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Quantifying and de-risking the exploration for geo-resources require knowledge of the subsurface. This is true for example for both mineral and geothermal exploration. Often that knowledge is built up by local geophysical studies on areas of interest but the broad deeper context and controls for the system are often missing due to a lack of appropriate deep (e.g., >2 km) geophysical imagery. The primary goal of this project is to develop a deep (range 5-100 km) 3-D electrical conductivity model of Ireland’s crust and uppermost mantle using magnetotelluric (MT) method. Deep probing MT imaging yields information on the structure, composition and temperature of Earth’s crust and upper mantle, and can detect processes associated with mineralisation and areas of high temperature and or permeability related to promising geothermal targets. It will also help better illuminate the deep geology of Ireland, particularly in the context of the mechanisms of the Caledonian and Variscan Orogenies that formed Ireland, the emplacement of its sizable granites, and the intraplate basaltic volcanism that followed the opening of the North Atlantic and created the famous Giant’s Causeway and other features. MT experiments have been conducted in Ireland since 1980s. These include the Irish Magnetotelluric Profile in the late 1980s, and the Irish Magnetotelluric Lithospheric Experiment ISLE-MT in the mid-2000s. In the framework of Space Weather ElectroMagnetic Database for Ireland, long-period MT (LMT) data were acquired at over twenty stations in 2018. Since June 2019, new LMT data have been acquired at twelve stations. The recent project HIbernian Regional GeoElectrical Structure Hi-RES aims to complete an all-island dataset of LMT soundings by acquiring an additional 22 sites across Ireland, expanding on previous MT campaigns. This contribution will present analysis and 3-D modelling results of these datasets.

Imaging the subsurface geology at volcanoes is crucial for understanding their structure and dynamics. Knowledge about the existence of magma chambers, fault and fluid systems improves natural hazard assessment and geothermal energy exploitation. However, the highly heterogeneous subsurface at volcanoes complicates the identification of geologic layers and objects. A strongly scattered seismic wavefield is typically recorded that masks coherent energy reflected at interfaces of interest. In addition, small geologic features such as magma bodies are often smeared out by tomographic techniques. A well-known example that highlights this problem is Krafla, a volcano caldera in the north-east of Iceland. In 2009, a magma body was unexpectedly found at a depth of 2.1km during drilling for geothermal purposes. Even though Krafla is one of the best-studied volcanoes worldwide, the shallow magma body remained undetected. In the summer of 2022, we conducted a six weeks long field experiment at Krafla as part of the IMPROVE project. We deployed densely spaced short seismic profiles comprising 114 seismometers in a passive experiment. Our goal is to image the magma body at 2.1 km depth. At first, we carry out a comprehensive data characterization in order to better understand the seismic wavefield and the influence of source, propagation, and near-station effects. In a subsequent step we apply targeted imaging methods including local earthquakes and high-frequency industrial noise. Krafla provides an optimal setting to test and calibrate seismic imaging, because the location of the magma body is known (through drilling). By combining different methods, we seek to improve seismic imaging techniques in order to obtain a high-resolution image of the subsurface in complex media.

Traditionally, there are different approaches to monitoring the ocean wave field consisting of 1) measurements using insitu buoys, 2) numerical ocean wave modeling using wind forecast, and 3) satellite altimetry. Each of these ocean wave monitoring techniques has their own advantages and disadvantages associated with their spatial and temporal resolution. For example, buoys are physical point measurements with excellent temporal resolution (e.g., sub-hourly), but their spatial resolution is very poor (e.g., a single point in space). Buoys are also expensive to maintain; ‘Real-time’ wave height estimations from numerical wave modeling is based on forecast wind, hence the model accuracy is dependent on wind prediction accuracy. Compare to buoys, the temporal resolution of available outputs from large-scale numerical models is usually low (e.g., every 3 hours), but the spatial resolution is much better (various resolutions depending on the grid size); Satellite altimetry looks over a large region so the spatial coverage is very good but the temporal resolution is very poor (e.g., once every four days). In this work, we consider terrestrial seismic (microseism) data as a proxy for wave heights. Under certain conditions, it has the potential for combined good spatial and temporal resolution, in quasi-real time. This technique is based on the relationship between secondary microseism amplitudes recorded on land and the ocean wave-wave interactions which excite the sea floor, generating these secondary microseisms. Here we take a data-driven approach, implementing an Artificial Neural Network (ANN) to quantify the complex underlying relationship between ocean wave height and microseism amplitude. Thus far we trained the ANN using the available seismic and numerical simulated data and then used the trained ANN to estimate significant Ocean Wave Height (SWH) at a particular location(s) in the Northeast Atlantic using amplitudes from seismic stations distributed across Ireland.Our preliminary results look very promising and show relatively small residuals for measured wave height using the ANN compare to the real buoy data for both small and moderate wave heights. However, currently larger residuals are seen for the largest ocean wave heights. We expect this to improve as ever more data becomes available.

The ambient seismic noise is dominated by surface waves associated with ocean microseisms that are defined by a strong acoustic/seismic coupling at the seafloor. The understanding of microseism sources not only benefits seismic passive imaging and monitoring, but can also help track ocean storms using seismic signals recorded on land. Numerical simulations show that heterogeneous seafloor morphologies and structures can significantly affect the propagation of microseism’s surface waves and therefore the accuracy in locating their origin using traditional methods, such as array beamforming. Here, we aim to investigate how the use of time-reversal imaging can help overcome those limitations. The technique has mainly been developed for acoustics but has been applied successfully in seismology for earthquake localisation. Time-reversal imaging consists on back-propagating, through a realistic model, the signal measured at a network of receivers so that it eventually refocuses back at its origin. For this study, simulations are performed using the code SPECFEM3D and a regional 3D acoustic/elastic model of the Irish offshore, with seismic receivers homogeneously distributed along the coast of Ireland. First, methodologies and stations layout are tested with synthetic data generated from forward modelling using different source distributions. Processing approaches for the time-reversed simulation results are investigated in order to optimize the recovery of the original sources. Following those tests, real time windows of seismic noise “events” are then back-propagated into the model with the aim to map the microseism sources associated with local storms in the model area. The results are compared with microseism sources derived from global ocean wave models. Overall, the use of time-reversal imaging for microseism sources localisation looks promising. Although challenging due to the diffuse distribution of sources, there is good potential for developing further our understanding of microseism sources and monitor dominant microseism generation areas in the North Atlantic region with the implementation of a larger model.

