ORCID Profile
0000-0002-9316-7605
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Publisher: American Geophysical Union (AGU)
Date: 09-2019
DOI: 10.1029/2019GL083453
Publisher: Copernicus GmbH
Date: 15-05-2023
DOI: 10.5194/EGUSPHERE-EGU23-900
Abstract: The need to better predict how the great ice sheets will respond to continued atmospheric and ocean warming is paramount. Ice deformation and mechanisms for ice sliding across the bedrock underneath are both key considerations. Constraints of this critical ice-bedrock interface zone, particularly over extensive inland areas of Antarctica and Greenland, remain a major hurdle in ice-sheet modeling and estimations of future sea level rise.Passive seismology offers a logistically-efficient avenue for such investigations, with improvements in sensor technologies, autonomous power solutions and telemetry systems encouraging the deployment of temporary arrays for subglacial mapping and real-time monitoring. Previous experiments have demonstrated the potential of techniques such as receiver functions, horizontal-to-vertical spectral ratios (HVSR) and ambient noise interferometry for characterising the depth and nature of the ice-bedrock zone. This research looks to fully explore the sensitivity range of available passive seismic methods for the ice-bedrock interface, with a view towards optimising data collection and array geometries for future applications. In this contribution, we present an optimised workflow making use of HVSR analysis and the spatial autocorrelation (SPAC) technique using numerical simulations and field data collected from East Antarctica. The results from this study provide a benchmark to guide future deployments in the polar regions.
Publisher: Oxford University Press (OUP)
Date: 23-09-2011
Publisher: Elsevier BV
Date: 08-2015
Publisher: Informa UK Limited
Date: 10-2013
Publisher: Informa UK Limited
Date: 06-2003
Publisher: Wiley
Date: 08-2004
Publisher: American Geophysical Union (AGU)
Date: 14-08-2022
DOI: 10.1029/2022GL098539
Abstract: Antarctic geothermal heat flow (GHF) affects the thermal regime of ice sheets and simulations of ice and subglacial meltwater discharge to the ocean, but remains poorly constrained. We use an ice sheet model to investigate the impact of GHF anomalies on subglacial meltwater production in the Aurora Subglacial Basin, East Antarctica. We find that spatially‐variable GHF fields produce more meltwater than a constant GHF with the same background mean, and meltwater production increases as the resolution of GHF anomalies increases. Our results suggest that model simulations of this region systematically underestimate meltwater production using current GHF models. We determine the minimum basal heating required to bring the basal ice temperature to the pressure melting point, which should be taken together with the scale‐length of likely local variability in targeting in‐situ GHF field c aigns.
Publisher: Springer Science and Business Media LLC
Date: 26-08-2021
Publisher: American Geophysical Union (AGU)
Date: 28-05-2014
DOI: 10.1002/2014GL060073
Publisher: Elsevier BV
Date: 11-2019
Publisher: Springer Science and Business Media LLC
Date: 26-10-2022
Publisher: Informa UK Limited
Date: 06-2010
Publisher: Elsevier BV
Date: 03-2005
Publisher: Copernicus GmbH
Date: 15-05-2023
DOI: 10.5194/EGUSPHERE-EGU23-1524
Abstract: Uncertainty, as applied to geophysical and multivariate initiatives to constrain aspects of Earth-ice interactions for East Antarctica, provides a number of approaches to appraise and interrogate research results.& We discuss a number of use cases: 1) making use of multiple uncertainty metrics 2) making comparisons between spatially variable maps of inferred properties such as geothermal heat flow 3) extrapolating crustal structure given the likelihood of tectonic boundaries and 4) providing research results for interdisciplinary studies in forms that facilitate ensemble approaches.& It proves extremely useful to assess a research finding, such as a mapped geophysical property, through multiple uncertainty metrics (e.g., standard deviation, information entropy, data count).& However, a thoughtful appraisal of multiple metrics could be misleading, i.e., potentially not useful in isolation, in a case where there are significant unquantified uncertainties.& Uncertainties supplied with the mapped geophysical properties can potentially be extended to capture this broader range, but that range in turn could become less helpful as the fine detail in the quantified uncertainty will be lost.& In the case of a property such as geothermal heat flow, indirectly determined for East Antarctica, insights can be drawn by subtracting a forward model map from an empirically determined result (e.g. Aq1) to yield the non-steady state components excluded in the forward model.& In such investigations, including the maximum and minimum possible difference between maps is essential to understand which non-steady state anomalies are real, and which could be artifacts attributable to (quantified) uncertainty.& In further use cases, we show how the few available seismic measurements that constrain the crust and upper mantle structure of East Antarctica can be placed in context, given the likelihood of major tectonic boundaries beneath the ice, and link this to published constraints on the seismic structure (and hence, rheology) of the deeper lithosphere.& In terms of how the solid Earth interacts with the ice sheet above, the impact of fine scale-length variations in spatial uncertainty may be investigated in relation to, for ex le, ice sheet modelling. For a large region and relatively unexplored region such as East Antarctica, uncertainty yields many and varied insights.&
Publisher: Copernicus GmbH
Date: 15-05-2023
DOI: 10.5194/EGUSPHERE-EGU23-898
