Seismic evidence of a link between subducted oceanic faults and volcanism: A case study from South Central Chile

The south-central Chilean subduction zone was investigated at 39-40°S by a passive seismic experiment. The investigation area comprises the maximum slip of the great 1960 Mw 9.5 Valdivia earthquake. The incoming Nazca plate is permeated by a number of major fault zones including the Valdivia fault zone and the Mocha fault zone which seem to have behaved as a barriers for the rupture propagation of large earthquakes in the past. The investigated sector is also home to the Villarrica volcano - one of South America’s most active volcanoes. In the extension of the Valdiva fault zone we observed a cluster of increased seismicity in the subducting plate at depths between 80 km and 120 km, where dehydration of the subducting plate occurs. The focal plane solutions of this cluster show predominantly strike-slip motion. Tomographic images show decreased P- and S-velocity and increased ratio between the seismic cluster and the volcanic center of Villarrica, Quetrupillán and Lanin, corresponding to an increased content of fluids or melt. Additional geochemical investigations show that the magma of Villarrica volcano has an enhanced fluid signal compared to the other volcanoes of the Southern Volcanic Zone of Chile. It can be assumed that the Valdivia fault zone serves as the source for the fluids. Before the plate subducts, water can penetrate the plate through faults within the Valdivia fault zone. Serpentinization would build the water into minerals. Inside the subduction zone the Valdiva fault zone is reactivated by dehydration reactions at a depth of about 100 km. The released fluids rise towards the volcanic center causing the tomographic anomalies. At the end this leads to an increased degree of melting and a higher activity of Villarrica volcano

Seismic tomography of the area of the 2010 Beni-Ilmane earthquake sequence, north-central Algeria

The region of Beni-Ilmane (District of M’sila, north-central Algeria) was the site of an earthquake sequence that started on 14 May 2010. This sequence, which lasted several months, was triggered by conjugate E–W reverse and N–S dextral faulting. To image the crustal structure of these active faults, we used a set of 1406 well located aftershocks events and applied the local tomography software (LOTOS) algorithm, which includes absolute source location, optimization of the initial 1D velocity model, and iterative tomographic inversion for 3D seismic P- and S-wave velocities (and the Vp/Vs ratio), and source parameters. The patterns of P-wave low-velocity anomalies correspond to the alignments of faults determined from geological evidence, and the P-wave high-velocity anomalies may represent rigid blocks of the upper crust that are not deformed by regional stresses. The S-wave low-velocity anomalies coincide with the aftershock area, where relatively high values of Vp/Vs ratio (1.78) are observed compared with values in the surrounding areas (1.62–1.66). These high values may indicate high fluid contents in the aftershock area. These fluids could have been released from deeper levels by fault movements during earthquakes and migrated rapidly upwards. This hypothesis is supported by vertical sections across the study area show that the major Vp/Vs anomalies are located above the seismicity clusters

Creating realistic models based on combined forward modeling and tomographic inversion of seismic profiling data

Amplitudes and shapes of seismic patterns derived from tomographic images often are strongly biased with respect to real structures in the earth. In particular, tomography usually provides continuous velocity distributions, whereas major velocity changes in the earth often occur on first-order interfaces. We propose an approach that constructs a realistic structure of the earth that combines forward modeling and tomographic inversion (FM&TI). Using available a priori information, we first construct a synthetic model with realistic patterns. Then we compute synthetic times and invert them using the same tomographic code and the same parameters as in the case of observed data processing. We compare the reconstruction result with the tomographicimage of observed data inversion. If a discrepancy is observed, we correct the synthetic model and repeat the FM&TI process. After several trials, we obtain similar results of synthetic and observed data inversion. In this case, the derived synthetic model adequately represents the real structure of the earth. In a working scheme of this approach, we three authors used two different synthetic models with a realistic setup. One of us created models, but the other two performed the reconstruction with no knowledge of the models. We discovered that the synthetic models derived by FM&TI were closer to the true model than the tomographic inversion result. Our reconstruction results from modeling marine data acquired in the Musicians Seamount Province in the Pacific Ocean indicate the capacity and limitations of FM&TI

Finding a realistic velocity distribution based on iterating forward modelling and tomographic inversion