Karst is a landscape with distinctive hydrology and landforms that arise when the underlying rock is soluble. Locating the flowing conduits and pathways in karst is important in terms of water resource management, groundwater flooding, geotechnical and engineering projects. Understanding flow pathways is particularly important for road and railway construction, so as not to adversely affect hydrological networks, in particular those associated with Turloughs.The aim of this study was to develop methods for directly detecting energetic groundwater flow in sub-surface conduits through passive seismic applications, by detecting the small ground vibrations (seismic microtremor) that flowing water in the sub-surface may generate. This is in contrast to the current ‘traditional’ approach of attempting to actively image the conduits using geophysical and other methods, in order to determine the geometry of flow paths. The imagery of conduits in karst is a very difficult problem and determining if they contain flowing structures is also a very significant challenge using traditional methods, which is the motivation for developing a new approach to the problem.We undertook experiments at two sites on karst in Ireland; one gently-sloping shallow conduit and one relatively deep and complex-structured conduit. We chose these sites as the caves had previously been dived and we had access to the shapefiles of these caves to ground-truth our findings.We observed that subterranean flow-related micro-tremor in karst appears as persistent frequency bands on the spectrograms that vary with time and seismic station location with respect to the conduit. This persistent frequency is different than the soil resonating frequency and relates to the subterranean water flow in the conduits. Application of an Amplitude Location Method (ALM) clearly delineated the conduit as the source of the micro-tremor.We also conducted an active Airgun experiment at the second site to locate the conduit by tracking a pressure wave, using two arrays of surface seismic stations, as it propagated into the conduit. This combination of detecting and locating seismic microtremor generated by water flow in the conduits and the use of seismic array analysis to track active Airgun source pressure waves propagating at depth in conduits offers a new tool kit for karst hydrology determination. In the next step, we will assess the applicability of Distributed Acoustic Sensing (DAS) using fiber optic cables as sensors for detecting sub-surface water flow, where we expect unrivaled spatial resolution of the flow-induced seismic wavefield. Such a study would be the first attempt to fill the current gap regarding an understanding of karst groundwater dynamics along the entire conduit pathway, at an exceptionally high spatial scale.

Summary Ireland and neighbouring Britain share much of their tectonic history and are both far from active plate boundaries at present. Their seismicity shows surprising lateral variations, with very few earthquakes in Ireland but many low-to-moderate ones in the adjacent western Britain. Understanding the cause of these variations is important for our understanding of the basic mechanisms of the intraplate seismicity distributions and for regional hazard assessment. The distribution of micro-seismicity within Ireland and its underlying causes have been uncertain due to the sparsity of the data sampling of the island, until recently. Here, we use the data from numerous recently deployed seismic stations in Ireland and map its seismicity in greater detail than previously. The majority of detectable seismic events are quarry and mine blasts. These can be discriminated from tectonic events using a combination of the waveform data, event origin times, and the epicentres’ proximity to quarries and mines, catalogued or identified from the satellite imagery. Our new map of natural seismicity shows many more events than known previously but confirms that the earthquakes are concentrated primarily in the northernmost part of the island, with fewer events along its southern coast and very few deeper inland. Comparing the seismicity with the recently published surface-wave tomography of Ireland and Britain, we observe a strong correspondence between seismicity and the phase velocities at periods sampling the lithospheric thickness. Ireland has relatively thick, cold and, by inference, mechanically strong lithosphere and has very few earthquakes. Most Irish earthquakes are in the north of the island, the one place where its lithosphere is thinner, warmer and, thus, weaker. Western Britain also has relatively thin lithosphere and numerous earthquakes. By contrast, southeastern England and, probably, eastern Scotland have thicker lithosphere and, also, few earthquakes. The distribution of earthquakes in Ireland and Britain is, thus, controlled primarily by the thickness and mechanical strength of the lithosphere. The thicker, colder, stronger lithosphere undergoes less deformation and features fewer earthquakes than thinner, weaker lithosphere that deforms more easily. Ireland and Britain are tectonically stable and the variations in the lithospheric thickness variations across them are estimated to be in a 75-110 km range. Our results thus indicate that moderate variations in the lithospheric thickness within stable continental interiors can exert substantial control on the distributions of seismicity and seismic hazard—in Ireland, Britain and elsewhere around the world.

In the past decade, the use of fiber optic cables to sense ground motion (Distributed Acoustic Sensing-DAS) has become a topic of great interest in seismology because of its wide sensitivity range, dense spatial sampling and new deployment possibilities.How exactly DAS cables respond to ground motion is however largely unknown, limiting the application of a number of staple seismological techniques (e.g. earthquake magnitude estimation, waveform tomography) that can require accurate knowledge of a signal’s amplitude and frequency content.Here we present a method for accurately simulating a DAS cable and its response. The scheme is based on particle-based numerical modelling, allowing the investigation of the effect of varying DAS-ground coupling scenarios. After computing the strain field directly, we define a virtual DAS cable, formed by a single string of interconnected particles. This allows us to control all aspects of the cable-ground coupling and their properties at an effective granular level through changing the bond strengths and bond types for both the cable and the surrounding medium. Arbitrary cable geometries and heterogeneous materials can be accommodated at the desired scale of investigation.We observe that at the meter scale, realistic DAS materials, cable-ground coupling and the presence of unconsolidated trench materials around it dramatically affect wave propagation, with differences exceeding at times the magnitude of the recorded signal. These differences show that cable coupling and local site effects have to be considered when designing a DAS deployment and analysing its data when either true or along-cable relative amplitudes are considered., The 28th IUGG General Assembly (IUGG2023) (Berlin 2023)

Subglacial floods are hazardous events. Since seismic tremor accompanies them, the source can be located and tracked in space and time using a seismic array. However, understanding how these seismic signals are generated remains elusive. Here, we study the seismic characteristics of the largest measured flood from the Eastern Skaftá cauldron, Iceland. We track the propagation of the flood in 2015 using two seismic arrays and a local seismic network. Data from three GPS instruments above the cauldron lake and the subglacial flood path and from hydrological instruments in the Skaftá river aid the interpretation. We find that as the water drained from the lake, quakes were generated in the area around the cauldron and the glacier surface subsided by more than 100 m.We detected several-hours-long, non-harmonic tremor migrating downglacier following the subglacial flood front. We suggest that this tremor is composed of repeated, closely spaced icequakes generated as the glacier was being lifted, cracked and deformed enabling the subglacial water flow. When the lake had largely drained, we recorded minute-long tremor bursts with hour-long harmonic tails emanating from the cauldron area. Body waves compose the bursts. We interpret them as hydrothermal explosions in the geothermal system underlying the cauldron, followed by vigorous boiling due to the pressure drop within the hydrothermal system as a consequence of the lowering of the water level in the lake. We conclude that the three different tremor characteristics are associated with three different geophysical processes.

