ALBERT

Description: Summary We deployed a seismic network near the source region of the 2017 Mw 6.5 Jiuzhaigou earthquake to monitor aftershock activity and to investigate the local fault structure. An aftershock deployment of Array of small Arrays (AsA) and a Geometric Mean Envelop (GME) algorithm are adopted to enhance detection performance. We also adopt a set of association, relocation, and matched-filter techniques to obtain a detailed regional catalog. 16,742 events are detected and relocated, including 1,279 aftershocks following the Mw 4.8 aftershock. We develop a joint inversion algorithm utilizing locations of event clusters and focal mechanisms to determine the geometry of planar faults. Six segments were finally determined, in which three segments are related to the Huya fault reflecting a change in fault dip direction near the mainshock hypocenter, while the other segments reflect branches showing orthogonal and conjugate geometries with the Huya fault. Aftershocks were active on branching faults between the Huya and Minjiang faults indicating that the mainshock may have ruptured both major faults. We also resolve a fault portion with ‘weak strength’ near the mainshock hypocenter, which is characterized by limited co-seismic slips, concentrated afterslip, low aftershock activities, high b-value, and high sensitivity to stress changes. These phenomena can be explained by fault frictional properties at conditional stable sliding status, which may be related to the localized high pore-fluid pressure produced by the fluid intrusion.

Description: Summary The Bayesian slip inversion offers a powerful tool for modeling the earthquake source mechanism. It can provide a fully probabilistic result and thus permits us to quantitively assess the inversion uncertainty. The Bayesian problem is usually solved with Monte Carlo methods, but they are computationally expensive and are inapplicable for high-dimensional and large-scale problems. Variational inference is an alternative solver to the Bayesian problem. It turns Bayesian inference into an optimization task and thus enjoys better computational performances. In this study, we introduce a general variational inference algorithm, automatic differentiation variational inference (ADVI), to the Bayesian slip inversion and compare it with the classic Metropolis-Hastings (MH) sampling method. The synthetic test shows that the two methods generate nearly identical mean slip distributions and standard deviation maps. In the real case study, the two methods produce highly consistent mean slip distributions, but the ADVI-derived standard deviation map differs from that produced by the MH method, possibly because of the limitation of the Gaussian approximation in the ADVI method. In both cases, ADVI can give comparable results to the MH method but with a significantly lower computational cost. Our results show that ADVI is a promising and competitive method for the Bayesian slip inversion.

Description: Summary The M=8.1, April 1st, 2014 Iquique earthquake, which broke part of the northern Chile seismic gap, was preceded by a strong foreshock sequence starting early January 2014. The reported analysis of the continuous records of the nearby GPS stations from the IPOC North Chili array lead to contradictory results concerning the existence and location of slow slip events (SSE) on the interplate contact. Resolving this controversy is an important issue, as although many SSEs are reported in subduction zones, only a few were found to be precursory to large earthquakes. Here we show that the records of a long base tiltmeter installed near Iquique, when corrected for coseismic steps, long term drift, tidal signals, and oceanic and atmospheric loading, show significant residual signals. These can be modelled with a sequence of four SSEs located close to Iquique. Their signature was already reported on some GPS stations, but their source was then characterized with a very low resolution in time and space, leading to contradicting models. With the tilt records, we can rule out the previously proposed models with a single large SSE closer to the mainshock. Combining tilt with GPS records greatly improves the resolution of GPS alone, and one could locate their sources 100 to 180 km south-southeast to the mainshock epicenter, with moment magnitudes between 5.8 and 6.2, at the edge of the main aftershock asperities. These moderate SSEs thus did not directly trigger the mainshock, but contributed to trigger the main foreshock and the main aftershock. Only the sensitivity and resolution of the tiltmeter, added to the GPS records, allowed us to describe with unprecedented accuracy this precursory process as a cascade of cross-triggered, short term aseismic slip events and earthquakes on the interplate contact. This three months of precursory activation appears to be the final acceleration burst of a weaker, longer term SSE which started mid-2013, already reported, with a moment release history which we could quantify. From the methodological point of view, our study takes advantage of an interesting complementarity of tilt and GPS measurements, due to their different dependence in distance to the source of strain, which turns out to be very efficient for resolving location and moment of strain sources, even when both instruments are close to each other. It finally demonstrates the efficient removal of sequences of small or even undetected coseismic steps from high resolution tilt record signal in order to retrieve the purely aseismic signal, a presently impossible task for high time resolution GPS records due to low signal to noise.