Tomography is like a photograph that was taken by a camera with blurred and defective lenses that deform the shapes and colours of objects. Reporting quantitative parameters derived from tomographic inversion is not always adequate because tomographic results are often strongly biased. To quantify the results of tomographic inversion, we propose a forward modelling and tomographic inversion (FM&TI) approach that aims to find a more realistic solution than conventional tomographic inversion. The FM&TI scheme is based on the assumption that if two tomograms derived from the inversion of observed and synthetic data are identical, the synthetic structure may appear to be closer to the real unknown structure in the ground than the inversion result. However, the manual design of the synthetic velocity distribution is usually time-consuming and ambiguous. In this study, we propose an approach that automatically searches for a probabilistic model. In this approach, a synthetic model is iteratively updated while taking into account the bias of the model in previous stages of the FM&TI performance. Here, we present an example of synthetic modelling and real data processing for an active source refraction data set corresponding to a marine profile across the subduction zone in Chile at about 32°S latitude. A key feature of the model is a low-velocity channel above the subducted oceanic crust, which was defined in the synthetic model and expected in the real case. The conventional first arrival traveltime tomography was barely able to resolve this channel. However, after several iterations of the FM&TI modelling, we succeeded in reconstructing this channel clearly. In the paper, we briefly discuss the nature of this low-velocity subduction channel, and we compare the results with other studies

The feeder system of the Toba supervolcano from the slab to the shallow reservoir

The Toba Caldera has been the site of several large explosive eruptions in the recent geological past, including the world’s largest Pleistocene eruption 74,000 years ago. The major cause of this particular behaviour may be the subduction of the fluid-rich Investigator Fracture Zone directly beneath the continental crust of Sumatra and possible tear of the slab. Here we show a new seismic tomography model, which clearly reveals a complex multilevel plumbing system beneath Toba. Large amounts of volatiles originate in the subducting slab at a depth of ∼150 km, migrate upward and cause active melting in the mantle wedge. The volatile-rich basic magmas accumulate at the base of the crust in a ∼50,000 km3 reservoir. The overheated volatiles continue ascending through the crust and cause melting of the upper crust rocks. This leads to the formation of a shallow crustal reservoir that is directly responsible for the supereruptions

Multi-station volcano tectonic earthquake monitoring based on transfer learning

Introduction: Developing reliable seismic catalogs for volcanoes is essential for investigating underlying volcanic structures. However, owing to the complexity and heterogeneity of volcanic environments, seismic signals are strongly affected by seismic attenuation, which modifies the seismic waveforms and their spectral content observed at different seismic stations. As a consequence, the ability to properly discriminate incoming information is compromised. To address this issue, multi-station operational frameworks that allow unequivocal real-time management of large volumes of volcano seismic data are needed.Methods: In this study, we developed a multi-station volcano tectonic earthquake monitoring approach based on transfer learning techniques. We applied two machine learning systems—a recurrent neural network based on long short-term memory cells (RNN–LSTM) and a temporal convolutional network (TCN)—both trained with a master dataset and catalogue belonging to Deception Island volcano (Antarctica), as blind-recognizers to a new volcanic environment (Mount Bezymianny, Kamchatka; 6 months of data collected from June to December 2017, including periods of quiescence and eruption).Results and discussion: When the systems were re-trained under a multi correlation-based approach (i.e., only seismic traces detected at the same time at different seismic stations were selected), the performances of the systems improved substantially. We found that the RNN-based system offered the most reliable recognition by excluding low confidence detections for seismic traces (i.e., those that were only partially similar to those of the baseline). In contrast, the TCN-based network was capable of detecting a greater number of events; however, many of those events were only partially similar to the master events of the baseline. Together, these two approaches offer complementary tools for volcano monitoring. Moreover, we found that our approach had a number of advantages over the classical short time average over long time-average (STA/LTA) algorithm. In particular, the systems automatically detect VTs in a seismic trace without searching for optimal parameter settings, which makes it a portable, scalable, and economical tool with relatively low computational cost. Moreover, besides obtaining a preliminary seismic catalog, it offers information on the confidence of the detected events. Finally, our approach provides a useful tentative label for subsequent analysis carried out by a human operator. Ultimately, this study contributes a new framework for rapid and easy volcano monitoring based on temporal changes in monitored seismic signals