Design of multichannel nonrecursive digital filters with applications to seismic reflection data

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IVGPR: A New Program for Advanced End-To-End GPR Processing

Ground penetrating radar (GPR) processing workflows commonly rely on techniques developed particularly for seismic reflection imaging. Although this practice has produced an abundance of reliable results, it is limited to basic applications. As the popularity of GPR continues to surge, a greater number of complex studies demand the use of routines that take into account the unique properties of GPR signals. Such is the case of surveys that examine the material properties of subsurface scatterers. The nature of these complicated tasks have created a demand for GPR-specific processing packages flexible enough to tackle new applications. Unlike seismic processing programs, however, GPR counterparts often afford only a limited amount of functionalities. This work produced a new GPR-specific processing package, dubbed IVGPR, that offers over 60 fully customizable procedures. This program was built using the modern Fortran programming language in combination with serial and parallel optimization practices that allow it to achieve high levels of performance. Within its many functions, IVGPR provides the rare opportunity to apply a three-dimensional single-component vector migration routine. This could be of great value for advanced workflows designed to develop and test new true-amplitude and inversion algorithms. Numerous examples given through this work demonstrate the effectiveness of key routines in IVGPR. Additionally, three case studies show end-to-end applications of this program to field records that produced satisfactory result well-suited interpretatio

A self-supervised scheme for ground roll suppression

In recent years, self-supervised procedures have advanced the field of seismic noise attenuation, due to not requiring a massive amount of clean labeled data in the training stage, an unobtainable requirement for seismic data. However, current self-supervised methods usually suppress simple noise types, such as random and trace-wise noise, instead of the complicated, aliased ground roll. Here, we propose an adaptation of a self-supervised procedure, namely, blind-fan networks, to remove aliased ground roll within seismic shot gathers without any requirement for clean data. The self-supervised denoising procedure is implemented by designing a noise mask with a predefined direction to avoid the coherency of the ground roll being learned by the network while predicting one pixel's value. Numerical experiments on synthetic and field seismic data demonstrate that our method can effectively attenuate aliased ground roll.Comment: 19 pages, 12 figures

An overview of ground-penetrating radar signal processing techniques for road inspections

Ground-penetrating radar (GPR) was firstly used in traffic infrastructure surveys during the first half of the Seventies for testing in tunnel applications. From that time onwards, such non-destructive testing (NDT) technique has found exactly in the field of road engineering one of the application areas of major interest for its capability in performing accurate continuous profiles of pavement layers and detecting major causes of structural failure at traffic speed. This work provides an overview on the main signal processing techniques employed in road engineering, and theoretical insights and instructions on the proper use of the processing in relation to the quality of the data acquired and the purposes of the surveys

Advanced Techniques for Ground Penetrating Radar Imaging

Ground penetrating radar (GPR) has become one of the key technologies in subsurface sensing and, in general, in non-destructive testing (NDT), since it is able to detect both metallic and nonmetallic targets. GPR for NDT has been successfully introduced in a wide range of sectors, such as mining and geology, glaciology, civil engineering and civil works, archaeology, and security and defense. In recent decades, improvements in georeferencing and positioning systems have enabled the introduction of synthetic aperture radar (SAR) techniques in GPR systems, yielding GPR–SAR systems capable of providing high-resolution microwave images. In parallel, the radiofrequency front-end of GPR systems has been optimized in terms of compactness (e.g., smaller Tx/Rx antennas) and cost. These advances, combined with improvements in autonomous platforms, such as unmanned terrestrial and aerial vehicles, have fostered new fields of application for GPR, where fast and reliable detection capabilities are demanded. In addition, processing techniques have been improved, taking advantage of the research conducted in related fields like inverse scattering and imaging. As a result, novel and robust algorithms have been developed for clutter reduction, automatic target recognition, and efficient processing of large sets of measurements to enable real-time imaging, among others. This Special Issue provides an overview of the state of the art in GPR imaging, focusing on the latest advances from both hardware and software perspectives