Description: Summary On 2020 December 29, the Mw 6.4 Petrinja earthquake hit the Kupa Valley region and set a record for the largest earthquake in northwestern (NW) Croatia. The coseismic surface displacements are well obtained on three pairs of interferometric synthetic aperture radar (InSAR) images from Sentinel-1 satellites. The interferograms exhibit coseismic ground deformation with a maximum line-of-sight (LOS) displacement of 0.4 m. Based on the coseismic deformation field, we investigate both the fault geometry and the coseismic slip distribution. The results show a dextral event with a peak slip of 3.50 m at a depth of 3.47 km. The shallow depth and unusually large coseismic slip correspond to obvious ground deformation and serious damage in the epicentral zone. The 2020 earthquake highlights an unmapped, steeply dipping strike-slip fault, which possibly enabled a potential ‘curve cut-off’ process on the bending segment of the Pokupsko fault in the context of ∼N-S compression in NW Croatia. The large coseismic slip and high stress drop associated with the Mw 6.4 Petrinja earthquake are likely products of the geometrically complex fault zones and immature seismotectonic environment in NW Croatia.

Description: Summary We have studied the active and recent tectonics of New Guinea, using earthquake source modelling, analysis of gravity anomalies, seismic reflection profiles, and thermal and mechanical models. Our aim is to investigate the behaviour and evolution of a young continental deformation belt, and to explore the effects of lateral variations in foreland rheology on the deformation. We find that along-strike gradients in the lithosphere thickness of the southern foreland have resulted in correlated changes in seismogenic thickness, likely due to the effects on the temperature structure of the crust. The resulting variation in the strength of the foreland means that in the east, the foreland is broken through on thrust faults, whereas in the west it is relatively intact. The lack of correlation between the elevation of the mountain belt and the seismogenic thickness of the foreland is likely to be due to the time taken to thicken the crust in the mountains following changes in the rheology of the underthrusting foreland, as the thinned passive margin of northern Australia is consumed. The along-strike variation in whether the force exerted between the mountains and the lowlands is able to break the foreland crust enables us to estimate the effective coefficient of friction on foreland faults to be in the range of 0.01-0.28. We use force-balance calculations to show that the recent tectonic re-organisation in western New Guinea is likely to be due to the development of increasing curvature in the Banda Arc, and that the impingement of continental material on the subduction zone may explain the unusually low force it exerts on western New Guinea.

Description: Summary Finite-difference (FD) modeling of seismic waves in the vicinity of dipping interfaces gives rise to artifacts. Examples are phase and amplitude errors, as well as staircase diffractions. Such errors can be reduced in two general ways. In the first approach, the interface can be anti-aliased (i.e., with an anti-aliased step-function, or a lowpass filter). Alternatively, the interface may be replaced with an equivalent medium (i.e., using Schoenberg & Muir (SM) calculus or orthorhombic averaging). We test these strategies in acoustic, elastic isotropic, and elastic anisotropic settings. Computed FD solutions are compared to analytical solutions. We find that in acoustic media, anti-aliasing methods lead to the smallest errors. Conversely, in elastic media, the SM calculus provides the best accuracy. The downside of the SM calculus is that it requires an anisotropic FD solver even to model an interface between two isotropic materials. As a result, the computational cost increases compared to when using isotropic FD solvers. However, since coarser grid spacings can be used to represent the dipping interfaces, the two effects (an expensive FD solver on a coarser FD grid) equal out. Hence, the SM calculus can provide an efficient means to reduce errors, also in elastic isotropic media.