Abstract: This work aims to contribute to progress in the detection of hidden or transient hydrological events. Passive seismic methods offer high temporal resolution and the ability to monitor seismic sources hidden from direct view, making it an ideal candidate to complement other in-situ and satellite methods in these cases. The dynamics of a glacier can be greatly affected by its hydrological system, whether this be through water mediated ice fracturing, or the influence the water has on friction at the ice-bed interface. Effective detection of moving meltwater is therefore of great interest for anticipating future glacier changes and sensitivities.To effectively infer any hidden process from the observed seismic waveforms, we require a physically rigorous modelling framework. Our work therefore combines hydrodynamic models depicting meltwater flow with seismic wave propagation methods to produce synthetic seismograms. The hydrodynamic model of choice is smoothed particle hydrodynamics (SPH). This is a full, three-dimensional computational fluid dynamics method, meaning we can make minimal assumptions on the exact seismogenic mechanism prior to simulation. SPH has the capacity to capture a broad range of signal-generating processes that may prove to be of interest for modelling meltwater flow, such as fluid-solid impact events, free-surface behaviour (e.g., wave breaks), and some forms of turbulence. Beyond the modelling of complex flow, SPH also allows a simple implementation of arbitrarily shaped solid boundaries and the computation of force of the water on these boundaries a necessary output for waveform simulation.We propose a correspondence between different types of meltwater flow and the attributes of the waveforms they produce, as a step towards better detection and characterisation of hidden and short-lived events. Across a erse set of model geometries and flow types, we anticipate the collection of synthetically generated signals will be useful for categorising archived and real-time signals according to a mechanistic process using unsupervised machine learning methods in ongoing work.
Publisher: Elsevier BV
Date: 09-2019
Publisher: Elsevier BV
Date: 12-2017
Publisher: Copernicus GmbH
Date: 20-07-2023
Publisher: Informa UK Limited
Date: 26-11-2014
Publisher: Society of Exploration Geophysicists
Date: 09-2013
Abstract: We constrain the depth and seismic structure of stiff sediment cover overlying a prospective basement terrane using a passive seismic technique which uses surface wave energy from microtremor (also known as ambient seismic energy or seismic noise). This may be applied to mineral exploration under cover to decrease the inherent ambiguity in modeling potential field data for exploration targeting. We use data from arrays of portable broadband seismometers, processed using both the multimode spatially averaged coherency (MMSPAC) method and the horizontal to vertical spectral ratio (HVSR) method, to produce profiles of seismic velocity structure along a 12-km transect. We have developed field protocols to ensure consistent acquisition of high-quality data in near-mine and remote locations and a variety of ground conditions. A wavefield approaching the theoretical ideal for MMSPAC processing is created by combining the energy content of an off-road vehicle, driven around the seismometer array, and ambient sources. We found that this combination results in significantly higher-quality MMSPAC waveforms in comparison with that obtained using ambient energy alone. Under ideal conditions, a theoretical maximum depth of investigation of 600 m can be achieved with a hexagonal sensor array with 50-m radius and MMSPAC and HVSR. The modeling procedure we employ is sensitive to layer thicknesses of [Formula: see text]. A high-velocity layer in the sediment package reduces the sensitivity to deeper structure. This can limit the modeling of underlying layers but may be addressed by detailed analysis of the HVSR peaks. Microtremor recordings including off-road vehicle noise, combined with the MMSPAC and HVSR processing techniques, may therefore be used to constrain sediment structure and depth to basement in a cost-effective and efficient method that could contribute greatly to future mineral exploration under cover.
Publisher: American Geophysical Union (AGU)
Date: 08-2015
DOI: 10.1002/2015JB012210
Publisher: Seismological Society of America (SSA)
Date: 26-05-2021
DOI: 10.1785/0220210068
Abstract: The amount of recorded seismic event data is rapidly growing, and manual processing by trained human experts to infer hypocenter, source parameters, and moment tensor solutions is therefore no longer feasible. Automated procedures are required to process data efficiently and include quality-control measures that allow for outlier detection. We present a modular cross-correlation location (CCLoc) algorithm for induced seismicity that uses cross correlations of either raw seismograms or characteristic functions derived from them followed by a reverse migration procedure. The novelty of this approach is the inclusion of cross pairs of P and S arrivals and the inclusion of autocorrelations, both of which add a distance constraint to the hypocenter estimation. The algorithm is modular in the sense that preprocessing can be tailored to specific data or task. Nine months of seismic data from an underground hard-rock tin mine are processed in a fully automated mode using a machine-learning approach for seismic phase arrival detection and using the estimated arrival functions as input for CCLoc. Making use of the average cross-correlation value as a quality constraint, CCLoc can successfully infer source information on 92% of previously manually processed data. The accuracy of automatic processing is demonstrated by comparing hypocenter, source parameter, and moment tensor solutions between the two datasets. The algorithm will potentially aid the analysis of induced or other seismicity and is particularly well suited to use in the case of large numbers of seismic sensors recording many events.
