• The Transactions of The Korean Institute of Electrical Engineers
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• v.67 no.7
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• pp.884-891
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• 2018

In this paper, we propose an automatic earthquake P-wave detection algorithm based on the variations of the impact momentum derived from the seismic acceleration signals. The amount of change in the impact momentum induced by the acceleration refers to the influence of buildings or facilities on the earthquake, The proposed algorithm can effectively detect the seismic P-wave by simultaneously considering the amplitude and the frequency change of the seismic wave when the earthquake occurs. Computer simulations using the observed seismic signals were performed to evaluate the validity of the induced impact momentum variation and the superiority of the proposed algorithm.

• The Transactions of The Korean Institute of Electrical Engineers
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• v.61 no.8
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• pp.1179-1185
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• 2012

This paper presents a new approach for the detection of seismic events using accumulated changes on time-frequency domain and variable threshold. To detect seismic P-wave arrivals with rapidness and accuracy, it is that the changes on the time and the frequency domains are simultaneously used. Their changes are parameters appropriated to reflect characteristics of earthquakes over moderate magnitude(${\geq}$ magnitude 4.0) and microearthquakes. In addition, adaptively controlled threshold values can prevent false P-wave detections due to low SNR. We tested our method on real earthquakes those have various magnitudes. The proposed algorithm gives a good detection performance and it is also comparable to STA/LTA algorithm in computational complexity. Computer simulation results shows that the proposed algorithm is superior to the conventional popular algorithm (STA/LTA) in the seismic P-wave detection.

• Geophysics and Geophysical Exploration
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• v.6 no.3
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• pp.138-142
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• 2003

Crosswell seismic data were acquired in three sections crossing a tunnel of 3 different types; one was empty, another was ailed by sand, and the other was filled by rock debris. Both the P- and S-wave first arrivals were picked and the traveltime tomography was conducted to generate the P- and S- wave velocity tomograms on the all three sections. Among six tomograms, only one tomogram shows a low velocity zone that can be interpreted as a tunnel image. The tomogram is the P wave velocity image of a section that crosses an empty tunnel. The result of numerical analysis for the spatial resolution of the traveltime tomography was consistent to this finding.

• Journal of the Society of Disaster Information
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• v.16 no.1
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• pp.133-143
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• 2020

Purpose: This study aims to derive a predictive empirical equation for PGV prediction from P-wave using earthquake records in Korea and to verify the reliability of Onsite EEW. Method: The noise of P wave is removed from the observations of 627 seismic events in Korea to derive an empirical equation with PGV on the base rock, and reliability of Onsite alarms is verified from comparing PGV's predictions and observations through simulation using the empirical equation. Result: P-waves were extracted using the Filter Picker from earthquake observation records that eliminated noises, a linear regression with PGV was used to derive a predictive empirical equation for Onsite EEW. Through the on-site warning simulation we could get a success rate of 80% within the MMI±1 error range above MMI IV or higher. Conclusion: Through this study, the design feasibility and performance of Onsite EEWS using domestic earthquake records were verified. In order to increase validity, additional medium-sized seismic observations from abroad are required, the mis-detection of P waves is controlled, and the effect of seismic amplification on the surface is required.

• Journal of the Korean Geosynthetics Society
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• v.18 no.4
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• pp.107-114
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• 2019

In this paper, the P-wave multiple detection system for the fast and accurate earthquake early warning nearby the epicenter was developed. The developed systems were installed in five selected public buildings for the validation. During the monitoring, a magnitude 2.3 earthquake occurred in Pohang on 26 September 2019. P-wave initial detection algorithms were operated in three out of four systems installed in Pohang area and recorded as seismic events. At the nearest station, 5.5 km from the epicenter, P-wave signal was detected 1.2 seconds after the earthquake, and S-wave was reached 1.02 seconds after the P-wave reached, providing some alarm time. The maximum accelerations recorded in three different stations were 6.28 gal, 6.1 gal, and 5.3 gal, respectively. The alarm algorithm did not work, due to the high threshold of the maximum ground acceleration (25.1 gal) to operate it. If continuous monitoring and analysis are to be carried out in the future, the developed system could use a highly effective earthquake warning system suitable for the domestic situation.

• Proceedings of the Earthquake Engineering Society of Korea Conference
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• 2006.03a
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• pp.64-69
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• 2006

At starting point, 1D velocity models were inverted by using 430 events with P-wave 5147, S-wave 3729 from KIGAM, KMA, KEPRI, and KINS's seismic networks. A minimum 1D model shows that P-wave velocities are around $6.0{\pm}0.5\;km/s$ slowly increasing with depth between surface and 15 km. The velocities are about $6.4{\pm}0.2\;km/s$ below 15km to 35km. The earthquake data number for 3D tomography was 630 adding to previous 430 events with limitation of more than 6 station detection and relocation stability of location. The checkerboard test shows that only upper curst part from surface to 17 km have reliable resolution. The results of upper crust part present that the boundary of Gyeong-sang basin and Youngnam massif is mach well velocity variation pattern. The western part of the basin is shown as lower velocity and south-eastern part as higher. This is because that sedimentary rocks are widely located around western part of the basin and volcanic origin rocks are distributed around south-eastern part.

