The front matter contains the title page, copyright page, table of contents, and preface.

Abstract Joint inversion of crosshole ground-penetrating radar and seismic data can improve model resolution and fidelity of the resultant individual models. Model coupling obtained by minimizing or penalizing some measure of structural dissimilarity between models appears to be the most versatile approach because only weak assumptions about petrophysical relationships are required. Nevertheless, experimental results and petrophysical arguments suggest that when porosity variations are weak in saturated unconsolidated environments, then radar wave speed is approximately linearly related to seismic wave speed. Under such circumstances, model coupling also can be achieved by incorporating cross-covariances in the model regularization. In two case studies, structural similarity is imposed by penalizing models for which the model cross-gradients are nonzero. A first case study demonstrates improvements in model resolution by comparing the resulting models with borehole information, whereas a second case study uses point-spread functions. Although radar seismic wave-speed crossplots are very similar for the two case studies, the models plot in different portions of the graph, suggesting variances in porosity. Both examples display a close, quasilinear relationship between radar seismic wave speed in unconsolidated environments that is described rather well by the corresponding lower Hashin-Shtrikman (HS) bounds. Combining crossplots of the joint inversion models with HS bounds can constrain porosity and pore structure better than individual inversion results can.

Abstract Near-surface shear-wave (S-wave) velocities and quality factors are key parameters for a wide range of geotechnical, environmental, and hydrocarbon-exploration research and applications. High-frequency Rayleigh-wave data acquired with a multichannel recording system have been used to determine near-surface S-wave velocities since the early 1980s. Multichannel analysis of surface waves —MASW — is a noninvasive, nondestructive, and cost-effective acoustic approach to estimating near-surface S-wave velocity. Inversion of high-frequency surface waves has been achieved by the geophysics research group at Kansas Geological Survey during the past 15 years, using surface-wave inversion algorithms of both a layered-earth model (commonly used in the MASW method) and a continuously layered-earth model (Gibson half-space). Comparison of the MASW results with direct borehole measurements reveals that the differences between the two are approximately 15% or less and have a random distribution. Studies show that simultaneous inversion of higher modes and the fundamental mode increases model resolution and investigation depth. Another important seismic property—quality factor ( Q )—can be estimated with the MASW method by inverting attenuation coefficients of Rayleigh waves. A practical algorithm uses the trade-off between model resolution and covariance to assess an inverted model. Real-world examples demonstrate the applicability of inverting high-frequency Rayleigh waves as part of routine MASW applications.

Abstract High-frequency surface-wave methods can provide reliable near-surface shear-wave (S-wave) velocity, which is a key parameter in many shallow-engineering applications, groundwater and environmental studies, and petroleum exploration. Recent research and key accomplishments at the China University of Geosciences at Wuhan into nearfield effects on surface-wave analysis provide not only insight into minimum-source geophone offsets required for generating high-quality surface-wave images but also provide a better understanding of the propagation characteristics of seismic wavefields through near-surface materials. New numerical modeling and dispersion-analysis algorithms are key tools used routinely in those studies. The modeling results illustrate very different energy-partitioning characteristics for Rayleigh and Love waves. Using a high-resolution linear Radon transform produces dispersion images with much better resolution and therefore represents a tool for more accurate separation and determination of phase velocities for different modes. Mode separation results in wavefield components that individually possess great potential for increasing horizontal resolution of S-wave velocity-field determinations. Amplitude corrections can significantly improve the accuracy of phase-velocity estimates from mixed-modal wavefields. Results from two simple models demonstrate how dramatic topographic changes can distort wavefields. This finding was the catalyst for suggesting that a topographic correction should be considered for surface-wave data acquired on a rugged ground surface. Phase-velocity inversion is an ill-posed problem. Rayleigh-wave sensitivity analysis reveals the difficulty in estimating S-wave velocities for a model with a low-velocity layer. Constraints in the model space are therefore necessary. Approximating cutoffs could help build a better initial model and provide critical information about the subsurface when higher modes are present.

Abstract Seismic methods are the primary characterization tools for several engineering and near-surface problems. Noninvasive and invasive methods based on the propagation of either body or surface waves are used widely. Often, more than one method is applied at the same site. In spite of possible synergies that exist between different methods, the data are often processed and interpreted independently. The integration of different data sets could provide more reliable final models and comprehensive site characterization. Acquisition can be optimized to obtain a multipurpose data set. Additional improvements might be obtained by a constrained or joint inversion of different seismic data. These can be demonstrated with real-world examples.

Abstract Much previous seismic and ground-penetrating radar (GPR) research has focused on investigating, theoretically and empirically, the relationship between the statistical characteristics of subsurface velocity heterogeneity and those of the associated surface-based reflection image. However, an effective and robust method for solving the corresponding inverse problem has not been presented. Assuming that waves are weakly scattered in the subsurface, a relatively simple relationship can be derived between the 2D autocorrelation of a geophysical reflection image and that of the underlying velocity field. A Monte Carlo inversion strategy based on this relationship can then be used to generate sets of parameters describing the autocorrelation of velocity that are consistent with recorded reflection data. Results of applying that strategy to realistic synthetic seismic and GPR data indicate that the inverse solution is inherently nonunique in that many combinations of the vertical and horizontal correlation lengths that describe the velocity heterogeneity can yield reflection images with the same 2D autocorrelation structure. However, the ratio of each of those combinations is approximately the same and corresponds to the aspect ratio of the velocity heterogeneity, which suggests that the aspect ratio is a quantity that can be recovered reliably from geophysical-reflection-survey data.