Publisher: Society of Exploration Geophysicists
Date: 07-2018
Abstract: The Eastern Goldfields of Western Australia is one of the world’s premier gold-producing regions however, large areas of prospective bedrock are under cover and lack detailed lithologic mapping. Away from the near-mine environment, exploration for new gold prospects requires mapping geology using the limited data available with robust estimates of uncertainty. We used the machine learning algorithm Random Forests (RF) to classify the lithology of an underexplored area adjacent to the historically significant Junction gold mine, using geophysical and remote-sensing data, with no geochemical s ling available at this reconnaissance stage. Using a sparse training s le, 1.6% of the total ground area, we produce a refined lithologic map. The classification is stable, despite including parts of the study area with later intrusions and variable cover depth, and it preserves the stratigraphic units defined in the training data. We assess the uncertainty associated with this new RF classification using information entropy, identifying those areas of the refined map that are most likely to be incorrectly classified. We find that information entropy correlates well with inaccuracy, providing a mechanism for explorers to direct future expenditure toward areas most likely to be incorrectly mapped or geologically complex. We conclude that the method can be an effective additional tool available to geoscientists in a greenfield, orogenic gold setting when confronted with limited data. We determine that the method could be used either to substantially improve an existing map, or produce a new map, taking sparse observations as a starting point. It can be implemented in similar situations (with limited outcrop information and no geochemical data) as an objective, data-driven alternative to conventional interpretation with the additional value of quantifying uncertainty.
Publisher: Elsevier BV
Date: 04-2019
Publisher: Oxford University Press (OUP)
Date: 25-06-2014
DOI: 10.1093/GJI/GGU183
Publisher: Elsevier BV
Date: 06-2006
Publisher: Institute of Electrical and Electronics Engineers (IEEE)
Date: 07-2022
Publisher: Elsevier BV
Date: 02-2014
Publisher: American Geophysical Union (AGU)
Date: 08-2018
DOI: 10.1029/2018JB015526
Publisher: Oxford University Press (OUP)
Date: 09-2001
Publisher: American Geophysical Union (AGU)
Date: 15-12-2016
DOI: 10.1002/2016GL071201
Publisher: The Royal Society
Date: 11-2020
Abstract: This paper presents two approaches to mathematical modelling of a synthetic seismic pulse, and a comparison between them. First, a new analytical model is developed in two-dimensional Cartesian coordinates. Combined with an initial condition of sufficient symmetry, this provides a valuable check for the validity of the numerical method that follows. A particular initial condition is found which allows for a new closed-form solution. A numerical scheme is then presented which combines a spectral (Fourier) representation for displacement components and wave-speed parameters, a fourth-order Runge–Kutta integration method, and an absorbing boundary layer. The resulting large system of differential equations is solved in parallel on suitable enhanced performance desktop hardware in a new software implementation. This provides an alternative approach to forward modelling of waves within isotropic media which is efficient, and tailored to rapid and flexible developments in modelling seismic structure, for ex le, shallow depth environmental applications. Visual comparisons of the analytic solution and the numerical scheme are presented.
Publisher: Ubiquity Press, Ltd.
Date: 30-01-2020
DOI: 10.5334/JORS.287
Publisher: American Geophysical Union (AGU)
Date: 02-2006
DOI: 10.1029/2005JB003803
Publisher: Ubiquity Press, Ltd.
Date: 19-10-2021
DOI: 10.5334/JORS.365
Publisher: Springer Science and Business Media LLC
Date: 03-02-2015
DOI: 10.1038/SREP08218
Publisher: Copernicus GmbH
Date: 15-05-2023
DOI: 10.5194/EGUSPHERE-EGU23-4074
Abstract: Antarctic subglacial properties impact geothermal heat, subglacial sedimentation, and glacial isostatic adjustment critical parameters for predicting the ice sheet's response to warming oceans. However, the tectonic architecture of the Antarctic interior is unresolved, with results dependent on datasets or extrapolation used. Most existing deterministic suggestions are derived from qualitative observations and often presented as robust results however, they hide possible alternative interpretations.& Using information entropy as a measure of certainty, we present a robust tectonic segmentation model generated from similarity analysis of multiple geophysical and geological datasets. The use of information entropy provides us with an unbiased and transparent metric to communicate the ambiguities from the uncertainties of qualitative classifications. Information theory also allows us to test and optimise the methods and data to evaluate how choices impact the distribution of alternative output maps. We further discuss how this metric can quantify the predictive power of parameters as a function of regions with different tectonic settings.
