ALBERT

Description: We present a detailed clustering analysis of the young stellar population across the star-forming ring galaxy NGC 6503, based on the deep Hubble Space Telescope photometry obtained with the Legacy ExtraGalactic UV Survey. We apply a contour-based map analysis technique and identify in the stellar surface density map 244 distinct star-forming structures at various levels of significance. These stellar complexes are found to be organized in a hierarchical fashion with 95 per cent being members of three dominant super-structures located along the star-forming ring. The size distribution of the identified structures and the correlation between their radii and numbers of stellar members show power-law behaviours, as expected from scale-free processes. The self-similar distribution of young stars is further quantified from their autocorrelation function, with a fractal dimension of ~1.7 for length-scales between ~20 pc and 2.5 kpc. The young stellar radial distribution sets the extent of the star-forming ring at radial distances between 1 and 2.5 kpc. About 60 per cent of the young stars belong to the detected stellar structures, while the remaining stars are distributed among the complexes, still inside the ring of the galaxy. The analysis of the time-dependent clustering of young populations shows a significant change from a more clustered to a more distributed behaviour in a time-scale of ~60 Myr. The observed hierarchy in stellar clustering is consistent with star formation being regulated by turbulence across the ring. The rotational velocity difference between the edges of the ring suggests shear as the driving mechanism for this process. Our findings reveal the interesting case of an inner ring forming stars in a hierarchical fashion.

Description: The frequency dependence of the quality factor Q has long been predicted by mathematical modelling and laboratory measurements; however, in situ evidence from seismic surveys is still lacking. We have conducted the cross-hole seismic surveys to investigate the near-surface seismic attenuation in the Daqing oilfield in northeastern China. The seismic waves were fired in a source hole of 40 m from the bottom to the surface at an interval of 1 m and were recorded in a receiver hole of 40 m by two geophones with one at the surface and the other one at the bottom. The direct waves were extracted to avoid the noise disturbance and the reflection interference, and the attenuations without the effects of the source signature and the receiver coupling were estimated by a method we proposed. The nonlinear attenuations were observed and fitted using the power-law-based Q . The reliability of Q estimate was verified by the high similarity between the real and the simulated attenuations. Therefore, the experiment we have conducted can be treated as a reliable evidence for the frequency dependence of near-surface  Q .

Description: Mahévas, S., Vermard, Y., Hutton, T., Iriondo, A., Jadaud, A., Maravelias, C. D., Punzón, A., Sacchi, J., Tidd, A., Tsitsika, E., Marchal, P., Goascoz, N., Mortreux, S., and Roos, D. 2011. An investigation of human vs. technology-induced variation in catchability for a selection of European fishing fleets. – ICES Journal of Marine Science, 68: 2252–2263. The impact of the fishing effort exerted by a vessel on a population depends on catchability, which depends on population accessibility and fishing power. The work investigated whether the variation in fishing power could be the result of the technical characteristics of a vessel and/or its gear or whether it is a reflection of inter-vessel differences not accounted for by the technical attributes. These inter-vessel differences could be indicative of a skipper/crew experience effect. To improve understanding of the relationships, landings per unit effort (lpue) from logbooks and technical information on vessels and gears (collected during interviews) were used to identify variables that explained variations in fishing power. The analysis was undertaken by applying a combination of generalized additive models and generalized linear models to data from several European fleets. The study highlights the fact that taking into account information that is not routinely collected, e.g. length of headline, weight of otter boards, or type of groundrope, will significantly improve the modelled relationships between lpue and the variables that measure relative fishing power. The magnitude of the skipper/crew experience effect was weaker than the technical effect of the vessel and/or its gear.

Description: SUMMARY Using a proper parametrization, the source displacement field of a seismic event can be efficiently reconstructed by a redundant dictionary of Green’s functions based on sparse representation theory. Then, by subjecting the pre-existing event records and pre-computed dictionary of Green’s functions into a sparsity-promoting algorithm, it is possible to simultaneously evaluate the origin time, hypocentre coordinates and seismic moment tensor. The proposed method is applicable to single- or multiple-source scenarios and, with minor adjustments, can be a valuable tool for real-time, automatic monitoring systems. This study demonstrates the effectiveness and accuracy of the dictionary-based approach via (1) detection of microseismic events produced during the hydraulic fracturing of oil and gas wells and (2) inversion of a small-magnitude, regional earthquake (2002 June 18 in Caborn, Indiana) data. Our experiments based on numerical simulations and earthquake observations underscore the largely untapped potential of dictionary-based approaches and sparse representation theory in continuous source parameter recovery.