Ultra-Shallow Imaging Using 2D & 3D Seismic Reflection Methods

The research presented in this dissertation focuses on the survey design, acquisition, processing, and interpretation of ultra-shallow seismic reflection (USR) data in two and three dimensions. The application of 3D USR methods to image multiple reflectors less than 20 m deep, including the top of the saturated zone (TSZ), a paleo-channel, and bedrock, are presented using conventional acquisition methods and a new automated method of acquiring 3D data using hydraulically planted geophones. Processing techniques that focus on near-surface problems, such as intersecting reflection hyperbolae caused by large vertical velocity changes and processing pitfalls, are also discussed. The application of AVO analysis of 2D USR data collected during a pumping test yielded amplitude variations related to the thickness of the partially saturated zone that correlated spatially and with changes in pumping. USR methods were also used to image the TSZ less than one meter deep, the shallowest TSZ reflection to date

Investigating Key Techniques to Leverage the Functionality of Ground/Wall Penetrating Radar

Ground penetrating radar (GPR) has been extensively utilized as a highly efficient and non-destructive testing method for infrastructure evaluation, such as highway rebar detection, bridge decks inspection, asphalt pavement monitoring, underground pipe leakage detection, railroad ballast assessment, etc. The focus of this dissertation is to investigate the key techniques to tackle with GPR signal processing from three perspectives: (1) Removing or suppressing the radar clutter signal; (2) Detecting the underground target or the region of interest (RoI) in the GPR image; (3) Imaging the underground target to eliminate or alleviate the feature distortion and reconstructing the shape of the target with good fidelity. In the first part of this dissertation, a low-rank and sparse representation based approach is designed to remove the clutter produced by rough ground surface reflection for impulse radar. In the second part, Hilbert Transform and 2-D Renyi entropy based statistical analysis is explored to improve RoI detection efficiency and to reduce the computational cost for more sophisticated data post-processing. In the third part, a back-projection imaging algorithm is designed for both ground-coupled and air-coupled multistatic GPR configurations. Since the refraction phenomenon at the air-ground interface is considered and the spatial offsets between the transceiver antennas are compensated in this algorithm, the data points collected by receiver antennas in time domain can be accurately mapped back to the spatial domain and the targets can be imaged in the scene space under testing. Experimental results validate that the proposed three-stage cascade signal processing methodologies can improve the performance of GPR system

Common-reflection-surface imaging of shallow and ultrashallow reflectors

We analyzed the feasibility of the common-reflection-surface (CRS) stack for near-surface surveys as an alternative to the conventional common midpoint (CMP) stacking procedure. The data-driven, less user-interactive CRS method could be more cost efficient for shallow surveys, where the high sensitivity to velocity analysis makes data processing a critical step. We compared the results for two field data sets collected to image shallow and ultrashallow reflectors: an example of shallow Pwave reflection for targets in the first few hundred meters, and an example of SH-wave reflection for targets in the first 10 m. By processing the shallow P-wave records using the CMP method, we imaged several nearly horizontal reflectors with onsets from 60 to about 250 ms. The CRS stack produced a stacked section more suited for a subsurface interpretation, without any preliminary formal and time-consuming velocity analysis, because the imaged reflectors possessed greater coherency and lateral continuity. With CMP processing of the SHwave records, we imaged a dipping bedrock interface below four horizontal reflectors in unconsolidated, very low velocity sediments. The vertical and lateral resolution was very high, despite the very shallow depth: the image showed the pinchout of two layers at less than 10 m depth. The numerous traces used by the CRS stack improved the continuity of the shallowest reflector, but the deepest overburden reflectors appear unresolved, with not well-imaged pinchouts. Using the kinematic wavefield attributes determined for each stacking operation, we retrieved velocity fields fitting the stacking velocities we had estimated in the CMP processing. The use of CRS stack could be a significant step ahead to increase the acceptance of the seismic reflection method as a routine investigation method in shallow and ultrashallow seismics