An official website of the United States government
Abstract By providing unrivaled resolution in both time and space, volcano seismicity helps to chronicle and interpret eruptions. Standard earthquake detection methods are often insufficient as the eruption itself produces continuous seismic waves that obscure earthquake signals. We address this problem by developing an earthquake processing workflow specific to a high‐noise volcanic environment and applying it to the explosive 2008 Okmok Volcano eruption. This process includes applying single‐channel template matching combined with machine‐learning and fingerprint‐based techniques to expand the existing earthquake catalog of the eruption. We detected an order of magnitude more earthquakes, then located, relocated, determined locally calibrated magnitudes, and classified the events in the enhanced catalog. This new high‐resolution earthquake catalog increases the number of observations by about a factor of 10 and enables the detailed spatiotemporal seismic analysis during a large eruption.
more »
« less
Array-Based Convolutional Neural Networks for Automatic Detection and 4D Localization of Earthquakes in Hawai‘i
Abstract The growing amount of seismic data necessitates efficient and effective methods to monitor earthquakes. Current methods are computationally expensive, ineffective under noisy environments, or labor intensive. We leverage advances in machine learning to propose an improved solution, ArrayConvNet—a convolutional neural network that uses continuous array data from a seismic network to seamlessly detect and localize events, without the intermediate steps of phase detection, association, travel-time calculation, and inversion. When testing this methodology with events at Hawai‘i, we achieve 99.4% accuracy and predict hypocenter locations within a few kilometers of the U.S. Geological Survey catalog. We demonstrate that training with relocated earthquakes reduces localization errors significantly. We outline several ways to improve the model, including enhanced data augmentation and use of relocated offshore earthquakes recorded by ocean-bottom seismometers. Application to continuous records shows that our algorithm detects 690% as many earthquakes as the published catalog, and 125% as many events than the Hawaiian Volcano Observatory internal catalog. Because of the enhanced detection sensitivity, localization granularity, and minimal computation costs, our solution is valuable, particularly for real-time earthquake monitoring.
more »
« less
- Award ID(s):
- 1949620
- PAR ID:
- 10397286
- Date Published:
- Journal Name:
- Seismological Research Letters
- Volume:
- 92
- Issue:
- 5
- ISSN:
- 0895-0695
- Page Range / eLocation ID:
- 2961 to 2971
- Format(s):
- Medium: X
- Sponsoring Org:
- National Science Foundation
More Like this
-
-
ABSTRACT Rapid association of seismic phases and event location are crucial for real‐time seismic monitoring. We propose a new method, named rapid earthquake association and location (REAL), for associating seismic phases and locating seismic events rapidly, simultaneously, and automatically. REAL combines the advantages of both pick‐based and waveform‐based detection and location methods. It associates arrivals of different seismic phases and locates seismic events primarily through counting the number of P and S picks and secondarily from travel‐time residuals. A group of picks are associated with a particular earthquake if there are enough picks within the theoretical travel‐time windows. The location is determined to be at the grid point with the most picks, and if multiple locations have the same maximum number of picks, the grid point among them with smallest travel‐time residuals. We refine seismic locations using a least‐squares location method (VELEST) and a high‐precision relative location method (hypoDD). REAL can be used for rapid seismic characterization due to its computational efficiency. As an example application, we apply REAL to earthquakes in the 2016 central Apennines, Italy, earthquake sequence occurring during a five‐day period in October 2016, midway in time between the two largest earthquakes. We associate and locate more than three times as many events (3341) as are in Italy's National Institute of Geophysics and Volcanology routine catalog (862). The spatial distribution of these relocated earthquakes shows a similar but more concentrated pattern relative to the cataloged events. Our study demonstrates that it is possible to characterize seismicity automatically and quickly using REAL and seismic picks.more » « less
-
