Investigation of Depth and Dimension Effects on Ireland’s Karst Aquifers Using Synthetic Seismic Reflected Data

Karst regions are frequently classed as aquifers because they often contain sufficient groundwater to meet various needs. In Ireland approximately 16 percent of public water supply is provided by groundwater resources and karst limestones are important sources of groundwater. There is evidence of karst features (conduits/caves) at depths >100 m below ground level in Irish limestones that can be water bearing. The nature and extent of these types of features are poorly understood, and, to date, deep groundwater resources are largely untapped and uncharacterised. Groundwater exploration and development of these deeper features could be based on 3-D imaging using geophysics to identify potential strategic drilling targets. Karst areas are very difficult environments for any geophysical exploration due to strong lateral and vertical heterogeneity. The main objective of the study is to develop a better understanding of deep groundwater resources in Ireland’s limestones using available seismic datasets. We focus on direct reflection of water filled structures using characteristic seismic feature

Anisotropic Seismic Structure of the Northern East African Rift System and Red Sea from Surface Waves

Continental rifting is a fundamental process of plate tectonics that has been shaping our planet for billions of years. The northern East African Rift system, including the Gulf of Aden and the Red Sea, presents an excellent opportunity to study this process in locations sub -aerially prior to continental break-up, through to full seafloor spreading. We present results from anisotropic surface wave imaging of the region’s crust and uppermost mantle. Anisotropic structures provide additional information about the form of structures at depth and deformation in the region. We find low seismic velocities within the Main Ethiopian Rift (MER), the Red Sea and Gulf of Aden that likely represent melt emplaced in the crust and uppermost mantle. Radial anisotropy, defined as a difference in wave speed of vertically versus horizontally polarized seismic waves, is observed across the region but is strongest within the rift. The strength of radial anisotropy in the MER suggests that horizontally layered melt intrusions are the dominant mode of melt storage in the mid to lower crust. Azimuthal anisotropy, defined as a variation in seismic wave speed as a function of direction, shows complex patterns that are likely related to ancient structures away from the rift, and structures related to extension and melt emplacement within the rift. Taken together, our results suggest melt has played an important role in shaping the crustal structure within the rift and may have also shaped the ancient pre-rift crustal structure

3D_DIG_Moho_and_LAB_Model_EChambers2024.nc

READ ME File For '3D_DIG_Moho_and_LAB_Model_EChambers2024_INTERPOLATED.nc' Dataset DOI: ReadMe Author: Emma L. Chambers, Dublin Institute for advanced Studies, ORCID: https://orcid.org/0000-0001-6969-2920 This dataset supports the publication: AUTHORS: Emma L. Chambers*, Javier Fullea, Duygu Kiyan, Sergei Lebedev, Christopher J. Bean, Pat Meere, J. Stephen Daly, Nicola Willmot Noller, Robert Raine, Sarah Blake, Brian M. O’Reilly TITLE: A new 3D temperature model for Ireland from joint geophysical-petrological inversion of seismic, surface heat flow and petrophysical data JOURNAL: Geophysical Journal International PAPER DOI IF KNOWN: PREPRINT: EarthArXiv PREPRINT DOI: https://doi.org/10.31223/X5RX3P This dataset contains: "3D_DIG_Moho_and_LAB_Model_EChambers2024_INTERPOLATED.nc" which has the final Moho and LAB depth models. Also included are latitude and longitude coordinate variables in both WGS84 and ITM coordinates. The model has been interpolated to 0.025 degree spacing laterally from an original 0.2 degree spacing. This file is in NetCDF format. NetCDF files can be opened in most data analysis environments. For example in MATLAB use the netcdf.open command or in python xr.open_dataset(dataset.nc). Date of data collection: 10/09/2024 Information about geographic location of data collection: Dataset covers the Republic of Ireland and Northern Ireland in both WGS84 (latitude and longitude, EPSG:4326) and ITM coordinates (latITM and lonITM, EPSG:2157). Licence: CC BY-SA 4.0 Related projects and datasets: 3D_DIG_Temp_and_RMS_Model_EChambers2024.nc 3D_DIG_Temp_and_RMS_Model_EChambers2024_INTERPOLATED.nc 3D_DIG_Moho_and_LAB_Model_EChambers2024.n

