• 한국신재생에너지학회:학술대회논문집
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• 2005.06a
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• pp.638-642
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• 2005

For gas hydrate exploration, long offset multichannel seismic data acquired using by the 4km streamer length in Ulleung basin of the East Sea. The dataset was processed to define the BSRs (Bottom Simulating Reflectors) and to estimate the amount of gas hydrates. Confirmation of the presence of Bottom Simulating reflectors (BSR) and investigation of its physical properties from seismic section are important for gas hydrate detection. Specially, faster interval velocity overlying slower interval velocity indicates the likely presences of gas hydrate above BSR and free gas underneath BSR. In consequence, estimation of correct interval velocities and analysis of their spatial variations are critical processes for gas hydrate detection using seismic reflection data. Using Dix's equation, Root Mean Square (RMS) velocities can be converted into interval velocities. However, it is not a proper way to investigate interval velocities above and below BSR considering the fact that RMS velocities have poor resolution and correctness and the assumption that interval velocities increase along the depth. Therefore, we incorporated Migration Velocity Analysis (MVA) software produced by Landmark CO. to estimate correct interval velocities in detail. MVA is a process to yield velocities of sediments between layers using Common Mid Point (CMP) gathered seismic data. The CMP gathered data for MVA should be produced after basic processing steps to enhance the signal to noise ratio of the first reflections. Prestack depth migrated section is produced using interval velocities and interval velocities are key parameters governing qualities of prestack depth migration section. Correctness of interval velocities can be examined by the presence of Residual Move Out (RMO) on CMP gathered data. If there is no RMO, peaks of primary reflection events are flat in horizontal direction for all offsets of Common Reflection Point (CRP) gathers and it proves that prestack depth migration is done with correct velocity field. Used method in this study, Tomographic inversion needs two initial input data. One is the dataset obtained from the results of preprocessing by removing multiples and noise and stacked partially. The other is the depth domain velocity model build by smoothing and editing the interval velocity converted from RMS velocity. After the three times iteration of tomography inversion, Optimum interval velocity field can be fixed. The conclusion of this study as follow, the final Interval velocity around the BSR decreased to 1400 m/s from 2500 m/s abruptly. BSR is showed about 200m depth under the seabottom

• KIPS Transactions on Software and Data Engineering
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• v.4 no.5
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• pp.219-224
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• 2015

In this paper, the designed fish robots DOMI ver1.0 is researched and development for aquarium underwater robot. The presented fish robot consists of the head, 1'st stage body, 2nd stage body and tail, which is connected two point driving joints. The model of the robot fish is analysis to maximize the momentum of the robot fish and the body of the robot is designed through the analysis of the biological fish swimming. Also, Lighthill was applied to the kinematics analysis of robot fish swimming algorithms, we are applied to the approximate method of the streamer model that utilizes techniques mimic the biological fish. The swimming robot has two operating mode such as manual and autonomous operation modes. In manual mode the fish robot is operated to using the RF transceiver, and in autonomous mode the robot is controlled by microprocessor board that is consist PSD sensor for the object recognition and avoidance. In order to the submerged and emerged, the robot has the bladder device in a head portion. The robot gravity center weight is transferred to a one-axis sliding and it is possible to the submerged and emerged of DOMI robot by the breath unit. It was verified by the performance test of this design robot DOMI ver1.0. It was confirmed that excellent performance, such as driving force, durability and water resistance through the underwater field test.

• The Korean Journal of Petroleum Geology
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• v.11 no.1 s.12
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• pp.9-17
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• 2005

In the main target area of the block II, Targe-scale faults occur below the unconformity developed around 1 km in depth. The contrast of seismic velocity around the unconformity is generally so large that the strong multiples and the radical velocity variation would deteriorate the quality of migrated section due to serious distortion. More than 15 kinds of data processing techniques have been applied to improve the image resolution for the structures farmed from this active crustal activity. The bad and noisy traces were edited on the common shot gathers in the first step to get rid of acquisition problems which could take place from unfavorable conditions such as climatic change during data acquisition. Correction of amplitude attenuation caused from spherical divergence and inelastic attenuation has been also applied. Mild F/K filter was used to attenuate coherent noise such as guided waves and side scatters. Predictive deconvolution has been applied before stacking to remove peg-leg multiples and water reverberations. The velocity analysis process was conducted at every 2 km interval to analyze migration velocity, and it was iterated to get the high fidelity image. The strum noise caused from streamer was completely removed by applying predictive deconvolution in time space and ${\tau}-P$ domain. Residual multiples caused from thin layer or water bottom were eliminated through parabolic radon transform demultiple process. The migration using curved ray Kirchhoff-style algorithm has been applied to stack data. The velocity obtained after several iteration approach for MVA (migration velocity analysis) was used instead or DMO for the migration velocity. Using various testing methods, optimum seismic processing parameter can be obtained for structural and stratigraphic interpretation in the Block II, Yellow Sea Basin.