Abstract We present the high-resolution Parkfield matched filter relocated earthquake (PKD-MR) catalog for the 2004 Mw 6 Parkfield earthquake sequence in central California. We use high-quality seismic data recorded by the borehole High Resolution Seismic Network combined with matched filter detection and relocations from cross-correlation derived differential travel times. We determine the magnitudes of newly detected events by computing the amplitude ratio between the detections and templates using a principal component fit. The relocated catalog spans from 6 November 2003 to 28 March 2005 and contains 13,914 earthquakes, which is about three times the number of events listed in the Northern California Seismic Network catalog. Our results on the seismicity rate changes before the 2004 mainshock do not show clear precursory signals, although we find an increase in the seismic activity in the creeping section of the San Andreas fault (SAF) (about ∼30 km northwest of the mainshock epicenter) in the weeks prior to the mainshock. We also observe a decrease in the b-value parameter in the Gutenberg–Richter relationship in the creeping section in the weeks prior to the mainshock. Our results suggest stress is increasingly released seismically in the creeping section, accompanied by a decreasing aseismic creeping rate before the mainshock occurrence. However, b-value and seismicity rates remain stable in the Parkfield section where the 2004 mainshock ruptured. This updated catalog can be used to study the evolution of aftershocks and their relations to afterslip following the 2004 Parkfield mainshock, seismicity before the mainshock, and how external stresses interact with the Parkfield section of the SAF and the 2004 sequence.more » « less
-
Abstract Seismicity during explosive volcanic eruptions remains challenging to observe through the eruptive noise, leaving first‐order questions unanswered. How do earthquake rates change as eruptions progress, and what is their relationship to the opening and closing of the eruptive vent? To address these questions for the Okmok Volcano 2008 explosive eruption, Volcano Explosivity Index 4, we utilized modern detection methods to enhance the existing earthquake catalog. Our enhanced catalog detected significantly more earthquakes than traditional methods. We located, relocated, determined magnitudes and classified all events within this catalog. Our analysis reveals distinct behaviors for long‐period (LP) and volcano‐tectonic (VT) earthquakes, providing insights into the opening and closing cycle. LP earthquakes occur as bursts beneath the eruptive vent and do not coincide in time with the plumes, indicating their relationship to an eruptive process that occurs at a high pressurization state, that is, partially closed conduit. In contrast, VT earthquakes maintain a steadier rate over a broader region, do not track the caldera deflation and have a largerb‐value during the eruption than before or after. The closing sequence is marked by a burst of LPs followed by small VTs south of the volcano. The opening sequence differs as only VTs extend to depth and migrate within minutes of the eruption onset. Our high‐resolution catalog offers valuable insights, demonstrating that volcanic conduits can transition between partially closed (clogged) and open (cracked) states during an eruption. Utilizing modern earthquake processing techniques enables clearer understanding of eruptions and holds promise for studying other volcanic events.more » « less
-
Abstract Template matching has proven to be an effective method for seismic event detection, but is biased toward identifying events similar to previously known events, and thus is ineffective at discovering events with non‐matching waveforms (e.g., those dissimilar to existing catalog events). In principle, this limitation can be overcome by cross‐correlating every segment (possible template) of a seismogram with every other segment to identify all similar event pairs, but doing so has been previously considered computationally infeasible for long time series. Here we describe a method, called the ‘Matrix Profile’ (MP), a “correlate everything with everything” calculation that can be efficiently and scalably computed. The MP returns the maximum value of the correlation coefficient of every sub‐window of continuous data with every other sub‐window, as well as the best‐correlated sub‐window location. Here we show how MP methods can obtain valuable results when applied to months and years of continuous seismic data in both local and global case studies. We find that the MP can identify many new events in Parkfield, California seismicity that are not contained in existing event catalogs and that it can efficiently find clusters of similar earthquakes in global seismic data. Either used by itself, or as a starting point for subsequent template matching calculations, the MP is likely to provide a useful new tool for seismology research.more » « less
- Free Publicly Accessible Full Text
-
Accepted Manuscript1.0
- Journal Article:
- https://doi.org/10.1785/0220200419