Publisher: Informa UK Limited
Date: 12-2016
Publisher: IEEE
Date: 09-2015
Publisher: Society of Exploration Geophysicists
Date: 11-2020
Abstract: Identifying the location of intrusions is a key component in exploration for porphyry Cu ± Mo ± Au deposits. In typical porphyry terrains, in the absence of outcrop, intrusions can be difficult to discriminate from the compositionally similar volcanic and volcanoclastic sedimentary rocks in which they are emplaced. The ability to produce lithological maps at an early exploration stage can significantly reduce costs by assisting in planning and prioritization of detailed mapping and s ling. Additionally, a data-driven strategy provides opportunity for the discovery of intrusions not identified during conventional mapping and interpretation. We used random forests (RF), a supervised machine-learning algorithm, to classify rock types throughout the Kliyul porphyry prospect in British Columbia, Canada. Rock types determined at geochemical s ling sites were used as training data. Airborne magnetic and radiometric data, geochemistry, and topographic data were used in classification. Results were validated using First Quantum Minerals’ geologic map, which includes additional detail from targeted location and transect mapping. The petrophysical and compositional similarity of rock types resulted in a noisy classification. Intrusions, particularly the more discrete, were inconsistently predicted, likely due to their limited extent relative to data s ling intervals. Closer examination of class membership probabilities (CMPs) identified locations where the probability of an intrusion being present was elevated significantly above the background. Indeed, a large proportion of mapped intrusions correspond to areas of elevated probability and, importantly, areas were highlighted as potential intrusions that were not identified in geologic mapping. The RF classification produced a reasonable lithological map, if lacking in resolution, but more significantly, great benefit comes from the insights drawn from the RF CMPs. Mapping the spatial distribution of elevated intrusion CMP, a soft classifier approach, produced a map product that can target intrusions and prioritize detailed mapping for mineral exploration.
Publisher: American Geophysical Union (AGU)
Date: 02-2020
DOI: 10.1029/2019JF005354
Abstract: The Southern Ocean (in the region 60–180° E) south of the Indian Ocean, Australia, and the West Pacific is noted for the frequent occurrence and severity of its storms. These storms give rise to high‐ litude secondary microseisms from sources, including the deep ocean regions, and primary microseisms where the swells impinge on submarine topographic features. A better understanding of the varying microseism wavefield enables improvements to seismic imaging and development of proxy observables to complement sparse in situ wave observations and hindcast models of the global ocean wave climate. We analyze 12–26 years of seismic data from 11 seismic stations either on the East Antarctic coast or sited in the Indian Ocean, Australia, and New Zealand. The power spectral density of the seismic wavefield is calculated to explore how the time‐changing microseism intensity varies with (i) sea ice coverage surrounding Antarctica and (ii) the Southern Annular Mode (SAM) climate index. Variations in sea ice extent are found to be the dominant control on the microseism intensity at Antarctic stations, which exhibit a seasonal pattern phase‐shifted by 4–5 months compared to stations in other continents. Peaks in extremal intensity at East Antarctic stations occur in March–April, with the highest peaks for secondary microseisms occurring during negative SAM events. This relationship between microseism intensity and the SAM index is opposite to that observed on the Antarctic Peninsula. This work informs the complexity of microseism litudes in the Southern Hemisphere and assists ongoing interdisciplinary investigations of interannual variability and long‐term trends.
Publisher: Copernicus GmbH
Date: 25-07-2023
Publisher: American Geophysical Union (AGU)
Date: 06-2017
DOI: 10.1002/2017JB014141
Publisher: Elsevier BV
Date: 02-2012
Publisher: International Joint Conferences on Artificial Intelligence Organization
Date: 08-2019
Abstract: Trust evaluation of people and information on Twitter is critical for maintaining a healthy online social environment. How to evaluate the trustworthiness of users and tweets becomes a challenging question. In this demo, we show how our proposed CoTrRank approach deal with this problem. This approach models users and tweets in two coupled networks and calculate their trust values in different trust spaces. In particular, our solution provides a configurable way when mapping the calculated raw evidences to the trust values. The CoTrRank demo system has an interactive interface to show how our proposed approach produces more effective and adaptive trust evaluation results comparing with baseline methods.
Publisher: Frontiers Media SA
Date: 22-10-2019
Publisher: Informa UK Limited
Date: 06-2003
Publisher: Oxford University Press (OUP)
Date: 16-01-2012
Publisher: Elsevier BV
Date: 10-2015
Publisher: American Geophysical Union (AGU)
Date: 07-2011
DOI: 10.1029/2011GL047971
Publisher: Elsevier BV
Date: 06-2019
Publisher: Springer Science and Business Media LLC
Date: 18-11-2022
Publisher: Elsevier BV
Date: 09-2019
Publisher: Geological Society of America
Date: 2007
DOI: 10.1130/G23341A.1
Publisher: Cambridge University Press (CUP)
Date: 02-03-2021
DOI: 10.1017/JOG.2021.21
Abstract: We use seismic refraction data to investigate the firn structure across a suture zone on the Amery Ice Shelf, East Antarctica, and the possible role of glacier dynamics in firn evolution. In the downstream direction, the data reveal decreasing compressional-wave velocities and increasing penetration depth of the propagating wave in the firn layer, consistent with $\\sim$ 1 m firn thickening every 6 km. The boundary between the Lambert Glacier unit to the west and a major suture zone and the Mawson Escarpment Ice Stream unit to the east, is marked by differences in firn thicknesses, compressional-wave velocities and seismic anisotropy in the across-flow direction. The latter does not contradict the presence of a single-maximum crystal orientation fabric oriented 45– $90^{\\circ }$ away from the flow direction. This is consistent with the presence of transverse simple shear governing the region's underlying ice flow regime, in association with elevated strain along the suture zone. The confirmation and quantification of the implied dynamic coupling between firn and the underlying ice requires integration of future seismic refraction, coring and modelling studies. Because firn is estimated to cover $\\sim$ 98% of the Antarctic continent any such coupling may have widespread relevance to ice-sheet evolution and flow.
