1,720,973 research outputs found
Automated Reflection Picking and Inversion Applied to Glaciological GPR Surveys
No full textThe purpose of this thesis is to present an automated picking and inversion procedure, which is designed to accurately and objectively identify the main reflections within Ground Penetrating Radar (GPR) data sets; to characterize them in terms of their arrival times, peak amplitudes, and polarities; and to recover from these and other quantities the internal stratigraphy and EM properties of the subsurface. In this text the main features and formulas of the developed algorithms are presented, while also highlighting both the advantages and limitations of the proposed auto-picking and inversion procedure with respect to other commonly used methods. In particular, the algorithms are tested on a synthetic GPR profile and their performance is assessed by comparing the inversion results with the initial model. The main uncertainty factors of the procedure are also analyzed, with a particular focus on sampling-related signal distortions, leading to the definition of a recommended minimum threshold for the sampling rate selected during data acquisition. The procedure is also applied to a glaciological 3-D GPR data set, in order to study the internal stratigraphy, density distribution, total volume, and water content of an alpine glacier
Automated reflection picking and polarity assessment through attribute analysis: Theory and application to synthetic and real ground-penetrating radar data
No full textWe have developed a procedure to automatically detect, pick, and characterize reflections in either seismic or ground-penetrating radar (GPR) data sets. Accurate picking results are essential in many research and application fields and are mandatory to recover the underground stratigraphy and reflectivity and, therefore, to create a more constrained subsurface model. We use the cosine of the instantaneous phase to track events with lateral phase continuity and record them in terms of time-space positions, amplitude, and polarity. Moreover, we use the cosine phase to reconstruct the shape of the reflected wavelets by averaging it along the picked horizons, to recover the initial phase of each reflection and, therefore, their polarities. By comparing the polarities of the transmitted and reflected wavelets, we can recover the impedance contrasts in the subsurface and evaluate the properties of the materials. We applied the picking and polarity assessment algorithms to a synthetic data set. We inverted the picked amplitudes and traveltimes to test the accuracy of the procedure by comparing the calculated stratigraphy and velocity distribution with the initial model. The inverted results were consistent with the original data, with most discordances in the stratigraphy within a few tens of centimeters, using a wavelet with a central frequency equal to 300 MHz. Local larger discrepancies were probably caused by interferences altering the amplitudes and resulting in the overestimation of the impedance contrasts. We also applied automatic picking and phase assessment procedures to real glaciological and archaeological GPR surveys, in which the influence of noise and diffractions was critically evaluated by comparing the picked results obtained from raw and processed data
Velocity analysis from common offset GPR data inversion: Theory and application to synthetic and real data
No full textWe implemented a procedure to estimate the electromagnetic (EM) velocity using common offset ground penetrating radar (GPR) data. The technique is based on the inversion of reflection amplitudes to compute the series of reflection coefficients used to estimate the velocity in each interpreted layer. The proposed method recursively calculates the incident angles at any interface, taking into account the offset between antennas, and needs as input, in addition to the picked amplitudes values, a reference amplitude for each analysed GPR trace and a velocity value for the first (shallowest) layer. The latter two parameters can be estimated directly from the available data or can be better constrained by further dedicated GPR acquisitions or by additional direct measurements. We critically evaluated the performances for both synthetic and real data acquired with different antenna frequencies and we demonstrated that the new method can be applied in several real situations. Despite the necessary approximations and simplifying hypotheses, the velocity values calculated for each layer are consistent with direct information and with cross-validations obtained considering profiles acquired using different antennas and various path directions. Tests of the method on synthetic and real data sets show that the errors in the calculated velocity fields are quite low and comparable with more demanding velocity analysis techniques. The obtained EM velocity field is crucial in many processing steps, such as, for example, true amplitude recovery, depth conversion and imaging, and provide essential information to characterize the subsurface materials
Automated phase attribute-based picking applied to reflection seismics
No full textWe have applied an attribute-based autopicking algorithm to reflection seismics with the aim of reducing the influence of the user’s subjectivity on the picking results and making the interpretation faster with respect to manual and semiautomated techniques. Our picking procedure uses the cosine of the instantaneous phase to automatically detect and mark as a horizon any recorded event characterized by lateral phase continuity. A patching procedure, which exploits horizon parallelism, can be used to connect consecutive horizons marking the same event but separated by noise-related gaps. The picking process marks all coherent events regardless of their reflection strength; therefore, a large number of independent horizons can be constructed. To facilitate interpretation, horizons marking different phases of the same reflection can be automatically grouped together and specific horizons from each reflection can be selected using different possible methods. In the phase method, the algorithm reconstructs the reflected wavelets by averaging the cosine of the instantaneous phase along each horizon. The resulting wavelets are then locally analyzed and confronted through crosscorrelation, allowing the recognition and selection of specific reflection phases. In case the reflected wavelets cannot be recovered due to shape-altering processing or a low signal-to-noise ratio, the energy method uses the reflection strength to group together subparallel horizons within the same energy package and to select those satisfying either energy or arrival time criteria. These methods can be applied automatically to all the picked horizons or to horizons individually selected by the interpreter for specific analysis. We show examples of application to 2D reflection seismic data sets in complex geologic and stratigraphic conditions, critically reviewing the performance of the whole process
A new fast methodology to estimate the density of frozen materials by means of common offset GPR data