• Geophysics and Geophysical Exploration
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• v.20 no.1
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• pp.43-48
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• 2017

The applicability of refraction survey has been tested using a wave glider widely used in long-term ocean observations around the world. To record seismic refractions, a single channel streamer with metal weight and a seismic recording system were mounted on the wave glider. We used GPS precise time synchronization signal and radio frequency (RF) communication to synchronize shot and recorder triggers and to control acquired data quality in real time. When the wave glider is positioned close to the set point, a 2,000 J sparker is exploded along the designed track at 2 second intervals. Through the test survey, we were able to successfully acquire refractions from the subsurface.

• Geophysics and Geophysical Exploration
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• v.2 no.2
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• pp.77-85
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• 1999

The 3-D seismic research vessel, Tamhae II, was built to raise up the probability of the hydrocarbon discovery in the Korean continental shelf and the first test survey was completed in the East Sea. During the survey, the 240 channel 2-D marine seismic data were acquired by the Korean flag vessel for the first time. Tamhae II has been equipped with source, receiver, recording equipment, and navigation equipment as well as an onboard processing system. The source is composed of four subarrays and each subarray has six airguns. Total airgun volume is 4578 $in^3$. The receiver consists of two sets of 3 km long 240 channel streamer. In the first survey, the successful acquisition of 2-D seismic data was accomplished. From the result of the data processing, we confirmed that the high quality seismic data were acquired. For the high quality data acquisition, technology of survey design and planning, operation of vessel and equipments and systematic quality control should be developed.

• International Journal of Oral Biology
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• v.33 no.4
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• pp.179-186
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• 2008

Several lines of evidence suggest that osteocytes play a critical role in bone remodeling. Both healthy and apoptotic osteocytes can send signals to other bone surface cells such as osteoblasts, osteoclasts, osteoclast precursors, and bone lining cells through canalicular networks. Osteocytes responding to mechanical strain may also send signals to other cells. To determine the role for osteocytes an mechanical strain in bone remodeling, we examined the effects of fluid flow shear stress on osteoclast precursor cell and osteoblast proliferation and recruitment induced by osteocytes. In addition, the effects of fluid flow shear stress on osteocyte M-CSF, RANKL, and OPG mRNA expression were also examined. MLO-Y4 cells were used as an in vitro model for osteocytes, RAW 264.7 cells and MOCP-5 cells as osteoclast precursors, and 2T3 cells as osteoblasts. MLO-Y4 cells conditioned medium (Y4-CM) was collected after 24h culture. For fluid flow experiments, MLO-Y4 cells were exposed to 2h of pulsatile fluid flow (PFF) at 2, 4, 8, $16{\pm}0.6\;dynes/cm^2$ using the Flexcell $Streamer^{TM}$ system. For proliferation assays, MOCP-5, RAW 264.7, and 2T3 cells were cultured with control media or 10-100% Y4 CM. Cells were cultured for 3d, and then cells were counted. RAW 264.7 and 2T3 cell migration was assayed using transwells with control media or 10-100% Y4-CM. M-CSF, RANKL and OPG in MLO-Y4 mRNA expression was determined by semiquantitative RT-PCR. Y4-CM increased osteoclast precursor proliferation and migration, but decreased 2T3 cell proliferation and migration. CM from MLO-Y4 cells exposed to PFF caused decreased RAW 267.4 cell proliferation and migration and 2T3 migration compared to control Y4-CM. However, Y4-CM from cells exposed to PFF had no effect on 2T3 osteoblastic cell proliferation. PFF decreased RNAKL mRNA and increased OPG mRNA in MLO-Y4 cells compared to control(without PFF). PFF had no effect on M-CSF mRNA expression in MLO-Y4 cells. These results suggest that osteocytes can regulate bone remodeling by communication with osteoclast precursors and osteoblasts and that osteocytes can communicate mechanical signals to other cells.

