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Showing papers in "Geophysical Journal International in 2018"


Journal ArticleDOI
TL;DR: A deep-neural-network-based arrival-time picking method called "PhaseNet" that picks the arrival times of both P and S waves, and has the potential to increase the number of S-wave observations dramatically over what is currently available.
Abstract: As the number of seismic sensors grows, it is becoming increasingly difficult for analysts to pick seismic phases manually and comprehensively, yet such efforts are fundamental to earthquake monitoring. Despite years of improvements in automatic phase picking, it is difficult to match the performance of experienced analysts. A more subtle issue is that different seismic analysts may pick phases differently, which can introduce bias into earthquake locations. We present a deep-neural-network-based arrival-time picking method called "PhaseNet" that picks the arrival times of both P and S waves. Deep neural networks have recently made rapid progress in feature learning, and with sufficient training, have achieved super-human performance in many applications. PhaseNet uses three-component seismic waveforms as input and generates probability distributions of P arrivals, S arrivals, and noise as output. We engineer PhaseNet such that peaks in probability provide accurate arrival times for both P and S waves, and have the potential to increase the number of S-wave observations dramatically over what is currently available. This will enable both improved locations and improved shear wave velocity models. PhaseNet is trained on the prodigious available data set provided by analyst-labeled P and S arrival times from the Northern California Earthquake Data Center. The dataset we use contains more than seven million waveform samples extracted from over thirty years of earthquake recordings. We demonstrate that PhaseNet achieves much higher picking accuracy and recall rate than existing methods.

433 citations



Journal ArticleDOI
TL;DR: A group of synthetic, real microseismic and earthquake data sets with different levels of complexity show that the proposed method is much more robust than the state-of-the-art STA/LTA method in picking microseISMic events, even in the case of moderately strong background noise.
Abstract: S U M M A R Y Effective and efficient arrival picking plays an important role in microseismic and earthquake data processing and imaging. Widely used short-term-average long-term-average ratio (STA/LTA) based arrival picking algorithms suffer from the sensitivity to moderate-to-strong random ambient noise. To make the state-of-the-art arrival picking approaches effective, microseismic data need to be first pre-processed, for example, removing sufficient amount of noise, and second analysed by arrival pickers. To conquer the noise issue in arrival picking for weak microseismic or earthquake event, I leverage the machine learning techniques to help recognizing seismic waveforms in microseismic or earthquake data. Because of the dependency of supervised machine learning algorithm on large volume of well-designed training data, I utilize an unsupervised machine learning algorithm to help cluster the time samples into two groups, that is, waveform points and non-waveform points. The fuzzy clustering algorithm has been demonstrated to be effective for such purpose. A group of synthetic, real microseismic and earthquake data sets with different levels of complexity show that the proposed method is much more robust than the state-of-the-art STA/LTA method in picking microseismic events, even in the case of moderately strong background noise.

133 citations




Journal ArticleDOI
TL;DR: In this article, two examples from the Western Canada Sedimentary Basin where earthquakes induced by hydraulic fracturing are strongly clustered within areas characterized by pore-pressure gradient in excess of 15 kPa m−1.
Abstract: S U M M A R Y Fluid-injection processes such as disposal of saltwater or hydraulic fracturing can induce earthquakes by increasing pore pressure and/or shear stress on faults. Natural processes, including transformation of organic material (kerogen) into hydrocarbon and cracking to produce gas, can similarly cause fluid overpressure. Here, we document two examples from the Western Canada Sedimentary Basin where earthquakes induced by hydraulic fracturing are strongly clustered within areas characterized by pore-pressure gradient in excess of 15 kPa m−1. Despite extensive hydraulic-fracturing activity associated with resource development, induced earthquakes are virtually absent in the Montney and Duvernay Formations elsewhere. Statistical analysis suggests a negligible probability that this spatial correlation developed by chance. This implies that, in addition to known factors such as anthropogenic pore-pressure increase and proximity to critically stressed faults, high in situ overpressure of shale formations may also represent a controlling factor for inducing earthquakes by hydraulic fracturing. On a geological timescale, natural pore-pressure generation may lead to fault-slip episodes that regulate the magnitude of formation overpressure.

