ORCID Profile
0000-0001-8906-8156
Current Organisation
University of Calgary
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Rings And Algebras | Theoretical Physics | Pure Mathematics | Group Theory And Generalisations (Incl. Topological Groups And Lie
Publisher: Springer Science and Business Media LLC
Date: 04-12-2022
DOI: 10.1038/S43247-022-00629-W
Abstract: Tailings dams retain the waste by-products of mining operations and are among the world’s largest engineered structures. Recent tailings dam failures highlight important gaps in current monitoring methods. Here we demonstrate how ambient noise interferometry can be applied to monitor dam performance at an active tailings dam using a geophone array. Seismic velocity changes of less than 1% correlate strongly with water level changes at the adjacent tailings pond. We implement a power-law relationship between effective stress and shear wave velocity, using the pond level recordings with shear wave velocity profiles obtained from cone penetration tests to model changes in shear wave velocities. The resulting one-dimensional model shows good agreement with the seismic velocity changes. As shear wave velocity provides a direct measure of soil stiffness and can be used to infer numerous other geotechnical design parameters, this method provides important advances in understanding changes in dam performance over time.
Publisher: Springer Science and Business Media LLC
Date: 30-12-2022
Publisher: Acoustical Society of America (ASA)
Date: 09-2013
DOI: 10.1121/1.4817833
Abstract: This paper presents estimates of seabed roughness and geoacoustic parameters and uncertainties on the Malta Plateau, Mediterranean Sea, by joint Bayesian inversion of mono-static backscatter and spherical wave reflection-coefficient data. The data are modeled using homogeneous fluid sediment layers overlying an elastic basement. The scattering model assumes a randomly rough water-sediment interface with a von Karman roughness power spectrum. Scattering and reflection data are inverted simultaneously using a population of interacting Markov chains to s le roughness and geoacoustic parameters as well as residual error parameters. Trans-dimensional s ling is applied to treat the number of sediment layers and the order (zeroth or first) of an autoregressive error model (to represent potential residual correlation) as unknowns. Results are considered in terms of marginal posterior probability profiles and distributions, which quantify the effective data information content to resolve scattering/geoacoustic structure. Results indicate well-defined scattering (roughness) parameters in good agreement with existing measurements, and a multi-layer sediment profile over a high-speed (elastic) basement, consistent with independent knowledge of sand layers over limestone.
Publisher: Research Square Platform LLC
Date: 14-09-2023
Publisher: American Geophysical Union (AGU)
Date: 22-11-2015
DOI: 10.1002/2015GL065868
Publisher: Acoustical Society of America (ASA)
Date: 05-2013
DOI: 10.1121/1.4806741
Abstract: This paper presents a highly efficient approach to matched-field localization of an unknown number of ocean acoustic sources employing a graphics processing unit (GPU) for massively parallel computations. A Bayesian formulation is developed in which the number, locations, and complex spectra ( litudes and phases) of multiple sources, as well as noise variance at each frequency, are considered unknown random variables constrained by acoustic data and prior information. The number of sources is determined during an initial burn-in stage by minimizing the Bayesian information criterion using an efficient birth/death scheme. Marginal posterior probability distributions for source locations are then computed using Gibbs s ling. Source and noise spectra are s led implicitly by applying analytic maximum-likelihood solutions in terms of the source locations (explicit parameters). This greatly reduces the dimensionality of the inversion, but requires solving a very large number (order 105) of complex matrix inversions for each s le of the explicit parameters. These inversions can be solved in parallel on a GPU, increasing efficiency by a factor of ~100. Ex les are given of localizing a large number of sources (up to 10) in near real time.
Publisher: Acoustical Society of America (ASA)
Date: 10-2015
DOI: 10.1121/1.4930186
Abstract: This paper develops a fast numerical approach to computing spherical-wave reflection coefficients (SWRCs) for layered seabeds, which provides substantial savings in computation time when used as the forward model for geoacoustic inversion of broadband seabed reflectivity data. The approach exploits the Sommerfeld-integral representation of SWRCs as the Hankel transform of a function proportional to the plane-wave reflection coefficient (PWRC), and applies Levin integration to the rapidly oscillating integrand cast as the product of a (pre-computed) media-independent matrix and a vector involving PWRCs at a sparse s ling of integration angles. Compared to conventional Simpson's rule integration for computation of the SWRC, the Levin integration yields speed-up factors of an order of magnitude or more. Further, it results in reduced memory requirements for storage of pre-computed quantities, a desirable property when a graphics processing unit (GPU) is used for parallel computation of SWRCs. The paper applies trans-dimensional Bayesian inversion to investigate the impact of forward modeling in terms of PWRCs and SWRCs on the estimation of geoacoustic parameters and uncertainties. Model comparisons are quantified in simulated- and measured-data inversions by comparing the estimated geoacoustic parameters to the true parameters or core measurements, respectively, and by calculating the deviance information criterion for model selection.
Publisher: Acoustical Society of America (ASA)
Date: 05-2013
DOI: 10.1121/1.4806740
Abstract: Bayesian inference algorithms in geoacoustic inversion have high computational requirements on multiple computational scales. Predicting (modeling) data to match observations represents fine-grained computations which often cannot be implemented efficiently on CPU clusters since high latency and communication overhead outweigh parallelization gains. However, GPUs, which operate efficiently on 100,000s of parallel threads with low latency and high bandwidth, can provide significant performance gains. Bayesian s ling is generally coarse-grained, and can be implemented efficiently in parallel on multi-core/cluster architectures. For ex le, population Monte Carlo simulates many Markov chains in parallel, with chains running independently between interactions (at predefined intervals) which exchange information throughout the population, substantially increasing s ling efficiency. This paper combines fine- and coarse-grained parallelization to profoundly improve the efficiency of geoacoustic inversion of seabed reflection data. Spherical-wave reflection-coefficient predictions, which require solving the Sommerfeld integral for a large number of grazing angles and frequencies, constitute fine-grained, data-parallel computations which are implemented efficiently on a GPU. S ling is based on population Monte Carlo simulation with chain interactions as exchange and crossover moves.The algorithm is applied to Malta Plateau data to study frequency dependence of velocity and attenuation in marine sediments. [Work supported by ONR.]
Publisher: Acoustical Society of America (ASA)
Date: 05-2013
DOI: 10.1121/1.4795804
Abstract: This paper develops a probabilistic two-dimensional (2D) inversion for geoacoustic seabed and water-column parameters in a strongly range-dependent environment. Range-dependent environments in shelf and shelf-break regions are of increasing importance to the acoustical-oceanography community, and recent advances in nonlinear inverse theory and s ling methods are applied here for efficient probabilistic range-dependent inversion. The 2D seabed and water column are parameterized using highly efficient, self-adapting irregular grids which intrinsically match the local resolving power of the data and provide parsimonious solutions requiring few parameters to capture complex environments. The self-adapting parameterization is achieved by implementing the irregular grid as a trans-dimensional hierarchical Bayesian model with an unknown number of nodes which is s led with the Metropolis-Hastings-Green algorithm. To improve s ling, population Monte Carlo is applied with a large number of interacting parallel Markov chains with adaptive proposal distributions. The inversion is applied to simulated data for a vertical-line array and several source locations to several kilometers range. Complex acoustic-pressure fields are computed using a parabolic equation model and results are considered in terms of 2D ensemble parameter estimates and credibility intervals.