• Proceedings of the Korean Vacuum Society Conference
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• 2010.08a
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• pp.125-126
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• 2010

플라즈마 아킹은 PECVD, 플라즈마 식각 그리고 토카막과 같은 플라즈마를 이용하는 여러 공정과 연구 분야에서 문제점을 야기시켜왔다. 하지만, 이에 대한 연구는 아킹 현상의 불규칙성과 과도적인 행동으로 인해 미비한 상태이다. 특히, RF 방전에서의 아킹 연구는 DC 방전에서의 아킹 연구에 비해 많이 부족한 것이 현실이다. 플라즈마 아킹은 집단전자방출(collective electron emission)에 의한 스파크 방전(spark discharge)현상이다. 집단전자방출은 전계방출(field emission)이나 플라즈마와 쉬스를 두고 인접한 표면위에서의 유전분극(dielec emission)에 의해 발생한다. 이렇게 방출된 집단 전자들은 쉬스에서 가속되어 에너지를 얻게 되고 원자와의 충돌로 전자 아발란체를 일으킨다. 이렇게 배가된 전자들은 아킹 스트리머(arcing streamer)를 형성하게 되고 아킹 발생 시 높은 전류와 공정 실패의 원인이 된다. 우리는 $30cm{\times}20cm$ 크기의 사각 전극을 위 아래로 가진 챔버에서 Ar 가스를 RF(13.56 MHz)파워를 이용해 방전시켰다. 방전 전압과 전류는 파워 전극 압단에서 High voltage probe (Tektronix P6015A)와 Current probe (TCPA300 + TCP312)를 이용해 측정했다. 플라즈마 아킹시 변하는 플라즈마 플로팅 포텐셜은 챔버 중앙에 위치한 랑뮈프 프로브에 의해 측정되고 챔버 옆의 뷰포트 앞에 위치한 PM-tube를 이용해 아킹시 변하는 광량을 측정한다. RF 방전에서의 플라즈마 아킹은 아킹시 플로팅 포텐셜의 변화에 의해 크게 세부분으로 나눌 수 있다. 아킹 발생과 동시에 급격히 감소하는 감소부분 (약 2us) 그리고 감소한 포텐셜이 유지되는 유지부분 (약 0~10ms) 그리고 감소했던 포텐셜이 서서히 원래 상태로 회복되는 회복부분(약 100 us)이다. 아킹 초기시 방출된 집단 전자들과 원자들간의 충돌에 의해 형성된 아킹 스트리머는 플라즈마 전체를 단락시키게 되고 이로 인해 플로팅 포텐셜은 급격히 감소하게 된다. 이렇게 감소한 플로팅 포텐셜은 아킹 스트리머가 유지되는 한 계속 감소한 상태를 유지하게 된다. 그리고 플라즈마를 섭동했던 아킹 스트리머가 중단되면 플라즈마는 섭동전의 원래 상태로 돌아가려 하기 때문에 플로팅 포텐셜은 서서히 증가하면서 원래 상태로 회복된다. 플라즈마 아킹 발생시 생성되는 아킹 스트리머는 순간적으로 많은 전자들을 국소적으로 생성하게 되고 이 전자들에 의해 광량이 순간적으로 증가하게 된다. PM-tube (750.4 nm)에 의해 측정된 아킹시 광량은 정상방전 상태의 두배 가량이 된다. 그리고 이 순간적으로 증가된 광량은 시간이 지남에 따라 감소하게 되고 정상방전 일때의 광량이 된다. 광량이 증가한 후 정상방전 상태의 광량에 이르는 부분은 플로팅 포텐셜이 감소한 상태에서 유지되는 부분과 일치하고 이는 플로팅 포텐셜의 유지부분동안 아킹 스트리머가 발생하고 있다는 간접적인 증거가 된다. 그리고 정상 방전 상태 일때의 광량이 되면 아킹 스트리머가 중단되었다는 것이므로 그 시점부터 플로팅 포텐셜은 정산 방전상태 일 때의 포텐셜로 복구되기 시작한다. 이처럼 PM-tube를 이용한 아킹 광량 측정은 아킹 스트리머를 간접적으로 측정하게 하고 아킹 스트리머를 이용해 아킹시의 플로팅 포텐셜의 변화를 설명하게 해 준다. 응용적인 측면에서 아킹 광량 측정을 이용한 아킹 판독은 방전 전류와 방전 전압과 같은 전기적 신호를 이용한 아킹 판독에 비해 여러가지 장점을 가진다. 우선, 전기적 신호를 이용한 아킹 판독처럼 매칭 회로나 플라즈마를 섭동시키지 않는다. 그리고 원하는 부분의 아킹만을 판독하는 것도 가능하며 photo-diode를 이용할 경우 전기적 신호를 이용하는 것에 비해 경제적으로 유리하다.

