DrumCorr program for selecting volcanic earthquake multiplets based on cross-correlation analysis

The DrumCorr program based on cross-correlation detection has been developed to identify multiplets of the volcanic earthquakes. The program is implemented in Python 3 and reads ASCII and MiniSEED seismic data formats. The article presents the algorithm of the program, describing the cross-correlation detector and an example of subsequent processing of seismic data. The program was applied to volcanic earthquakes of the «drumbeats» seismic regime and allowed to identify earthquake multiplets characterized by various wave forms. The article presents the algorithm of the program, describing the cross-correlation detector, the features of the weak volcanic earthquakes selection by the STA/LTA method. And the primary analysis of the values of the correlation coefficients with the calculation of their standard errors depending on different signal-to-noise ratios.

Determination of Hypocenter Using Geiger Method in Sinabung Volcano, April-July 2016 Period

Sinabung is a volcano located in the Karo Highlands, Karo District, North Sumatra, Indonesia, with the highest peak of 2460 meters mean sea level. Volcanic earthquake is an earthquake that occurs due to volcanic activity. This is caused by the movement of magma upwards in the volcano. This study aims to determine the type of earthquake, hypocenter position and epicenter of volcanic earthquakes in Sinabung volcano in April-July 2016. The principle of this study was carried out by analyzing volcanic earthquake data in Sinabung volcano in April-July 2016. The data is recorded data (seismogram) or in other words is secondary data from Sinabung volcano on 7 seismometer stations namely Sukanalu, Lau Kawar, Sigarang-Garang, Mardinding, Gamber, Sibayak, and Kebayaken stations. Earthquake data in April-July 2016 revealed that there were 24 earthquake events in a period of 3 months which were the results of picking up the P and S waves, where volcanic earthquakes were obtained only in the form of volcanic earthquake type A and type B volcanic earthquake. Sinabung volcano has an earthquake activity that high enough so that the status of Sinabung volcano is still at level III (standby) status. Based on the hypocenter of several VA and VB earthquakes that occurred in April-July 2016, it can be concluded that the distribution of the hypocenter of the volcanic earthquake shows that the maximum depth of the volcanic earthquake is 10.000 meters and the position of the earthquake is spread at the point between Sinabung volcano and Mount Sibayak.

Fluid migrations and volcanic earthquakes from depolarized ambient noise

Ambient noise polarizes inside low-velocity fault zones, yet the spatial and temporal resolution of polarized noise on gas-bearing fluids migrating through stressed volcanic systems is unknown. Pressurized fluids increase stress and lead to volcanic earthquakes; imaging their location in real time would be a giant leap toward forecasting eruptions and monitoring volcanic unrest. Here, we show that depolarized noise detects fluid injections and migrations leading to earthquakes inside the laterally-stressed hydrothermal systems of Campi Flegrei caldera (Southern Italy). A polarized transfer structure connects the deforming centre of the caldera to open hydrothermal vents and extensional caldera-bounding faults during periods of low seismic release. Fluids depolarize the transfer structure and pressurize the hydrothermal system, building up stress before earthquakes and migrating after seismic sequences. During sequences, fluid migration pathways connect the location of the last eruption (Monte Nuovo, 1538AD) with the part of the eastern caldera trapped between transfer and extensional structures. After recent intense seismicity (December 2019-April 2020), the transfer structure appears sealed while fluids stored in the east caldera have moved further east. Depolarized noise has the potential to monitor fluid migrations and earthquakes at stressed volcanoes quasi-instantaneously and with minimum processing.

Source location of volcanic earthquakes and subsurface characterization using fiber-optic cable and distributed acoustic sensing system

We present one of the first studies on source location determination for volcanic earthquakes and characterization of volcanic subsurfaces using data from a distributed acoustic sensing (DAS) system. Using the arrival time difference estimated from well-correlated waveforms and a dense spatial distribution of seismic amplitudes recorded along the fiber-optic cable, we determine the hypocenters of volcanic earthquakes recorded at Azuma volcano, Japan. The sources are located at a shallow depth beneath active volcanic areas with a range of approximately 1 km. Spatial distribution of the site amplification factors determined from coda waves of regional tectonic earthquakes are well correlated with old lava flow distributions and volcano topography. Since DAS observation can be performed remotely and buried fiber-optic cables are not damaged by volcanic ash or bombs during eruptions, this new observation system is suitable for monitoring of volcanoes without risk of system damage and for evaluating volcanic structures.