Publisher: Institute of Electrical and Electronics Engineers (IEEE)
Date: 04-2017
Publisher: Acoustical Society of America (ASA)
Date: 07-2016
DOI: 10.1121/1.4954755
Abstract: This paper estimates bowhead whale locations and uncertainties using non-linear Bayesian inversion of their modally-dispersed calls recorded on asynchronous recorders in the Chukchi Sea, Alaska. Bowhead calls were recorded on a cluster of 7 asynchronous ocean-bottom hydrophones that were separated by 0.5–9.2 km. A warping time-frequency analysis is used to extract relative mode arrival times as a function of frequency for nine frequency-modulated whale calls that dispersed in the shallow water environment. Each call was recorded on multiple hydrophones and the mode arrival times are inverted for: the whale location in the horizontal plane, source instantaneous frequency (IF), water sound-speed profile, seabed geoacoustic parameters, relative recorder clock drifts, and residual error standard deviations, all with estimated uncertainties. A simulation study shows that accurate prior environmental knowledge is not required for accurate localization as long as the inversion treats the environment as unknown. Joint inversion of multiple recorded calls is shown to substantially reduce uncertainties in location, source IF, and relative clock drift. Whale location uncertainties are estimated to be 30–160 m and relative clock drift uncertainties are 3–26 ms.
Publisher: American Geophysical Union (AGU)
Date: 11-2021
DOI: 10.1029/2021JB022358
Abstract: We demonstrate the logistic feasibility and scientific potential of distributed acoustic sensing (DAS) in alpine volcano‐glacial environments that are subject to a broad range of natural hazards. Our work considers the Mount Meager massif, an active volcanic complex in British Columbia, estimated to have the largest geothermal potential in Canada, and home of Canada's largest recorded landslide in 2010. From September to October 2019, we acquired continuous strain data, using a 3‐km long fiber‐optic cable, deployed on a ridge of Mount Meager and on the uppermost part of a glacier above 2,000 m altitude. The data analysis detected a broad range of unexpectedly intense, low‐magnitude, local seismicity. The most prominent events include long‐lasting, intermediate‐frequency (0.01–1 Hz) tremor, and high‐frequency (5–45 Hz) earthquakes that form distinct spatial clusters and often repeat with nearly identical waveforms. We conservatively estimate that the number of detectable high‐frequency events varied between several tens and nearly 400 per day. We also develop a beamforming algorithm that uses the signal‐to‐noise ratio (SNR) of in idual channels, and implicitly takes the direction‐dependent sensitivity of DAS into account. Both the tremor and the high‐frequency earthquakes are most likely related to fluid movement within Mount Meager's geothermal reservoir. Our work illustrates that DAS carries the potential to reveal previously undiscovered seismicity in challenging environments, where comparably dense arrays of conventional seismometers are difficult to install. We hope that the logistics and deployment details provided here may serve as a starting point for future DAS experiments.
Publisher: Oxford University Press (OUP)
Date: 13-10-2015
DOI: 10.1093/GJI/GGV368
Publisher: Acoustical Society of America (ASA)
Date: 10-2014
DOI: 10.1121/1.4892787
Abstract: This paper presents a polynomial spline-based parameterization for trans-dimensional geoacoustic inversion. The parameterization is demonstrated for both simulated and measured data and shown to be an effective method of representing sediment geoacoustic profiles dominated by gradients, as typically occur, for ex le, in muddy seabeds. Specifically, the spline parameterization is compared using the deviance information criterion (DIC) to the standard stack-of-homogeneous layers parameterization for the inversion of bottom-loss data measured at a muddy seabed experiment site on the Malta Plateau. The DIC is an information criterion that is well suited to trans-D Bayesian inversion and is introduced to geoacoustics in this paper. Inversion results for both parameterizations are in good agreement with measurements on a sediment core extracted at the site. However, the spline parameterization more accurately resolves the power-law like structure of the core density profile and provides smaller overall uncertainties in geoacoustic parameters. In addition, the spline parameterization is found to be more parsimonious, and hence preferred, according to the DIC. The trans-dimensional polynomial spline approach is general, and applicable to any inverse problem for gradient-based profiles. [Work supported by ONR.].
Publisher: Acoustical Society of America (ASA)
Date: 03-2008
DOI: 10.1121/1.2832619
Abstract: This paper develops a joint time/frequency-domain inversion for high-resolution single-bounce reflection data, with the potential to resolve fine-scale profiles of sediment velocity, density, and attenuation over small seafloor footprints (∼100m). The approach utilizes sequential Bayesian inversion of time- and frequency-domain reflection data, employing ray-tracing inversion for reflection travel times and a layer-packet stripping method for spherical-wave reflection-coefficient inversion. Posterior credibility intervals from the travel-time inversion are passed on as prior information to the reflection-coefficient inversion. Within the reflection-coefficient inversion, parameter information is passed from one layer packet inversion to the next in terms of marginal probability distributions rotated into principal components, providing an efficient approach to (partially) account for multi-dimensional parameter correlations with one-dimensional, numerical distributions. Quantitative geoacoustic parameter uncertainties are provided by a nonlinear Gibbs s ling approach employing full data error covariance estimation (including nonstationary effects) and accounting for possible biases in travel-time picks. Posterior examination of data residuals shows the importance of including data covariance estimates in the inversion. The joint inversion is applied to data collected on the Malta Plateau during the SCARAB98 experiment.
Publisher: Authorea, Inc.
Date: 23-07-2023
DOI: 10.22541/ESSOAR.169008320.06546433/V1
Abstract: Although marine controlled source electromagnetic (CSEM) methods are effective for investigating offshore freshened groundwater (OFG) systems, interpreting the spatial extent and salinity of OFG remains challenging. Integrating CSEM resistivity models with information on sub-surface properties, such as host-rock porosity, allows for estimates of pore-water salinity. However, deterministic inversion approaches pose challenges in quantitatively analyzing these estimates as they provide only one best-fit model with no associated estimate of model parameter uncertainty. To address this limitation, we employ a trans-dimensional Markov-Chain Monte-Carlo inversion on marine CSEM data, under the assumption of horizontal stratification, collected from the Canterbury Bight, New Zealand. We integrate the resulting posterior distributions of electrical resistivity with borehole and seismic reflection data to quantify pore-water salinity with uncertainty estimates. The results reveal a low-salinity groundwater body in the center of the survey area at varying depths, hosted by consecutive silty- and fine-sand layers approximately 20 to 60 km from the coast. These observations support the previous study’s results obtained through deterministic 2-D inversion and suggest freshening of the OFG body closer to the shore within a permeable, coarse-sand layer 40 to 150 m beneath the seafloor. This implies a potential active connection between the OFG body and the terrestrial groundwater system. We demonstrate how the Bayesian approach constrains the uncertainties in resistivity models and subsequently in pore-water salinity estimates. Our findings highlight the potential of Bayesian inversions in enhancing our understanding of OFG systems, providing crucial boundary conditions for hydrogeological modeling and sustainable water resource development.
