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Atmospheric and oceanic pressure perturbations deform the ground surface and the seafloor, respectively. This mechanical deformation, where the fluid perturbations propagate as plane waves, occurs not only on Earth but also on other planets/bodies with atmospheres, such as Mars, Titan and Venus. Studying this type of deformation improves our understanding of the mechanical interaction between the fluid layer (atmosphere/ocean) and the underlying solid planet/body, and aids investigation of subsurface structures. In this study, we utilize eigenfunction theory to unify existing theories for modelling this deformation and to comprehensively demonstrate possible scenarios of this deformation in homogeneous and 1-D elastic media, including static loading, air-coupled Rayleigh waves and leaky-mode surface waves. Our computations quantitatively reveal that the deformation amplitude generally decays with depth and that reducing seismic noise due to Martian atmosphere requires deploying seismometers at least 1 m beneath Martian surface. We also apply our theory to illustrate how this deformation and the corresponding air-to-solid energy conversion vary on different planetary bodies. Finally, we discuss how medium anelasticity and other factors affect this deformation. [ABSTRACT FROM AUTHOR]

Passive seismic methods in highly populated urban areas have gained much attention from the geophysics and civil engineering communities. Linear arrays are usually deployed for passive surface wave investigations because of their high convenience, and passive surface wave imaging methods commonly used for linear arrays can be grouped as non-interferometric methods (e.g. passive multichannel analysis of surface wave, refraction microtremor) and interferometric methods (e.g. multichannel analysis of passive surface waves and spatial autocorrelation). It is well known that the seismic interferometry method is able to retrieve Green's function between inter-station pairs based on passive seismic data and that is how interferometric methods work. Although non-interferometric methods are also popular and effective in near-surface seismic imaging, particularly in the geotechnical industry, there is no theoretical proof to clarify the accuracy and/or the bias of these methods. In this study, we use numerical derivations and simulations to demonstrate the underlying physics for both non-interferometric and interferometric methods, under two common noise source environments including a homogeneous source distribution and a dominant in-line source distribution. We also prove the strength of interferometric methods for accurate dispersion imaging over the non-interferometric methods, and provide a way to estimate the biases in non-interferometric measurements. Finally, we present comprehensive comparisons between different passive surface wave methods with three typical field examples considering various observation systems. [ABSTRACT FROM AUTHOR]

Seismic coda waves are commonly used in estimation of subsurface Q values and monitoring subsurface changes. Coda waves mainly consist of multiply scattered body and surface waves. These two types of waves interact with each other in the multiple scattering process, which thus leads to a spatiotemporal evolution of the body and surface wave energies. One cannot characterize the evolution because one has not fully understood the multiple scattering of the two types of waves. Thus one commonly assumes only one type of waves exists or ignores their interaction while studying the coda waves. However, neglecting the interaction leads to an incorrect energy evolution of the two types of waves and consequently biases the Q estimation or interpretation of coda wave changes for monitoring. To better understand the interaction between these waves during multiple scattering and to model the energy evolution correctly, we propose a Monte Carlo algorithm to model the multiple scattering process. We describe the physics of the scattering for the two types of waves and derive scattering properties like cross sections for perturbations in elastic properties (e.g. density, shear modulus and Lamé parameters). Our algorithm incorporates this knowledge and thus physically models the body- and surface wave energy evolution in space and time. The energy partitioning ratios between surface and body waves provided by our algorithm match the theoretical prediction based on equipartition theory. In the equipartition state, our simulation results also match Lambert's cosine law for body waves on the free surface. We discuss how the Rayleigh-to-body-wave scattering affects the energy partitioning ratios. Our algorithm provides a new tool to study multiple scattering and coda waves in elastic media with a free surface. [ABSTRACT FROM AUTHOR]

Estimation of ambient seismic source distributions (e.g. location and strength) can aid studies of seismic source mechanisms and subsurface structure investigations. One can invert for the ambient seismic (noise) source distribution by applying full-waveform inversion (FWI) theory to seismic (noise) crosscorrelations. This estimation method is especially applicable for seismic recordings without obvious body-wave arrivals. Data pre-processing procedures are needed before the inversion, but some pre-processing procedures commonly used in ambient noise tomography can bias the ambient (noise) source distribution estimation and should not be used in FWI. Taking this into account, we propose a complete workflow from the raw seismic noise recording through pre-processing procedures to the inversion. We present the workflow with a field data example in Hartoušov, Czech Republic, where the seismic sources are CO2 degassing areas at Earth's surface (i.e. a fumarole or mofette). We discuss factors in the processing and inversion that can bias the estimations, such as inaccurate velocity model, anelasticity and array sensitivity. The proposed workflow can work for multicomponent data across different scales of field data. [ABSTRACT FROM AUTHOR]

Cross-correlation-based seismic interferometry is commonly used to retrieve surface-wave Green's functions from ambient seismic noise recordings. This approach requires that seismic sources are isotropically distributed in all directions around two receivers. However, this assumption is rarely valid in practice. Thus full-waveform inversion theory has recently been applied to seismic noise cross-correlation functions, functions that include both source and structure information. Source information (e.g. location or strength) is essential for accurate structure information estimation. In this paper, we explain physically two types of source sensitivity kernels: one derived from traveltime misfits and the other derived from waveform misfits. We use these kernels for source inversion and demonstrate the benefits of using multicomponent cross-correlations in this source estimation process. [ABSTRACT FROM AUTHOR]