Machine Learning Approaches to Seismic Velocity Model and Seismogram Prediction in Earth’s Shallow Crust

Recent advances in machine learning present new ways for geoscientists to predict geological subsurface properties. Fourier Neural Operators (FNOs) are increasingly being used as an alternative to conventional seismic imaging approaches. FNOs have been shown to predict accurate simulations of seismic waves several hundred times faster than physics-based solvers post-training. In synthetic volcanic settings, FNOs have been applied successfully to both the forward and inverse problem, capturing fine-scale velocity structure in heterogeneous models and seismograms. However, transferring the successful performance of simulation-trained FNOs to field-gathered seismic data is yet to be attained. To achieve this, training models must contain representative small-scale velocity heterogeneities and topography to produce highly scattered codas in synthetic seismograms. This research presents work in progress on simulation-to-real FNO applications using field-gathered seismic data from offshore sedimentary basin settings as a testbed environment. Historical seismic survey datasets from Atlantic sedimentary basins are often accompanied by additional site-specific geological constraints. This makes the creation of synthetic velocity models and seismograms with field-derived properties possible, centering the collation of data for real-world machine learning applications in the numerical domain. The longterm research goal is to bring insights gained from training FNOs on a better understood seismic environment to volcanic and other complex environments in future work

Understanding Unrest and Dynamic Triggering Processes on Sierra Negra, Galápagos Islands

Dynamic earthquake triggering refers to the phenomenon where local seismic activity is induced by dynamic stress disturbances, originating from teleseismic earthquakes. An understanding of dynamic triggering on volcanoes offers a window into volcano stress states and seismicity initiation. Sierra Negra, a basaltic shield volcano situated on Isabela Island, Galápagos, has been the site of recurring episodes of dynamic triggering. Sierra Negra features a large elliptical summit caldera with a trap-door fault system and a magma reservoir extending 2km below the surface. Sierra Negra experienced an eruption in June 2018, characterized by a sequence of pre-eruption inflation, co-eruption deflation, and post-eruption inflation. The occurrence of dynamic earthquake triggering at Sierra Negra was observed in response to high magnitude teleseismic events from 2010 to 2018. The frequency of dynamically triggered earthquakes correlates with the increasing inflation of the magma reservoir. In this study, we aim to answer two questions: 1) How confident are we that the seismicity on Sierra Negra is dynamically triggered? And, 2) What is the location of these dynamically triggered events? Random simulations are used to calculate the likelihood that triggered events are related to teleseismic arrivals rather than being representative of local seismic activity. Results show that pre-2018 eruption, the likelihood that events are dynamic triggering is very high, compared to post-2018 eruption where events are more likely to be representative of local seismic activity. We only have access to a single station (VCH1) on Sierra Negra meaning the single-station location method must be used to locate all dynamically triggered events. To test and refine this method, 79 known seismic events are located using a full network from April 2018 – December 2018. Rotation of the 3-component VCH1 is used to calculate the back-azimuth and the P-wave to S-wave delay is used to calculate the distance between event and station. 21 unknown dynamically triggered events are located in and around the caldera using this method. Looking forward we hope to understand the relationship between the location and timing of dynamic triggering, and its potential use in understanding volcano unrest state

InsituMarine Laboratory for Geosystems Research

The iMARL marine equipment pool , led by the Dublin Institute for Advanced Studies (DIAS), is a significant initiative in oceanographic research, leveraging a diverse array of ocean sensors for various purposes. • It comprises broadband Ocean Bottom Seismographs (OBS), acoustic sensors, and sensors for measuring absolute pressure and temperature in the water column. • The sensor pool is mobile and can be deployed around the world. • The equipment will allow for the detection of offshore earthquakes and offshore storms, as well underwater noise from vessels and biologically generated acoustic signals (e.g. from cetaceans). • Important impacts from this equipment include: natural resources quantification, natural hazard estimation, environmental and baseline climate related “insitu” ocean monitoring and the monitoring of marine noise pollution

Tuairisc Bhliantúil 2023 Institiúid Ard-Léinn Bhaile Átha Cliath.

Communications of the Dublin Institute for Advanced Studie