Publisher: Seismological Society of America (SSA)
Date: 07-03-2017
DOI: 10.1785/0120160271
Publisher: Seismological Society of America (SSA)
Date: 21-04-2021
DOI: 10.1785/0220200350
Abstract: Stretching nearly the extent of the Canadian Cordillera, the Rocky Mountain trench (RMT) forms one of the longest valleys on Earth. Yet, the level of seismicity, and style of faulting, on the RMT remains poorly known. We assess earthquakes in the southern RMT using a temporary network of seismometers around Valemount, British Columbia, and identify active structures using a probabilistic earthquake catalog spanning from September 2017 to August 2018. Together with results from earlier geological and seismic studies, our new earthquake catalog provides a constraint on the geometry of subsurface faults and their level of activity during a year of recording. The tectonic analysis presented here benefits from the catalog of 47 earthquakes, including robust horizontal and vertical uncertainty quantification. The westward dip of the southern RMT fault is one of the prominent subsurface structures that we observe. The seismicity observed here occurs on smaller surrounding faults away from the RMT and shifts from the east to the west of the trench from north to south of Valemount. The change in distribution of earthquakes follows changes in the style of deformation along the length of the RMT. Focal mechanisms calculated for two earthquakes with particularly clear waveforms reveal northeast–southwest-oriented thrusting. The seismicity reveals a change in the pattern of deformation from narrowly focused transpression north of Valemount to more broadly distributed activity in an area characterized by normal faulting to the south. Six sets of repeating events detected here produce similar waveforms whose P waves exhibit correlation coefficients that exceed 0.7 and may result from the migration of fluids through the fractured crust.
Publisher: Seismological Society of America (SSA)
Date: 12-09-2023
DOI: 10.1785/0220220001
Abstract: On 10 September, 2008, an Mw 5.7 earthquake occurred under the Central Valley of northern Chile near the town of Pica at a depth of ∼33 km within the continental crust of the South America plate. We find this earthquake to be a high stress-drop, reverse-oblique event that generated unusually high ground accelerations of up to 0.67g. Overall, its observed ground motion intensities are considerably larger than those predicted by ground motion models, particularly at short periods. The source properties inferred through waveform modeling indicate reverse-oblique fault motion on a ∼75 km2 plane dipping to the northeast, which is corroborated by the located aftershock distribution. Stress-drop values of the mainshock and larger aftershocks were estimated through S-wave spectrum modeling, with values up to ∼250 MPa for the mainshock. The event occurred in a cold section of the continental crust under the Central Valley, and its fault kinematics and orientation are consistent with the dominant style of faulting and stress field under the neighboring Coastal Cordillera. Although our recurrence analysis shows that crustal events in the region occur at a lower rate than interplate and inslab events, crustal events of similar or higher magnitude than the Pica earthquake have occurred, on average, approximately once every three years in northern Chile, which could pose an important hazard to nearby populations or critical infrastructure.
Publisher: Oxford University Press (OUP)
Date: 23-01-2019
DOI: 10.1093/GJI/GGZ044
Publisher: Acoustical Society of America (ASA)
Date: 02-2012
DOI: 10.1121/1.3672696
Abstract: Seabed geoacoustic variability is driven by geological processes that occur over a wide spectrum of space-time scales. While the acoustics community has some understanding of horizontal fine-scale geoacoustic variability, less than O(100) m, and large-scale variability, greater than O(103) m, there is a paucity of data resolving the geoacoustic meso-scale O(100–103) m. Measurements of the meso-scale along an ostensibly “benign” portion of the outer shelf reveal three classes of variability. The first class was expected and is due to horizontal variability of layer thicknesses: this was the only class that could be directly tied to seismic reflection data. The second class is due to rapid changes in layer properties and/or boundaries, occurring over scales of meters to hundreds of meters. The third class was observed as rapid variations of the angle/frequency dependent reflection coefficient within a single observation and is suggestive of variability at scales of meter or less. Though generally assumed to be negligible in acoustic modeling, the second and third classes are indicative of strong horizontal geoacoustic variability within a given layer. The observations give early insight into possible effects of horizontal geoacoustic variability on long-range acoustic propagation and reverberation.
Publisher: Acoustical Society of America (ASA)
Date: 04-2011
DOI: 10.1121/1.3557052
Abstract: This paper develops a sequential trans-dimensional Monte Carlo algorithm for geoacoustic inversion in a strongly range-dependent environment. The algorithm applies advanced Markov chain Monte Carlo methods in combination with sequential techniques (particle filters) to carry out geoacoustic inversions for consecutive data sets acquired along a track. Changes in model parametrization along the track (e.g., number of sediment layers) are accounted for with trans-dimensional partition modeling, which intrinsically determines the amount of structure supported by the data information content. Challenging issues of rapid environmental change between consecutive data sets and high information content (peaked likelihood) are addressed by bridging distributions implemented using annealed importance s ling. This provides an efficient method to locate high-likelihood regions for new data which are distant and/or disjoint from previous high-likelihood regions. The algorithm is applied to simulated reflection-coefficient data along a track, such as can be collected using a towed array close to the seabed. The simulated environment varies rapidly along the track, with changes in the number of layers, layer thicknesses, and geoacoustic parameters within layers. In addition, the seabed contains a geologic fault, where all layers are offset abruptly, and an erosional channel. Changes in noise level are also considered.
Publisher: Research Square Platform LLC
Date: 17-09-0006
DOI: 10.21203/RS.3.RS-2998116/V1
Abstract: A sequence of injection-induced earthquakes in western Canada demonstrates a resurgent response of a fault system to persistent, post-mainshock saltwater disposal. Compared with independent analysis, joint inference of InSAR and seismic waveform data significantly reduces uncertainty in source parameters, showing that the mainshock nucleated at 5-km depth, propagating up-dip towards the injection source, arresting at 1.9-km depth. Precise hypocenter relocations, combined with Bayesian inference, reveal that four subparallel faults were reactivated, likely part of a regional, basement-rooted graben system. The reactivated faults appear to be truncated by a conjugate fault that is misoriented for slip in the present-day stress regime. The nearest saltwater disposal well targets a permeable Devonian reef that is in direct contact with Precambrian basement, atop a ridge-like uplift. Our observations show that a fault system can be activated more than a decade after initiation of saltwater disposal, and continued disposal may lead to resurgence of seismicity.
Publisher: Acoustical Society of America (ASA)
Date: 11-2013
DOI: 10.1121/1.4831591
Abstract: This paper considers Bayesian inversion of seabed reflection-coefficient data for the compressional- and shear-wave velocity dispersion and attenuation-frequency dependence in arbitrarily layered porous and elastic media. The seabed is modeled using Buckingham's viscous grain shearing model which obeys causality. Seabed layers are parametrized in terms of six fundamental parameters, including thickness, porosity, compressional and shear grain-to-grain moduli, material exponent, and the compressional visco-elastic time constant. These fundamental parameters are used to compute density, compressional- and shear-wave dispersion curves, and compressional and shear attenuation-frequency curves for each layer. The curves are used in the inversion to predict spherical-wave reflection coefficients as a function of frequency (300–3000 Hz) and grazing angle (12–75 degrees), which include the effects of shear waves in arbitrarily layered media. In addition, the seabed layering is estimated from the data by applying a trans-dimensional Bayesian model. The ability to resolve shear-wave velocity and attenuation structure is studied using simulated data. Finally, compressional- and shear-wave dispersion are presented and discussed from measured reflection data at a sandy site in the Tyrrhenian Sea. [Work supported by ONR Ocean Acoustics.]
