Subsurface Imaging Research Articles

Subsurface imaging dataset acquired at the Garner Valley Downhole Array site using a dense network of three-component nodal stations

There is a growing need to characterize the engineering material properties of the shallow subsurface in three dimensions for advanced engineering analyses. However, imaging the near-surface in three dimensions at spatial resolutions required for such purposes remains in its infancy and requires further study before it can be adopted into practice. To enable and accelerate research in this area, we present a large subsurface imaging data set acquired using a dense network of three-component (3C) nodal stations acquired in 2019 at the Garner Valley Downhole Array (GVDA) site. Acquisition of this data set involved the deployment of 196 stations positioned on a 14 × 14 grid with a 5 m spacing. The array was used to acquire active-source data generated by a vibroseis truck and an instrumented sledgehammer, and passive-wavefield data containing ambient noise. The active-source acquisition included 66 vibroseis and 209 instrumented sledgehammer source locations. Multiple source impacts were recorded at each source location to enable stacking of the recorded signals. The active-source recordings are provided in terms of both raw, uncorrected units of counts and corrected engineering units of meters per second. For each source impact, the force output from the vibroseis or instrumented sledgehammer was recorded and is provided in both raw counts and engineering units of kilonewtons. The passive-wavefield data include 28 h of ambient noise recorded over two nighttime deployments. The data set is shown to be useful for active-source and passive-wavefield three-dimensional imaging and other subsurface characterization techniques, which include horizontal-to-vertical spectral ratios (HVSRs), multichannel analysis of surface waves (MASW), and microtremor array measurements (MAM).

A Novel, Efficient Algorithm for Subsurface Radar Imaging below a Non-Planar Surface.

In classical radar imaging, such as in Earth remote sensing, electromagnetic waves are usually assumed to propagate in free space. However, in numerous applications, such as ground penetrating radar or non-destructive testing, this assumption no longer holds. When there is a multi-material background, the subsurface image reconstruction becomes considerably more complex. Imaging can be performed in the spatial domain or, equivalently, in the wavenumber domain (k-space). In subsurface imaging, to date, objects with a non-planar surface are commonly reconstructed in the spatial domain, by the Backprojection algorithm combined with ray tracing, which is computationally demanding. On the other hand, objects with a planar surface can be reconstructed more efficiently in k-space. However, many non-planar surfaces are partly planar. Therefore, in this paper, a novel concept is introduced that makes use of the efficient k-space-based reconstruction algorithms for partly planar scenarios, too. The proposed algorithm forms an image from superposing sub-images where as many image parts as possible are reconstructed in the wavenumber domain, and only as many as necessary are reconstructed in the spatial domain. For this, a segmentation scheme is developed to determine which parts of the image volume can be reconstructed in the wavenumber domain. The novel concept is verified by measurements, both from monostatic synthetic aperture radar data and multiple-input-multiple-output radar data. It is shown that the computational efficiency for imaging irregularly shaped geometries can be significantly augmented when applying the proposed concept.

Transdimensional ambient-noise surface wave tomography of the Reykjanes Peninsula, SW Iceland

