create an effective mesh. By introducing a weighting factor and adjusting the relative weights of the hybrid posterior errors, the numerical accuracy and convergence rate are greatly improved. To handle the huge difference of EM responses at different time channels, we introduce another weighting factor defined by the exponential power of time to achieve a synchronous refinement of shallow and deep meshes. The numerical experiments on a homogenous half-space model show that our algorithm performs better than the traditional adaptive method both from the accuracy and convergence. Further, we also test the effectiveness of our algorithm for modeling different abnormal bodies under a topographic earth.
To reduce the impact of attenuation and dispersion in ground penetrating radar (GPR) detection and to effectively improve GPR profile recording and to identify a weak detection target, a high-resolution processing method based on orthogonal matching pursuit and wavelet spectrum whitening (the OMWS method) is presented. First, according to the matching pursuit algorithm and the strong reflection-forming mechanism and based on sparse representation theory, a sparse dictionary suitable for the characteristics of a strong reflection signal was selected, and the signal was decomposed, which displayed the weak target signal well. Second, wavelet analysis was used to decompose the processed GPR signal into time-domain subsignals in different frequency bands, and each subsignal was whitened by a whitening filter. Then, the processed subsignals were reconstructed. The final results were compared with the results of conventional spectrum whitening method and showed that the OMWS method can accurately weaken the effect of the strong impedance interface and effectively enhance the local information of microcrack-reflected signals in both the time and frequency domains. The resolution of the processed GPR image is greatly improved, and the reflected signal of the hidden microcrack is easily visible. The method is clearer and more intuitive in the expression of the weak signals of hidden microcrack than the conventional spectrum whitening method, and the compensation for the high-frequency of the signals is more obvious.
The detection of deep targets has always been a challenging topic for controlled source electromagnetic methods; however, the time-frequency electromagnetic method (TFEM) can overcome some of these challenges. In this paper, we introduce the method and showcase the technique for imaging deep targets using optimal offsets and transmission periods. In addition, we implement a simulated annealing constrained inversion, based on well-seismic data, to illustrate improvement in the effective detection depth and the ability to identify deep targets. We apply TFEM for two targets in North Xinjiang to show that internal multiple sets of layered series in a deep Carboniferous system and the volcanic rock mass developed in this area can be imaged. We conclude that the low-resistivity layer inside the Carboniferous system is the response of hydrocarbon source beds of muddy elastic rocks and predict that the high-resistivity layer is a favorable reservoir of volcanic rocks. Subsequent drilling confirmed the structural characteristics of the Carboniferous system revealed by TFEM data.
Similar to any other geophysical method, seismic refraction method faces non-uniqueness in the estimation of model parameters. Recently, different nonlinear seismic processing techniques have been introduced, particularly for seismic inversion. One of the recently developed metaheuristic algorithms is bat optimization algorithm (BA). Standard BA is usually quick at the exploitation of the solution, while its exploration ability is relatively poor. In order to improve exploration ability of BA, in the current study, a hybrid metaheuristic algorithm by inclusion a mutation operator into BA, so-called mutation based bat algorithm (MBA), is introduced to inversion of seismic refraction data. The efficiency and stability of the proposed inversion algorithm were tested on different synthetic cases. Finally, the MBA inversion algorithm was applied to a real dataset acquired from Leylanchay dam site at East-Azerbaijan province, Iran, to determine alluvium depth. Then, the performance of MBA on both synthetic and real datasets was compared with standard BA. Moreover, the dataset was further processed following a tomographic approach and the results were compared to the results of the proposed MBA inversion method. In general, the MBA inversion results were superior to standard BA inversion and results of MBA were in good agreement with available boreholes data and geological sections at the dam site. The analysis of the seismic data showed that the studied site comprises three distinct layers: a saturated alluvial, an unsaturated alluvial, and a dolomite bedrock. The measured seismic velocity across the dam site has a range of 400 to 3,500 m/s, with alluvium thickness ranging from 5 to 19 m. Findings showed that the proposed metaheuristic inversion framework is a simple, fast, and powerful tool for seismic data processing.
With the increase in mining depth, the presence of goafs has become increasingly severe in mine safety. The accurate and effective detection of underground goafs and their water abundance is the key to ensure the safety of mine production. On the basis of the relevant research, this paper defines different goaf types from the perspective of geophysical exploration and discusses the geophysical prerequisites for goaf detection. DC methods, electromagnetic methods, seismic methods, and other geophysical methods on the ground and in the subsurface are reviewed and summarized using the method's principle, research status, and technical features. Research progress on the geophysical methods in goafs and their water abundance detection are introduced, including the electrical source short-offset transient electromagnetic method (SOTEM), the wave-field transformation and synthetic aperture of the transient electromagnetic method, and comprehensive detection. At the end of the paper, a direction for the development of coal mined-out areas and their water abundance detection is put forward, including information fusion technology, ground-airborne electromagnetic methods, magnetic resonance sounding (MRS), surface-borehole transient electromagnetic method, surface-borehole seismic methods, and seismic while tunneling technology. The application prospects of these methods are discussed, and the results of this study are expected to considerably improve the location precision and resolution of the goaf detection on the basis of the implications of these techniques.
This study aims to determine the chromium contamination at an abandoned chemical factory by electrical resistivity tomography (ERT). Five ERT survey lines were conducted in the main production plant and two boreholes were drilled to collect soil samples for soil analysis. The 2D and 3D resistivity model were constructed to evaluate the pollution plumes. The ERT results showed that seven low-resistivity zones are observed in the 2D resistivity profiles, which may indicate the main pollution areas at the site. The 3D electrical resistivity model further showed that the soil pollution is more severe in the southwest than in the other areas of the site. The ERT results were partly verified by chemical analysis of soil samples. These ERT results can be further used for additional designs of soil and groundwater sampling.
The geotechnical properties of unconsolidated geo-materials such as soils are influenced by modifications of their micro-structure, texture, mineralogy, water content and imposed effective stress levels. Fundamental relations between the characteristic electrical parameters describing the electrical responses soils based on a fractal power law model with scaling properties, and parameters influencing their geotechnical behavior are investigated. Low frequency electrical conductivity laboratory measurements were performed on sand and clay mixtures subjected to varying effective stress levels with concurrent measurements of their geotechnical properties. The conductivity spectra of the mixtures were described using a Jonschcr fractal power law model characterized with three characteristic parameters, the dc conductivity (sigma(dc)), the characteristic frequency (f(c)) and an exponent (n). Changes in effective stress, water content, clay content, and other engineering properties of the mixture such as dry density, porosity, pore size and intergranular void ratio are discussed with respect to changes in the electrical parameters. The dc conductivity and characteristic frequency decrease with an increase in effective stress levels. The exponent, however, has the opposite behavior and increases with an increase in effective stress. As the water content increases, sigma(dc) and f(c) increase while n decreases for all mixtures. With increasing stress levels, the average pore size of the mixtures decreases which results in a decrease in sigma(dc) and f(c) but an increase in the values of the exponent. An increase in dry density of the mixtures leads to a decrease in sigma(dc) and f(c) whilst n increases. Both sigma(dc) and f(c) increase with increase in the intergranular void ratio of the mixture whilst the exponent values decrease with an increase in the intergranular void ratio. This study serves as a contribution to our quest in utilizing electrical geophysical methods, to assess and monitor non-invasively, the geotechnical properties of the subsurface in a less expensive and faster manner.