We investigate the scattering attenuation characteristics of the Martian crust and uppermost mantle to understand the structure of the Martian interior. We examine the energy decay of the spectral envelopes for 21 high-quality Martian seismic events from Sol 128 to Sol 500 of InSight operations. We use the model of Dainty et al. (1974b) to approximate the behavior of energy envelopes resulting from scattered wave propagation through a single diffusive layer over an elastic half-space. Using a grid search, we mapped the layer parameters that fit the observed InSight data envelopes. The single diffusive layer model provided better fits to the observed energy envelopes for High Frequency (HF) and Very High Frequency (VF) than for the Low Frequency (LF) and Broadband (BB) events. This result is consistent with the suggested source depths (Giardini et al., 2020) for these families of events and their expected interaction with a shallow scattering layer. The shapes of the observed data envelopes do not show a consistent pattern with event distance, suggesting that the diffusivity and scattering layer thickness is non-uniform in the vicinity of InSight at Mars. Given the consistency in the envelope shapes between HF and VF events across epicentral distances and the tradeoffs between the parameters that control scattering, the dimensions of the scattering layer remain unconstrained but require that scattering strength decreases with depth and that the rate of decay in scattering strength is fastest near the surface. This is generally consistent with the processes that would form scattering structures in planetary lithospheres.

The Seismic Experiment for Interior Structure (SEIS) of the mission to Mars, has been providing direct information on Martian interior structure and dynamics of that planet since it landed. Compared to seismic recordings on Earth, ground motion measurements acquired by SEIS on Mars are made under dramatically different ambient noise conditions, but include idiosyncratic signals that arise from coupling between different sensors and spacecraft components. This work is to synthesize what is known about these signal types, illustrate how they can manifest in waveforms and noise correlations, and present pitfalls in structural interpretations based on standard seismic analysis methods. We show that glitches, a type of prominent transient signal, can produce artifacts in ambient noise correlations. Sustained signals that vary in frequency, such as lander modes which are affected by variations in temperature and wind conditions over the course of the Martian Sol, can also contaminate ambient noise results. Therefore, both types of signals have the potential to bias interpretation in terms of subsurface layering. We illustrate that signal processing in the presence of identified nonseismic signals must be informed by an understanding of the underlying physical processes in order for high fidelity waveforms of ground motion to be extracted. While the origins of most idiosyncratic signals are well understood, the 2.4 Hz resonance remains debated and the literature does not contain an explanation of its fine spectral structure. Even though the selection of idiosyncratic signal types discussed in this paper may not be exhaustive, we provide guidance on best practices for enhancing the robustness of structural interpretations.

Violent, dynamic failures of rockmasses in underground mines pose significant hazards to workers and operations. Over the past several decades, hardrock mines have widely adopted seismic monitoring to help address such risks. However, coal mines, particularly those employing the longwall mining method, have struggled to implement similar monitoring strategies. This is because typical longwall mines are much larger and mine more rapidly than hardrock mines. Moreover, regulations place significant restrictions on the subsurface use of electronics in coal mines due to potentially explosive atmospheres. We present a new monitoring concept that uses distributed acoustic sensing (DAS) to turn an entire longwall face into a seismoacoustic array. After exploring the acoustic response of our sensors in the laboratory, we deployed the array at an active underground longwall mine for several days. We examine 33 events recorded by both the in-mine DAS array and a surface seismic network. We observed that the array records both seismic vibrations traveling through rock and mining equipment as well as sound waves propagating in the workings. We show that waveform moveouts are clearly visible, and that the standard deviation of the audio recordings is a straightforward yet promising metric that could help quantify burst damage. Although improvements are needed before mines can routinely use this monitoring strategy, DAS-based seismoacoustic arrays may assist in understanding coal-burst mechanisms and managing associated risks in underground longwall mines as well as enable better understanding of damage associated with dynamic failures in other underground environments.