Related papers: Towards Global Earthquake Early Warning with the M…
I study a recently proposed statistical model of earthquake dynamics that incorporates aging as a fundamental ingredient. The model is known to generate earthquake sequences that quantitatively reproduce the spatial and temporal clustering…
Earthquake network captures the complexity of seismicity in a peculiar manner. Given a seismic data, the procedure of constructing an earthquake network proposed in [S. Abe, N, Suzuki, Europhys. Lett. 65 (2004) 581] contains as a single…
Microseismic event detection and location are two primary components in microseismic monitoring, which offers us invaluable insights into the subsurface during reservoir stimulation and evolution. Conventional approaches for event detection…
Bayesian neural networks (BNN) are the probabilistic model that combines the strengths of both neural network (NN) and stochastic processes. As a result, BNN can combat overfitting and perform well in applications where data is limited.…
Deep learning-based models, such as convolutional neural networks, have advanced various segments of computer vision. However, this technology is rarely applied to seismic shot gather noise localization problem. This letter presents an…
Deep learning is fast emerging as a potential disruptive tool to tackle longstanding research problems across the sciences. Notwithstanding its success across disciplines, the recent trend of the overuse of deep learning is concerning to…
We provide a general model for Brownian motions on metric graphs with interactions. In a general setting, for (sticky) Brownian propagations on edges, our model provides a characterization of lifetimes and holding times on vertices in terms…
We use wireless voice-call and text-message volumes to quantify spatiotemporal communication patterns in the New York Metro area before, during, and after the Virginia earthquake and Hurricane Irene in 2011. The earthquake produces an…
Smartphones sensors are now commonly used by a worldwide audience thanks to their availability, high connectivity, and versatility. Here, we present a methodology to use a collection of smartphones, namely a fleet, as a distributed network…
The dragon-king earthquake hypothesis proposes that some very large to great earthquakes are not merely the extreme end of the frequency-magnitude Gutenberg-Richter distribution (FMD), but are generated by distinct physical mechanisms,…
In this paper, we investigate how to network smartphones for providing communications in disaster recovery. By bridging the gaps among different kinds of wireless networks, we have designed and implemented a system called TeamPhone, which…
Tectonic earthquakes of high magnitude can cause considerable losses in terms of human lives, economic and infrastructure, among others. According to an evaluation published by the U.S. Geological Survey, 30 is the number of earthquakes…
In this study, we evaluated the performance of SAIPy, an open-source Python package for deep learning-based seismic data analysis, by applying its single-station monitoring tools and extending its use to a seismic network based approach,…
Seismic phase picking, which aims to determine the arrival time of P- and S-waves according to seismic waveforms, is fundamental to earthquake monitoring. Generally, manual phase picking is trustworthy, but with the increasing number of…
This paper introduces EQSA, an interactive exploratory tool for earthquake situational analytics using social media. EQSA is designed to support users to characterize the condition across the area around the earthquake zone, regarding…
In volcano monitoring, effective recognition of seismic events is essential for understanding volcanic activity and raising timely warning alerts. Traditional methods rely on manual analysis, which can be subjective and labor-intensive.…
One of the risks of large-scale geologic carbon sequestration is the potential migration of fluids out of the storage formations. Accurate and fast detection of this fluids migration is not only important but also challenging, due to the…
Accurately predicting the dynamic responses of building structures under seismic loads is essential for ensuring structural safety and minimizing potential damage. This critical aspect of structural analysis allows engineers to evaluate how…
With fiber-optic seismic acquisition development, continuous dense seismic monitoring is becoming increasingly more accessible. Repurposing fiber cables in telecommunication conduits makes it possible to run seismic studies at low cost,…
In meteorology, engineering and computer sciences, data assimilation is routinely employed as the optimal way to combine noisy observations with prior model information for obtaining better estimates of a state, and thus better forecasts,…