Publisher: American Geophysical Union (AGU)
Date: 11-2014
DOI: 10.1002/2014JB011067
Publisher: American Geophysical Union (AGU)
Date: 05-03-2016
DOI: 10.1002/2015GL067418
Publisher: Wiley
Date: 30-04-2021
Publisher: Acoustical Society of America (ASA)
Date: 12-2010
DOI: 10.1121/1.3506345
Abstract: This paper applies a general Bayesian inference approach, based on Bayesian evidence computation, to geoacoustic inversion of interface-wave dispersion data. Quantitative model selection is carried out by computing the evidence (normalizing constants) for several model parameterizations using annealed importance s ling. The resulting posterior probability density estimate is compared to estimates obtained from Metropolis–Hastings s ling to ensure consistent results. The approach is applied to invert interface-wave dispersion data collected on the Scotian Shelf, off the east coast of Canada for the sediment shear-wave velocity profile. Results are consistent with previous work on these data but extend the analysis to a rigorous approach including model selection and uncertainty analysis. The results are also consistent with core s les and seismic reflection measurements carried out in the area.
Publisher: Wiley
Date: 04-05-2021
Publisher: Acoustical Society of America (ASA)
Date: 07-2009
DOI: 10.1121/1.3147489
Abstract: This paper considers Bayesian inversion of seabed reflection-coefficient data for multi-layer geoacoustic models at several sites, with the goal of studying lateral variability of the seabed. Rigorous uncertainty estimation is carried out to resolve lateral variability of the sediments from inherent inversion uncertainties. The uncertainty analysis includes Bayesian model selection, comprehensive quantification of data error statistics, and a Markov-chain Monte Carlo approach to transforming data uncertainties to model uncertainties. Model selection is addressed using the Bayesian information criterion to ensure parsimony of the parametrizations. Data error statistics are quantified by estimating full covariance matrices from data residuals, with posterior statistical validation. A Metropolis–Hastings s ling algorithm is used to compute posterior probability densities. Four experiment sites are considered along a track located on the Malta Plateau, Mediterranean Sea, and the inversion results are compared to cores taken at each site. Differences between profile marginal-probability distributions at adjacent sites are quantified using the Bhattacharyya coefficient. Differences that exceed the estimated geoacoustic uncertainties are interpreted as spatial variability of the seabed. The results are compared to an interpretation of geologic features evident in a chirp sub-bottom-profiler section.
Publisher: Institute of Electrical and Electronics Engineers (IEEE)
Date: 10-2005
Publisher: Acoustical Society of America (ASA)
Date: 11-2015
DOI: 10.1121/1.4934517
Abstract: This paper develops a matched-field approach to localization and spectral estimation of an unknown number of ocean acoustic sources employing massively parallel implementation on a graphics processing unit (GPU) for real-time efficiency. A Bayesian formulation is developed in which the locations and complex spectra of multiple sources and noise variances are considered unknown random variables, and the Bayesian information criterion is minimized to estimate these parameters, as well as the number of sources present. Optimization is carried out using simulated annealing and includes steps that attempt to add/delete sources to/from the model. Closed-form maximum-likelihood (ML) solutions for source spectra and noise variances in terms of the source locations allow these parameters to be s led implicitly, substantially reducing the dimensionality of the inversion. Source s ling, addition, and deletion are based on joint conditional probability distributions for source range and depth, which incorporate the ML spectral estimates. Computing these conditionals requires solving a very large number of systems of equations, which is carried out in parallel on a GPU, improving efficiency by 2 orders of magnitude. Simulated ex les illustrate localizations and spectral estimation for a large number of sources (up to eight), and investigate mitigation of environmental mismatch via efficient multiple-frequency inversion.
Publisher: Authorea, Inc.
Date: 14-10-2023
Publisher: Institute of Electrical and Electronics Engineers (IEEE)
Date: 2020
Publisher: Society of Exploration Geophysicists
Date: 2023
Abstract: Distributed acoustic sensing (DAS) technology is, increasingly, the seismic acquisition mode of choice for its high spatial s ling rate, low cost, and nonintrusive deployability. It is being widely evaluated as an enabler of seismic monitoring for [Formula: see text] sequestration in building subsurface time-lapse images and in characterizing near-surface environments. To advance this evaluation, field seismic surveys with optical fibers have been conducted at the Containment and Monitoring Institute’s Field Research Station (CaMI.FRS) in Newell County, Alberta, Canada. In comparison to the standard geophones, optical fibers deployed in surface trenches at CaMI.FRS have recorded high-quality surface waves, rich in low frequencies and exhibiting limited spatial aliasing. These benefits have motivated us to apply the full-waveform inversion (FWI) approach to image the S-wave velocity ([Formula: see text]) and attenuation (quality factor [Formula: see text]) models at shallow site using the surface waves recorded by optical fibers. Compared to the conventional surface-wave dispersion approach, FWI can intrinsically incorporate fundamental and high-order modes and produce [Formula: see text] model with high spatial resolution that resolves horizontal variations. The low-frequency components below 10 Hz measured in the DAS recordings are helpful to overcome the cycle-skipping problem of FWI. Following the adjoint-state method, [Formula: see text] sensitivity kernel can be calculated efficiently with memory strain variables. The [Formula: see text] model is iteratively estimated with a new misfit function measuring root-mean-square litude differences, which helps to reduce the trade-off artifacts. The synthetic data obtained from the inverted models are consistent with the observed data in litude and phase. The inversion results provide valuable information to characterize the near-surface environments at CaMI.FRS and are expected to support seismic imaging in deeper [Formula: see text] injection zones.
Publisher: Seismological Society of America (SSA)
Date: 14-07-2020
DOI: 10.1785/0120200048
Abstract: The calculation of earthquake hypocenters requires careful treatment, particularly when prior knowledge of the study area is limited. The prior knowledge, such as wave velocity and data noise, is often assumed to be known in earthquake location algorithms. Such assumptions can greatly simplify the inverse problem but are less general than nonlinear approaches. A nonlinear treatment is of particular importance when the uncertainty quantification of locations is of interest. We present a nonlinear multiple-earthquake location method that is applicable when little prior knowledge of the area exists. Efficient Markov chain Monte Carlo (MCMC) s ling is employed in conjunction with a hierarchical Bayesian model that treats earthquake hypocenter parameters, as well as P-wave velocity, ratio in P-/S-wave velocities, and P- and S-data noise standard deviations as unknown. Hypocenters for multiple earthquakes are located concurrently to provide sufficient constraints for the parameter’s P-wave velocity, ratio in P-/S-wave velocity, and P- and S-data noise standard deviations, which are shared among events. The algorithm is applied to simulated and field data. With field data, 47 event hypocenters are located in 1 yr of data from 10 sensors in the Canadian Rocky Mountain trench. To analyze the probabilistic solutions, we compare single-earthquake and multiple-earthquake locations for the 47 events and find that the multiple-earthquake location produces better-constrained solutions when compared with the single-event case. In particular, depth uncertainties are significantly reduced for the multiple-earthquake location. The algorithm is inexpensive, considering that it is based on an MCMC approach and highly objective, requiring little practitioner choice for tuning.