Description: Summary Distributed Acoustic Sensing (DAS) networks promise to revolutionize observational seismology by providing cost-effective, highly dense spatial sampling of the seismic wavefield, especially by utilizing pre-deployed telecomm fiber in urban settings for which dense seismic network deployments are difficult to construct. However, each DAS channel is sensitive only to one projection of the horizontal strain tensor and therefore gives an incomplete picture of the horizontal seismic wavefield, limiting our ability to make a holistic analysis of instrument response. This analysis has therefore been largely restricted to pointwise comparisons where a fortuitious coincidence of reference three-component seismometers and co-located DAS cable allows. We evaluate DAS instrument response by comparing DAS measurements from the PoroTomo experiment with strain-rate wavefield reconstructed from the nodal seismic array deployed in the same experiment, allowing us to treat the entire DAS array in a systematic fashion irrespective of cable geometry relative to the location of nodes. We found that, while the phase differences are in general small, the amplitude differences between predicted and observed DAS strain-rates average a factor of 2 across the array and correlate with near-surface geology, suggesting that careful assessment of DAS deployments is essential for applications that require reliable assessments of amplitude. We further discuss strategies for empirical gain corrections and optimal placement of point sensor deployments to generate the best combined sensitivity with an already deployed DAS cable, from a wavefield reconstruction perspective.

Description: Summary This article proposes the use of geostatistical techniques to estimate dispersion curves between other known ones. To do it, we introduce two novel methodologies: the stacking method and the group-velocity mapping method. We obtain our set of group-velocity fundamental mode dispersion curves from seismic noise correlation. Consequently, we first assign their attribution point at the mid-distance between the stations used for the dispersion curves calculation. The stacking method uses the range of the omnidirectional semivariogram of a regionalized variable that quantifies the similarity between dispersion curves to stack them according to their spatial correlation. We test this technique with dispersion curves obtained in Mexico City and get a range of ∼400 m for the omnidirectional semivariogram. We also calculate directional semivariograms and observe a maximum range (∼500 m) in the NW-SE direction, agreeing with the city's spatial distribution of natural periods. On the other hand, the group-velocity mapping method uses the ordinary kriging estimator in the group velocities for all the ranges of periods to generate maps and then dispersion curves. Estimated dispersion curves retrieved from both, the stacking and the group-velocity mapping method, were compared with those obtained with the fast marching tomographic method. We also establish analogies between getting group-velocity maps with the tomographic method and with the group-velocity mapping method. Finally, we observe that the range of the omnidirectional semivariogram used in the stacking method may be related to the tomographic method resolution.

Description: The state-space assessment model (SAM) is extended by allowing a functional relationship between observation variance and the corresponding prediction. An estimated relationship between observation variance and predicted value for each individual observation allows the model to assign smaller (or larger) variance to predicted larger log-observations. This relation is different from the usual assumption of constant variance of log-observations within age groups. The prediction–variance link is implemented and compared to the usual constant variance assumption for the official assessments of North East Arctic cod and haddock. For both of these stocks, the prediction–variance link is found to give a significant improvement.

Description: Summary We present a technique for lithofacies classification of well-log data using an active semi-supervised algorithm. This method considers both the input of domain experts and the distribution characteristics of well-log properties. It aims to obtain lithofacies that are more geologically meaningful and seismically interpretable than the conventional clustering methods. We impose guidance from experts (e.g., geologist, petrophysicist and seismic interpreter) as pairwise constraints. The acquired constraints were incorporated into facies classification in two ways: modification of the objective function and optimization of the classification subspace. An iterative expectation-maximization (EM) algorithm was used to minimize the objective function. We applied the method to a set of well logs from the Glitne field, North Sea, where six lithofacies had been defined initially. Classification results illustrated that facies predicted with the semi-supervised approach achieved good matches with true labels. Comparisons among different methods (semi-supervised method, quadratic determinant analysis and expectation-maximization with Gaussian mixture model algorithm) also demonstrated that the proposed method significantly outperformed the others. We also tested a scenario with five facies, where we combined silty shale and shale into one group due to significant overlap in the elastic domain. Results demonstrated that the semi-supervised approach produced facies that were more consistent with expert intention, and they were more geologically interpretable. The techniques and results illustrated here could be performed in different types of reservoir facies classification, and the facies classified using semi-supervised algorithm honors the input of the users and data characteristics.