Severe acute respiratory syndrome (SARS) coronavirus 2 (SARS-CoV-2) is a novel human coronavirus that was identified in 2019. SARS-CoV-2 infection results in an acute, severe respiratory disease called coronavirus disease 2019 (COVID-19). The emergence and rapid spread of SARS-CoV-2 has led to a global public health crisis, which continues to affect populations across the globe. Real time reverse transcription polymerase chain reaction (RT-PCR) is the reference standard test for COVID-19 diagnosis. Serological tests are valuable tools for serosurveillance programs and establishing correlates of protection from disease. This study evaluated the performance of one in-house enzyme linked immunosorbent assay (ELISA) utilizing the pre-fusion stabilized ectodomain of SARS-CoV-2 spike (S), two commercially available chemiluminescence assays Ortho VITROS Immunodiagnostic Products Anti-SARS-CoV-2 Total Reagent Pack and Abbott SARS-CoV-2 IgG assay and one commercially available Surrogate Virus Neutralization Test (sVNT), GenScript USA Inc., cPass SARS-CoV-2 Neutralization Antibody Detection Kit for the detection of SARS-CoV-2 specific antibodies. Using a panel of RT-PCR confirmed COVID-19 patients’ sera and a negative control group as a reference standard, all three immunoassays demonstrated high comparable positivity rates and low discordant rates. All three immunoassays were highly sensitive with estimated sensitivities ranging from 95.4%-96.6%. ROC curve analysis indicated that all three immunoassays had high diagnostic accuracies with area under the curve (AUC) values ranging from 0.9698-0.9807. High positive correlation was demonstrated among the conventional microneutralization test (MNT) titers and the sVNT inhibition percent values. Our study indicates that independent evaluations are necessary to optimize the overall utility and the interpretation of the results of serological tests. Overall, we demonstrate that all serological tests evaluated in this study are suitable for the detection of SARS-CoV-2 antibodies.

Wind driven ocean wave-wave interactions produce continuous Earth vibrations at the seafloor called secondary microseisms. While the origin of associated Rayleigh waves is well understood, there is currently no quantified explanation for the existence of Love waves in the most energetic region of the microseism spectrum (3–10 s). Here, using terrestrial seismic arrays and 3D synthetic acoustic-elastic simulations combined with ocean wave hindcast data, we demonstrate that, observed from land, our general understanding of Rayleigh and Love wave microseism sources is significantly impacted by 3D propagation path effects. We show that while Rayleigh to Love wave conversions occur along the microseism path, Love waves predominantly originate from steep subsurface geological interfaces and bathymetry, directly below the ocean source that couples to the solid Earth. We conclude that, in contrast to Rayleigh waves, microseism Love waves observed on land do not directly relate to the ocean wave climate but are significantly modulated by continental margin morphologies, with a first order effect from sedimentary basins. Hence, they yield rich spatio-temporal information about ocean-land coupling in deep water., The authors here study the origin of seismic Love waves induced by ocean waves. The study finds Love waves to originate along steep bathymetry and underlying geological interfaces, particularly sedimentary basins, yielding spatio-temporal information about ocean-land coupling in deep water.

Seismic tremor observed near active volcanoes is an important tool for volcano monitoring as it often appears shortly before eruptions. Although tremor can be generated by a variety of physical processes it is usually interpreted as direct evidence for flowing magma in the sub-surface. These interpretations typically feed into risk assessments for potential eruptions. Using the temporal evolution of tremor amplitude and spectral data from a distributed seismic network that captured the 2018 eruption at Sierra Negra in Galapagos, we determine that tremor is not directly related to sub-surface fluid movement. Instead at Sierra Negra tremor likely indicates a slowly propagating fracture, which is later exploited as a pathway for silent magma flow. Distinct differences in the source migration and the spectral character of pre-eruptive and co-eruptive tremor allow both a location estimate of the future eruption site and a precise timing of the eruption onset.

In this study, we present a new approach based on recent advances in deep learning for rapid source-parameter estimation of microseismic earthquakes. The seismic inversion is represented in compact form by two convolutional neural networks, with individual feature extraction, and a fully connected neural network, for feature aggregation, to simultaneously obtain moment tensor and spatial location of microseismic sources. The neural network algorithm encapsulates the information about the relationship between seismic waveforms and underlying point-source mechanisms and locations allowing rapid inversion (within a small fraction of a second) once input data are available. A key advantage of the algorithm is that it can be trained using synthesized seismic data only, so it is directly applicable to scenarios where there are insufficient real data for training including temporary seismic networks and hydraulic stimulation experiments, for example. Moreover, we find that the method is robust with respect to perturbations such as observational noise and data incompleteness (missing stations). We apply the new approach on a database of small magnitude (M ≤ 2) earthquakes recorded at the Hellisheiði geothermal field in the Hengill area, Iceland, which is the demonstration site in the EU-GEOTHERMICA project COSEISMIQ (http://www.coseismiq.ethz.ch). For the examined events, the model achieves very good agreement with the inverted solutions determined through standard methodology. The new approach offers great potential for automatic and rapid real-time information on microseismic sources in a deep geothermal context and can be viably used for microseismic monitoring tasks in general.