79 citations



Journal ArticleDOI
TL;DR: In this paper, the impact of uncertainties related to the choice of a fault geometry in source inversion problems is explored and a sensitivity analysis to small perturbations of fault dip and position is developed.
Abstract: The ill-posed nature of earthquake source estimation derives from several factors including the quality and quantity of available observations and the fidelity of our forward theory. Observational errors are usually accounted for in the inversion process. Epistemic errors, which stem from our simplified description of the forward problem, are rarely dealt with despite their potential to bias the estimate of a source model. In this study, we explore the impact of uncertainties related to the choice of a fault geometry in source inversion problems. The geometry of a fault structure is generally reduced to a set of parameters, such as position, strike and dip, for one or a few planar fault segments. While some of these parameters can be solved for, more often they are fixed to an uncertain value. We propose a practical framework to address this limitation by following a previously implemented method exploring the impact of uncertainties on the elastic properties of our models. We develop a sensitivity analysis to small perturbations of fault dip and position. The uncertainties of our fixed fault geometry are included in the inverse problem under the formulation of the misfit covariance matrix that combines both prediction and observation uncertainties. We validate this approach with the simplified case of a fault that extends infinitely along strike, using both Bayesian and optimization formulations of a static slip inversion. If epistemic errors are ignored, predictions are overconfident in the data and slip parameters are not reliably estimated. In contrast, inclusion of uncertainties in fault geometry allows us to infer a robust posterior slip model. Epistemic uncertainties can be many orders of magnitude larger than observational errors for great earthquakes (Mw > 8). Not accounting for uncertainties in fault geometry may partly explain observed shallow slip deficits for continental earthquakes. Similarly, ignoring the impact of epistemic errors can also bias estimates of near-surface slip and predictions of tsunamis induced by megathrust earthquakes.

71 citations


Journal ArticleDOI
TL;DR: In this paper, a probabilistic 3D shear wave velocity model, including probability densities for the depth of layer boundaries and S-wave velocity values, is obtained by nonlinear Bayesian inversion.
Abstract: Taking advantage of the large number of seismic stations installed in Europe, in particular in the greater Alpine region with the AlpArray experiment, we derive a new high-resolution 3-D shear wave velocity model of the European crust and uppermost mantle from ambient-noise tomography. The correlation of up to 4 yr of continuous vertical-component seismic recordings from 1293 broad-band stations (10 • W-35 • E, 30 • N-75 • N) provides Rayleigh wave group velocity dispersion data in the period band 5-150 s at more than 0.8 million virtual source-receiver pairs. 2-D Rayleigh wave group velocity maps are estimated using adaptive parametrization to accommodate the strong heterogeneity of path coverage. A probabilistic 3-D shear wave velocity model, including probability densities for the depth of layer boundaries and S-wave velocity values, is obtained by nonlinear Bayesian inversion. A weighted average of the probabilistic model is then used as starting model for the linear inversion step, providing the final V s model. The resulting S-wave velocity model and Moho depth are validated by comparison with previous geophysical studies. Although surface wave tomography is weakly sensitive to layer boundaries, vertical cross-sections through our V s model and the associated probability of the presence of interfaces display striking similarities with reference controlled-source seismology (CSS) and receiver function sections across the Alpine belt. Our model even provides new structural information such as an ∼8 km Moho jump along the CSS ECORS-CROP profile that was not imaged by the reflection data due to poor penetration across a heterogeneous upper crust. Our probabilistic and final shear wave velocity models have the potential to become new reference models of the European crust, both for crustal structure probing and geophysical studies including waveform modelling or full-waveform inversion.

