• Geophysics and Geophysical Exploration
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• v.2 no.4
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• pp.184-190
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• 1999

A study of gas hydrate is a worldwide popular interesting subject as a potential energy source. A seismic survey for gas hydrate have performed over the East sea by the KIGAM since 1997. General indicators of natural submarine gas hydrates in seismic data is commonly inferred from the BSR (Bottom Simulating Reflection) that occurred parallel to the see floor, amplitude decrease at the top of the BSR, amplitude Blanking at the bottom of the BSR, decrease of the interval velocity, and the reflection phase reversal at the BSR. So the seismic data processing for detecting gas hydrates indicators is required the true amplitude recovery processing, a accurate velocity analysis and the AVO (Amplitude Variation with Offset) analysis. In this paper, we had processed the field data to detect the gas hydrate indicators, which had been acquired over the East sea in 1998. Applied processing modules are spherical divergence, band pass filtering, CDP sorting and accurate velocity analysis. The AVO analysis was excluded, since this field data had too short offset to apply the AVO analysis. The accurate velocity analysis was performed by XVA (X-window based Velocity Analysis). This is the method which calculate the velocity spectrum by iterative and interactive. With XVA, we could determine accurate stacking velocity. Geobit 2.9.5 developed by the KIGAM was used for processing data. Processing results say that the BSR occurred parallel to the sea floor were shown at $367\~477m$ depths (two way travel time about 1800 ms) from the sea floor through shot point 1650-1900, the interval velocity decrease around BSR and the reflection phase reversal corresponding to the reflection at the sea floor.

• Geophysics and Geophysical Exploration
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• v.25 no.1
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• pp.1-13
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• 2022

For surveying shallow gas reservoirs in the Pohang basin, we proposed a seismic exploration method applicable to the transition zone in which land and marine areas are connected. We designed the seismic acquisition geometry considering both environments. We installed land nodal receivers on the ground and employed vibroseis and airgun sources in both land and marine areas. For seismic exploration in the transition zone, specific acquisition and processing techniques are required to ensure precise matching of reflectors at the boundary between the onshore and offshore regions. To enhance the continuity of reflection events on the seismic section, we performed amplitude and phase corrections with respect to the source types and applied a static correction. Following these processing steps, we obtained a seismic section showing connected reflectors around the boundary in the transition zone. We anticipate that our proposed seismic exploration method can also be used for fault detection in the transition zone.

• 한국지구물리탐사학회:학술대회논문집
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• 1999.08a
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• pp.176-201
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• 1999

Principles, data acquisition, data processing of four frequently used borehole seismic methods, i.e., downhole seismic, vertical seismic profiling(VSP), crosshole seismic, and seismic tomography, are reviewed briefly. Field data examples are presented and their application to civil engineering area was also discussed.

• Geophysics and Geophysical Exploration
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• v.5 no.3
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• pp.145-149
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• 2002

The static correction, which is classified into refraction based static correction and reflection based residual static correction, removes distortions caused by irregularities of thickness or velocity in near-surface. Generally, refraction statics is a time consuming process because of high dependence on the interpreter's analysis. Therefore, for huge 3D seismic data, automatic static correction which minimizes the interpreter's analysis is required. In this research, we introduce an efficient method of refraction static correction for land 3D seismic survey.

• Geophysics and Geophysical Exploration
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• v.26 no.3
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• pp.103-113
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• 2023

In the oil and gas exploration market, various cableless seismic systems have been developed as an alternative to improve data acquisition efficiency. However, developing such equipment at a small scale for academic research is not available owing to highly priced commercial products. Fortunately, building and experimenting with open-source hardware enable the academic utilization of cableless seismic equipment with relatively low cost. This study aims to develop a cableless seismic acquisition module using Arduino. A cableless seismic system requires the combination of signal sensing, simple pre-processing, and data storage in a single device. A conventional geophone is used as the sensor that detects the seismic wave signal. In addition, it is connected to an Arduino circuit that plays a role in implementing the processing and storing module for the detected signals. Three main functions are implemented in the Arduino module: preprocessing, A/D conversion, and data storage. The developed single-channel module can acquire a common receiver gather from multiple source experiments.

• Geophysics and Geophysical Exploration
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• v.23 no.3
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• pp.192-207
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• 2020

We acquire seismic data with regularly or irregularly missing traces, due to economic, environmental, and mechanical problems. Since these missing data adversely affect the results of seismic data processing and analysis, we need to reconstruct the missing data before subsequent processing. However, there are economic and temporal burdens to conducting further exploration and reconstructing missing parts. Many researchers have been studying interpolation methods to accurately reconstruct missing data. Recently, various machine learning technologies such as support vector regression, autoencoder, U-Net, ResNet, and generative adversarial network (GAN) have been applied in seismic data interpolation. In this study, by reviewing these studies, we found that not only neural network models, but also support vector regression models that have relatively simple structures can interpolate missing parts of seismic data effectively. We expect that future research can improve the interpolation performance of these machine learning models by using open-source field data, data augmentation, transfer learning, and regularization based on conventional interpolation technologies.