The determination of seismic moment tensors (MTs) for microseismicity poses challenges because of both the large number of events that are typically recorded, and their low signal to noise ratio. In recent years, automated moment tensor inversion methods have become more and more accurate, but an objective evaluation of their performance is often problematic due to the absence of site-specific, reference databases for comparison. In this study, we build a database of manually inverted MTs for the recent COSEIMIQ project, using the well-tested FociMT/HybridMT inversion method. COSEISMIQ focussed on microseismic monitoring in the Hellisheiði geothermal field, in the Hengill region, southern Iceland, where a dense network of 33 temporary seismic stations was deployed during 2018-2021, offering an ideal case study for microseismic MT inversion.As a first step, we test the efficacy and possible pitfalls of the manual MT inversion on both a realistic and a simplified synthetic events waveform database. After careful, repeated manual tests, we observe that the inversion is robust across widely different choices of frequency band, but can be triggered to fail by not including key stations in some rare source-station geometries.We then analyse the real data from the COSEISMIQ experiment, using previously located events from a large, recently developed microseismic catalog of the area. By running preliminary inversions of a subset of events in the centre of the deployment, we are able to pinpoint pre-processing steps that have a key effect on the MT inversion. We find that in strong noise conditions such as in the Hengill region, the order and phase of the used frequency filter are fundamental parameters in correctly processing the P-wave onset used later for inversion.After fine-tuning the event preprocessing, we select a larger subset of 197 events with magnitude > 0.8 from the catalog across the whole COSEISMIQ area, including several seismicity clusters at the edge of the deployment. We then pick all 197 events and invert them first with FociMT, then cluster the events based on their location using K-means clustering, and finally re-invert each cluster using HybridMT. The clustered inversion using HybridMT changes some MT solutions significantly, reducing the intra-cluster MT variance for most clusters. Interestingly, some event clusters show increased variance after the HybridMT inversion, suggesting that these include substantially different source mechanisms within a small area.This new database of carefully inverted MT solutions can now be used as a test dataset to evaluate the performance of automated inversion tools.

Changes in external stress state and fluid content alter the mechanical properties of an elastic medium. Hence, variations in seismic wave velocity and (crack-induced) seismic anisotropy can be used as proxies for changes in stress and possible fluid ingression. Temporal variations in seismic wave velocity have previously been monitored and observed prior to volcanic eruptions. In the absence of additional constraints related to stress or fluid changes on the volcano, these pre-eruptive changes are difficult to interpret and hence their causes are often not well understood.Sierra Negra volcano is one of the most active volcanoes on the Galapagos Islands, about 1000 km west of continental Ecuador. On 26th June 2018 at 09:15 UTC, a magnitude 5.4 earthquake occurred near the southwest caldera rim and an intense seismic swarm started around 17:15 UTC. Seismic tremor dominated at about 19:35 UTC, which marked the onset of the eruption. Both prior to and during the eruption period several families of repeating earthquakes have been identified in a very large seismicity sequence.In this study, we use the Coda Wave Interferometry (CWI) technique on repeating earthquakes to measure time-lapse changes in seismic velocity prior to the 2018 eruption.We used 3 months of continuous seismic data from different temporary broadband stations, and 1 year of data from one of six permanent stations, the VCH1 station located on the caldera rim, managed by the IGEPN.Our results show a decrease in the seismic velocities observed from June 2017 to June 2018. In particular, we see a large systematic decrease in velocity starting up to a year before the eruption. A large velocity decrease of almost 2% is detected, over the year preceding the 2018 eruption at Sierra Negra. We suggest that this is related to progressive damage of the edifice, as it continues to inflate.

Study objective We provide an updated assessment of trends in sickle cell disease (SCD)–related mortality, a significant source of mortality in the United States among black persons, using 1979 to 2017 US mortality data. Methods SCD-related deaths were identified with International Classification of Diseases codes. Because SCD-related death is rare in other races, the analysis focused on black decedents. Age-specific and average annual SCD-related death rates were calculated. Causes of death codes were categorized into 20 groups relevant to SCD outcomes. SCD-related deaths were compared with non–SCD-related deaths after matching on race, sex, age group, and year of death. Results There were 25,665 SCD-related deaths reported among blacks in the United States from 1979 through 2017. During that period, the annual SCD-related death rate declined in children and increased in adults, and the median age at death increased from 28 to 43 years. Acute causes of death, such as infection and cerebrovascular complications, were more common in younger age groups. Chronic complications were more common in adults. SCD-related deaths were more likely to be related to acute cardiac, pulmonary, and cerebrovascular complications; acute infections; and chronic cardiac and pulmonary complications and renal disorders; and less likely to be related to drug overdose and chronic infections than non–SCD-related deaths. Conclusion These data indicate SCD-related deaths are now more likely to be related to chronic complications of the disease than to acute complications. More research regarding prevention and treatment of chronic complications of SCD is necessary because persons with SCD are living longer.

A conventional processing workflow favors only the specular reflections, reducing or removing other wavefield interactions. These specular reflections are unsuitable for directly imaging sharp corners, such as those in fault zones and pinch outs; therefore, diffractions are used instead in a technique known as diffraction imaging. Plane-wave destruction (PWD) is a well-established method for removing reflections and imaging diffractions. However, this method assumes a gently variable slope; therefore, it fails to remove energy in areas that do not follow this assumption such as curved interfaces. To remove the remnant energy in these areas and thus enhance the overall interpretability of the diffraction images, we have adopted a simple spatial-variable filter in the frequency-wavenumber f-k domain based on the calculated dip field used for PWD, applied post PWD. To demonstrate the method, we have examined this on a range of synthetic data, complex synthetic data, and real data. The created diffraction images have then been interpreted to evidence the benefit of diffraction imaging in seismic interpretation, helping to delineate pinch outs, faults, and rugose surfaces.

We use a passive seismic high‐frequency receiver function method to image the shallow structure around a mine site. This is a relatively new application of a standard method for mapping major discontinuities in the crust and upper mantle at a scale small enough to be relevant in an exploration context. Data collected in a 21‐instrument array is inverted for isotropic velocity structure. The retrieved velocities in the south‐eastern part of the array match very well with available sonic log measurements in the top 800 m. Based on the differences in receiver function behaviour for stations across the array, recovered velocity profiles and their similarity to sonic log measurements, the target area is split into two separate regions along a north‐northeast trending line that correlates well to the strike of the dominant structure in the area – the Navan Fault. Our results demonstrate the ability of receiver functions to provide both qualitative and quantitative information in an exploration environment.