70 citations


Journal ArticleDOI
TL;DR: In this paper, the authors applied template matching to the distributed acoustic sensing (DAS) data recorded in the Brady Hot Springs geothermal field, Nevada using 5 catalogued events, detecting 116 events and finding 68 of them well below the noise level.
Abstract: Template matching has been widely applied in the detection of earthquakes and other seismic events due to its power in detecting weak signals. Recent studies using synthetics have shown that application of template matching to large-N arrays can potentially detect earthquakes substantially below the noise level. Here we apply template matching to the distributed acoustic sensing (DAS) data recorded in the Brady Hot Springs geothermal field, Nevada. Using 5 catalogued events, we detect 116 events and find 68 of them well below the noise level. We confirm 112 events are true earthquakes by examining the patterns of their sensor-to-sensor cross-correlation sections. This demonstrates that the combination of DAS and template matching has capability to detect microseismicity below the noise level, which is unusual for conventional seismic arrays and methods. With the updated catalogue, we observe a surge of earthquakes during the shutdown of a geothermal power plant nearby. In addition, the rapid increases in the downhole pressure record coincide with intense swarms of earthquakes. These observations show a strong correlation between the seismicity frequencies and the downhole pressure changes. Finally, we investigate several factors that may affect the detection performance and compare different strategies for spatial down-sampling, in order to provide helpful insights for future large-N design and data processing.

63 citations


Journal ArticleDOI
TL;DR: In this paper, a joint inversion of noise correlation functions for the distribution of noise sources and for Earth structure is proposed, where the forward problem is free of assumptions required to equate noise correlations with Green functions.
Abstract: We develop a method for the joint inversion of noise correlation functions for the distribution of noise sources and for Earth structure. The forward problem is free of assumptions required to equate noise correlations with Green functions and allows us to compute inter-station correlations for arbitrary distributions of noise sources in space and time. Using adjoint techniques, we design an iterative inversion scheme for noise sources and Earth structure based on waveform and energy differences as misfit functional. Starting from an initial model from a wave equation traveltime inversion, we recover the target velocity model with high accuracy. A key prerequisite is a good inference of the noise source distribution.

Journal ArticleDOI
TL;DR: In this article, the authors examined trends in ocean mass, ice loss from Antarctica, Greenland, arcticislands and trends in water storage over land and glaciers from GRACE data (2005-2015) and explored the associated uncertainty.
Abstract: Observations from the Gravity Recovery and Climate Experiment (GRACE) satellite missionprovide quantitative estimates of the global water budget components However, these estimatesare uncertain as they show discrepancies when different parameters are used in the processing ofthe GRACE data We examine trends in ocean mass, ice loss from Antarctica, Greenland, arcticislands and trends in water storage over land and glaciers from GRACE data (2005–2015) andexplore the associated uncertainty We consider variations in six different GRACE processingparameters, namely the processing centre of the raw GRACE solutions, the geocentre motion,the Earth oblateness, the filtering, the leakage correction and the glacial isostatic adjustment(GIA) Considering all possible combinations of the different processing parameters leads toan ensemble of 1500 post-processed GRACE solutions, which is assumed to cover a significantpart of the uncertainty range of GRACE estimates The ensemble-mean trend in all globalwater budget components agree within uncertainties with previous estimates based on differentsources of observations The uncertainty in the global water budget is±027 mm yr−1[at the 90per cent confidence level (CL)] over 2005–2015 We find that the uncertainty in the geocentremotion and GIA corrections dominate the uncertainty in GRACE estimate of the globalwater budget Their contribution to the uncertainty in GRACE estimate is respectively±021and±012 mm yr−1(90 per cent CL) This uncertainty in GRACE estimate implies anuncertainty in the net warming of the ocean and the Earth energy budget of±025 W m−2(90per cent CL) when inferred using the sea level budget approach

Journal ArticleDOI
TL;DR: In this paper, a micromechanics based constitutive model was proposed to account for the dynamic evolution of elastic moduli at high-strain rates in a 2D in-plane model with a 1-D right lateral fault featuring slip-weakening friction law.
Abstract: S U M M A R Y Geophysical observations show a dramatic drop of seismic wave speeds in the shallow offfault medium following earthquake ruptures. Seismic ruptures generate, or reactivate, damage around faults that alter the constitutive response of the surrounding medium, which in turn modifies the earthquake itself, the seismic radiation and the near-fault ground motion. We present a micromechanics based constitutive model that accounts for dynamic evolution of elastic moduli at high-strain rates. We consider 2-D in-plane models, with a 1-D right lateral fault featuring slip-weakening friction law. The two scenarios studied here assume uniform initial off-fault damage and an observationally motivated exponential decay of initial damage with fault normal distance. Both scenarios produce dynamic damage that is consistent with geological observations. A small difference in initial damage actively impacts the final damage pattern. The second numerical experiment, in particular, highlights the complex feedback that exists between the evolving medium and the seismic event. We show that there is a unique off-fault damage pattern associated with supershear transition of an earthquake rupture that could be potentially seen as a geological signature of this transition. These scenarios presented here underline the importance of incorporating the complex structure of fault zone systems in dynamic models of earthquakes.