Publisher: Institute of Electrical and Electronics Engineers (IEEE)
Date: 2020
Publisher: Society of Exploration Geophysicists
Date: 05-2013
Abstract: We have applied probabilistic inversion using a transdimensional hierarchical model to ocean-acoustic reflection measurements to recover shallow sediment structure including sound-velocity dispersion, frequency-dependent attenuation, and their uncertainties. Parameter and uncertainty inferences were obtained from Markov-chain simulations using the Metropolis-Hastings algorithm for transdimensional models where the number of sediment layers is unknown. Transdimensional algorithms often exhibit slow convergence that is greatly exacerbated by computationally intensive data predictions. Advances were made to improve the performance of Markov-chain simulation and data prediction. Chain-mixing across dimensions was addressed using a tempered sequence of interacting Markov chains, which substantially improves convergence rates. The acoustic recordings were processed to give seabed reflection coefficients as a function of frequency, grazing angle, and integration time (penetration depth). Such reflection-coefficient data cannot be generally described by plane-wave theory. Therefore, data were predicted using plane-wave decomposition and solving the Sommerfeld integral to compute spherical-wave reflection coefficients. This computationally intensive forward model was implemented massively in parallel using the compute unified device architecture on an inexpensive graphics processing unit, which substantially increases performance and allows transdimensional uncertainty estimation for complex layered seabeds. Velocity- and attenuation-frequency dependence were modeled using Buckingham’s viscous grain-shearing theory, which predicts frequency dependence similar to that of Biot’s theory at low frequencies but due to different physical causes. The algorithm was applied at two experiment sites off the coast of Sicily that exhibit different degrees of sediment complexity. The rigorous uncertainty estimation allows inferences that can distinguish between friction- and viscous-loss mechanisms in complex layered media. Results at both sites indicated dispersive sediments at some depths where the variability of velocity and attenuation as a function of frequency clearly exceeds the estimated uncertainties.
Publisher: Research Square Platform LLC
Date: 07-06-2022
DOI: 10.21203/RS.3.RS-1647118/V1
Abstract: Tailings dams retain the waste by-products of mining operations and are amongst the world’s largest engineered structures. Recent tailings dam failures highlight important gaps in current monitoring methods and a pressing need to advance research on tailings dam monitoring technologies, considering growth predictions for the mining of metals. At an active tailings dam in northern Canada, we combine ambient noise interferometry with a quantitative stress model to monitor shear wave velocity (V s ) changes. Changes in seismic velocities of less than 1% correlate strongly with water level fluctuations at the adjacent tailings pond. A stress model, calibrated using pond level recordings and V s profiles obtained from cone penetration tests, demonstrates that the seismic velocity changes obtained with ambient noise interferometry are predominantly changes in V s . Furthermore, this model constrains V s changes to a depth of ~16 m, corresponding to uncompacted tailings below the dam. As V s is used to assess the liquefaction potential of soils, this method provides important advances for understanding changes in dam performance over time.
Publisher: American Geophysical Union (AGU)
Date: 06-2016
DOI: 10.1002/2015JB012764
Publisher: Acoustical Society of America (ASA)
Date: 05-2013
DOI: 10.1121/1.4806565
Abstract: This paper develops an efficient Bayesian s ling approach to geoacoustic scattering and reflection inversion based on trans-dimensional (trans-D) s ling over both the seabed model (number of sediment layers) and error model (autoregressive order to represent residual correlation). S ling is carried out using a population of interacting Markov chains employing a range of s ling temperatures (parallel tempering). The approach is applied to both simulated and measured data. The advantages of trans-D autoregressive model s ling over alternative methods of error model selection is explored in terms of the reduction in posterior uncertainty of geoacoustic parameters and evaluation of residual correlation. The seabed is modeled as a stack of homogeneous fluid sediment layers overlying an elastic basement. Including elastic (shear) parameters in the basement makes this layer distinct from the overlying sediment layers and requires a novel formulation of the partition prior distribution for trans-D s ling. [Work supported by ONR.]
Publisher: Acoustical Society of America (ASA)
Date: 05-2013
DOI: 10.1121/1.4805114
Abstract: Because electromagnetic radiation is strongly attenuated in seawater while sound propagates efficiently to long (even global) ranges, scientists and engineers have devised many ingenious methods to use acoustics in the ocean in place of light, radio, and microwaves. Myriad underwater acoustic applications include remote sensing, remote control, communications, navigation, and source detection/localization. This talk will present a semi-historical overview of the use of sound to study the sea (including the seabed), from philosophical musings of Aristotle, through the Renaissance, two world wars, and into the modern era of advanced measurement technologies and computer analysis. A final emphasis involves on-going research to estimate seabed geophysical properties and quantify their uncertainty and variability using a variety of ocean acoustic measurements and probabilistic inversion theory.
Publisher: Seismological Society of America (SSA)
Date: 22-01-2020
DOI: 10.1785/0220190075
Abstract: The Bayesian earthquake analysis tool (BEAT) is an open-source Python software to conduct source-parameter estimation studies for crustal deformation events, such as earthquakes and magma intrusions, by employing a Bayesian framework with a flexible problem definition. The software features functionality to calculate Green’s functions for a homogeneous or a layered elastic half-space. Furthermore, algorithm(s) that explore the solution space may be selected from a suite of implemented s lers. If desired, BEAT’s modular architecture allows for easy implementation of additional features, for ex le, alternative s ling algorithms. We demonstrate the functionality and performance of the package using five earthquake source estimation ex les: a full moment-tensor estimation a double-couple moment-tensor estimation an estimation for a rectangular finite source a static finite-fault estimation with variable slip and a full kinematic finite-fault estimation with variable hypocenter location, rupture velocity, and rupture duration. This software integrates many aspects of source studies and provides an extensive framework for joint use of geodetic and seismic data for nonlinear source- and noise-covariance estimation within layered elastic half-spaces. Furthermore, the software also provides an open platform for further methodological development and for reproducible source studies in the geophysical community.
Publisher: Acoustical Society of America (ASA)
Date: 05-2013
DOI: 10.1121/1.4805233
Abstract: This paper presents seabed interface-scattering and geoacoustic parameters estimated on the Malta Plateau, Mediterranean Sea, by joint Bayesian inversion of monostatic backscatter and spherical-wave reflection-coefficient data. The data are modeled assuming a stack of homogeneous fluid sediment layers overlying an elastic basement. The scattering model also assumes a randomly rough water-sediment interface with a von Karman roughness power spectrum. Scattering and reflection data are inverted simultaneously using a population of interacting Markov-chains to s le roughness and geoacoustic parameters as well as residual error parameters. Trans-dimensional s ling is applied to treat the unknown number of sediment layers and unknown autoregressive order of the errors (to represent residual correlation). Results are considered in terms of marginal posterior probability profiles and distributions, which quantify the effective data information content to resolve scattering/geoacoustic parameters and structure. Results indicate well-defined scattering (roughness) parameters in good agreement with existing measurements, and a multi-layer sediment profile over a high-speed (elastic) basement, consistent with independent knowledge of sand layers over limestone. [Work supported by ONR.]