15 pages, 9 figures, 1 table, supplementary data https://doi.org/10.1016/j.marpetgeo.2022.105652, The Porcupine basin is a failed rift that formed during the opening of the North Atlantic Ocean. Here, we provide additional insights into the crustal structure of the northern Porcupine Basin and assess the degree of crustal extension from long streamer seismic data and free-air gravity modelling. Recent re-processing of the 2013/2014 streamer data involved de-multiple and de-noise processing with pre-stack-depth migration using velocity models derived from reflection travel time tomography and full waveform inversion. Forward modelling of satellite gravity data was used to constrain the velocity and mass density of the basement and lower crust, where the seismic constraints are limited. Prior knowledge, from previous geophysical and geological studies, was included to guide the modelling and reconcile the gravity data with the seismic sections. It also served to minimize the non-uniqueness inherent in the forward problem. Crustal thinning occurs across the basin axis and increases southwards. We infer maximum stretching factor (β) at the basin axis, increasing from ∼4 to 6 in the North Porcupine at 52.5°N to >10 at ∼51°N in the Central Porcupine. The gravity modelling supports the presence of mantle serpentinisation, and the high β implies that crustal break up and mantle exhumation may have locally occurred in the Central Porcupine Basin, in agreement with previous seismic tomographic studies. Basaltic melt generation in the centre of the basin where the maximum bulk stretching factor exceeds10 in the hyper-extended crust may have led to localized sea-floor-spreading, This project was funded by the Irish centre for Research in Applied Geosciences (iCRAG), Science Foundation Ireland (SFI), Irish Shelf and Petroleum Studies Group (ISPSG) of the Petroleum Infrastructure Programme (PiP) and DIAS. This publication uses data reprocessed during a project undertaken on behalf of the Irish Shelf Petroleum Studies Group (ISPSG) of the Irish Petroleum Infrastructure Programme Group 4. The ISPSG comprises: AzEire Petroleum Ltd, Cairn Energy Plc, BP Exploration Operating Company Ltd, CNOOC Petroleum Europe Limited, ENI Ireland BV, Equinor Energy Ireland Limited, Europa Oil & Gas Plc, ExxonMobil E&P Ireland (Offshore) Ltd, Husky Energy, Petroleum Affairs Division of the Department of Communications, Climate Action and Environment, Providence Resources plc, Repsol Exploración SA, Sosina Exploration Ltd, Total EP, Tullow Oil Plc and Woodside Energy (Ireland) Pty Ltd”. Manel Prada has received funding support of the “Severo Ochoa Centre of Excellence” accreditation (CEX 2019-000928-S) of the Spanish Research Agency (AEI)

Description, Dynamically triggered earthquakes track pre-eruptive unrest evolution at Sierra Negra volcano, Galápagos Islands., The propensity for dynamic earthquake triggering is thought to depend on the local stress state and amplitude of the stress perturbation. However, the nature of this dependency has not been confirmed within a single crustal volume. Here, we show that at Sierra Negra volcano, Galápagos Islands, the intensity of dynamically triggered earthquakes increased as inflation of a magma reservoir elevated the stress state. The perturbation of short-term seismicity within teleseismic surface waves also increased with peak dynamic strain. Following rapid coeruptive subsidence and reduction in stress and background seismicity rates, equivalent dynamic strains no longer triggered detectable seismicity. These findings offer direct constraints on the primary controls on dynamic triggering and suggest that the response to dynamic stresses may help constrain the evolution of volcanic unrest.

Did the mantle plume that fuels Iceland’s volcanoes today cause eruptions in Ireland and Great Britain long ago? A new project investigates, while also inspiring students and recording whale songs.

Event detection capability plays an important role in the operation of seismic observatories and temporary networks. The magnitude threshold for the detection of seismic events with a given network geometry is frequently derived from the observed magnitude of completeness. However, the latter might be unknown for regions that have not been monitored previously or where the observed seismicity rate is low. We present the open-source Python program SN-CAST with which the geographical distribution of event detection capability can be calculated as a function of station coordinates and station ambient noise amplitudes. The method employs the local magnitude scale, and hence is mainly applicable to regional networks with an aperture of less than about 1000 km. The attenuation characteristics of the study region need to be derived independently or be known a priori. SN-CAST can easily be employed to determine network performance in quasi real-time if station data streams are available. It can also be used for designing the geometry of new networks or assessing the effect of adding or removing stations from an existing network. We present examples from the Irish National Seismic Network ( https://www.insn.ie ), which operates in a region of low seismicity and large variations in ocean and wind-generated seismic noise. The seismicity in Ireland is too low to allow the calculation of a magnitude of completeness for comparison with the derived capability maps. However, the maps are in good agreement with the location and magnitude of detected local and regional earthquakes demonstrating that SN-CAST is a reliable tool for assessing the detection capability of seismic networks.

Freight trains are one of the most powerful and persistent seismic sources of cultural noise. They generate tremors equivalent to earthquakes of magnitude 1 that can be detectable up to 100 km distance. Here, we propose to use the freight train passages as an opportunistic source of noise for passive seismic interferometry (SI). Usually, passive SI relies on blind correlations of long time series of noise for imaging and monitoring purposes. We suggest an alternative method based on noise source characterization, signal and station pairs selection, and specific seismic phase extraction (surface and body waves) for each virtual source to imaging the subsurface. To illustrate our novel method's potential, we show a case study in Canada's mineral exploration context, where we use retrieved body waves to estimate travel time tomography. This noise recovery approach to create valuable sources could be applied for several seismic noise sources and in different contexts improving spatial and temporal resolutions.

We present a 3-D multiphysics joint inversion framework that in a certain sense is a trade-off between “simultaneous” and “cooperative” approaches to data integration. Using a variable splitting approach, inverse problems are solved by individual inverse solvers, on individual grids, while coupling combined with interpolation is implemented separately. Up to date, first-arrival seismic tomography, gravity and magnetotelluric inverse problems are included in this framework. Magnetotelluric inversion uses the NLCG method implemented in the ModEM code (Kelbert et al., 2014). Seismic tomography is based on the Gauss-Newton method with a finite-difference eikonal solver and posterior ray tracing. Gravity inversion uses the conjugate gradient method with wavelet compression of the sensitivity matrix. Structure coupling is based on mixed-norm regularization inducing joint sparsity between the models. Among particular functionals that were studied, following numerical experiments, joint total variation and joint minimum support have proved to be the most efficient options. In the numerical experiments, we invert synthetics simulating regional datasets observed in Ireland.