SUMMARY Ambient noise seismic tomography has proven to be an effective tool for subsurface imaging, particularly in volcanic regions such as the Reykjanes Peninsula (RP), SW Iceland, where ambient seismic noise is ideal with isotropic illumination. The primary purpose of this study is to obtain a reliable shear wave velocity model of the RP, to get a better understanding of the subsurface structure of the RP and how it relates to other geoscientific results. This is the first tomographic model of the RP which is based on both on- and off-shore seismic stations. We use the ambient seismic noise data and apply a novel algorithm called one-step 3-D transdimensional tomography. The main geological structures in the study area (i.e. covered by seismic stations) are the four NE–SW trending volcanic systems, orientated highly oblique to the plate spreading on the RP. These are from west to east; Reykjanes, Eldvörp-Svartsengi, Fagradalsfjall and Krýsuvík, of which all except Fagradalsfjall host a known high-temperature geothermal field. Using surface waves retrieved from ambient noise recordings, we recovered a 3-D model of shear wave velocity. We observe low-velocity anomalies below these known high-temperature fields. The observed low-velocity anomalies below Reykjanes and Eldvörp-Svartsengi are significant but relatively small. The low-velocity anomaly observed below Krýsuvík is both larger and stronger, oriented near-perpendicular to the volcanic system, and coinciding well with a previously found low-resistivity anomaly. A low-velocity anomaly in the depth range of 5–8 km extends horizontally along the whole RP, but below the high-temperature fields, the onset of the velocity decrease is shallower, at around 3 km depth. This is in good agreement with the brittle–ductile transition zone on the RP. In considerably greater detail, our results confirm previous tomographic models obtained in the area. This study demonstrates the potential of the entirely data-driven, one-step 3-D transdimensional ambient noise tomography as a routine tomography tool and a complementary seismological tool for geothermal exploration, providing an enhanced understanding of the upper crustal structure of the RP.

2D Marine Seismic data Analysis Using Comparison of Kirchhoff’s Migration Method and Finite Difference Method (Case Study: Nias Basin, North Sumatera)

Seismic migration is one of the important stages in seismic data processing which aims to map seismic events to their actual positions. The migration process used in this study is post-stack time migration in the time domain using the Kirchhoff migration technique and the finite difference method to determine the results of subsurface imaging from the two migration techniques and then compare them to determine the accuracy of selecting the appropriate migration for the L08 basin trajectory research area. Nias basin, North Sumatra. The processing steps are carried out according to the preprocessing to processing stages in the Promax 5000 software. Based on the results of the study, the optimum use of aperture migration in Kirchhoff migration will produce good subsurface cross-sectional imaging. The aperture value used is 3000 ms. In the finite difference migration subsurface imaging is much more focused with a time step variation of 10 ms, whose function is to focus the hyperbolic diffraction energy on the migration data.

New wiggles from old cables: Acquisition, cable, and data aspects

Seismic imaging is essential for detailed characterization and understanding of the subsurface. Traditionally, marine seismic data have been acquired either using towed streamers or ocean-bottom receivers. Distributed acoustic sensing (DAS) is a novel and fast-emerging technology that makes it possible to use fiber-optic cables for acoustic measurements. The technology turns the fiber-optic cable into a densely sampled receiver array. A controlled source experiment comparing DAS and conventional towed streamer data for seismic imaging purposes is described. An existing 130 km telecommunication fiber-optic cable was interrogated to acquire DAS data to analyze the signal at long distances and for subsurface imaging. A seismic source vessel was used to create seismic data along the full cable length, while at the same time acquiring conventional towed streamer data for comparison. In addition, the telecommunication fiber-optic cable was used to acquire passive DAS data. The results show that seismic signals in the telecommunication fiber-optic cable are detectable at distances above 100 km from the source point. Furthermore, comparisons of the DAS data and towed streamer data show that the DAS technology allows for the acquisition of large offset seismic data that are comparable with conventional seismic data. Analysis of the passive DAS data shows that the infragravity waves correlate with the observed weather conditions during the acquisition.

Induced Seismicity Hazard Assessment for a Potential CO2 Storage Site in the Southern San Joaquin Basin, CA

California’s Central Valley offers vast opportunities for CO2 storage in deep saline aquifers. We conducted an induced seismicity hazard assessment for a potential injection site in the southern San Joaquin Basin for 18 years of injection at 0.68 MtCO2/yr and 100 years of monitoring. We mapped stress, faults, and seismicity in a 30 km radius around the site to build a geomechanical model and resolve the stresses on major faults. From a 3D hydromechanical simulation of the CO2 plume, we calculated the change in pressure over time on these faults and determined the conditions for safe injection. Lacking any subsurface imaging, we also conducted a probabilistic fault slip analysis using numerous random distributions of faults and a range of geomechanical parameters. Our results show that the change in probability of fault slip can be minimized by controlling the size, migration, and magnitude of the pressure plume. We also constructed a seismic catalog for the last 20 years around the site and characterized the natural patterns of seismicity. We use these results to establish criteria for evaluating potential-induced events during the storage period and to develop a traffic light response system. This study represents a first-order procedure to evaluate the seismic hazards presented by CO2 storage and incorporate uncertainties in hydrological and geomechanical parameters.