• Geophysics and Geophysical Exploration
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• v.23 no.1
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• pp.38-49
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• 2020

Full-waveform inversion (FWI) is an optimization process of fitting observed and modeled data to reconstruct high-resolution subsurface physical models. In acoustic FWI (AFWI), pressure data acquired using a marine streamer has mainly been used to reconstruct the subsurface P-wave velocity models. With recent advances in marine seismic-acquisition techniques, acquiring multi-component data in marine environments have become increasingly common. Thus, AFWI strategies must be developed to effectively use marine multi-component data. Herein, we proposed an AFWI strategy using horizontal and vertical particle-acceleration data. By analyzing the modeled acoustic data and conducting sensitivity kernel analysis, we first investigated the characteristics of each data component using AFWI. Common-shot gathers show that direct, diving, and reflection waves appearing in the pressure data are separated in each component of the particle-acceleration data. Sensitivity kernel analyses show that the horizontal particle-acceleration wavefields typically contribute to the recovery of the long-wavelength structures in the shallow part of the model, and the vertical particle-acceleration wavefields are generally required to reconstruct long- and short-wavelength structures in the deep parts and over the whole area of a given model. Finally, we present a sequential-inversion strategy for using the particle-acceleration wavefields. We believe that this approach can be used to reconstruct a reasonable P-wave velocity model, even when the pressure data is not available.

• Fire Science and Engineering
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• v.33 no.2
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• pp.30-38
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• 2019

Tracking, which is one of the main causes of electrical fires, is perceived as a physical phenomenon of electrical discharge. Hence tracking should be explained based on electric field analysis, conduction path by electron generation, and gas discharge physics. However, few papers have considered these details. This paper proposes a tracking mechanism including their effects on tracking progress. In order to prove this mechanism, a tracking experiment, an electric field analysis for the carbonization evolution model, and an explanation of the tracking process by gas discharge physics were conducted. From the tracking experiment, the current waveforms were measured at each stage of the tracking progress from corona discharge to tracking breakdown. The electric field analysis was carried out in order to determine the electric field on the surface of a dry-band and the high electric field region for electron generation during the generation and progress of carbonization. In this paper, the proposed tracking mechanism consisted of six stages including electron avalanche by corona discharge, accumulation of positive ions, expansion of electron avalanche, secondary electron emission avalanche, streamer, and tracking by conductive path. The pulse current waveforms measured in the tracking experiment can be explained by the proposed tracking mechanism. The results of this study will be used as the technical data to detect tracking phenomenon, which is the cause of electric fire, and to improve the proof tracking index.

• Geophysics and Geophysical Exploration
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• v.26 no.2
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• pp.84-93
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• 2023

The supervised learning-based deep-learning seismic inversion techniques have demonstrated successful performance in synthetic data examples targeting small-scale areas. The supervised learning-based deep-learning seismic inversion uses time-domain wavefields as input and subsurface velocity models as output. Because the time-domain wavefields contain various types of wave information, the data size is considerably large. Therefore, research applying supervised learning-based deep-learning seismic inversion trained with a significant amount of field-scale data has not yet been conducted. In this study, we predict subsurface velocity models using Laplace-domain wavefields as input instead of time-domain wavefields to apply a supervised learning-based deep-learning seismic inversion technique to field-scale data. Using Laplace-domain wavefields instead of time-domain wavefields significantly reduces the size of the input data, thereby accelerating the neural network training, although the resolution of the results is reduced. Additionally, a large grid interval can be used to efficiently predict the velocity model of the field data size, and the results obtained can be used as the initial model for subsequent inversions. The neural network is trained using only synthetic data by generating a massive synthetic velocity model and Laplace-domain wavefields of the same size as the field-scale data. In addition, we adopt a towed-streamer acquisition geometry to simulate a marine seismic survey. Testing the trained network on numerical examples using the test data and a benchmark model yielded appropriate background velocity models.