Despite advanced seismological methods, source characterization for micro-seismic events remains challenging since current inversion and modelling of high-frequency waveforms are complex and time consuming. For a real-time application like induced-seismicity monitoring, these methods are slow for true real-time information because they require repeated evaluation of the often computationally expensive forward operation. Moreover, because of the low amplitude and high-frequency content of the recorded micro-seismic signals, routine inversion procedure can become unstable and manual parameter tuning is often required. Therefore, real-time and automatic source inversion procedures are difficult and not standard. A more promising alternative to the current inversion methods for rapid source parameter inversion is to use a deep-learning neural network model that is calibrated on a data set of past and/or possible future observations. Such data-driven model, once trained, offers the potential for rapid real-time information on seismic sources in a monitoring context.In this study, we investigate how a supervised deep-learning model trained on a data set of synthetic seismograms can be used to rapidly invert for source parameters. The inversion is represented in compact form by a convolutional neural network which yields seismic moment tensor. In other words, a neural-network algorithm is trained to encapsulate the information about the relationship between observations and underlying point-source models. The learning-based model allows rapid inversion once seismic waveforms are available. Moreover, we find that the method is robust with respect to perturbations such as observational noise and missing data. In this study, we seek to demonstrate that this approach is viable for micro-seismicity real-time estimation of source parameters. As a demonstration test, we plan to apply the new approach to data collected at the geothermal field system in the Hengill area, Iceland, within the framework of the COSEISMIQ project funded through the EU GEOTHERMICA programme.

Since explosive and impulsive seismic sources such as dynamite, air guns, gas guns, or even vibroseis can have a big impact on the environment, some companies have decided to record ambient seismic noise and use it to estimate the physical properties of the subsurface. Big challenges arise when the aim is extracting body-waves from recorded passive signals, especially in the presence of strong surface waves. In passive seismic signals, such body-waves are usually weak in comparison to surface waves which are much more prominent. To understand the characteristics of passive signals and the effect of natural source locations, three simple synthetic models were created. To extract body-waves from simulated passive signals we propose and test a Radon-correlation method. This is a time-spatial correlation of amplitudes with a train of time-shifted Dirac delta functions through different hyperbolic paths. It is tested on a two-layer horizontal model, three-layer model which includes a dipping layer (with and without lateral heterogeneity) and also on synthetic Marmousi model data sets. Synthetic tests show that the introduced method is able to reconstruct reflection events at the correct time-offset positions which are hidden in results obtained by the general cross-correlation method. Also, a depth migrated section shows a good match between imaged-horizons and the true model. It is possible to generate off-end virtual gathers by applying the method to a linear array of receivers and to construct a velocity model by semblance velocity analysis of individually extracted gathers.

The EUROVOLC project aims to promote an integrated and harmonised European volcanological community, with one of its main themes focusing on understanding sub-surface processes. Early identification of magma moving towards the surface is very important for the mitigation of risks from volcanic hazards, and joint research activities within the project aim to develop and improve schemes for detecting pre-eruptive unrest. Volcanic tremor is a sustained seismic signal that is often associated with such volcanic unrest, and has been linked to the movement of magmatic fluids in the subsurface. However, signals with similar spectral content can be generated by other surface processes such as flooding, rockfalls or lahars. Hence, one of the best ways of distinguishing between different possible mechanisms for generating tremor is by tracking the location of its source, which is also important for mitigating volcanic risk. Due to its emergent nature, tremor cannot be located using travel-time based methods, and therefore alternatives such as amplitude-based techniques or array analysis must be used. Dense, small-aperture arrays are particularly suited for analyzing volcanic tremor, yet costs associated with installation and maintenance have meant few long-term or permanent seismic arrays in use for routine monitoring.Given the potential for wider usage of arrays, this work presents a freely available python-based software tool, developed as part of the EUROVOLC project, that uses array data and array processing techniques to analyze and locate volcanic tremor signals. RETREAT utilizes existing routines from the open-source ObsPy framework to carry out analysis of array data in real-time and performs either f-k (frequency-wavenumber) analysis, or alternatively Least-Squares beamforming, to calculate the backazimuth and slowness in overlapping time windows, which can help track the location of volcanic tremor sources. A graphical, or web-based, interface is used to configure a set of input parameters, before fetching chunks of waveform data and performing the array analysis. On each update the tool returns several plots, including timeseries of the backazimuth and slowness, a polar representation of the relative power and a map of the array with the dominant backazimuth overlaid.The tool has been tested using real-time seismic data from the small-aperture SPITS array in Spitsbergen, as well as on data from a small aperture seismic array deployed during the 2014 eruption of Bárðarbunga volcano, Iceland. Although designed specifically for seismic array data (with a particular focus on volcanic tremor), RETREAT can also be used with infrasound sensors and has been successfully tested on infrasonic array data of explosive activity recorded at Mt. Etna, Italy, in 2019.Although RETREAT has been designed for deployment as part of volcano monitoring systems and provides the ability to track tremor sources in real-time, it also has the capability to analyse existing datasets for testing, comparison and research purposes. However, RETREAT is primarily intended for use in real-time monitoring settings and it is hoped that it will facilitate wider use of arrays in tracking volcanic tremor or infrasonic sources in real-time, thereby enhancing monitoring capabilities.

Deep geothermal resources in low- to medium-temperature settings remain poorly understood and untapped in Ireland and much of Europe. Our new project DIG (De-risking Ireland’s Geothermal Potential) integrates multi-disciplinary, multi-scale datasets in order to investigate Ireland’s low-enthalpy geothermal energy potential. Seismic measurements constrain the distributions of seismic velocities and, through them, the composition and temperature within the lithosphere and underlying mantle. Recent deployments of broadband seismic stations and the surface-wave measurements using the new data yield an unprecedentedly dense data sampling of the crust and upper mantle beneath Ireland and neighbouring Britain. These data form a foundation for the region-scale, multi-parameter modelling of the thermal state of the lithosphere.We use the recently assembled dataset of over 11,000 Rayleigh-wave, phase-velocity curves, measured for pairs of stations across Ireland and Britain (Bonadio et al. 2021) and complement it with new interstation measurements of Love-wave phase velocities. The measurements were performed using two methods with complementary period ranges, the teleseismic cross-correlation method and waveform inversion. Spanning a very broad period range (from as short as 4 s to as long as 500 s), the phase velocities provide resolution from the upper-middle crust to the asthenosphere. The joint analysis of Rayleigh and Love measurements constrains the isotropic-average shear-wave velocity, relatable to temperature and composition. The optimal-resolution, phase-velocity maps of Bonadio et al. (2021) for Rayleigh waves and the new maps for Love waves computed in this study provide essential constraints on the thermal structure of the region’s lithosphere. We demonstrate this by inverting the data using an integrated geophysical-petrological thermodynamically self-consistent approach (Fullea et al., 2021). The multi-parameter models produced by the integrated inversions fit the surface-wave and surface-elevation data and reveal the temperatures and geothermal gradients within the crust. Bonadio, R., Lebedev, S., Meier, T., Arroucau, P., Schaeffer, A. J., Licciardi, A., Agius, M. R., Horan, C., Collins, L., O'Reilly, B. M., Readman, P. and the Ireland Array Working Group (2021). Optimal resolution tomography with error tracking: imaging the upper mantle beneath Ireland and Britain. Geophys. J. Int., in revision.Fullea, J., Lebedev, S., Martinec, Z., & Celli, N. L. (2021). WINTERC-G: mapping the upper mantle thermochemical heterogeneity from coupled geophysical-petrological inversion of seismic waveforms, heat flow, surface elevation and gravity satellite data. Geophys. J. Int., revised version under evaluation.