Publisher: Informa UK Limited
Date: 12-2016
Publisher: American Geophysical Union (AGU)
Date: 02-2021
DOI: 10.1029/2020GC009428
Abstract: We present a refined map of geothermal heat flow for Antarctica, Aq1, based on multiple observables. The map is generated using a similarity detection approach by attributing observables from geophysics and geology to a large number of high‐quality heat flow values ( N = 5,792) from other continents. Observables from global, continental, and regional datasets for Antarctica are used with a weighting function that allows the degree of similarity to increase with proximity and how similar the observables are. The similarity detection parameters are optimized through cross correlation. For each grid cell in Antarctica, a weighted average heat flow value and uncertainty metrics are calculated. The Aq1 model provides higher spatial resolution in comparison to previous results. High heat flow is shown in the Thwaites Glacier region, with local values over 150 mW m −2 . We also map elevated values over 80 mW m −2 in Palmer Land, Marie Byrd Land, Victoria Land and Queen Mary Land. Very low heat flow is shown in the interior of Wilkes Land and Coats Land, with values under 40 mW m −2 . We anticipate that the new geothermal heat flow map, Aq1, and its uncertainty bounds will find extended use in providing boundary conditions for ice sheet modeling and understanding the interactions between the cryosphere and solid Earth. The computational framework and open architecture allow for the model to be reproduced, adapted and updated with additional data, or model subsets to be output at higher resolution for regional studies.
Publisher: Oxford University Press (OUP)
Date: 30-05-2020
DOI: 10.1093/GJI/GGAA265
Abstract: Accurate measurement of the local component of geodetic motion at GPS stations presents a challenge due to the need to separate this signal from the tectonic plate rotation. A pressing ex le is the observation of glacial isostatic adjustment (GIA) which constrains the Earth’s response to ice unloading, and hence, contributions of ice-covered regions such as Antarctica to global sea level rise following ice mass loss. While both vertical and horizontal motions are of interest in general, we focus on horizontal GPS velocities which typically contain a large component of plate rotation and a smaller local component primarily relating to GIA. Incomplete separation of these components introduces significant bias into estimates of GIA motion vectors. We present the results of a series of tests based on the motions of GPS stations from East Antarctica: (1) signal separation for sets of synthetic data that replicate the geometric character of non-separable, and separable, GIA-like horizontal velocities and (2) signal separation for real GPS station data with an appraisal of uncertainties. For both synthetic and real motions, we compare results where the stations are unweighted, and where each station is areal-weighted using a metric representing the inverse of the spatial density of neighbouring stations. From the synthetic tests, we show that a GIA-like signal is recoverable from the plate rotation signal providing it has geometric variability across East Antarctica. We also show that areal-weighting has a very significant effect on the ability to recover a GIA-like signal with geometric variability, and hence on separating the plate rotation and local components. For the real data, assuming a rigid Antarctic plate, fitted plate rotation parameters compare well with other studies in the literature. We find that 25 out of 36 GPS stations examined in East Antarctica have non-zero local horizontal velocities, at the 2σ level, after signal separation. We make the code for weighted signal separation available to assist in the consistent appraisal of separated signals, and the comparison of likely uncertainty bounds, for future studies.
Publisher: Oxford University Press (OUP)
Date: 14-04-2016
DOI: 10.1093/GJI/GGW150
Publisher: Oxford University Press (OUP)
Date: 23-08-2022
DOI: 10.1093/GJI/GGAC322
Abstract: Modern microseismic monitoring systems can generate extremely large data sets with signals originating from a variety of natural and anthropogenic sources. These data sets may contain multiple signal types that require classification, analysis and interpretation: a considerable task if done manually. Machine learning techniques may be applied to these data sets to expedite and improve such analysis. In this study, we apply an unsupervised technique, the Self-Organizing Map (SOM), to high-volume data recorded by an in-mine microseismic network. This represents a good ex le of a large seismic data set that contains a wide range of signals, owing to the ersity of source processes occurring within the mine. The signals are quantified by extracting a number of features (temporal and spectral) from the waveforms which are provided as input data for the SOM. We develop and implement a weighted variant of the SOM in which the contributions of various different features to the training of the map are allowed to evolve. The standard and weighted SOMs are applied to the data, and the output maps compared. Both variants are able to separate source types based on the waveform characteristics, allowing for rapid, automatic classification of signals and the ability to find sources with similar waveforms. Fast classification of such signals provides practical benefit by automatically discarding waveforms associated with anthropogenic sources within the mine while seismic signals originating from genuine microseismic events, which constitute a small fraction of all signals, can be prioritized for subsequent processing and analysis. The weighted variant provides an exploratory tool through quantification of the contribution of different features to the clustering process. This helps to optimize the performance of the SOM through the identification of redundant features. Furthermore, those features that are assigned large weights are considered to be more representative of the source generation processes as they contribute more to the cluster separation process. We apply weighted SOMs to data from a mine recorded during two different time periods, corresponding to different stages of the mine development. Changes in feature importance and in the observed distribution of feature values indicate evolving source generation processes and may be used to support investigatory analysis. The weighted SOM therefore represents an effective tool to help manage and investigate large seismic data sets, providing both practical benefit and insight into underlying event mechanisms.
