Abstract: For more than two decades the Puerto Rico – Virgin Islands region has been monitored for crustal deformation using GPS geodesy. This objective was first done through a campaign style network that consisted of a dozen sites collecting one measurement annually during the nineties. Today, fifteen continuously operating GPS sites distributed throughout Puerto Rico and the Virgin Islands form the Puerto Rico Seismic Network (PRSN) GPS network. These sites provide data in two forms; 1Hz Real-time data available through an NTRIP Caster and 1Hz and 30sps BINEX archived files transferred from site to PRSN hourly and daily, respectively. Here we present data flow methods employed at PRSN to bring continuously operated GPS station data from the field back to PRSN, both in Real-time form and archived. This presentation seeks to encourage other GPS or GNSS networks in the Caribbean, particularly those hosting COCONet sites, to develop their own data acquisition methods based on the solutions that have been either adopted or developed at the PRSN. Empowering Caribbean networks to have control over their data is critical for capacity building and enables the region to develop scientifically as well as increase their education in matters of earthquake and tsunamis.
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Abstract: The inflation of the ground surface can indicate that magma ascends to shallower levels and that a volcano gets ready for an eruption. These changes can be observed by the use of stacks of SAR images and performing an interferometric time series analysis to obtain the value and rate of displacements. Furthermore, backscatter values analysis gives a complementary understanding of what is happening on the earth’s surface. We present InSAR time series analysis we have implemented to monitor the activities of the Ecuadorian volcanoes. SAR data are provided in the framework of the Group on Earth Observation’s Ecuadorian Volcano Geohazard Supersite. We use data from TerraSAR-X and Sentinel-1 and inverse modelling to better understand the mechanism and dynamic of these volcanoes. The InSAR data reveal uplift at three volcanoes, Pichincha, Cayambe and Chiles at rates of 2-3 cm/yr. The uplift at Pichincha is limited to the caldera area, indicating a shallow (< 1 km depth) source. The beginning of inflation coincides with the 2016 M7.8 earthquake, suggesting that it was triggered by the earthquake.
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Abstract: Demand on the development of non-invasive measurement methods for shallow S-wave velocity structure is increasing. Active and passive surface wave method will play important role in such measurements. Passive surface wave method or microtremor array measurements particularly receive large attention since the method can penetrate several hundreds to several kilometers easily. Applicability of microtremor array measurements to complex velocity structures with horizontal velocity change is the one of the issues to be figured out to apply the method to site investigations. We performed numerical simulation of microtremor array measurements at 2D and 3D structures using 3D finite-difference method to evaluate the effect complex structures on the analysis of microtremor array measurements. Two-layer models were used in the simulation. S-wave velocities of two layers are 200 and 400 m/s respectively. Depth to the boundary ranges 20 to 40 m. Receivers are deployed in a 100 x 100 m square. The size of the model is 550 x 550 x 150 m cube. Sources are randomly distributed outside of receiver array to simulate ambient noise field. Cell size is 1 m, time step is 0.25 ms and data length is 65 s. A 3D viscoelastic finite-difference method with 4th order velocity stress staggered grid scheme was used to calculate seismic wave field. Ten records are calculated with different source distribution. Ambient noise data were processed by common mid-point spatial auto correlation (CMPSPAC). SPACs were calculated all possible pairs and SPACs whose CMP belonged to the same bin were grouped. A dispersion curve was calculated for each bin and an 1D inversion was applied to each dispersion curve with horizontal constraint. The 1D velocity profiles were interpolated to a 3D velocity model. Obtained velocity were models generally consistent with true models and the simulation shows the applicability of the microtremor array measurements to complex velocity structures.