Journal ArticleDOI
TL;DR: In this paper, the authors present an approach that generates a set of output parameters and uncertainty estimates that are consistent with both small/moderate (≤M6.5) and large earthquakes (>M6,5) as is required for a robust parameter interpretation and shaking forecast.
Abstract: Recent studies suggest that small and large earthquakes nucleate similarly, and that they often have indistinguishable seismic waveform onsets. The characterization of earthquakes in real time, such as for earthquake early warning, therefore requires a flexible modeling approach that allows a small earthquake to become large as fault rupture evolves over time. Here, we present a modeling approach that generates a set of output parameters and uncertainty estimates that are consistent with both small/moderate (≤M6.5) and large earthquakes (>M6.5) as is required for a robust parameter interpretation and shaking forecast. Our approach treats earthquakes over the entire range of magnitudes (>M2) as finite line-source ruptures, with the dimensions of small earthquakes being very small (<100 m) and those of large earthquakes exceeding several tens to hundreds of kilometres in length. The extent of the assumed line source is estimated from the level and distribution of high-frequency peak acceleration amplitudes observed in a local seismic network. High-frequency motions are well suited for this approach, because they are mainly controlled by the distance to the rupturing fault. Observed ground-motion patterns are compared with theoretical templates modeled from empirical ground-motion prediction equations to determine the best line source and uncertainties. Our algorithm extends earlier work by Bose et al. for large finite-fault ruptures. This paper gives a detailed summary of the new algorithm and its offline performance for the 2016 M7.0 Kumamoto, Japan and 2014 M6.0 South Napa, California earthquakes, as well as its performance for about 100 real-time detected local earthquakes (2.2 ≤ M ≤ 5.1) in California. For most events, both the rupture length and the strike are well constrained within a few seconds (<10 s) of the event origin. In large earthquakes, this could allow for providing warnings of up to several tens of seconds. The algorithm could also be useful for resolving fault plane ambiguities of focal mechanisms and identification of rupturing faults for earthquakes as small as M2.5.

Journal ArticleDOI
TL;DR: The results imply that the combination of fully 3-D dynamic modelling, complex fault geometries and off-fault plastic yielding is important to realistically capture dynamic rupture transfers in natural fault systems.
Abstract: The dynamics and potential size of earthquakes depend crucially on rupture transfers between adjacent fault segments. To accurately describe earthquake source dynamics, numerical models can account for realistic fault geometries and rheologies such as nonlinear inelastic processes off the slip interface. We present implementation, verification and application of off-fault Drucker-Prager plasticity in the open source software SeisSol (www.seissol.org). SeisSol is based on an arbitrary high-order derivative modal Discontinuous Galerkin method using unstructured, tetrahedral meshes specifically suited for complex geometries. Two implementation approaches are detailed, modelling plastic failure either employing subelemental quadrature points or switching to nodal basis coefficients. At fine fault discretizations, the nodal basis approach is up to six times more efficient in terms of computational costs while yielding comparable accuracy. Both methods are verified in community benchmark problems and by 3-D numerical h-and p-refinement studies with heterogeneous initial stresses. We observe no spectral convergence for on-fault quantities with respect to a given reference solution, but rather discuss a limitation to low-order convergence for heterogeneous 3-D dynamic rupture problems. For simulations including plasticity, a high fault resolution may be less crucial than commonly assumed, due to the regularization of peak slip rate and an increase of the minimum cohesive zone width. In large-scale dynamic rupture simulations based on the 1992 Landers earthquake, we observe high rupture complexity including reverse slip, direct branching and dynamic triggering. The spatiotemporal distribution of rupture transfers are altered distinctively by plastic energy absorption, correlated with locations of geometrical fault complexity. Computational cost increases by 7 per cent when accounting for off-fault plasticity in the demonstrating application. Our results imply that the combination of fully 3-D dynamic modelling, complex fault geometries and off-fault plastic yielding is important to realistically capture dynamic rupture transfers in natural fault systems.