Publisher: Acoustical Society of America (ASA)
Date: 05-2013
DOI: 10.1121/1.4806561
Abstract: This paper develops a probabilistic two-dimensional (2D) inversion for geoacoustic seabed and water-column parameters in a strongly range-dependent environment. Range-dependent environments in shelf and shelf-break regions are of increasing importance to the acoustical-oceanography community, and recent advances in nonlinear inverse theory and s ling methods are applied here for efficient probabilistic inversion in 2D. The 2D seabed and water column are parameterized by highly efficient, self-adapting irregular grids which match the local resolving power of the data and provide parsimonious solutions requiring few parameters to capture complex environments. The self-adapting parameterization in the water-column and seabed is achieved by implementing the irregular grid as a trans-dimensional hierarchical Bayesian model which is s led with the Metropolis-Hastings-Green algorithm. To improve s ling, population Monte Carlo is applied with a large number of interacting parallel Markov chains employing a loadbalancing algorithm on a computer cluster. The inversion is applied to simulated data for a vertical line array and several source locations to several kilometers range. Complex pressure fields are computed using a parabolic equation model and results are considered in terms of 2D ensemble parameter estimates and marginal uncertainty distributions. [Work supported by NSERC.]
Publisher: Acoustical Society of America (ASA)
Date: 19-12-2012
DOI: 10.1121/1.4771975
Abstract: This letter applies trans-dimensional Bayesian geoacoustic inversion to quantify the uncertainty due to model selection when inverting bottom-loss data derived from wind-driven ambient-noise measurements. A partition model is used to represent the seabed, in which the number of layers, their thicknesses, and acoustic parameters are unknowns to be determined from the data. Exploration of the parameter space is implemented using the Metropolis–Hastings algorithm with parallel tempering, whereas jumps between parameterizations are controlled by a reversible-jump Markov chain Monte Carlo algorithm. Sediment uncertainty profiles from inversion of simulated and experimental data are presented.
Publisher: Wiley
Date: 09-01-2019
Publisher: Oxford University Press (OUP)
Date: 02-08-2017
DOI: 10.1093/GJI/GGX323
Publisher: American Geophysical Union (AGU)
Date: 09-2015
DOI: 10.1002/2015JB011942
Publisher: Wiley
Date: 27-09-2015
Publisher: Acoustical Society of America (ASA)
Date: 11-2013
DOI: 10.1121/1.4831446
Abstract: Cohesive or muddy sediments have received relatively sparse attention in the ocean acoustics community—this despite the fact that they form a non-negligible fraction of the sediments found in shallow water (roughly 25%) and by far the major sediment type in the deep ocean. Seabed reflection measurements have provided some understanding about the frequency dependence of the sound speed and attenuation in muddy sediments. The evidence is for weak dispersion from 300–200,000 Hz and an approximately linear dependence of attenuation on frequency from 300–3000 Hz. In addition, the measurements have yielded information on gradients. Surprisingly large near-surface density gradients exist that vary across the shelf. Given the large density gradients, the gradients in sound speed are curiously small, suggesting that the bulk modulus is nearly proportional to the density, at least in depth. Dispersion and gradient results are discussed for muddy sediments in various mid to outer shelf regions.
Publisher: Acoustical Society of America (ASA)
Date: 10-2012
DOI: 10.1121/1.4746016
Abstract: This paper develops a trans-dimensional approach to matched-field geoacoustic inversion, including interacting Markov chains to improve efficiency and an autoregressive model to account for correlated errors. The trans-dimensional approach and hierarchical seabed model allows inversion without assuming any particular parametrization by relaxing model specification to a range of plausible seabed models (e.g., in this case, the number of sediment layers is an unknown parameter). Data errors are addressed by s ling statistical error-distribution parameters, including correlated errors (covariance), by applying a hierarchical autoregressive error model. The well-known difficulty of low acceptance rates for trans-dimensional jumps is addressed with interacting Markov chains, resulting in a substantial increase in efficiency. The trans-dimensional seabed model and the hierarchical error model relax the degree of prior assumptions required in the inversion, resulting in substantially improved (more realistic) uncertainty estimates and a more automated algorithm. In particular, the approach gives seabed parameter uncertainty estimates that account for uncertainty due to prior model choice (layering and data error statistics). The approach is applied to data measured on a vertical array in the Mediterranean Sea.
Publisher: Acoustical Society of America (ASA)
Date: 06-2015
DOI: 10.1121/1.4921284
Abstract: This paper presents estimated water-column and seabed parameters and uncertainties for a shallow-water site in the Chukchi Sea, Alaska, from trans-dimensional Bayesian inversion of the dispersion of water-column acoustic modes. Pulse waveforms were recorded at a single ocean-bottom hydrophone from a small, ship-towed airgun array during a seismic survey. A warping dispersion time-frequency analysis is used to extract relative mode arrival times as a function of frequency for source-receiver ranges of 3 and 4 km which are inverted for the water sound-speed profile (SSP) and subbottom geoacoustic properties. The SSP is modeled using an unknown number of sound-speed/depth nodes. The subbottom is modeled using an unknown number of homogeneous layers with unknown thickness, sound speed, and density, overlying a halfspace. A reversible-jump Markov-chain Monte Carlo algorithm s les the model parameterization in terms of the number of water-column nodes and subbottom interfaces that can be resolved by the data. The estimated SSP agrees well with a measured profile, and seafloor sound speed is consistent with an independent headwave arrival-time analysis. Environmental properties are required to model sound propagation in the Chukchi Sea for estimating sound exposure levels and environmental research associated with marine mammal localization.
Publisher: American Geophysical Union (AGU)
Date: 02-2020
DOI: 10.1029/2019TC005489
Publisher: Wiley
Date: 20-01-2020
DOI: 10.1002/NSG.12081
Publisher: IOP Publishing
Date: 29-10-2014
Publisher: Acoustical Society of America (ASA)
Date: 12-2007
DOI: 10.1121/1.2793609
Abstract: This paper develops a Bayesian inversion for recovering multilayer geoacoustic (velocity, density, attenuation) profiles from a full wave-field (spherical-wave) seabed reflection response. The reflection data originate from acoustic time series windowed for a single bottom interaction, which are processed to yield reflection coefficient data as a function of frequency and angle. Replica data for inversion are computed using a wave number-integration model to calculate the full complex acoustic pressure field, which is processed to produce a commensurate seabed response function. To address the high computational cost of calculating short range acoustic fields, the inversion algorithms are parallelized and frequency averaging is replaced by range averaging in the forward model. The posterior probability density is interpreted in terms of optimal parameter estimates, marginal distributions, and credibility intervals. Inversion results for the full wave-field seabed response are compared to those obtained using plane-wave reflection coefficients. A realistic synthetic study indicates that the plane-wave assumption can fail, producing erroneous results with misleading uncertainty bounds, whereas excellent results are obtained with the full-wave reflection inversion.