Potential deep (greater > 400 m) geothermal resources, within low to medium temperature settings remain poorly understood and largely untapped in Europe. DIG (De-risking Ireland’s Geothermal Potential) is a new academic project started in 2020, which aims to develop a better understanding of Ireland’s (all-island) low-enthalpy geothermal energy potential through the gathering, modelling and interpretation of geophysical, geological, and geochemical data.The overarching research objectives, are to (i) determine the regional geothermal gradient with uncertainty estimates across Ireland using new and existing geophysical and geochemical-petrophysical data, (ii) investigate the thermochemical crustal structure and secondary fracture porosity in Devonian/Carboniferous siliciclastic and carbonate lithologies using wide-angle seismic, gravity and available geochemical data, and (iii) identify and assess the available low-enthalpy geothermal resources at reservoir scale within the Upper Devonian Munster Basin, i.e. the Mallow warm springs region, using electromagnetic and passive seismic methods, constrained by structural geological mapping results. A new hydrochemistry programme to characterise deep reservoir water composition will add further constraints.In the island-scale strand of the project, we are using Rayleigh and Love surface waves in order to determine the seismic-velocity and thermal structure of the lithosphere, with crustal geometry. Together with the legacy surface heat flow, gravity, and newly available long-period MT data, this will place bounds on the shape of regional geotherms. Radiogenic heat production and thermal conductivity measurements for Irish rocks will be incorporated into an integrated geophysical-petrological model, within a scheme able to provide critical temperature uncertainties. Regional-scale research will exploit legacy wide-angle seismic data across the Laurentian and Avalonian geological terranes. Geochemical and petrophysical databases will guide in-house Bayesian inversion tools, to estimate probabilities on model outcomes.Local-scale research will derive subsurface electrical conductivity and velocity images from electromagnetic and passive seismic surveys from the northern margin of the Munster Basin, where the thermal waters tend to have a distinctive chemical fingerprint and a meteoric origin based on available geochemical and isotopic compositions. This local focus aims to directly image fault conduits and fluid aquifer sources at depth, within a convective/conductive region associated with warm springs. This will determine the scale of the geothermal anomaly and hence will evaluate the potential for local- and industrial-scale space heating in the survey locality.This presentation will give an overview of this new research project and will deliver preliminary multi-parameter crustal models produced by the thermodynamic inversions that fit the surface-wave and surface elevation data. The project is funded by the Sustainable Energy Authority of Ireland under the SEAI Research, Development & Demonstration Funding Programme 2019 (grant number 19/RDD/522) and by the Geological Survey Ireland.

Karst is an important landscape in many locations incorporating many subterranean waterflow passages in the form of caves, conduits, and fractures. Although challenging, some karst structures can be imaged by active geophysical techniques however they generally cannot facilitate differentiation between flowing and non-flowing waterways. In this study, we aim to locate flowing conduits by passively capturing flow-induced seismic signals.To gain a broad understanding of seismic source versus path effect in these complex structures and to help us design bespoke field experiments, we commence our study by undertaking 3D numerical simulation (using SPECFEM3D) for different cases of shallow and deep conduits. These choices are informed by known conduit geometries in Ireland (they have been dived). Spectral resonance, synthetic heat maps, and amplitude-based locations of synthetic data reveal interesting information regarding the conduit response.Based on the results of these simulations, we designed the layout of a passive field experiment on karst on Pollnagran cave in County Roscommon, Ireland using 1Hz seismometers and 5 Hz Geophones. The karst deployment is also complemented by smaller experiments on surface rivers in order to help better understand observed signals. We also undertake an active hammer seismic survey at the site in order the build a model for future site-specific numerical simulations.Consistent with numerical experiments, clear discrete frequencies associated with water flow are observed in the field data. A complex picture is emerging where the largest dived caves are not necessarily the flow structures with the largest seismic amplitudes.

Hekla is one of Iceland’s most active volcanoes having had 18 summit eruptions in the last 1,100 years with the most recent eruption in 2000. Hekla volcano has been studied extensively using various geodetic methods. Most recent deformation studies (InSAR) in relation to the 2000 eruption of Hekla have addressed the proposed location of a deep-seated magma reservoir at approximately 10 km (Sturkell et al., 2013) where other studies indicate a greater depth (Ofeigsson et al., 2011). A regional-scale magnetotelluric (MT) survey (Eysteinsson and Hermance 1985) conducted in 1982 suggested the estimated depths for the magma chamber beneath the volcano to be between 5 and 24 km. Our new project MTHEK (MagnetoTelluric Assessment of the HEKla Volcano) aims at identifying low-resistivity zones at depth, which may be a proxy for melt accumulation and migration pathways, and may constrain the location of the proposed magma reservoir. The geoelectrical models obtained will enable us to highlight potential real-time electromagnetic monitoring locations which may complement the current real-time seismic/deformation monitoring.In September 2020, broadband MT data were acquired at 20 stations around and to the south of Hekla volcano. The horizontal electric field components were recorded using 50-60 m dipoles, and the three components of the magnetic field were measured using induction coils. At most stations, the recording time was approximately 20 hours, and a distant remote reference site (approximately 100 km away) was recording during the whole survey. The period range of good quality data obtained is about 300 Hz to 1,000 - 2,000 s. In addition, at 17 MT stations central loop transient electromagnetic (TEM) data were collected using a transmitter loop of 200 m × 200 m and a 1 m2 receiver loop with 100 windings (effective area 100 m2). The TEM data are used to correct the MT data for static shift effects caused by near surface inhomogeneities or steep topography. State of the art data processing and analysis methods are being applied to the data. Preliminary inversion models will be presented and provide a first idea of the resistivity structure of the volcano.