Journal ArticleDOI
TL;DR: In this paper, a 3D isotropic full-waveform inversion (FWI) of nine teleseismic events recorded by the CIFALPS experiment is used to infer 3D models of both density and P- and S-wave velocities of the Alpine lithosphere.
Abstract: The Western Alps, although being intensively investigated, remains elusive when it comes to determining its lithospheric structure. New inferences on the latter are important for the understanding of processes and mechanisms of orogeny needed to unravel the dynamic evolution of the Alps. This situation led to the deployment of the CIFALPS temporary experiment, conducted to address the lack of seismological data amenable to high-resolution seismic imaging of the crust and the upper mantle. We perform a 3-D isotropic full-waveform inversion (FWI) of nine teleseismic events recorded by the CIFALPS experiment to infer 3-D models of both density and P- and S-wave velocities of the Alpine lithosphere. Here, by FWI is meant the inversion of the full seismograms including phase and amplitude effects within a time window following the first arrival up to a frequency of 0.2 Hz. We show that the application of the FWI at the lithospheric scale is able to generate images of the lithosphere with unprecedented resolution and can furnish a reliable density model of the upper lithosphere. In the shallowest part of the crust, we retrieve the shape of the fast/dense Ivrea body anomaly and detect the low velocities of the Po and SE France sedimentary basins. The geometry of the Ivrea body as revealed by our density model is consistent with the Bouguer anomaly. A sharp Moho transition is followed from the external part (30 km depth) to the internal part of the Alps (70–80 km depth), giving clear evidence of a continental subduction event during the formation of the Alpine Belt. A low-velocity zone in the lower lithosphere of the S-wave velocity model supports the hypothesis of a slab detachment in the western part of the Alps that is followed by asthenospheric upwelling. The application of FWI to teleseismic data helps to fill the gap of resolution between traditional imaging techniques, and enables integrated interpretations of both upper and lower lithospheric structures.

Journal ArticleDOI
TL;DR: In this article, the authors examined the performances of various model parameterizations in isotropic-elastic FWI with walk-away vertical seismic profile (W-VSP) dataset for unconventional Heavy oil reservoir characterization.
Abstract: Seismic full-waveform inversion (FWI) methods hold strong, though still largely untapped, potential to recover multiple subsurface elastic properties for hydrocarbon reservoir characterization. Simultaneously updating multiple physical parameters introduces the problem of interparameter tradeoff, arising from the inherent ambiguities between different physical parameters, which increases nonlinearity and uncertainty of multiparameter FWI. The coupling effects of different physical parameters are significantly influenced by model parameterization and acquisition arrangement. An appropriate choice of model parameterization is critical to successful field data applications of multiparameter FWI. The objective of this paper is to examine the performances of various model parameterizations in isotropic-elastic FWI with walk-away vertical seismic profile (W-VSP) dataset for unconventional Heavy oil reservoir characterization. Six model parameterizations are considered: velocity-density (α, β and ρ′), modulus-density (κ, μ and ρ), Lamé-density (λ, μ′ and ρ′′′), impedance-density (IP , IS and ρ′′), velocity-impedance-I (α′, β′ and I ′ P ), and velocity-impedance-II (α′′, β′′ and I ′ S). We begin analyzing the interparameter tradeoff with scattering radiation patterns for each of these parameterizations, which is one common strategy for qualitative parameter resolution studies in isotropic-elastic FWI. In this paper, we discuss the advantages and limitations of the scattering radiation patterns for interparameter tradeoff analysis and recommend to evaluate the interparameter tradeoffs using interparameter contamination kernels, which provide complete and quantitative measurements of the interparameter contaminations and can be constructed efficiently with the adjoint-state approach. Synthetic W-VSP isotropic-elastic FWI experiments verify our conclusions about interparameter tradeoffs for various model parameterizations. Density profiles are most strongly influenced by the interparameter contaminations; depending on model parameterization, the inverted density profile can be over-estimated, under-estimated or spatially distorted. The model parameterization, velocity-density, appears amongst the six cases to provide stable and informative density features not included in the starting model. Field data applications of multicomponent W-VSP isotropic-elastic FWI were also carried out with various model parameterizations. The target Heavy oil reservoir zone, characterized by low α-to-β ratios and low Poisson’s ratios, can be identified clearly with the inverted isotropic-elastic parameters.