Reducing Numerical Dispersion with High-Order Finite Difference to Increase Seismic Wave Energy

The numerical dispersion of 2D acoustic wave modeling has become an interesting subject in wave modeling in producing better subsurface images. Numerical dispersion is often caused by error accumulation with increased grid size in wave modeling. Wave modeling with high-order finite differences was carried out to reduce the numerical error. This study focused on variations in the numerical order to suppress the dispersion due to numerical errors. The wave equation used in modeling was discretized to higher orders for the spatial term, while the time term was discretized up to the second order, with every layer unabsorbed. The results showed that high-order FD was effective in reducing numerical dispersion. Thus, subsurface layers could be distinguished and observed clearly. However, from the modeling results, the wave energy decreased with increasing distance, so the layer interfaces were unclear. To increase the wave energy, we propose a new source in modeling. Furthermore, to reduce the computational time we propose a proportional grid after numerical dispersion has disappeared. This method can effectively increase the energy of reflected and transmitted waves at a certain depth. The results also showed that the computational time of high-order FD is relatively low, so this method can be used in solving dispersion problems.

Imaging Subsurface Channels within the Tertiary Niger Delta Basin using Spectral Decomposition Methods

Abstract Channels are hydrocarbon prospective areas which are often below the resolution of seismic data. This study was therefore conducted with the aim of using spectral decomposition methods for imaging of buried channels and associated structures in a 3D Post-Stack Depth Migrated (PSDM) volume acquired from a field in the Niger Delta Basin. Two commonly used spectral decomposition methods were used to enhance the resolution of seismic data for interpretation. The methods utilized included Fast Fourier Transform (FFT) and Continuous Wavelet Transform (CWT). Petrel and Opendtect were the interpretational software tools utilized for the study. The seismic data was conditioned using structural smoothing, and a zone of interest was selected around -1000 to -3000ms. Three dominant frequencies were selected from the sub-volume generated around the zone of interest. The frequencies were 10Hz, 25Hz and 32Hz respectively. These frequencies were extracted from the seismic data using FFT and CWT decomposition methods. The results were colored using Red, Green and Blue (Red for 10Hz, Green for 25Hz and Blue for 32Hz). These frequencies were then blended together in a process called RGB blending. The resultant output was a mix of only these three dominant frequencies. Analysis of these results revealed the presence of several channels, crevasse splay deposits, flood-plains and faults on two time-slices obtained at -2020ms and -1800ms. The channels were meandering channels of low sinuosity, some of which were fault controlled. The crevasse splay deposits were significantly large and increased in number at the shallow time-slice. Some of the crevasse splay deposits were found bifurcating fault lines and being deposited on floodplains, indicating that they were younger than the faults. Channel flow direction was from East to West, while channel migration was from South to North of the study area. The increase in the number of channels from the base to the top of the seismic data suggested a multistory stacked channel system. It was established that channels and crevasse splays were best enhanced using the FFT decomposition method while major and minor faults were best enhanced using CWT method. Hence, this study has proven that the spectral decomposition method is very effective in imaging subsurface buried channels, thus delineating prospects and can be used for reservoir characterization. Keywords: Spectral decomposition, Fast Fourier Transform (FFT), Continuous Wavelet Transform (CWT), Channels, Crevasse splays, Faults, Reservoir Characterization.

Improvement of LED-based photoacoustic imaging using lag-coherence factor (LCF) beamforming.

