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Register a new userRobust and high-resolution seismic complex trace analysis
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M. Kazemnia Kakhki
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Seismic attributes calculated by conventional methods are susceptible to noise. Conventional filtering reduces the noise in the cost of losing the spectral bandwidth. The challenge of having a high-resolution and robust signal processing tool motivated us to propose a sparse time-frequency decomposition while is stabilized for random noise. The procedure initiates by using Sparsity-based adaptive S-transform to regularize abrupt variations in frequency content of the nonstationary signals. Then, considering the fact that a higher amplitude of a frequency component results in a higher signal to noise ratio, an adaptive filter is applied to the time-frequency spectrum which is sparcified previously. The proposed zero adaptive filter enhances the high amplitude frequency components while suppresses the lower ones. The performance of the proposed method is compared to the sparse S-transform and the robust window Hilbert transform in estimation of instantaneous attributes by applying on synthetic and real data sets. Seismic attributes estimated by the proposed method is superior to the conventional ones in terms of its robustness and high resolution image. The proposed approach has a vast application in interpretation and identification of geological structures.
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Inspired by recent work on extended image volumes that lays the ground for randomized probing of extremely large seismic wavefield matrices, we present a memory frugal and computationally efficient inversion methodology that uses techniques from randomized linear algebra. By means of a carefully selected realistic synthetic example, we demonstrate that we are capable of achieving competitive inversion results at a fraction of the memory cost of conventional full-waveform inversion with limited computational overhead. By exchanging memory for negligible computational overhead, we open with the presented technology the door towards the use of low-memory accelerators such as GPUs.
We base our study on the statistical analysis of the Rigan earthquake 2010 December 20, which consists of estimating the earthquake network by means of virtual seismometer technique, and also considering the avalanche-type dynamics on top of this complex network.The virtual seismometer complex network shows power-law degree distribution with the exponent $gamma=2.3pm 0.2$. Our findings show that the seismic activity is strongly intermittent, and have a textit{cyclic shape} as is seen in the natural situations, which is main finding of this study. The branching ratio inside and between avalanches reveal that the system is at (or more precisely close to) the critical point with power-law behavior for the distribution function of the size and the mass and the duration of the avalanches, and with some scaling relations between these quantities. The critical exponent of the size of avalanches is $tau_S=1.45pm 0.02$. We find a considerable correlation between the dynamical Green function and the nodes centralities.
The Campi Flegrei caldera (southern Italy) is one of the most hazardous volcanic systems on Earth, having produced >60 eruptions in the past 15 ka. The caldera remains active and its potential for future eruptions is high, posing a danger to the dense population living nearby. Despite this, our understanding of pre-eruptive processes and the architecture of the sub-volcanic system are poorly constrained. Here, we combine established petrological techniques, geothermobarometric evaluation, and high resolution trace element crystal mapping, to present a multifaceted, coherent reconstruction of the complex pre eruptive dynamics and eruption timescales of Astroni volcano located in the eastern sector of Campi Flegrei caldera. The Astroni volcano is an important case study for investigating plumbing system processes and dynamics at Campi Flegrei caldera because it produced the most recent (ca. 4 ka ago) Plinian eruption within the caldera (Astroni 6); current long-term forecasting studies postulate that a similar sized event in this location is a probable future scenario. Geothermobarometric results indicate interaction between an evolved, shallow magma chamber, and a less evolved, deeper pocket of magma, in agreement with previous studies focused on the Astroni 6 eruption products. In addition, a range of textural and trace element zoning patterns point to a complex evolution of both magmas prior to their subsequent interaction. High resolution trace element crystal maps reveal discrete zonations in compatible elements. These zonations, combined with knowledge of Kfeldspar growth rates, highlight a recharge event in the shallow plumbing system a few hours to days before the Astroni 6 eruption.
Crack microgeometries pose a paramount influence on effective elastic characteristics and sonic responses. Geophysical exploration based on seismic methods are widely used to assess and understand the presence of fractures. Numerical simulation as a promising way for this issue, still faces some challenges. With the rapid development of computers and computational techniques, discrete-based numerical approaches with desirable properties have been increasingly developed, but have not yet extensively applied to seismic response simulation for complex fractured media. For this purpose, we apply the coupled LSM-DFN model (Liu and Fu, 2020b) to examining the validity in emulating elastic wave propagation and scattering in naturally-fractured media. By comparing to the theoretical values, the implement of the schema is validated with input parameters optimization. Moreover, dynamic elastic moduli from seismic responses are calculated and compared with static ones from quasi-static loading of uniaxial compression tests. Numerical results are consistent with the tendency of theoretical predictions and available experimental data. It shows the potential for reproducing the seismic responses in complex fractured media and quantitatively investigating the correlations and differences between static and dynamic elastic moduli.
Holm (ASR, 2018) claims that Scafetta (ASR 57, 2121-2135, 2016) is irreproducible because I would have left undocumented the values of two parameters (a reduced-rank index p and a regularization term) that he claimed to be requested in the Magnitude Squared Coherence Canonical Correlation Analysis (MSC-CCA). Yet, my analysis did not require such two parameters. In fact: 1) using the MSC-CCA reduced-rank option neither changes the result nor was needed since Scafetta (2016) statistically evaluated the significance of the coherence spectral peaks; 2) the analysis algorithm neither contains nor needed the regularization term. Herein, I show that Holm could not replicate Scafetta (2016) because he used different analysis algorithms. In fact, although Holm claimed to be using MSC-CCA, for his figures 2-4 he used a MatLab code labeled gcs_cca_1D.m (see paragraph 2 of his Section 3), which Holm also modified, that implements a different methodology known as the Generalized Coherence Spectrum using the Canonical Correlation Analysis (GCS-CCA). This code is herein demonstrated to be unreliable under specific statistical circumstances such as those required to replicate Scafetta (2016). On the contrary, the MSC-CCA method is stable and reliable. Moreover, Holm could not replicate my result also in his figure 5 because there he used the basic Welch MSC algorithm by erroneously equating it to MSC-CCA. Herein I clarify step-by-step how to proceed with the correct analysis, and I fully confirm the 95% significance of my results. I add data and codes to easily replicate my results.
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