Journal ArticleDOI
TL;DR: In this paper, a 1-step 3D non-linear surface wave tomography method was proposed to reveal the subsurface structure of the Earth using the reversible jump Markov chain Monte Carlo (McMC) algorithm with a fully 3D model parametrization.
Abstract: S U M M A R Y Seismic surface wave tomography is a tried and tested method to reveal the subsurface structure of the Earth. However, the conventional 2-step scheme of inverting first for 2-D maps of surface wave phase or group velocity and then inverting for the 3-D spatial velocity structure preserves little information about lateral spatial correlations, and introduces additional uncertainties and errors into the 3-D result. We introduce a 1-step 3-D non-linear surface wave tomography method that removes these effects by inverting for 3-D spatial structure directly from frequencydependent traveltime measurements. We achieve this using the reversible jump Markov chain Monte Carlo (McMC) algorithm with a fully 3-D model parametrization. Synthetic tests show that the method estimates the velocity model and associated uncertainties significantly better than the conventional 2-step McMC method, and that the computational cost seems to be comparable with 2-step McMC methods. The resulting uncertainties are more intuitively reasonable than those from the 2-step method, and provide directly interpretable uncertainty on volumetrics of structures of interest.

Journal ArticleDOI
TL;DR: In this paper, the Sentinel-1 mission comprises two synthetic aperture radar satellites, each with a 12-day orbital repeat, orbiting 6 days apart within a narrow tube, and process the first post-event interferogram with the shortest possible time-span for each using the ISCE software.
Abstract: Author(s): Funning, Gareth; Garcia, Astrid | Abstract: The Sentinel-1 mission comprises two synthetic aperture radar satellites, each with a 12 day orbital repeat, orbiting 6 days apart within a narrow tube. The mission design promises the ability to respond quickly to earthquakes with InSAR, and to facilitate production of interferograms with good interferometric correlation globally. We report on our efforts to study global seismicity using Sentinel-1 Interferometric Wide-Swath data between April 2015 and December 2016. We select 35 potentially detectable terrestrial earthquakes in the range 5.5 ≤ Mw ≤ 7.8 on the basis of their locations, depths and magnitudes, and process the first post-event interferogram with the shortest possible time-span for each using the ISCE software. We evaluate each interferogram for earthquake deformation signals by visual inspection. We can identify deformation signals attributable to earthquakes in 18 of these interferograms (51%); a further six interferograms (17%) have ambiguous interferometric phase affected by tropospheric noise. 11 events (31%) could not be identified from their interferograms. The majority of these failed detections were due to interferogram decorrelation, particularly apparent for earthquakes that occurred between 15°N and 15°S, where climate conditions promote dense vegetation. The majority of the ambiguous interferograms are affected by tropospheric noise, suggesting that techniques to mitigate such noise could improve detection performance. The largest event we do not detect with Sentinel-1 data is a Mw7.0 earthquake that occurred in Vanuatu in April 2016; we also fail to detect the 2016 Mw6.2 Kurayoshi earthquake in one out of two possible 24-day interferograms. We propose these as upper and lower estimates on the magnitude of completeness for earthquakes studied with Sentinel-1 data; to lower the magnitude of completeness we suggest that more frequent (e.g. six day) recurrence may be necessary in low latitude areas.