• Geomechanics and Engineering
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• v.13 no.1
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• pp.99-117
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• 2017

Rock physics modeling of sandstone reservoir from gas fields of Krishna-Godavari basin represents the link between reservoir parameters and seismic properties. The rock physics diagnostic models such as contact cement, constant cement and friable sand are chosen to characterize reservoir sands of two wells in this basin. Cementation is affected by the grain sorting and cement coating on the surface of the grain. The models show that the reservoir sands in two wells under examination have varying cementation from 2 to more than 6%. Distinct and separate velocity-porosity and elastic moduli-porosity trends are observed for reservoir zones of two wells. A methodology is adopted for generation of Rock Physics Template (RPT) based on fluid replacement modeling for Raghavapuram Shale and Gollapalli Sandstones of Early Cretaceous. The ratio of P-wave velocity to S-wave velocity (Vp/Vs) and P-impedance template, generated for this above formations is able to detect shale, brine sand and gas sand with varying water saturation and porosity from wells in the Endamuru and Suryaraopeta gas fields having same shallow marine depositional characters. This RPT predicted detection of water and gas sands are matched well with conventional neutron-density cross plot analysis.

• Geophysics and Geophysical Exploration
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• v.12 no.1
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• pp.85-98
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• 2009

The tau-p inversion algorithm is widely employed to generate starting models with most computer programs, which implement refraction tomography. This algorithm emphasises the vertical resolution of many layers, and as a result, it frequently fails to detect even large lateral variations in seismic velocities, such as the decreases which are indicative of shear zones. This study demonstrates the failure of the tau-p inversion algorithm to detect or define a major shear zone which is 50m or 10 stations wide. Furthermore, the majority of refraction tomography programs parameterise the seismic velocities within each layer with vertical velocity gradients. By contrast, the Generalized Reciprocal Method (GRM) inversion algorithms emphasise the lateral resolution of individual layers. This study demonstrates the successful detection and definition of the 50m wide shear zone with the GRM inversion algorithms. The existence of the shear zone is confirmed by a 2D analysis of the head wave amplitudes and by numerous closely spaced orthogonal seismic profiles carried out as part of a later 3D refraction investigation. Furthermore, an analysis of the shot record amplitudes indicates that a reversal in the seismic velocities, rather than vertical velocity gradients, occurs in the weathered layers. The major conclusion reached in this study is that while all seismic refraction operations should aim to provide as accurate depth estimates as is practical, those which emphasise the lateral resolution of individual layers generate more useful results for geotechnical and environmental applications. The advantages of the improved lateral resolution are obtained with 2D traverses in which the structural features can be recognised from the magnitudes of the variations in the seismic velocities. Furthermore, the spatial patterns obtained with 3D investigations facilitate the recognition of structural features such as faults which do not display any intrinsic variation or 'signature' in seismic velocities.

• Geophysics and Geophysical Exploration
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• v.14 no.1
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• pp.42-49
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• 2011

To locate anomalous features including seepage pathways through the Daeryong earth-fill dam, P and Rayleigh waves were recorded along a 250-m profile on the crest of the dam. Seismic energy was generated using a 5-kg sledgehammer and detected by 24 4.5-Hz vertical-axis geophones installed at 3-m intervals. P-wave and apparent S-wave velocities of the reservoir dam and underlying bedrock were then inverted from first-arrival traveltimes and dispersion curves of Rayleigh waves, respectively. Apparent dynamic Poisson's ratios as high as 0.46 were obtained at the base of the dam near its north-east end, where an outlet conduit occurs, and in the clay core body near the south-west end of the profile where the dam was repeatedly grouted to abate seepage before our survey. These anomalies of higher Poisson's ratios in the upper part of clay core were also associated with effusion of grout on the downstream slope of the dam during post-survey grouting to abate leakage. Combining P-wave traveltime tomography and inversion of Rayleigh wave velocities was very effective in detecting potential pathways for seepage and previous grouted zones in this earthen dam.

• Geophysics and Geophysical Exploration
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• v.25 no.4
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• pp.177-188
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• 2022

Recently, the application of distributed acoustic sensors (DAS), which can replace geophones and seismometers, has significantly increased along with interest in micro-seismic monitoring technique, which is one of the CO₂ storage monitoring techniques. A significant amount of temporally and spatially continuous data is recorded in a DAS monitoring system, thereby necessitating fast and accurate data processing techniques. Because event detection and seismic phase picking are the most basic data processing techniques, they should be performed on all data. In this study, a machine learning-based P, S wave phase picking algorithm was developed to compensate for the limitations of conventional phase picking algorithms, and it was modified using a transfer learning technique for the application of DAS data consisting of a single component with a low signal-to-noise ratio. Our model was constructed by modifying the convolution-based EQTransformer, which performs well in phase picking, to the ResUNet structure. Not only the global earthquake dataset, STEAD but also the augmented dataset was used as training datasets to enhance the prediction performance on the unseen characteristics of the target dataset. The performance of the developed algorithm was verified using K-net and KiK-net data with characteristics different from the training data. Additionally, after modifying the trained model to suit DAS data using the transfer learning technique, the performance was verified by applying it to the DAS field data measured in the Pohang Janggi basin.