• Geophysics and Geophysical Exploration
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• v.23 no.1
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• pp.13-21
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• 2020

The acquisition and processing of long-offset data are essential for imaging deep geological structures in marine seismic surveys. It is challenging to derive an accurate subsurface image by employing conventional data processing to long-offset data owing to the normal moveout (NMO) stretch and non-hyperbolic moveout phenomena induced by seismic anisotropy. In 2017, the Korea Institute of Geoscience and Mineral Resources conducted a simultaneous two-dimensional multichannel streamer and ocean-bottom seismic survey using a 5.7-km streamer and an ocean-bottom seismometer to identify the deep geological structure of the Ulleung Basin. Herein, the actual geological subsurface structure was obtained via the sequential iterative updating of the velocity and anisotropic parameters of the long-offset data obtained using a multichannel streamer, and anisotropic prestack Kirchhoff migration was performed using the updated velocity and anisotropic parameters as input parameters. As a result, the reflection energy in the long-offset traces, which showed non-hyperbolic moveout owing to seismic anisotropy, was well aligned horizontally and NMO stretches were also reduced. Thus, a more precise and accurate migrated image was obtained, minimizing the distortion of reflectors and mispositioned reflection energy.

• Geophysics and Geophysical Exploration
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• v.21 no.3
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• pp.183-197
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• 2018

In the delineation of geological structures using seismic exploration, it is very important to improve resolution of seismic data as well as accurate velocity model building and subsurface imaging. The resolution of seismic data can be enhanced by employing high-frequency energy sources or by applying deconvolution techniques in data processing. In marine seismic exploration, however, the main reason for degradation of resolution is the loss of specific frequency components due to ghosts. If we remove the ghosts, we can obtain broadband seismic data by avoiding frequency loss, and thus providing high-resolution subsurface images. Although ghosts can be properly filtered out in the data processing step, more effective broadband seismic technologies have been developing through the evolution of seismic instruments and the innovation of survey design. Overseas exploration companies developed brand-new configurations of receivers such as over/under streamer and variable-depth streamer, or ghost removal techniques using dual-sensor streamer to serve high-resolution imaging technologies. Unfortunately, neither broadband seismic instrument nor processing technique has been studied in Korea. In this paper, we introduce fundamental theories and current status of broadband seismic technologies to assist domestic researchers to study those technologies.

• Geophysics and Geophysical Exploration
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• v.21 no.3
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• pp.171-182
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• 2018

We performed the seismic field data processing using an open-source software (Madagascar) to verify if it is applicable to processing of field data, which has low signal-to-noise ratio and high uncertainties in velocities. The Madagascar, based on Python, is usually supposed to be better in the development of processing technologies due to its capabilities of multidimensional data analysis and reproducibility. However, this open-source software has not been widely used so far for field data processing because of complicated interfaces and data structure system. To verify the effectiveness of the Madagascar software on field data, we applied it to a typical seismic data processing flow including data loading, geometry build-up, F-K filter, predictive deconvolution, velocity analysis, normal moveout correction, stack, and migration. The field data for the test were acquired in Gunsan Basin, Yellow Sea using a streamer consisting of 480 channels and 4 arrays of air-guns. The results at all processing step are compared with those processed with Landmark's ProMAX (SeisSpace R5000) which is a commercial processing software. Madagascar shows relatively high efficiencies in data IO and management as well as reproducibility. Additionally, it shows quick and exact calculations in some automated procedures such as stacking velocity analysis. There were no remarkable differences in the results after applying the signal enhancement flows of both software. For the deeper part of the substructure image, however, the commercial software shows better results than the open-source software. This is simply because the commercial software has various flows for de-multiple and provides interactive processing environments for delicate processing works compared to Madagascar. Considering that many researchers around the world are developing various data processing algorithms for Madagascar, we can expect that the open-source software such as Madagascar can be widely used for commercial-level processing with the strength of expandability, cost effectiveness and reproducibility.

• The Korean Journal of Petroleum Geology
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• v.1 no.1 s.1
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• pp.29-35
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• 1993

Seismic reflection data can be used to extract information about the velocity structure of the earth. This process is called a velocity inversion of the seismic data. However, it is difficult to recover a broad band reflection coefficient series because the frequency band of seismic trace is limited. The linear programming method has been examined to find the simplest velocity model that has frequency components consistent with the usable frequencies of the seismic trace and interval velocity data. The velocity structure of the earth is displayed in pseudovelocity section. After the linear program had been tested with a synthetic seismic trace, it was applied to the seismic reflection data of the Block Ⅱ in the Yellow Sea. By comparing the pseudovelocity section with sonic logs obtained from the well in the same area, it was possible to define the lithostratigraphy and the boundaries of Cretaceous volcanics and Cretaceous metavolcanics.