Determination of Mount Merapi Volcanic Earthquake Hypocentre By Using Seismic Wave Polarization Analysis

Volcanic earthquakes of mount Merapi have been investigated periodically. The investigation aims to determine the hypocenter and epicenter of mount Merapi's volcanic earthquake using wave polarization analysis. The analysis was carried out in three domains, which are the time domain, the frequency domain, and the space domain. The analysis in the time domain was conducted by the arrival time of the volcanic earthquake, and the analysis in the frequency domain was done by observing the spectrum to get information on source frequency and bandwidth passed from polarization analysis, while the analysis in the space domain was conducted especially on hypocenter determination of the volcanic earthquakes. The analysis leads to the frequency of source 6 Hz and a bandwidth of 0.1 Hz. Thus, the hypocenter of volcanic earthquakes by polarization analysis was distributed to depth from 670 m to 3250 m from Merapi's top

PENENTUAN HIPOSENTER DAN EPISENTER GEMPA VOLKANIK GUNUNG MERAPI DENGAN HIPO9

ABSTRAKTelah dilakukan penelitian terhadap gempa volkanik gunung Merapi. Penelitian ini bertujuan menentukan hiposenter dan episenter gempa volkanik gunung Merapi dengan HIPO9. Analisis dilakukan dalam dua kawasan, yaitu kawasan waktu dan kawasan frekuensi. Dalam kawasan waktu ditentukan waktu tiba gempa volkanik. Dalam kawasan frekuensi diperoleh informasi tentang frekuensi sumber dan lebar pita frekuensi yang akan diloloskan. Hasil analisis mendapatkan frekuensi sumber 6 Hz dan lebar pita frekuensi 0,1 Hz. Hasil pengeplotan dengan HIPO9, episenter gempa volkanik cenderung mengumpul di sekitar puncak gunung merapi, dengan hiposenter gempa volkanik terdistribusi pada kedalaman 1200 m sampai 1300 m. Kata kunci : hiposenter; episenter; gunung Merapi; HIPO9; gempa volkanik. ABSTRACTVolcanic earthquakes of mount Merapi have been investigated. The aim of the investigation to determine the hypocenter and epicenter of the volcanic earthquake of mount Merapi by HIPO9. The analysis was carried out in two domains, the time domain and the frequency domain. The analysis in the time domain was conducted by the arrival time of volcanic earthquake. The analysis in the frequency domain was done by observing spectrum to get information on frequency of source and frequency band width passed from polarization. The analysis lead to frequency of source 6 Hz and band width of 0,1 Hz. The results of plotting with HIPO9, the epicenter of volcanic earthquakes tend to gather around the top of Mount Merapi, with the hypocenter of the volcanic earthquake distributed at a depth of 1200 m to 1300 m. Keywords: hypocenter; epicenter; mount Merapi; HIPO9; volcanic earthquake.

Integrated Study on Forecasting Volcanic Hazards of Sakurajima Volcano, Japan

Several types of eruptions have occurred at Sakurajima volcano in the past 100 years. The eruption in 1914 was of a Plinian type followed by an effusion of lava. The progression of seismicity of volcanic earthquakes prior to the eruption is reexamined and seismic energy is estimated to be an order of 1014 J. Lava also effused from the Showa crater in 1946. Since 1955, eruptions frequently have occurred at the Minamidake or Showa craters at the summit area. Vulcanian eruptions are a well-known type of summit eruption of Sakurajima, however Strombolian type eruptions and continuous ash emissions have also occurred at the Minamidake crater. The occurrence rate of pyroclastic flows significantly increased during the eruptivity of Showa crater, with the occurrence of lava fountains. Tilt and strain observations are reliable tools to forecast the eruptions, and their combination with the seismicity of volcanic earthquakes is applicable to forecasting the occurrence of pyroclastic flows. An empirical event branch logic based on magma intrusion rate is proposed to forecast the scale and type of eruption. Forecasting the scale of an eruption and real-time estimations of the discharge rate of volcanic ash allows us to assess ash fall deposition around the volcano. Volcanic ash estimation is confirmed by an integrated monitoring system of X Band Multi-Parameter radars, lidar and the Global Navigation Satellite System to detect volcanic ash particles with different wave lengths. Evaluation of the imminence of eruptions and forecasting of their scale are used for the improvement of planning and drilling of volcanic disaster measures.