Publisher: Elsevier BV
Date: 12-2019
Publisher: Society of Exploration Geophysicists
Date: 05-2013
Abstract: Recently developed methods for inferring abrupt changes in data series enable such change points in time or space to be identified, and also allow us to estimate noise levels of the observed data. The inferred probability distributions of these parameters provide insights into the capacity of the observed data to constrain the geophysical analysis and hence the magnitudes, and likely sources, of uncertainty. We carry out a change-point analysis of sections of four borehole geophysical logs (density, neutron absorption, sonic interval time, and electrical resistivity) using transdimensional Bayesian Markov chain Monte Carlo to s le a model parameter space. The output is an ensemble of values which approximate the posterior distribution of model parameters. We compare the modeled change points, borehole log parameters, and the variance of the noise distribution of each log with the observed lithology classes down the borehole to make an appraisal of the uncertainty characteristics inherent in the data. Our two ex les, one with well-defined lithology changes and one with more subtle contrasts, show quantitatively the nature of the lithology contrasts for which the geophysical borehole log data will produce a detectable response in terms of inferred change points. We highlight the different components of variation in the observed data: due to the geologic process (dominant lithology changes) that we hope to be able to infer, geologic noise due to variability within each lithology, and analytical noise due to the measurement process. This inference process will be a practical addition to the analytical tool box for borehole and other geophysical data series. It reveals the level of uncertainties in the relationships between the data and the observed lithologies and would be of great use in planning and interpreting the results of subsequent routine processing.
Publisher: Institute of Electrical and Electronics Engineers (IEEE)
Date: 03-2015
Publisher: Copernicus GmbH
Date: 15-05-2023
DOI: 10.5194/EGUSPHERE-EGU23-913
Abstract: We present an analytic framework to model seismic body waves due to supraglacial, englacial or subglacial flows in solid ice based on a smoothed particle hydrodynamic (SPH) simulation. Consisting of two parts, i) hydrodynamic modelling and ii) seismic wave propagation, the flexible framework allows for a pre-existing fluid simulation to be supplied to generate synthetic seismic signals. The field of glacier-related seismology has seen rapid development in recent years, with an expanded availability of passive seismic datasets that contain records of seismic disturbances generated by glacier processes. Some of these processes, such as basal slip and crevasse propagation, have mechanisms with plate tectonic deformation counterparts, however, many glacier signals are generated by moving melt water. This contribution aims to inform the interpretation of such signals.Our approach tracks the trajectories of fluid particles near the water-ice interface, as recorded in standard simulation outputs, to create a catalogue describing the energetics of each collision. We illustrate the capability of this framework using four end-member cases of water flow along surface channels with different geometries. Seismic signals are simulated at a variety of locations around the channel based on the impulse of the database of simulated collisions. We consider the change in character of the seismic waveforms by modelling frequency-dependent attenuation and weak dispersion in the glacial ice, in addition to the standard geometric spreading. The acceleration time series produced in this work are invariant to the temporal and spatial resolution of the hydrodynamic simulation, provided more than some minimum resolution is used. These time series may be converted to velocity or displacement for comparison with observed seismic signals.Investigating the seismic waves generated for our four channel geometries, we find distinct waveform envelope shapes with different first and later litude peaks matching initial and subsequent collisions of the melt water surge with the supraglacial channel walls. The change in waveform character with distance is also captured such that the character attributes due to the process and the those due to the propagation effects may be understood. The flexibility inherent in the model framework will allow for the generation of the seismic signals from simulations of a variety of different water flow geometries including simple 3D channels into and through a glacier. We make the code available as an open source resource for the polar geophysics community with the aim of adding to the toolbox of available approaches to inform the potential future seismic monitoring of melt water movement and related glacier processes.