No full textWe propose a methodology to estimate the density of frozen media (snow, firn and ice) using common offset (CO) GPR data. The technique is based on reflection amplitude analysis to calculate the series of reflection coef- ␣cients used to estimate the dielectric permittivity of each layer. We determine the vertical density variations for all the GPR traces by applying an empirical equation. We are thus able to infer the nature of frozen materials, from fresh snow to firn and ice. The proposed technique is critically evaluated and validated on synthetic data and further tested on real data of the Glacier of Mt. Canin (South-Eastern Alps). Despite the simplifying hypotheses and the necessary approximations, the average values of density for different levels are calculated with acceptable accuracy. The resulting large-scale density data are fundamental to estimate the water equivalent (WE), which is an essential parameter to determine the actual water mass within a certain frozen volume. Moreover, this analysis can help to find and locate debris or moraines embedded within the ice bodies
Application of attribute-based automated picking to GPR and seismic surveys
No full textWe presented a few examples of application of an automated process designed to detect and track, in an accurate and objective way, reflections inside a recorded data set by exploiting their lateral phase continuity. The results, obtained in different profiles from both reflection seismic and GPR surveys, are quite accurate, since they are able to mark most of the recorded reflections and their different phases, with only a few exceptions in more complex areas characterized by noise or interference. Although the presented examples were limited to just 2D sections, the procedure can be easily extended to 3D data sets. A few input parameters must be selected and carefully evaluated by the interpreter, nevertheless the degree of subjectivity is greatly reduced with respect to other commonly used picking algorithms, leading to a faster and more objective process. Further improvements can be achieved by using integrated attributes as additional thresholds, or by evaluating the behavior of other physical parameters, such as changes in the spectral distribution
Automated diffraction tracking and inversion for EM velocity estimation
No full textWe apply an automated diffraction tracking and inversion algorithm to oversampled GPR data sets, in order to assess the influence of time and space sampling on the resulting EM velocity model. The accuracy of such model depends on the actual presence and regular distribution of undistorted diffraction hyperbolas within the recorded CO profiles. Nevertheless, hyperbolic inversion techniques on CO data are the only alternative to amplitude inversion methods in absence of clearly defined reflections. Commonly used diffraction tracking methods include manual picking, automated hyperbola fitting, edge detection, and machine learning techniques. The presented auto-picking algorithm tracks potential diffractions by transforming the coordinates of the profile so that the hyperbolas are turned into straight lines. Through a linear fit in the transformed space, the algorithm is then able to recover the average EM velocity above the tracked diffractors. We apply the procedure on GPR data sets acquired on urban environments, observing a significant impact of both temporal and spatial sampling intervals on the resulting average EM velocities and uncertainty values
Auto-picking and phase assessment by means of attribute analysis applied to GPR pavement inspection
No full textWe propose an automated procedure, based on attribute analysis, to quickly and objectively detect and characterize reflections along GPR profiles. The process uses the cosine of the instantaneous phase to mark as a horizon any event that shows lateral phase continuity, defining its time-space positions and peak amplitudes, to be used in interpretation and inversion processes. Such attribute allows to efficiently track even the weakest events, as well as those showing large lateral amplitude variations. Furthermore, the algorithm is able to extract the polarity of each reflection, by identifying their actual initial phase. This analysis is done by assessing the behavior of the cosine phase in the vicinity of each picked horizon, searching for other sub-parallel horizons that can be grouped into the same event. The proposed procedure is mostly independent from the interpreter, except for a few required thresholds. Moreover, since it uses only the cosine phase, it can be applied to data sets after basic processing without the need of any amplitude recovery, which introduces a certain degree of subjectivity on the results and prevents further quantitative analyses and data inversion. In this paper we validate the method and discuss its accuracy, as well as its limitations and possible applications. The algorithm successfully tracked events with lateral phase continuity in the tests performed on GPR data acquired on an airport runway
The search for brines: GPR markers, proxies, and challenges
No full textGPR is one of the most applicable geophysical techniques to detect brines at shallow depths due to their peculiar electromagnetic characteristics, in particular related to overall high electrical conductivity. However, the range of chemical and physical parameters of brines is very wide and can change with time, thus making their imaging and characterization sometimes challenging.
We analyze different GPR datasets collected in continental Antarctica, focusing on amplitude and spectral behavior, also calculating several GPR attributes to detect shallow brine ponds. We show that the geophysical signature of the brines is quite elusive, being sometimes characterized by clear strong reflectors, by extremely high attenuation of the GPR signal with a remarkable spectral shift, or by high scattering.
Results are validated by ice coring, direct sampling, and by means of physical and chemical analyses of the brines. We demonstrate the existence of a relevant temporal and spatial variability of the brines, which requires integrated data analyses to achieve a robust GPR data interpretation.
The integrated study of amplitude, frequency, and phase behavior is described in detail for different case studies, always trying to get general outcomes and site-independent interpretation criteria
Automated detection and tracking of hyperbolic diffractions applied to engineering GPR data sets
No full textWe developed an algorithm to automatically detect and track hyperbolic diffractions within GPR data sets. The procedure uses the apexes as initial seeds, and also pre-estimates the widths of their hyperbolas, thus producing a more objective search window that is automatically adapted to local conditions. Within the search window, hyperbolas with varying EM velocities are fitted to the signal phases surrounding the initial seed, which are then connected to form preliminary hyperbolic paths. Among these paths, the algorithm selects the best fit by assessing several attributes, while possible false positives and redundant hyperbolas are subsequently removed. The proposed procedure can be applied with minimal signal processing, and it requires only limited input from the interpreter. The algorithm was able to accurately track most diffractions within engineering GPR data sets, with very few false positives and negatives
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