Description: Microseismic monitoring is an essential tool for the characterization of hydraulic fractures. Fast estimation of the parameters that define a microseismic event is relevant to understand and control fracture development. The amount of data contained in the microseismic records however, poses a challenge for fast continuous detection and evaluation of the microseismic source parameters. Work inspired by the emerging field of Compressive Sensing has showed that it is possible to evaluate source parameters in a compressed domain, thereby reducing processing time. This technique performs well in scenarios where the amplitudes of the signal are above the noise level, as is often the case in microseismic monitoring using downhole tools. This paper extends the idea of the compressed domain processing to scenarios of microseismic monitoring using surface arrays, where the signal amplitudes are commonly at the same level as, or below, the noise amplitudes. To achieve this, we resort to the use of an imaging operator, which has previously been found to produce better results in detection and location of microseismic events from surface arrays. The operator in our method is formed by full-waveform elastodynamic Green's functions that are band-limited by a source time function and represented in the frequency domain. Where full-waveform Green's functions are not available, ray tracing can also be used to compute the required Green's functions. Additionally, we introduce the concept of the compressed inverse, which derives directly from the compression of the migration operator using a random matrix. The described methodology reduces processing time at a cost of introducing distortions into the results. However, the amount of distortion can be managed by controlling the level of compression applied to the operator. Numerical experiments using synthetic and real data demonstrate the reductions in processing time that can be achieved and exemplify the process of selecting the compression rate that produces a tolerable amount of distortion into the results.

Description: Microseismic monitoring is an essential tool for the characterization of hydraulic fractures. Fast estimation of the parameters that define a microseismic event is relevant to understand and control fracture development. The amount of data contained in the microseismic records however, poses a challenge for fast continuous detection and evaluation of the microseismic source parameters. Work inspired by the emerging field of Compressive Sensing has showed that it is possible to evaluate source parameters in a compressed domain, thereby reducing processing time. This technique performs well in scenarios where the amplitudes of the signal are above the noise level, as is often the case in microseismic monitoring using downhole tools. This paper extends the idea of the compressed domain processing to scenarios of microseismic monitoring using surface arrays, where the signal amplitudes are commonly at the same level as, or below, the noise amplitudes. To achieve this, we resort to the use of an imaging operator, which has previously been found to produce better results in detection and location of microseismic events from surface arrays. The operator in our method is formed by full-waveform elastodynamic Green's functions that are band-limited by a source time function and represented in the frequency domain. Where full-waveform Green's functions are not available, ray tracing can also be used to compute the required Green's functions. Additionally, we introduce the concept of the compressed inverse, which derives directly from the compression of the migration operator using a random matrix. The described methodology reduces processing time at a cost of introducing distortions into the results. However, the amount of distortion can be managed by controlling the level of compression applied to the operator. Numerical experiments using synthetic and real data demonstrate the reductions in processing time that can be achieved and exemplify the process of selecting the compression rate that produces a tolerable amount of distortion into the results.

Description: SUMMARY Simultaneous estimation of origin time, location and moment tensor of seismic events is critical for automatic, continuous, real-time monitoring systems. Recent studies have shown that such systems can be implemented via waveform fitting methods based on pre-computed catalogues of Green’s functions. However, limitations exist in the number and length of the recorded traces, and the size of the monitored volume that these methods can handle without compromising real-time response. This study presents numerical tests using a novel waveform fitting method based on compressive sensing, a field of applied mathematics that provides conditions for sampling and recovery of signals that admit a sparse representation under a known base or dictionary. Compressive sensing techniques enable us to determine source parameters in a compressed space, where the dimensions of the variables involved in the inversion are significantly reduced. Results using a hypothetical monitoring network with a dense number of recording stations show that a compressed catalogue of Green’s functions with 0.004 per cent of its original size recovers the exact source parameters in more than 50 per cent of the tests. The gains in processing time in this case drop from an estimated 90 days to browse a solution in the uncompressed catalogue to 41.57 s to obtain an estimation using the compressed catalogue. For simultaneous events, the compressive sensing approach does not appear to influence the estimation results beyond the limitations presented by the uncompressed case. The main concern in the use of compressive sensing is detectability issues observed when the amount of compression is beyond a minimum value that is identifiable through numerical experiments. Tests using real data from the 2002 June 18 Caborn Indiana earthquake show that the presence of noise and inaccurate Green’s functions require a smaller amount of compression to reproduce the solution obtained with the uncompressed catalogue. In this case, numerical simulation enables the assessment of the amount of compression that provides a reasonable rate of detectability. Overall, the numerical experiments demonstrate the effectiveness of our compressed domain inversion method in the real-time monitoring of seismic sources with dense networks of receivers. As an added benefit of the compression process, the size of the monitored volume can also be increased under specific restrictions while maintaining the real-time response.

Description: Time-domain elastic least-squares reverse time migration (LSRTM) can provide higher spatial resolution images with fewer artefacts and a superior balance of amplitudes than elastic reverse time migration (RTM). More important, it can mitigate the crosstalk between P- and S-wave images. In previously proposed elastic LSRTM algorithms, density is either assumed to be constant or known. In other words, the density perturbation is not part of the least-squares inversion formulation. Neglecting density in elastic LSRTM may lead to crosstalk artefacts in the P- and S-wave images. In this paper, we propose a time-domain three-parameter elastic LSRTM algorithm to simultaneously invert for density, P- and S-wave velocity perturbation images. We derive the elastic Born approximation and elastic RTM operators using the continuous adjoint-state method. We carefully discretize the two operators to assure that they pass the dot-product test. This allows us to use the conjugate gradient least-squares method to solve the least-squares migration problem. We evaluate the proposed algorithm on two synthetic examples. We show that our proposed three-parameter elastic LSRTM can suppress the multiparameter crosstalk among density, P- and S-wave velocity perturbation images. Moreover, including density image in the elastic LSRTM inversion can improve the convergence of the least-squares inversion.