Diffraction imaging is the technique of separating diffraction energy from the source wavefield and processing it independently. As diffractions are formed from objects and discontinuities, or diffractors, which are small in comparison to the wavelength, if the diffraction energy is imaged, so too are the diffractors. These diffractors take many forms such as faults, fractures, and pinch-out points, and are therefore geologically significant. Diffraction imaging has been applied here to the Porcupine Basin; a hyperextended basin located 200km to the southwest of Ireland with a rich geological history. The basin has seen interest both academically and industrially as a study on hyperextension and a potential source of hydrocarbons. The data is characterised by two distinct, basin-wide, fractured carbonates nestled between faulted sandstones and mudstones. Additionally, there are both mass-transport deposits and fans present throughout the data, which pose a further challenge for diffraction imaging. Here, we propose the usage of diffraction imaging to better image structures both within the carbonate, such as fractures, and below.To perform diffraction imaging, we have utilised a trained Generative Adversarial Network (GAN) which automatically locates and separates the diffraction energy on pre-migrated seismic data. The data has then been migrated to create a diffraction image. This image is used in conjunction with the conventional image as an attribute, akin to coherency or semblance, to identify diffractors which may be geologically significant. Using this technique, we highlight the fracture network of a large Cretaceous chalk body present in the Porcupine, the internal structure of mass-transport deposits, potential fan edges, and additional faults within the data which may affect fluid flow pathways.

High-frequency seismic surface waves sample the top few tens of meters to the top few kilometres of the subsurface. They can be used to determine three-dimensional distributions of shear-wave velocities and to map the depths of discontinuities (interfaces) within the crust. Passive seismic imaging, using ambient noise as the source of signal, can thus be an effective tool of exploration for mineral, geothermal and other resources, provided that sufficient high-frequency signal is available in the ambient noise wavefield and that accurate, high-frequency measurements can be performed on this signal. Ambient noise imaging using the ocean-generated noise at 5-30 s periods is now a standard method, but less signal is available at frequencies high enough for deposit-scale imaging (0.2-30 Hz), and few studies have reported successful measurements in broad frequency bands. Here, we develop a workflow for the measurement of high-frequency, surface-wave phase velocities in very broad frequency ranges. Our workflow comprises (1) a new noise cross-correlation procedure that accounts for the non-stationary properties of the high frequency noise sources, removes bandpass filtering, replaces temporal normalization with short time window stacking, and drops the explicit spectral normalization by adopting cross-coherence; (2) a new phase-velocity measurement method that extends the bandwidth of reliable measurements by exploiting the (resolved) 2π ambiguity of phase-velocity measurements; (3) interstation-distance-dependent quality control that uses the similarity of subgroups of dispersion curves to reject outliers and identify the frequency ranges with accurate measurements. The workflow is highly automated and applicable to large arrays. Applying our method to data from a large-N array that operated for one month near Marathon, Ontario, Canada, we use rectangular subarrays with 150-m station spacing and, typically, 1 hour of data and obtain Rayleigh-wave phase-velocity measurements in a 0.55-23.8 Hz frequency range, spanning over 5.4 octaves, nearly twice the typical frequency range of 1.5-3 octaves in previous studies. Phase-velocity maps and the subregion-average 1D velocity models they constrain show a high-velocity anomaly consistent with the known, west-dipping gabbro intrusions beneath the area. The new structural information can improve our understanding of the geometry of the gabbro intrusions, hosting the Cu-PGE Marathon deposit.

Funder: Institut de Recherche pour le Développement (French Research Institute for Development); doi: https://doi.org/10.13039/100012947, Recent large basaltic eruptions began after only minor surface uplift and seismicity, and resulted in caldera subsidence. In contrast, some eruptions at Galápagos Island volcanoes are preceded by prolonged, large amplitude uplift and elevated seismicity. These systems also display long-term intra-caldera uplift, or resurgence. However, a scarcity of observations has obscured the mechanisms underpinning such behaviour. Here we combine a unique multiparametric dataset to show how the 2018 eruption of Sierra Negra contributed to caldera resurgence. Magma supply to a shallow reservoir drove 6.5 m of pre-eruptive uplift and seismicity over thirteen years, including an Mw5.4 earthquake that triggered the eruption. Although co-eruptive magma withdrawal resulted in 8.5 m of subsidence, net uplift of the inner-caldera on a trapdoor fault resulted in 1.5 m of permanent resurgence. These observations reveal the importance of intra-caldera faulting in affecting resurgence, and the mechanisms of eruption in the absence of well-developed rift systems.

SUMMARYHigh-frequency seismic surface waves sample the top few tens of meters to the top few kilometres of the subsurface. They can be used to determine 3-D distributions of shear-wave velocities and to map the depths of discontinuities (interfaces) within the crust. Passive seismic imaging, using ambient noise as the source of signal, can thus be an effective tool of exploration for mineral, geothermal and other resources, provided that sufficient high-frequency signal is available in the ambient noise wavefield and that accurate, high-frequency measurements can be performed on this signal. Ambient noise imaging using the ocean-generated noise at 5–30 s periods is now a standard method, but less signal is available at frequencies high enough for deposit-scale imaging (0.2–30 Hz), and few studies have reported successful measurements in broad frequency bands. Here, we develop a workflow for the measurement of high-frequency, surface wave phase velocities in very broad frequency ranges. Our workflow comprises (1) a new noise cross-correlation procedure that accounts for the non-stationary properties of the high-frequency noise sources, removes bandpass filtering, replaces temporal normalization with short time window stacking, and drops the explicit spectral normalization by adopting cross-coherence; (2) a new phase-velocity measurement method that extends the bandwidth of reliable measurements by exploiting the (resolved) 2π ambiguity of phase-velocity measurements and (3) interstation-distance-dependent quality control that uses the similarity of subgroups of dispersion curves to reject outliers and identify the frequency ranges with accurate measurements. The workflow is highly automated and applicable to large arrays. Applying our method to data from a large-N array that operated for one month near Marathon, Ontario, Canada, we use rectangular subarrays with 150-m station spacing and, typically, 1 hr of data and obtain Rayleigh-wave phase-velocity measurements in a 0.5–30 Hz frequency range, spanning over 5.9 octaves, twice the typical frequency range of 1.5–3 octaves in previous studies. Phase-velocity maps and the subregion-average 1-D velocity models they constrain show a high-velocity anomaly consistent with the known, west-dipping gabbro intrusions beneath the area. The new structural information can improve our understanding of the geometry of the gabbro intrusions, hosting the Cu-PGE Marathon deposit.