Geoacoustic Estimation of the Seafloor Sound Speed Profile in Deep Passive Margin Setting Using Standard Multichannel Seismic Data

Seafloor geoacoustic properties are important in determining sound propagation in the marine environment, which broadly affects sub-sea activities. However, geoacoustic investigation of the deep seafloor, which is required by the recent expansion of deep-water operations, is challenging. This paper presents a methodology for estimating the seafloor sound speed, c0, and a sub-bottom velocity gradient, K, in a relatively deep-water-compacting (~1000 m) passive-margin setting, based on standard commercial 2D seismic data. Here we study the seafloor of the southeastern Mediterranean margin based on data from three commercial seismic profiles, which were acquired using a 7.2 km-long horizontal receiver array. The estimation applies a geoacoustic inversion of the wide-angle reflections and the travel times of the head waves of bending rays. Under the assumption of a constant positive K, the geoacoustic inversion converges to a unique set of parameters that best satisfy the data. The analysis of 24 measurement locations revealed an increase in the average estimates of c0 from 1537 ± 13 m s−1 to 1613 ± 12 m s−1 for seafloor depths between ~1150 m and ~1350 m. K ranged between 0.75 and 0.85 m s−1 with an average of 0.80 ± 0.035 s−1. The parameters were consistent across the different locations and seismic lines and they match the values that were obtained through depth-migration-velocity analysis and empiric relations, thereby validating our estimation methodology.

Can Identifying Discrete Behavioral Groups With Individual-Based Acoustic Telemetry Advance the Understanding of Fish Distribution Patterns?

Identifying patterns of organismal distribution can provide valuable insights for basic and applied marine and coastal ecology because understanding where animals are located is foundational to both research and science-based conservation. Understanding variation in distributional patterns can lead to a better assessment of ecological drivers and an improved ability to predict consequences of natural and altered relationships. Here, our purpose is to explore if quantifying coexisting groups of individual fish predators advances our understanding of field distribution patterns. Toward this end, we quantified locations of 59 acoustically tagged striped bass (Morone saxatilis) within a 26-stationary unit telemetry receiver array in Plum Island Estuary (PIE), MA, United States. We then used cluster analyses on spatial and temporal-spatial metrics from this dataset to (1) assess if distinct groups of individuals coexisted, (2) quantify group characteristics, and (3) test associations between groups and distribution (e.g., physical site type and region). Based on multiple lines of evidence, we identified four groups of striped bass with different space use patterns that persisted across seasons (summer and fall). Similar-sized striped bass clustered at spatial and temporal scales at which individuals within distinct groups could, and did, physically overlap. In addition, distributional groups were linked to components of physical site type and region suggesting that discrete groups of individuals can interact differently with the environment within the same ecological system. The identification of these distinct groups of individuals creates a baseline from which to explore further ecological implications of grouping behavior for research and conservation in geographically large, temporally dynamic, and spatially heterogeneous marine and coastal environments.

RF Coil Setup for 31P MRSI in Tongue Cancer in vivo at 7 T

Surgery for tongue cancer often results in a major loss in quality of life. While MRI may be used to minimise the volume of excised tissue, often the full tumour extent is missed. This tumour extent may be detected with metabolic imaging. One of the main reasons for the lack of metabolic information on tongue cancer would be the absence of an x-nuclear coil with the tongue as a focus target. Metabolic MRI through 31P MRSI is known as a powerful tool to non-invasively study elevated cell proliferation and disturbed energy metabolism in tumours. Severe magnetic field non-uniformities are inherently caused by the substantial difference in magnetic susceptibilities of tissue and air in the mouth and its environs. Despite this, the wide chemical shift dispersion of 31P could still facilitate precise detection of the cell proliferation biomarkers, phospomonoesters and diesters, as well as energy metabolites ATP, inorganic phosphate, and phosphocreatine potentially mapped over the tongue or tumour in vivo. In this study, we present the first 31P MRSI data of the human tongue in vivo from healthy volunteers and a patient with a tongue tumour at 7 T MRI using a 1H 8-channel transceiver setup placed inside a body 31P transmitter, which is able to get a uniform excitation from the tongue while providing comfortable access to the patient. In addition, a user-friendly external 31P receiver array is used to provide high sensitivity (80%) comparable to an uncomfortable inner mouth loop coil positioned on the tongue. The primary aim is the demonstration of 31P metabolite profiles in the tongue and the differences between healthy and malignant tissue. Indeed, clear elevated cell proliferation expressed as enhanced phosphomonoesters is observed in the tumour vs. the healthy part of the tongue. This can be performed within a total scan duration of 30 min, comparable to clinical scans, with a spatial resolution of 1.5 cm for the 10-min 31P MRSI scan.