Publisher: Acoustical Society of America (ASA)
Date: 12-2016
DOI: 10.1121/1.4968203
Abstract: This paper develops an inversion method for the seabed transition layer at the water-sediment interface, often found in muddy sediments, which provides density and sound-speed profiles that were previously not resolvable. The resolution improvements are achieved by introducing a parametrization that captures general depth-dependent gradients in geoacoustic parameters with a small number of parameters. In particular, the gradients are represented by a sum of Bernstein basis functions, weighted by unknown coefficients. Compared to previous forms found in the literature, the Bernstein-based parametrization can represent a wider range of depth-dependent geoacoustic profiles using fewer parameters which leads to reduced uncertainty and improved resolution. In addition, the Bernstein basis is the most stable polynomial representation in that small perturbations to the unknown coefficients result in small, localized perturbations to the geoacoustic profile, thereby providing an efficient exploration of the parameter space using Markov-chain methods in nonlinear inversion. Geoacoustic profiles at four mud sites on the Malta Plateau are studied with the proposed approach. Results show exceptional resolution of density profiles, estimated with low uncertainty and clear sensitivity to sediment features of centimeter scale.
Publisher: American Geophysical Union (AGU)
Date: 26-07-2023
DOI: 10.1029/2022GL102131
Abstract: Microseismic data acquired during hydraulic stimulations is routinely used to characterize hydraulic fracture (HF) propagation away from a wellbore. When the data include induced seismicity (IS) related to induced fault slip, separating HF‐related and IS‐related events is essential for HF treatment optimization and IS mitigation. Linear and non‐linear analytical diffusivity models can be used to interpret microseismic data and quantify the propagation of HFs, but their accuracy reduces when significant induced microseismicity is present. A Bayesian quantile regression is used to extend these existing diffusivity models to data contaminated with IS. A plausible ellipsoid filters events that are clearly anomalous prior to the quantile regression. The regression effectively separates HF‐related microseismic events from induced events in a case study for all stages without interpretative bias. This reveals faults that are directed connected to HFs, as well as those solely related with induced seismicity.
Publisher: Informa UK Limited
Date: 12-2016
Publisher: Wiley
Date: 13-02-2021
Publisher: Acoustical Society of America (ASA)
Date: 04-2012
DOI: 10.1121/1.3688482
Abstract: This paper applies Bayesian inversion to bottom-loss data derived from wind-driven ambient noise measurements from a vertical line array to quantify the information content constraining seabed geoacoustic parameters. The inversion utilizes a previously proposed ray-based representation of the ambient noise field as a forward model for fast computations of bottom loss data for a layered seabed. This model considers the effect of the array’s finite aperture in the estimation of bottom loss and is extended to include the wind speed as the driving mechanism for the ambient noise field. The strength of this field relative to other unwanted noise mechanisms defines a signal-to-noise ratio, which is included in the inversion as a frequency-dependent parameter. The wind speed is found to have a strong impact on the resolution of seabed geoacoustic parameters as quantified by marginal probability distributions from Bayesian inversion of simulated data. The inversion method is also applied to experimental data collected at a moored vertical array during the MAPEX 2000 experiment, and the results are compared to those from previous active-source inversions and to core measurements at a nearby site.
Publisher: IOP Publishing
Date: 07-04-2011
Publisher: Acoustical Society of America (ASA)
Date: 12-2010
DOI: 10.1121/1.3500674
Abstract: This paper develops a general trans-dimensional Bayesian methodology for geoacoustic inversion. Trans-dimensional inverse problems are a generalization of fixed-dimensional inversion that includes the number and type of model parameters as unknowns in the problem. By extending the inversion state space to multiple subspaces of different dimensions, the posterior probability density quantifies the state of knowledge regarding inversion parameters, including effects due to limited knowledge about appropriate parametrization of the environment and error processes. The inversion is implemented here using a reversible-jump Markov chain Monte Carlo algorithm and the seabed is parametrized using a partition model. Unknown data errors are addressed by including a data-error model. Jumps between dimensions are implemented with a birth–death methodology that allows transitions between dimensions by adding or removing interfaces while maintaining detailed balance in the Markov chain. Trans-dimensional inversion results in an inherently parsimonious solution while partition modeling provides a naturally self-regularizing algorithm based on data information content, not on subjective regularization functions. Together, this results in environmental estimates that quantify appropriate seabed structure as supported by the data, allowing sharp discontinuities while approximating smooth transitions where needed. This approach applies generally to geoacoustic inversion and is illustrated here with seabed reflection-coefficient data.
Publisher: American Geophysical Union (AGU)
Date: 26-04-2021
DOI: 10.1029/2021GL092889
Abstract: We study the spatial variability of the crustal stress in northern Chile. A margin‐parallel compressive crustal stress regime is inferred along the coastal region between 19° and 23.5°S, similar to stress observations in Cascadia and Japan. The Andean Precordillera shows a distinct stress field associated with a strike‐slip faulting regime around 21°S. These results are constrained by over a decade of observations, for which earthquake catalogs report thousands of events in the continental crust. We present focal mechanisms for 817 of these crustal earthquakes, including mechanism qualities. The best mechanisms were grouped and inverted to infer the stress‐field variability. We interpret the margin‐parallel compression to be caused by the concave shape of the margin and the locking of the plate interface. The inferred strike‐slip regime in the Andes agrees with previous studies and has been proposed to be mostly caused by local stresses imposed by a thicker crust.
Publisher: Oxford University Press (OUP)
Date: 29-03-2011
Publisher: Acoustical Society of America (ASA)
Date: 03-2013
DOI: 10.1121/1.4789930
Abstract: This paper examines joint inversion of acoustic scattering and reflection data to resolve seabed interface roughness parameters (spectral strength, exponent, and cutoff) and geoacoustic profiles. Trans-dimensional (trans-D) Bayesian s ling is applied with both the number of sediment layers and the order (zeroth or first) of auto-regressive parameters in the error model treated as unknowns. A prior distribution that allows fluid sediment layers over an elastic basement in a trans-D inversion is derived and implemented. Three cases are considered: Scattering-only inversion, joint scattering and reflection inversion, and joint inversion with the trans-D auto-regressive error model. Including reflection data improves the resolution of scattering and geoacoustic parameters. The trans-D auto-regressive model further improves scattering resolution and correctly differentiates between strongly and weakly correlated residual errors.
Publisher: Oxford University Press (OUP)
Date: 09-2014
DOI: 10.1093/GJI/GGU280
Abstract: This paper develops a probabilistic Bayesian approach to the problem of inferring the spatiotemporal evolution of earthquake rupture on a fault surface from seismic data with rigorous uncertainty estimation. To date, uncertainties of rupture parameters are poorly understood, and the effect of choices such as fault discretization on uncertainties has not been studied. We show that model choice is fundamentally linked to uncertainty estimation and can have profound effects on results. The approach developed here is based on a trans-dimensional self-parametrization of the fault, avoids regularization constraints and provides rigorous uncertainty estimation that accounts for model-selection ambiguity associated with the fault discretization. In particular, the fault is parametrized using self-adapting irregular grids which intrinsically match the local resolving power of the data and provide parsimonious solutions requiring few parameters to capture complex rupture characteristics. Rupture causality is ensured by parametrizing rupture-onset time by a rupture-velocity field and obtaining first rupture times from the eikonal equation. The Bayesian s ling of the parameter space is implemented on a computer cluster with a highly efficient parallel tempering algorithm. The inversion is applied to simulated and observed W-phase waveforms from the 2010 Maule (Chile) earthquake. Simulation results show that our approach avoids both over- and underparametrization to ensure unbiased inversion results with uncertainty estimates that are consistent with data information. The simulation results also show the ability of W-phase data to resolve the spatial variability of slip magnitude and rake angles. In addition, sensitivity to spatially dependent rupture velocities exists for kinematic slip models. Application to the observed data indicates that residual errors are highly correlated and likely dominated by theory error, necessitating the iterative estimation of a non-stationary data covariance matrix. The moment magnitude for the Maule earthquake is estimated to be ∼8.9, with slip concentrated in two zones updip of and north and south of the hypocentre, respectively. While this aspect of the slip distribution is similar to previous studies, we show that the slip maximum in the southern zone is poorly resolved compared to the northern zone. Both slip maxima are higher than reported in previous studies, which we speculate may be due to the lack of bias caused by the regularization used in other studies.