Publisher: Informa UK Limited
Date: 12-2013
Publisher: Informa UK Limited
Date: 12-2015
Publisher: Frontiers Media SA
Date: 17-08-2022
DOI: 10.3389/FEART.2022.963525
Abstract: Geothermal heat flow is inferred from the gradient of temperature values in boreholes or short-penetration probe measurements. Such measurements are expensive and logistically challenging in remote locations and, therefore, often targeted to regions of economic interest. As a result, measurements are not distributed evenly. Some tectonic, geologic and even topographic settings are overrepresented in global heat flow compilations other settings are underrepresented or completely missing. These limitations in representation have implications for empirical heat flow models that use catalogue data to assign heat flow by the similarity of observables. In this contribution, we analyse the s ling bias in the Global Heat Flow database of the International Heat Flow Commission the most recent and extensive heat flow catalogue, and discuss the implications for accurate prediction and global appraisals. We also suggest correction weights to reduce the bias when the catalogue is used for empirical modelling. From comparison with auxiliary variables, we find that each of the following settings is highly overrepresented for heat flow measurements continental crust, sedimentary rocks, volcanic rocks, and Phanerozoic regions with hydrocarbon exploration. Oceanic crust, cratons, and metamorphic rocks are underrepresented. The findings also suggest a general tendency to measure heat flow in areas where the values are elevated however, this conclusion depends on which auxiliary variable is under consideration to determine the settings. We anticipate that using our correction weights to balance disproportional representation will improve empirical heat flow models for remote regions and assist in the ongoing assessment of the Global Heat Flow database.
Publisher: Oxford University Press (OUP)
Date: 04-07-2019
DOI: 10.1093/GJI/GGZ057
Publisher: American Geophysical Union (AGU)
Date: 08-2008
DOI: 10.1029/2007TC002116
Publisher: American Geophysical Union (AGU)
Date: 03-2019
DOI: 10.1029/2018JB016959
Publisher: Informa UK Limited
Date: 12-2015
Publisher: Copernicus GmbH
Date: 25-07-2023
DOI: 10.5194/EGUSPHERE-2023-1341
Abstract: Abstract. Given the high number and ersity of events in a typical cryoseismic dataset, in particular those recorded on ice sheet margins, it is desirable to use a semi-automated method of grouping similar events for reconnaissance and ongoing analysis. We present a workflow for employing semi-unsupervised cluster analysis to inform investigations of the processes occurring in glaciers and ice sheets. In this demonstration study, we make use of a seismic event catalogue previously compiled for the Whillans Ice Stream, for the 2010–2011 austral summer (outlined in companion paper, Latto et al., 2023). We address the challenges of seismic event analysis for a complex wavefield by clustering similar seismic events into groups using characteristic temporal, spectral, and polarization attributes of seismic time series with the k-means++ algorithm. This provides the basis for a reconnaissance analysis of a seismic wavefield that contains local events (from the ice stream) set in an ambient wavefield that itself contains a ersity of signals (mostly from the Ross Ice Shelf). As one result, we find that two clusters include stick-slip events that erge in terms of length and initiation locality (i.e. Central Sticky Spot and/or the grounding line). We also identify a swarm of high frequency signals on January 16–17, 2011 that are potentially associated with a surface melt event from the Ross Ice Shelf. Used together with the event detection presented in the companion paper, the semi-automated workflow could readily generalize to other locations, and as a possible benchmark procedure, could enable the monitoring of remote glaciers over time and comparisons between locations.
Publisher: Society of Exploration Geophysicists
Date: 09-2020
Abstract: The Heazlewood-Luina-Waratah area is a prospective region for minerals in northwest Tasmania, Australia, associated with historically important ore deposits related to the emplacement of granite intrusions and/or ultramafic complexes. The geology of the area is poorly understood due to the difficult terrain and dense vegetation. We have constructed an initial high-resolution 3D geologic model of this area using constraints from geologic maps and geologic and geophysical cross sections. This initial model is improved upon by integrating results from 3D geometry and physical property inversion of potential field (gravity and magnetic) data, petrophysical measurements, and updated field mapping. Geometry inversion reveals that the Devonian granites in the south are thicker than previously thought, possibly connecting to deep sources of mineralization. In addition, we identified gravity anomalies to the northeast that could be caused by near-surface granite cupolas. A newly discovered ultramafic complex linking the Heazlewood and Mount Stewart Ultramafic Complexes in the southwest also has been modeled. This implies a greater volume of ultramafic material in the Cambrian successions and points to a larger obducted component than previously thought. The newly inferred granite cupolas and ultramafic complexes are targets for future mineral exploration. Petrophysical property inversion reveals a high degree of variation in these properties within the ultramafic complexes indicating a variable degree of serpentinization. Sensitivity tests suggest maximum depths of 2–3 km for the contact aureole that surrounds major granitic intrusions in the southeast, whereas the Heazlewood River complex is likely to have a deeper source up to 4 km. We have demonstrated the value of adding geologic and petrophysical constraints to 3D modeling for the purpose of guiding mineral exploration. This is particularly important for the refinement of geologic structures in tectonically complex areas that have lithology units with contrasting magnetic and density characteristics.