Abstract The amplitudes and phases of raw ground-penetrating-radar (GPR) data depend on the antenna radiation patterns, the vector nature of electromagnetic (EM) wave propagation, and the EM properties of the subsurface. Migrated GPR data should accurately represent the subsurface EM property contrasts alone. To achieve this, migration algorithms must explicitly account for the radiation patterns and vector wave propagation. A specific vector-migration algorithm models and corrects for exact-field radiation patterns, which include far-, intermediate-, and near-field contributions and propagation effects. When applied to GPR data containing dipping planar reflections, the algorithm produces images largely invariant to the relative orientations of the antennae and reflectors, indicating that most radiation-pattern effects are corrected for. In contrast, strongly orientation-dependent amplitudes and phases in scalar Gazdag and far-field vector images show that these algorithms do not adequately account for radiation-pattern effects. For polarization-dependent features (e.g., most underground utilities), the exact-field vector-migration algorithm produces images with orientation-dependent amplitude variations in qualitative agreement with theoretical expectations, suggesting that the algorithm may serve as a starting point for reconstructing the scattering properties of the targets. In contrast, the scalar Gazdag and far-field algorithms yield distinctly false amplitude variations.

Abstract A novel approach can be used to simulate porosity fields constrained by borehole-radar tomography images. The cornerstone of the method is statistical analysis of the approximation wavelet coefficients of a petrophysical analog scenario. The method is tested with a 2D synthetic porosity field generated from a digital picture of a real sand deposit. The porosity field is translated into electrical properties and a crosshole tomography synthetic survey is built using a finite-difference modeling algorithm. Hereafter, this synthetic survey is considered as the measured one. In parallel, an analog deposit is created based on geologic knowledge of the area under study. The analog porosity field is converted into electrical property fields using the same equation. A synthetic ground-penetrating-radar (GPR) tomography also is computed from the latter. Then, wavelet decomposition of both measured and analog tomography and porosity analog fields is calculated. Based on the assumption that geophysical data carry essentially large-scale information about the geology, statistical analysis of the approximation wavelet coefficients of each variable is carried out. From measured tomographic approximation coefficients and cross statistics evaluated on the analogs, approximation of the real porosity field is inferred. Finally, based on the statistical relationships between wavelet coefficients across the different scales, all porosity wavelet-detail coefficients are simulated using a standard geostatistical cosimulation algorithm. The wavelet coefficients then are back-transformed in the porosity space. The final simulated porosity fields contain the large wavelengths of the measured radar tomographic images and the texture of the analog porosity field.

Abstract The magnitude and temporal changes of in situ horizontal stress at shallow depths in the subsoil are crucial information in geotechnical engineering. Although various methods of monitoring in situ horizontal stress have shown some success, such monitoring remains extremely challenging, especially for sands and stiff clays, and large uncertainties are usual. Laboratory experiments are performed that involve realistic values of stress and porosity, combined with seismic-array data acquisition, to monitor changes in shear-wave velocity ( V S ) induced solely by changes in horizontal stress. Seismic-array data have been instrumental in distinguishing the small velocity changes associated with horizontal stress changes. Stress-porosity empirical models and micromechanical models have predicted quite accurately the observed trend of variation in V S as a function of horizontal stress. This trend is unique for a given combination of vertical stress, porosity, and soil type. Therefore, by monitoring the temporal change of V S by means of a seismic receiver array fixed at a given depth range and then by using the velocity–horizontal stress trend predicted by the model, one can estimate the temporal change and magnitude of in situ effective horizontal stress. A data-driven inversion approach has been tested on laboratory-experiment data for which the effective horizontal stress is known. The results demonstrate the possibility of estimating in situ effective horizontal stress at a given depth in subsoil, with an uncertainty of less than 15–20%, even when the porosity, vertical stress, and field factor are unknown. This approach shows potential for use on real field data.

Abstract Modern slim-hole sonic-logging tools designed for surficial environmental and engineering applications allow for measurements of the phase velocity and the attenuation of P-waves at multiple emitter frequencies over a bandwidth covering five to 10 octaves. One can explore the possibility of estimating the permeability of saturated surficial alluvial deposits based on the poroelastic interpretation of the velocity dispersion and frequency-dependent attenuation of such broadband sonic-log data. Methodological considerations indicate that for saturated, unconsolidated sediments in the fine silt to coarse sand range and typical nominal emitter frequencies ranging from approximately 1 to 30 kHz, the observable P-wave velocity dispersion should be sufficiently pronounced to allow for reliable first-order estimations of the underlying permeability structure based on the theoretical foundation of poroelastic seismic-wave propagation. Theoretical predictions also suggest that the frequency-dependent attenuation behavior should show a distinct peak and detectable variations for the entire range of unconsolidated lithologies. With regard to the P-wave velocity dispersion, results indicate that the classical framework of poroelasticity allows for obtaining first-order estimates of the permeability of unconsolidated clastic sediments with granulometric characteristics ranging between fine silts and coarse sands. The results of attenuation measurements are more difficult to interpret because the inferred attenuation values are systematically higher than the theoretically predicted ones, and the form of their dependence on frequency is variable and is only partially consistent with theoretical expectations.

Abstract On a 2D profile of subsurface permittivity structure derived from guided GPR pulses recorded in the Kuparuk River watershed, Alaska, the transition from a stream channel to a peat layer is interpreted. Although multi-channel data are used, guided waves are analyzed using single-channel analysis, which sidesteps assumptions regarding lateral homogeneity within receiver arrays. As a result, 2D structure is obtained along a profile using an inversion procedure. These data were processed in three steps: (1) picking group traveltimes, (2) performing tomography in the lateral direction, and (3) inverting local group-velocity dispersion curves. When the permittivity profile obtained from the guided waves is compared to a GPR reflection profile, it is clear that the guided waves capture shallow structure near a stream channel that is not imaged accurately on the reflection profile. This demonstrates the utility of using guided waves to provide information on shallow structure that cannot be obtained from reflections.