Publisher: Oxford University Press (OUP)
Date: 16-12-2011
Publisher: Oxford University Press (OUP)
Date: 17-07-2018
DOI: 10.1093/GJI/GGY289
Publisher: Acoustical Society of America (ASA)
Date: 07-2005
DOI: 10.1121/1.1925988
Abstract: The geoacoustic properties of marine sediments, e.g., bulk density and compressional velocity, commonly exhibit large variations in depth near the water–sediment interface. This layer, termed the transition layer, is typically of O(10−1–100)m in thickness. Depth variations within the transition layer may have important implications for understanding and modeling acoustic interaction with the seabed, including propagation and reverberation. In addition, the variations may contain significant clues about the underlying depositional or erosional processes. Characteristics of the transition layer can be measured directly (e.g., coring) or remotely. Remote measurements have the advantage of s ling without disturbing the sediment properties they also have the potential to be orders of magnitude faster and less expensive than direct methods. It is shown that broadband seabed reflection data can be exploited to remotely obtain the depth dependent density and velocity profiles in the transition layer to high accuracy. A Bayesian inversion approach, which accounts for correlated data errors, provides estimates and uncertainties for the geoacoustic properties. These properties agree with direct (i.e., core) measurements within the uncertainty estimates.
Publisher: Acoustical Society of America (ASA)
Date: 2013
DOI: 10.1121/1.4765300
Abstract: One of the difficulties in validating sediment models has been the lack of reliable low frequency dispersion measurements. A reflection method is presented that yields in situ dispersion without sediment disturbance over a broad range of frequencies and can explicitly disentangle frequency-dependent effects of vertical structure, e.g., layers and gradients. Measurements on the outer shelf from 300 to 3000 Hz show that dispersion is a strong function of depth in the sediment column. The depth and frequency-dependent results generally agree well with independent measurements on core data. Cohesive sediments in the upper few meters exhibit a nearly frequency-independent sound speed and a nearly linear frequency dependence of attenuation. In the lower part of the sediment column the sediments are more granular: the lowest layer exhibits an attenuation with a peak frequency at 1100 Hz, where its dependence below and above trends to f2 and f1/2, respectively. While Biot theory predicts this dependence, its underlying physical explanation, fluid flow through interstitial pores, does not seem plausible for this sediment due to the unreasonable permeability value required. Viscous grain shearing theory also predicts this dependence, but it is not known whether the parameter values are reasonable.
Publisher: Acoustical Society of America (ASA)
Date: 02-2009
DOI: 10.1121/1.3056553
Abstract: This paper applies Bayesian inference, including model selection and posterior parameter inference, to inversion of seabed reflection data to resolve sediment structure at a spatial scale below the pulse length of the acoustic source. A practical approach to model selection is used, employing the Bayesian information criterion to decide on the number of sediment layers needed to sufficiently fit the data while satisfying parsimony to avoid overparametrization. Posterior parameter inference is carried out using an efficient Metropolis–Hastings algorithm for high-dimensional models, and results are presented as marginal-probability depth distributions for sound velocity, density, and attenuation. The approach is applied to plane-wave reflection-coefficient inversion of single-bounce data collected on the Malta Plateau, Mediterranean Sea, which indicate complex fine structure close to the water-sediment interface. This fine structure is resolved in the geoacoustic inversion results in terms of four layers within the upper meter of sediments. The inversion results are in good agreement with parameter estimates from a gravity core taken at the experiment site.
Publisher: Oxford University Press (OUP)
Date: 15-04-2016
DOI: 10.1093/GJI/GGW149
Publisher: American Geophysical Union (AGU)
Date: 19-10-2019
DOI: 10.1029/2019GL083406
Abstract: Microseismicity is generated by slip on fractures and faults and can be used to infer natural or anthropogenic deformation processes in the subsurface. Yet identifying patterns and fractures from microseismic point clouds is a major challenge that typically relies on the skill and judgment of practitioners. Clustering has previously been applied to tackle this problem, but with limited success. Here, we introduce a probabilistic clustering method to identify fracture networks, based on a Gaussian mixture model algorithm with physical constraints. This method is applied to a rich microseismic data set recorded during the hydraulic fracturing of eight horizontal wells in western Canada. We show that the method is effective for distinguishing hydraulic‐fracture‐created events from induced seismicity. These fractures follow a log‐normal distribution and reflect the physical mechanisms of the hydraulic fracturing process. We conclude that this method has wide applicability for interpreting natural and anthropogenic processes in the subsurface.
Publisher: Wiley
Date: 03-2006
Publisher: Acoustical Society of America (ASA)
Date: 10-2014
DOI: 10.1121/1.4892752
Abstract: A quantitative inversion procedure is developed and applied to determine the dominant scattering mechanism (surface roughness and/or volume scattering) from seabed scattering-strength data. The classification system is based on trans-dimensional Bayesian inversion with the deviance information criterion used to select the dominant scattering mechanism. Scattering is modeled using first-order perturbation theory as due to one of three mechanisms: Interface scattering from a rough seafloor, volume scattering from a heterogeneous sediment layer, or mixed scattering combining both interface and volume scattering. The classification system is applied to six simulated test cases where it correctly identifies the true dominant scattering mechanism as having greater support from the data in five cases the remaining case is indecisive. The approach is also applied to measured backscatter-strength data where volume scattering is determined as the dominant scattering mechanism. Comparison of inversion results with core data indicates the method yields both a reasonable volume heterogeneity size distribution and a good estimate of the sub-bottom depths at which scatterers occur.
Publisher: Oxford University Press (OUP)
Date: 13-10-2015
DOI: 10.1093/GJI/GGV375
Publisher: Acoustical Society of America (ASA)
Date: 07-2007
DOI: 10.1121/1.2736514
Abstract: This paper develops a nonlinear Bayesian inversion for high-resolution seabed reflection travel time data including rigorous uncertainty estimation and examination of statistical assumptions. Travel time data are picked on seismo-acoustic traces and inverted for a layered sediment sound-velocity model. Particular attention is paid to picking errors which are often biased, correlated, and nonstationary. Non-Toeplitz data covariance matrices are estimated and included in the inversion along with unknown travel time offset (bias) parameters to account for these errors. Simulated experiments show that neglecting error covariances and biases can cause misleading inversion results with unrealistically high confidence. The inversion s les the posterior probability density and provides a solution in terms of one- and two-dimensional marginal probability densities, correlations, and credibility intervals. Statistical assumptions are examined through the data residuals with rigorous statistical tests. The method is applied to shallow-water data collected on the Malta Plateau during the SCARAB98 experiment.
Location: Germany
Start Date: 02-2008
End Date: 12-2011
Amount: $225,000.00
Funder: Australian Research Council
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