Publisher: Copernicus GmbH
Date: 20-07-2023
DOI: 10.5194/EGUSPHERE-2023-1340
Abstract: Abstract. Cryoseismology is a powerful toolset for progressing the understanding of the structure and dynamics of glaciers and ice sheets. It can enable the detection of hidden processes such as brittle fracture, basal sliding, transient hydrological processes, and calving. Due to the ersity and often low signal-to-noise levels of glacier processes, the automated detection of seismic events caused by such processes can pose a challenge. We present a novel approach for the automated detection of events in glacier environments, the multi-STA/LTA algorithm, with a focus on capturing the many signal types recorded on ice sheet margins. This develops the use of approaches that use the ratio between short and long time averages (sta,lta) of signal litude as the means of event detection. Implemented in the open source and widely used ObsPy python package, the algorithm constructs a hybrid characteristic function from a set of sta, lta pairs. We apply the multi-STA/LTA algorithm to data from a seismic array deployed on the Whillans Ice Stream (WIS) in West Antarctica (austral summer 2010–2011), to form an event catalogue. The new algorithm compares favorably with standard approaches, yielding a ersity of seismic events, including all previously identified stick-slip events (Pratt et al., 2014), teleseisms, and other noise-type signals. We investigate a partial association of seismicity with the tidal cycle, and a slight association with ice temperature changes of the Antarctic summer. The new algorithm and workflow has the potential to yield systematic catalogues for further cryoseismology studies: conventional glacier seismology, and those tailored to pattern recognition by machine learning.
Publisher: American Geophysical Union (AGU)
Date: 2003
DOI: 10.1029/2003GL018090
Publisher: Frontiers Media SA
Date: 27-11-2020
DOI: 10.3389/FEART.2020.577502
Abstract: Interdisciplinary research concerning solid Earth–cryosphere interaction and feedbacks requires a working model of the Antarctic crust and upper mantle. Active areas of interest include the effect of the heterogeneous Earth structure on glacial isostatic adjustment, the distribution of geothermal heat, and the history of erosion and deposition. In response to this research need, we construct an adaptable and updatable 3D grid model in a software framework to contain and process solid Earth data. The computational framework, based on an open source software package agrid , allows different data sources to be combined and jointly analyzed. The grid model is populated with crustal properties from geological observations and geochronology results, where such data exist, and published segmentation from geophysical data in the interior where direct observations are absent. The grid also contains 3D geophysical data such as wave speed and derived temperature from seismic tomographic models, and 2D datasets such as gravity anomalies, surface elevation, subglacial temperature, and ice sheet boundaries. We demonstrate the usage of the framework by computing new estimates of subglacial steady-state heat flow in a continental scale model for east Antarctica and a regional scale model for the Wilkes Basin in Victoria Land. We hope that the 3D model and framework will be used widely across the solid Earth and cryosphere research communities.
Publisher: Oxford University Press (OUP)
Date: 09-2001
Publisher: MDPI AG
Date: 27-10-2021
DOI: 10.3390/MIN11111195
Abstract: Over the last two decades, Mineral Resources Tasmania has been developing regional 3D geological and geophysical models for prospective terranes at a range of scales and extents as part of its suite of precompetitive geoscience products. These have evolved in conjunction with developments in 3D modeling technology over that time. Commencing with a jurisdiction-wide 3D model in 2002, subsequent modeling projects have explored a range of approaches to the development of 3D models as a vehicle for the better synthesis and understanding of controls on ore-forming processes and prospectivity. These models are built on high-quality potential field data sets. Assignment of bulk properties derived from previous well-constrained geophysical modeling and an extensive rock property database has enabled the identification of anomalous features that have been targeted for follow-up mineral exploration. An aspect of this effort has been the generation of uncertainty estimates for model features. Our experience is that this process can be hindered by models that are too large or too detailed to be interrogated easily, especially when modeling techniques do not readily permit significant geometric changes. The most effective 3D modeling workflow for insights into mineral exploration is that which facilitates the rapid hypothesis testing of a wide range of scenarios whilst satisfying the constraints of observed data.
Publisher: Elsevier BV
Date: 12-2020
No related organisations have been discovered for Anya Reading.
Start Date: 2015
End Date: 2015
Funder: Australian Research Council
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Funder: AMIRA International Ltd
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Funder: Newcrest Mining Limited
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Funder: Australian Research Council
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Funder: Anglo American Exploration Philippines Inc
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Funder: Australian National University
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Funder: University of Melbourne
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Funder: Zinifex Australia Ltd
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Funder: AMIRA International Ltd
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Funder: Oz Minerals Australia Limited
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Funder: AngloGold Ashanti Australia Limited
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Funder: CSIRO Earth Science & Resource Engineering
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End Date: 2009
Funder: Mineral Resources Tasmania
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Funder: Barrick (Australia Pacific) PTY Limited
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Funder: Rio Tinto Exploration
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Funder: BHP Billiton Ltd
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Funder: St Barbara Limited
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Funder: University of Queensland
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Funder: Newcrest Mining Limited
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Funder: ARC C of E Industry Partner $ to be allocated
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Funder: Minerals Council of Australia
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End Date: 2013
Funder: Newmont Australia Ltd
View Funded ActivityStart Date: 2021
End Date: 2024
Funder: Australian Research Council
View Funded ActivityStart Date: 2005
End Date: 2013
Funder: Australian Research Council
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