Owing to its portability, affordability, and energy-efficiency, LED-based photoacoustic (PA) imaging is increasingly becoming popular when compared to its laser-based alternative, mainly for superficial vascular imaging applications. However, this technique suffers from low SNR and thereby limited imaging depth. As a result, visual image quality of LED-based PA imaging is not optimal, especially in sub-surface vascular imaging applications. Combination of linear ultrasound (US) probes and LED arrays are the most common implementation in LED-based PA imaging, which is currently being explored for different clinical imaging applications. Traditional delay-and-sum (DAS) is the most common beamforming algorithm in linear array-based PA detection. Side-lobes and reconstruction-related artifacts make the DAS performance unsatisfactory and poor for a clinical-implementation. In this work, we explored a new weighting-based image processing technique for LED-based PAs to yield improved image quality when compared to the traditionalmethods. We are proposing a lag-coherence factor (LCF), which is fundamentally based on the combination of the spatial auto-correlation of the detected PA signals. In LCF, the numerator contains lag-delay-multiply-and-sum (DMAS) beamformer instead of a conventional DAS beamformer. A spatial auto-correlation operation is performed between the detected US array signals before using DMAS beamformer. We evaluated the new method on both tissue-mimicking phantom (2D) and human volunteer imaging (3D) data acquired using a commercial LED-based PA imagingsystem. Our novel correlation-based weighting technique showed LED-based PA image quality improvement when it is combined with conventional DAS beamformer. Both phantom and human volunteer imaging results gave a direct confirmation that by introducing LCF, image quality was improved and this method could reduce side-lobes and artifacts when compared to the DAS and coherence-factor (CF) approaches. Signal-to-noise ratio, generalized contrast-to-noise ratio, contrast ratio and spatial resolution were evaluated and compared with conventional beamformers to assess the reconstruction performance in a quantitative way. Results show that our approach offered image quality enhancement with an average signal-to-noise ratio and spatial resolution improvement of around 20% and 25% respectively, when compared with conventional CF based DASalgorithm. Our results demonstrate that the proposed LCF based algorithm performs better than the conventional DAS and CF algorithms by improving signal-to-noise ratio and spatial resolution. Therefore, our new weighting technique could be a promising tool to improve the performance of LED-based PA imaging and thus accelerate its clinicaltranslation.

Microseismic Data-Direct Velocity Modeling Method Based on a Modified Attention U-Net Architecture

In microseismic monitoring, the reconstruction of a reliable velocity model is essential for precise seismic source localization and subsurface imaging. However, traditional methods for microseismic velocity inversion face challenges in terms of precision and computational efficiency. In this paper, we use deep learning (DL) algorithms to achieve precise and efficient real-time microseismic velocity modeling, which holds significant importance for ensuring engineering safety and preventing geological disasters in microseismic monitoring. Given that this task was approached as a non-linear regression problem, we adopted and modified the Attention U-Net network for inversion. Depending on the degree of coupling among microseismic events, we trained the network using both single-event and multi-event simulation records as feature datasets. This approach can achieve velocity modeling when dealing with inseparable microseismic records. Numerical tests demonstrate that the Attention U-Net can automatically uncover latent features and patterns between microseismic records and velocity models. It performs effectively in real time and achieves high precision in velocity modeling for Tilted Transverse Isotropy (TTI) velocity structures such as anticlines, synclines, and anomalous velocity models. Furthermore, it can provide reliable initial models for traditional methods.

Pseudo-3D cubes from densely spaced subbottom profiles via projection onto convex sets interpolation: An open-source workflow applied to a pockmark field

High-resolution subbottom profiler (SBP) data are commonly recorded during academic or industrial surveys and analyzed as 2D profiles. However, there is growing interest in 3D imaging of the shallow seafloor subsurface, e.g., site surveys prior to the installation of offshore wind farms. Despite ongoing advancements in 3D systems, SBPs continue to be used mainly for 2D profiling. In other seismic imaging applications, “pseudo-3D” seismic cubes have been successfully generated from dense 2D seismic surveys. We developed a novel open-source Python-based workflow to interpolate densely spaced 2D SBP profiles acquired with a hull-mounted parametric SBP into pseudo-3D cubes. This workflow is applied to a study area on the Chatham Rise east of New Zealand’s South Island, comprising numerous seafloor pockmarks and subsurface paleo-pockmarks. Our workflow consists of two stages: (1) processing of individual 2D profiles to compensate for existing vertical offsets and (2) sparse data interpolation by applying the iterative projection onto convex sets algorithm. We correct the residual static effect caused by the sea state during acquisition, compensate for the varying tidal elevations, and apply vertical time shifts to individual profiles to correct misties at profile intersections. The interpolation of the binned sparse 3D cube is performed in the frequency domain using the fast Fourier transform and executed in parallel processes, which significantly increases the computational efficiency. We validate our workflow by testing different bin sizes, sparse transforms, thresholding approaches, and varying total iterations, which noticeably impact the resulting interpolation quality. Our developed workflow generates pseudo-3D subsurface images from densely spaced SBP profiles, with numerous potential applications for academic and industrial surveys.