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Abstract: Seismic velocity models are becoming increasingly important due to their use in simulation, and other applications in seismology and engineering. We describe the development of a three-dimensional seismic velocity model for the Bengal basin, covering Bangladesh and the neighboring regions of India and Myanmar. The model encompasses an area of 760 x 780 km2. It is bordered by the stable Indian continent on the west and north-west, the Himalayas on the north and north-east, and the Burma plate on the east and south-east. The basin is shaped by the Ganges-Brahmaputra-Meghna delta—the largest delta system in the world—and rests over a sedimentary structure with thicknesses that can reach up to 20 km in depth. This is a region under high seismic hazard due to the collision between the Indian, Eurasian, and Burmese plates. The velocity model is developed based on available sedimentology and geological investigations. We collected and digitized information in the form of geological borehole logs; seismic, aeromagnetic and gravity profiles; and geologic mapping and contours developed from sedimentary deposition studies. Most of the borehole logs came from natural gas and other mineral exploration studies concentrated in the north-western and north-eastern regions. Aeromagnetic and gravity profiles were used to build contours of different sedimentary deposits and major velocity contrasts in the deep basin. The model is built as a computer code application interface (or API) designed to provide values of seismic velocities (Vp and Vs) and density. We have used the model to produce low frequency (<0.5 Hz) ground motion simulations of a few local earthquakes, and compared the results with available seismic data to test the model’s reliability. In the future, as we continue to make improvements, we expect to use the model in simulations of past and scenario earthquakes to gain insights about the region’s seismic hazard and the basin’s response.
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Abstract: We used an unsupervised cortical algorithm to detect in real time anomalies in simulated and real seismic signals. The algorithm works on-line receiving continuous seismic acceleration signals from a streaming station. This could be a software source that is simulating the data stream from a suitable algorithm, or could be data timeseries from a database of real seismic events. Our system is based on the Numenta HTM engine that implements a cortical algorithm based on an innovative neural model in which dendrites act as coincidence detectors and synapses are formed continuously. The HTM networks learns and adapts to the seismic background noises and it is able to notice anomalies in real time and without the necessity of supervision. This approach to seismic detection could be useful not only to recognize earthquakes and contribute to early warning networks, but also could be of importance for detecting variations of the background noises characteristics that are not detectable with conventional methods or by conventional machine learning methods. We will show tests that demonstrate the ability of the HTM algorithm to recognize efficiently simulated and real earthquake waves we will report on our tests on seismic noises of specific types. Our approach points forward the possibility of the use of HTM networks to recognize signals form different kinds of seismic sources and types.
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Abstract: The mechanism of intermediate-depth earthquakes occurring within subducting slabs remains controversial. Two proposed mechanisms for these earthquakes are dehydration embrittlement and thermal shear instability. By analyzing the stress drops and radiated energies determined from the recorded waveforms of these earthquakes, we can constrain the radiated efficiencies of the events and hence determine to what degree the mechanisms causing them are dissipative. We use the method of empirical Green’s functions (eGfs) and spectral ratios to obtain stress drops for moderate to large (M4.0 and greater) intermediate-depth earthquakes since 2006 in the Kyushu and Hokkaido regions of Japan using data from the Hi-Net, F-Net, and Kiban seismic networks. With events at intermediate depth, the quality of small events usable as eGfs is a major limiting factor of the spectral ratio method. We examine the robustness of stress drop estimates determined from different source models, varying falloff rate and number of corner frequencies to better constrain the uncertainty in these estimates. We also look at the effects of near-source heterogeneities on the eGf waveforms, as in practice the data for intermediate-depth earthquakes often does not allow us to select smaller events within one source radius of the larger event. We are able to constrain the source parameters for the larger events, and can place bounds on them for the smaller events. The two loci of intermediate-depth earthquake activity differ in the character of the subducting plate, in that the Kyushu events occur in a plate that is younger and warmer. While we find generally larger stress drops and lower radiated efficiencies than shallow events in both regions, the difference is not as marked as has been found in previous studies of regions with anomalously high intermediate-depth activity, such as the Bucaramanga Nest in Colombia.
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