Evidence of Long-Distance Coastal Sea Migration of Atlantic Salmon, Salmo Salar, Smolts from Northwest England (River Derwent).

Combining data from multiple acoustic telemetry studies has revealed that west coast England Atlantic salmon (Salmo salar L.) smolts use a northward migration pathway through the Irish Sea to reach their feeding grounds. 100 Atlantic salmon smolts were tagged in May 2020 in the River Derwent, northwest England as part of an Environment Agency/Natural England funded project. Three tagged smolts were detected on marine acoustic receivers distributed across two separate arrays from different projects in the Irish Sea. One fish had migrated approximately 262km in 10 days from the river mouth at Workington Harbour, Cumbria to the northernmost receiver array operated by the SeaMonitor project; this is the longest tracked marine migration of an Atlantic salmon smolt migrating from United Kingdom. This migrating fish displayed behaviours which resulted in fast northward migration. The remaining two fish were detected on a receiver array operated by a third project: “COMPASS”. These detections further provide evidence that migration to reach marine feeding grounds of salmon smolts from rivers draining into the Irish Sea is northerly. The pattern of these detections would not have been possible without the collaborative efforts of three distinct and separately funded projects to share data. Further work is required to fully understand migration trajectories in this species on the west coast of the British Isles.

Interferometric body-wave retrieval from ambient noise after polarization filtering: application to shallow reflectivity imaging

Interferometric retrieval of body waves from ambient noise recorded at surface stations is usually challenged by the dominance of surface-wave energy, in particular in settings dominated by anthropogenic activities (e.g., natural resource exploitation, traffic, infrastructure construction). As a consequence, ambient noise imaging of shallow structures such as sedimentary layers remains a difficult task for sparse and irregularly distributed receiver networks. We demonstrate how polarization filtering can be used to automatically extract steeply inclined P-waves from continuous three-component recordings and in turn improves passive body-wave imaging. Being a single-station approach, the technique does not rely on a dense receiver array and is therefore well suited for data collected during surveillance monitoring for tasks such as reservoir hydraulic stimulation, CO_2 sequestration, and wastewater disposal injection. We apply the method on a continuous dataset acquired in the Wellington oilfield (Kansas, US), where local and regional seismicity, and other forms of ambient noise provide an abundant source of both surface- and body-wave energy recorded at 15 short-period receivers. We use autocorrelation to derive the shallow (lt; 1 km) reflectivity structure below the receiver array and validate our workflow and results with well logs and active seismic data. Raytracing analysis and waveform modeling indicates that converted shear waves need to be taken into account for realistic ambient noise body-wave source distributions, as they can be projected on the vertical component and might lead to misinterpretation of the P-wave reflectivity structure. Overall, our study suggests that polarization filtering significantly improves passive body-wave imaging on both autocorrelation and interstation crosscorrelation. It reduces the impact of time-varying noise source distributions and is therefore also potentially useful for time-lapse ambient noise interferometry.

Comparison of Single-Well Microseismic Focal Mechanism Inversions with Different Source Models

ABSTRACT Through downhole monitoring, the focal mechanisms of microearthquakes can be quantitatively determined, thus providing valuable information for characterizing the fracturing process and the in situ stress status. The double-couple (DC) and moment tensor (MT) source models are commonly used to study microearthquakes. However, the DC model fails to include non-DC mechanisms, and MT inversion from single-well data is still challenging. One possible way to address this is using the shear–tensile general dislocation (GD) source model. We provide a detailed comparison of the DC, GD, and MT models, and introduce the differences in their modeling and inversion theories. These three models are described by four, five, and six parameters, and correspond to a single point, a straight line, and the entire space in the Hudson source-type plots, respectively. Both the DC and GD models yield nonlinear inversions, whereas the MT inversion is linear. Synthetic tests set up from a field single-well monitoring case are performed to study the resolvability of the DC, GD, and MT models in single-well focal mechanism inversions. The results indicate that the inversion error increases from DC→GD→MT for a single-well acquisition system, and the GD and DC inversions are both stable, whereas the MT inversion deviates from the inputs in cases with a perfectly vertical receiver array, 5% model velocity perturbations, 10 m horizontal source location errors, or 40% noise levels. We also find that the focal mechanism inversion mainly depends on the horizontal source–receiver azimuth coverage, and that the nonvertical well direction is helpful for constraining single-well inversions. According to our study, focal mechanism inversions based on the GD model can obtain reliable solutions from near-vertical single-well data, which will help improve non-DC earthquake studies.