Non invasive subsurface imaging to investigate the site evolution of Machu Picchu

The construction history of a site is partially preserved underground and can be revealed through archaeological investigations, including excavations, integrated with earth observation (EO) methods and technologies that make it possible to overcome some operational limits regarding the areal dimensions and the investigation depths along with the invasiveness of the excavations themselves. An integrated approach based on EO and archaeological records has been applied to improve the knowledge of Machu Picchu. The attention has been focused on the first construction phase of Machu Picchu, and for this reason the investigations were directed to the imaging and characterization of the subsoil of the Plaza principal, considered the core of the whole archaeological area. Archaeological records and multiscale remote sensing (including satellite, UAS, and geophysical surveys) enabled the identification and characterization of the first construction phase of the site, including the preparation phases before building Machu Picchu. The interpretative hypothesis on the constructive history of Machu Picchu started from the identification and use of the quarry, followed by the planification and set of the drainage systems and by the next steps based on diverse reshaping phases of what would be the central plaza.

Towards the usage of quarry blasts as an active seismic source for subsurface characterization and imaging

SUMMARY Active or man-made seismic sources are often used to delineate subsurface geological structures via seismic imaging techniques. Although conventional controlled seismic sources have provided high-resolution subsurface images, the high cost of data acquisition necessitates improved use of cheaper alternative seismic sources for subsurface imaging, such as traffic noise, quarry blasts and earthquakes. Here, we explore the potential use of quarry blasts as an active seismic source for subsurface imaging. The goal of our study is to demonstrate the utility of quarry blasts as seismic sources for investigating subsurface structure with a field experiment in Mill Creek, southern Oklahoma. We deployed a 7455-m-long receiver line of 72 receivers (105 m spacing) extending away from a quarry, with a recording time of 28 d. We analyse similarities between blasts, wave types, origin time and excitation location of quarry blasts, which is important information for using such signal as an active source. Given a relative homogeneous geological condition in the study area, we could not observe clear reflected waves. However, the use of P- and S-wave velocities led to the delineation of a major basement damage zone in the study area, which further demonstrates the viability of quarry blasts as a useful seismic source for subsurface geological imaging.

Shear-wave velocity imaging of weathered granite in La Campana (Chile) from Bayesian inversion of micro-tremor H/V spectral ratios

Subsurface imaging of the regolith layer is an important tool for weathering zone characterization. For example, the extent of bedrock modification by weathering processes can be modelled by means of differing seismic velocities. We acquired a 360 m-long seismic profile in central Chile to characterise weathering at a semi-arid site. We used 87 3-component geophones, which continuously recorded ambient seismic noise for three days. The seismic line was centered at an 88 m deep borehole, providing core and downhole logging data for calibration. We extract Horizontal-to-Vertical Spectral Ratio (HVSR) curves along the seismic line to image the subsurface. Temporal analysis of the HVSR curves shows that the ambient noise vibrations recorded during the nighttime provide more stable HVSR curves. The trans-dimensional Bayesian Markov chain Monte Carlo (McMC) approach was used to invert the micro-tremor HVSR curves at each station to reconstruct 1D shear-wave velocity (Vs) models. The resulting individual 1D Vs models were merged to create a 2D Vs model along the linear seismic array in La Campana. The resulting Vs model shows an increase from 0.85 km/s at the surface to ca. 2.5 km/s at 100 m depth. We use the interface probability as a by-product of the Bayesian inversion to apply a more data-driven approach in identifying the different weathering layers. This method identified the boundary between saprolite and fractured bedrock at 42 m depth at the borehole, as evidenced by the interpretation of downhole logging data such as magnetic susceptibility. The resulting 2D Vs model of this site in Mediterranean climate shows a strong correlation between the interpreted weathering front at around 90-m depth and a higher precipitation rate in the study site compared to arid sites. The horizontal alignment of the weathering front indicates a correlation between the weathering front depth with topography and fractures in the bedrock.