Journal ArticleDOI
TL;DR: In this paper, an expression for the error introduced by the second-order accurate temporal finitedifference (FD) operator, as present in the pseudospectral and spectral element methods for seismic wave modeling applied to time-invariant media, is derived.
Abstract: We derive an expression for the error introduced by the second-order accurate temporal finitedifference (FD) operator, as present in the FD, pseudospectral and spectral element methods for seismic wave modeling applied to time-invariant media. The 'time-dispersion' error speeds up the signal as a function of frequency and time step only. Time dispersion is thus independent of the propagation path, medium or spatial modeling error.We derive two transforms to either add or remove time dispersion from synthetic seismograms after a simulation. The transforms are compared to previous related work and demonstrated on wave modeling in acoustic as well as elastic media. In addition, an application to imaging is shown. The transforms enable accurate computation of synthetic seismograms at reduced cost, benefitting modeling applications in both exploration and global seismology. The Author(s) 2017. Published by Oxford University Press. All rights reserved. (Less)

Journal ArticleDOI
TL;DR: In this paper, a 3D frequency-domain full waveform inversion (FWI) is applied on North Sea wide-azimuth ocean-bottom cable data at low frequencies (≤10 Hz) to jointly update vertical wave speed, density and quality factor Q in the viscoacoustic VTI approximation.
Abstract: 3-D frequency-domain full waveform inversion (FWI) is applied on North Sea wide-azimuth ocean-bottom cable data at low frequencies (≤10 Hz) to jointly update vertical wave speed, density and quality factor Q in the viscoacoustic VTI approximation. We assess whether density and Q should be viewed as proxy to absorb artefacts resulting from approximate wave physics or are valuable for interpretation in the presence of soft sediments and gas cloud. FWI is performed in the frequency domain to account for attenuation easily. Multiparameter frequency-domain FWI is efficiently performed with a few discrete frequencies following a multiscale frequency continuation. However, grouping a few frequencies during each multiscale step is necessary to mitigate acquisition footprint and match dispersive shallow guided waves. Q and density absorb a significant part of the acquisition footprint hence cleaning the velocity model from this pollution. Low Q perturbations correlate with low-velocity zones associated with soft sediments and gas cloud. However, the amplitudes of the Q perturbations show significant variations when the inversion tuning is modified. This dispersion in the Q reconstructions is however not passed on the velocity parameter suggesting that cross-talks between first-order kinematic and second-order dynamic parameters are limited. The density model shows a good match with a well log at shallow depths. Moreover, the impedance built a posteriori from the FWI velocity and density models shows a well-focused image with however local differences with the velocity model near the sea bed where density might have absorbed elastic effects. The FWI models are finally assessed against time-domain synthetic seismogram modelling performed with the same frequency-domain modelling engine used for FWI.



Journal ArticleDOI
TL;DR: It is found that the trans-D tree based approach together with parallel tempering for navigating rugged likelihood (i.e. misfit) topography provides a promising, easily generalized method for solving large-scale geophysical inverse problems which are difficult to optimize, but where the true model contains a hierarchy of features at multiple scales.
Abstract: S U M M A R Y Limited illumination, insufficient offset, noisy data and poor starting models can pose challenges for seismic full waveform inversion. We present an application of a tree based Bayesian inversion scheme which attempts to mitigate these problems by accounting for data uncertainty while using a mildly informative prior about subsurface structure. We sample the resulting posterior model distribution of compressional velocity using a trans-dimensional (trans-D) or Reversible Jump Markov chain Monte Carlo method in the wavelet transform domain of velocity. This allows us to attain rapid convergence to a stationary distribution of posterior models while requiring a limited number of wavelet coefficients to define a sampled model. Two synthetic, low frequency, noisy data examples are provided. The first example is a simple reflection + transmission inverse problem, and the second uses a scaled version of the Marmousi velocity model, dominated by reflections. Both examples are initially started from a semi-infinite half-space with incorrect background velocity. We find that the trans-D tree based approach together with parallel tempering for navigating rugged likelihood (i.e. misfit) topography provides a promising, easily generalized method for solving large-scale geophysical inverse problems which are difficult to optimize, but where the true model contains a hierarchy of features at multiple scales.


Journal ArticleDOI
TL;DR: In this article, the authors investigated the specific role of smectite in the electrical response of igneous basaltic rocks and evaluated what physical processes make smectites a better electrical conductor than surrounding minerals.
Abstract: The underground circulation of hot water, of interest for geothermal energy production, is often indirectly inferred from the presence of minerals formed by hydrothermal alteration at different temperatures. Clay minerals, such as smectite and chlorite, can be mapped from the surface using electrical soundings and give information about the structure of the geothermal system. Here, we investigate the specific role of smectite in the electrical response of igneous basaltic rocks and evaluate what physical processes make smectite a better electrical conductor than surrounding minerals. Laboratory measurements of cation exchange capacity (CEC), mineralogy, porosity and electrical conductivity are presented for 88 core samples from four boreholes at the Krafla volcano, Northeast Iceland. CEC is found to be a reliable measure of the smectite weight fraction in these volcanic samples, through a comparison with an independent quantification of the smectite content using Rietveld refinements of X-ray diffraction patterns. The bulk electrical conductivity, measured at fluid conductivities in the range 0.02-11.7 S m −1 , increases non-linearly with the fluid conductivity for samples with high smectite content. This non-linear variation is fitted with a function and a model for a conduction process through connected interlayer spaces within smectite. The process differs from electrical double layer conduction, which involves only cations on the crystal edges of smectite, not in the interlayer spaces. The laboratory results can help refine interpretations of electrical soundings in the context of geothermal exploration.

Journal ArticleDOI
TL;DR: In this paper, a nearly unbiased approximation of the vector sparsity, denoted as L1−2 minimization, for exact and stable seismic attenuation compensation is proposed, which can be performed on either pre-stack or post-stack data so as to mitigate amplitude absorption and phase dispersion effects resulting from intrinsic anelasticity of subsurface media.
Abstract: S U M M A R Y Frequency-dependent amplitude absorption and phase velocity dispersion are typically linked by the causality-imposed Kramers–Kronig relations, which inevitably degrade the quality of seismic data. Seismic attenuation compensation is an important processing approach for enhancing signal resolution and fidelity, which can be performed on either pre-stack or post-stack data so as to mitigate amplitude absorption and phase dispersion effects resulting from intrinsic anelasticity of subsurface media. Inversion-based compensation with L1 norm constraint, enlightened by the sparsity of the reflectivity series, enjoys better stability over traditional inverse Q filtering. However, constrained L1 minimization serving as the convex relaxation of the literal L0 sparsity count may not give the sparsest solution when the kernel matrix is severely ill conditioned. Recently, non-convex metric for compressed sensing has attracted considerable research interest. In this paper, we propose a nearly unbiased approximation of the vector sparsity, denoted as L1−2 minimization, for exact and stable seismic attenuation compensation. Non-convex penalty function of L1−2 norm can be decomposed into two convex subproblems via difference of convex algorithm, each subproblem can be solved efficiently by alternating direction method of multipliers. The superior performance of the proposed compensation scheme based on L1−2 metric over conventional L1 penalty is further demonstrated by both synthetic and field examples.

Journal ArticleDOI
TL;DR: In this article, the internal structure of the San Jacinto fault zone (SJFZ) in the trifurcation area southeast of Anza, California, with seismic records from dense linear and rectangular arrays was analyzed.
Abstract: We image the internal structure of the San Jacinto fault zone (SJFZ) in the trifurcation area southeast of Anza, California, with seismic records from dense linear and rectangular arrays. The examined data include recordings from more than 20 000 local earthquakes and nine teleseismic events. Automatic detection algorithms and visual inspection are used to identify P and S body waves, along with P- and S-types fault zone trapped waves (FZTW). The location at depth of the main branch of the SJFZ, the Clark fault, is identified from systematic waveform changes across lines of sensors within the dense rectangular array. Delay times of P arrivals from teleseismic and local events indicate damage asymmetry across the fault, with higher damage to the NE, producing a local reversal of the velocity contrast in the shallow crust with respect to the large-scale structure. A portion of the damage zone between the main fault and a second mapped surface trace to the NE generates P- and S-types FZTW. Inversions of high-quality S-type FZTW indicate that the most likely parameters of the trapping structure are width of ∼70 m, S-wave velocity reduction of 60 per cent, Q value of 60 and depth of ∼2 km. The local reversal of the shallow velocity contrast across the fault with respect to large-scale structure is consistent with preferred propagation of earthquake ruptures in the area to the NW.