Reconstruction of Holocene relative sea-level from beach ridges of the central west coast of India using GPR and OSL dating

The Holocene sea-level and associated shoreline regression of beach ridges in the central west coast of India have been reconstructed based on internal sedimentary architecture and luminescence chronology. For this purpose, various techniques namely ground penetrating radar (GPR), optically-stimulated luminescence (OSL) dating, and interferometry synthetic aperture radar (InSAR) have been used. The berm and beach-dune boundary of paleo beach ridges have been mapped from the high-resolution sub-surface images and converted into sea-level indicators using modern analogs and OSL ages. GPR reflection data shows a number of seaward dipping radar facies with a few landward dipping facies in paleo beach ridges. In the case of the swale, radar signal has been highly attenuated due to the presence of water and mud causing the appearance of multiple horizontal and parallel positive and negative couplets in the sedimentary layer. The results of the research reveal that the oldest beach ridge was formed around 7.7 kyr BP and sea-level was +2 m above mean sea-level. The average progradation rate of these ridges is 0.14 m/yr. From the grain size analysis, it has been found that the larger share of grain size falls into the classes of fine and moderate sand. The present displacement map of the region, which has been generated from the Sentinel-1 datasets, demonstrates that the average upliftment is 2.5 mm/yr whereas subsidence is 1 mm/yr. The fall of the Holocene relative sea-level with respect to the study region is the consequence of both global and regional events.

The effect of current and lambda on white-etch-crack failures

White etching cracks (WECs) have been associated with premature failure of wind turbine roller bearings. Various drivers for the generation of WECs have been identified such as loading conditions, slip, steel quality, lubrication, hydrogen embrittlement, corrosion fatigue cracking, and stray electrical currents passing through the surface. In this work, a benchtop test rig utilizing a three-ring-on-roller test configuration was used to investigate the effect of electrical current and operation in different lubricating regimes, defined by lambda (λ), on high-quality bearing steel samples tested in a commercially available power transmission EP gear lubricant. It was observed that there is an inverse correlation between the magnitude of electric current applied to the ring/roller system and time-to-failure. Higher current magnitudes lead to shorter time-to-failure than lower current magnitudes, with macropitting as the main failure mode. Sub-surface investigation revealed the presence of WECs in all cases. For the same current magnitude, tests conducted in boundary and mixed lubrication regimes showed that time-to-failure increased as λ increased, and the tests resulted in WEC related macropits, whereas tests conducted in near-hydrodynamic regime resulted in surface damage with no macropit. It was also noted that a shift toward near-hydrodynamic lubrication resulted in a distinct surface distress on the roller surface. Furthermore, there seems to be a transition in the mixed regime during which the surface distress occurred. The damage on the surface of the test samples resembled non-spatially, periodic, groove-like corrugations and, in some cases, crater-like depressions. Sub-surface imaging, performed by sequential sectioning, revealed the presence of WECs in all cases, and broad, branching cracks that were more prevalent under the more severe boundary conditions.

Robust low-rank diffraction separation and imaging by CUR matrix decomposition

Diffractions from underground discontinuities, which appear as common wavefields in seismic records, contain rich geologic information regarding small-scale structures. As a result of their weak amplitude characteristics, a key preliminary task in imaging subsurface inhomogeneities using seismic diffractions is to simultaneously eliminate strong reflections and separate weak diffractions. Traditional low-rank diffraction separation methods predict linear reflections and separate diffractions by applying a low-rank approximation, such as truncated singular value decomposition (TSVD). However, these methods require the accurate estimation of the rank, which influences the separation and imaging quality of diffractions. A robust low-rank diffraction separation method is developed using CUR matrix decomposition rather than the TSVD calculation to avoid the rank estimate. CUR matrix decomposition expresses a data matrix as a product of the matrices [Formula: see text], [Formula: see text], and [Formula: see text] by randomly selecting a small number of actual columns and rows from the matrix to achieve a low-rank approximation. A near-optimal sampling algorithm is used to randomly select columns and rows from the Hankel matrix and calculate the CUR decomposition. Oversampling of columns and rows effectively eliminates the requirement for an accurate rank. Moreover, synthetic and field applications demonstrate the good performance of our CUR-based diffraction separation method in attenuating reflections and highlighting diffractions.

Frequency domain electromagnetic calibration for improved detection of sand intrusions in river embankments

Sand intrusions pose significant risks to river embankments due to potential flow pathways that can lead to instability during flood events. Visual inspection is a first step to recognize critical segments, but it does not deliver information about the subsurface. In this context, the electromagnetic induction (EMI) technique is a useful method for preliminary zoning at regional scale while the electrical resistivity tomography (ERT) method, widely used for hydrological purposes, is considered among the most reliable techniques for local subsurface imaging. A major sand intrusion within the levees of the Brenta River, located near Venice (northern Italy), resulted in water seeping during seasonal floods and posed severe threats to embankment stability. ERT and EMI techniques, along with geotechnical investigations, were the best survey choices to address the problem. Resistivity profiling successfully imaged the sand body geometry within and underneath the levee, and results correlated nicely with borehole stratigraphy. A first multiarray EMI device, which represented a faster and less expensive survey, was deployed to map further anomalies along nearby levees, but results were not satisfactory because the inverted profile failed to image the known intrusion. A second multiarray EMI device, with larger coil spacing, was also tested. Although it performed better in detecting the intrusion, results were still below expectations. A calibration procedure based on Pearson's coefficients and using ERT as a reference was then devised and implemented to correct the EMI data prior to carrying out inversion. The procedure was successful for both EMI data sets, leading to realistic subsurface resistivity in the inverted sections. EMI measurements could then be recovered and interpreted correctly to estimate subsurface textures. The possibility of calibrating EMI data and obtaining subsurface resistivity images comparable to standard ERT profiling is an important improvement for cost-effective EMI surveying of river embankments to mitigate flood hazards.

An improved reverse time migration for subsurface imaging over complex geological structures: A numerical study

In seismic exploration, it is a critical task to image and interpret different seismic signatures over complex geology due to strong lateral velocity contrast, steep reflectors, overburden strata and dipping flanks. To understand the behavior of these seismic signatures, nowadays Reverse Time Migration (RTM) technique is used extensively by the oil & gas industries. During the extrapolation phase of RTM, the source wavefield needs to be saved, which needs high storage memory and large computing time. These two are the main obstacles of RTM for production use. In order to overcome these disadvantages, in this study, a second-generation improved RTM technique is proposed. In this improved form, a shift operator is introduced at the time of imaging condition of RTM algorithm which is performed automatically both in space and time domain. This effort is made to produce a better-quality image by minimizing the computational time as well as numerical artefacts. The proposed method is applied over various benchmark models and validated by implementing over one field data set from the Jaisalmer Basin, India. From the analysis, it is observed that the method consumes a minimum of 45% less storage space and reduce the execution time by 20%, as compared to conventional RTM. The proposed RTM is found to work efficiently in comparison to the conventional RTM both in terms of imaging quality and minimization of numerical artefacts for all the benchmark models as well as field data.

Contrast Source Inversion-Enhanced Synthetic Aperture Approach for Microwave Multilayered Subsurface Imaging

Contrast Source Inversion-Enhanced Synthetic Aperture Approach for Microwave Multilayered Subsurface Imaging