• Title/Summary/Keyword: Seismic Data Processing

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1D Wavelet Filtering for Groundroll Suppression in Land Seismic-Reflection Data

  • Sa, Jin-Hyeon;Lee, Jae-Eun;Kim, Sung-Soo;Kim, Ji-Soo
    • The Journal of Engineering Geology
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    • v.27 no.4
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    • pp.513-518
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    • 2017
  • Groundroll is a coherent noise showing dispersive behavior in land seismic-reflection records and its rejection has been a stubborn problem in data processing because they severely degrade the continuities and resolution of reflection signals. Conventional processing schemes of attenuating noises are the kind of frequency filtering (i.e., bandpass and f-k) that uses the Fourier transform (FT) along the entire trace in the time domain. To suppress them in this study, 1D wavelet filtering (WT) that can control time-varying frequency properties is tested and performed in the land-based synthetic and field seismic data. The results are compared to the ones from conventional filtering techniques in terms of continuities and resolution of reflection events. This filtering technique enhanced the reflection events by effectively eliminating the dispersive groundroll and random noises with control of time-scale function on wavelet domain.

Characteristics of local events occured in and around the Korean Peninsula in 2002 (한반도 일원에서 발생한 Event 특성)

  • 전정수;제일영;지헌철;박윤경
    • Proceedings of the Earthquake Engineering Society of Korea Conference
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    • 2003.03a
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    • pp.12-15
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    • 2003
  • Korea Institute of Geoscience and Mineral Resources(KIGAM) is operating Wonju Korea Seismic Research Station(KSRS), 29 regional seismic research stations and 5 Korea-China joint seismic stations in China. Also KIGAM is operating Korea Earthquake Monitoring System (KEMS) to archive the real-time data stream and to determine event parameters (epicenter, origin time, and magnitude) by the automatic processing and analyst review. To do this, KEMS used KIGAM's regional seismic network and other institute's network in a near real-time base. From Dec. 1, 2001 to Nov. 30, 2002, 3,827 seismic events were analyzed in a automatic processing procedure and finally 3,437 events were analyzed by analyst and archived. But problem is this event catalog includes not only natural earthquake, but also artificial events produced by the blast. More than 80 % events were concentrated in daytime and many events were concentrated in the confirmed blast sites, Pyeongyang, Pocheon, Yeongjong-do, Donghae city, etc. Because these artificial events are a major potential cause of error when estimating the seismicity of a specific region, discrimination procedure has to be developed in the first place.

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Seismic Research Network in KIGAM (한국자원연구소 지진 네트워크)

  • 이희일
    • Proceedings of the Earthquake Engineering Society of Korea Conference
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    • 2000.10a
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    • pp.49-56
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    • 2000
  • Instrumental observation of earth quakes in KIGAM was first attempted in the earty 1980`s by using 6 portable seismographs in the vicinity of Yang-San Faults. Now twenty-four permanent stations, which are equipped with short-period or broad-band seismometer, are included in seismic research network in KIGAM, including KSRS array station in Wonju which is consisted of 26 bore-hole stations. The seismic network of KIGAM is also linked to that of KEPRI(Korea Electric Power Research Institute)which is consisted of eight stations installed within and around the nuclear power plants. Owing to real-time data acquisition by telemetry, it became feasible to automatically locate hypocenters of the local events within fifteen minutes by computer data processing system, named KEMS(Korea Earthquake Monitoring System). Results of the hypocenter determination, together with observational data, are compiled and stored in the data base system. And they are published via web site whose URL is http://quake.kigam.re.kr KIGAM is also running t재 permanent geomagnetic stations installed in Daejun and Kyungju. The observed geomagnetic data are transmitted to Earthquake Research Centre in KIGAM by seismic network and compiled for the purpose of earthquake prediction research and other basic geophysical research.

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SUPPRESSION OF SWELL EFFECT IN HIGH-RESOLUTION MARINE SEISMIC DATA USING CROSS-CORRELATION SCHEME (상호상관기법을 이용한 고분해능 천부해저탄성파탐사 자료에서의 너울효과 제거)

  • Kim,Jong-Cheon;Lee,Ho-Yeong;Kim,Ji-Su;Gang,Dong-Hyo
    • Journal of the Korean Geophysical Society
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    • v.6 no.1
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    • pp.31-38
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    • 2003
  • Multi-channel seismic survey, which has been mainly employed in oil prospecting, is carried out as a high resolution shallow marine seismic exploration. Fault drop as small as 1 m can be resolved by employing high-resolution seismic survey. Similar to the effect of shallow inhomogenities in the land seismic data, due to occurrence of swell quite often higher than 1 m, shallow marine seismic data tend to be severely degraded. Suppression of such a swell effect is critical in processing of steps of marine seismic shallow high-resolution data. Compared to the moving average depth method, a newly developed method using cross-correlation technique is found out to be very effective in increasing the resolution of the shallow reflection events by accuratly elucidating the depth of sea bottom.

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Comparison of Seismic Data Interpolation Performance using U-Net and cWGAN (U-Net과 cWGAN을 이용한 탄성파 탐사 자료 보간 성능 평가)

  • Yu, Jiyun;Yoon, Daeung
    • Geophysics and Geophysical Exploration
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    • v.25 no.3
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    • pp.140-161
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    • 2022
  • Seismic data with missing traces are often obtained regularly or irregularly due to environmental and economic constraints in their acquisition. Accordingly, seismic data interpolation is an essential step in seismic data processing. Recently, research activity on machine learning-based seismic data interpolation has been flourishing. In particular, convolutional neural network (CNN) and generative adversarial network (GAN), which are widely used algorithms for super-resolution problem solving in the image processing field, are also used for seismic data interpolation. In this study, CNN-based algorithm, U-Net and GAN-based algorithm, and conditional Wasserstein GAN (cWGAN) were used as seismic data interpolation methods. The results and performances of the methods were evaluated thoroughly to find an optimal interpolation method, which reconstructs with high accuracy missing seismic data. The work process for model training and performance evaluation was divided into two cases (i.e., Cases I and II). In Case I, we trained the model using only the regularly sampled data with 50% missing traces. We evaluated the model performance by applying the trained model to a total of six different test datasets, which consisted of a combination of regular, irregular, and sampling ratios. In Case II, six different models were generated using the training datasets sampled in the same way as the six test datasets. The models were applied to the same test datasets used in Case I to compare the results. We found that cWGAN showed better prediction performance than U-Net with higher PSNR and SSIM. However, cWGAN generated additional noise to the prediction results; thus, an ensemble technique was performed to remove the noise and improve the accuracy. The cWGAN ensemble model removed successfully the noise and showed improved PSNR and SSIM compared with existing individual models.

A Review of Seismic Full Waveform Inversion Based on Deep Learning (딥러닝 기반 탄성파 전파형 역산 연구 개관)

  • Sukjoon, Pyun;Yunhui, Park
    • Geophysics and Geophysical Exploration
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    • v.25 no.4
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    • pp.227-241
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    • 2022
  • Full waveform inversion (FWI) in the field of seismic data processing is an inversion technique that is used to estimate the velocity model of the subsurface for oil and gas exploration. Recently, deep learning (DL) technology has been increasingly used for seismic data processing, and its combination with FWI has attracted remarkable research efforts. For example, DL-based data processing techniques have been utilized for preprocessing input data for FWI, enabling the direct implementation of FWI through DL technology. DL-based FWI can be divided into the following methods: pure data-based, physics-based neural network, encoder-decoder, reparameterized FWI, and physics-informed neural network. In this review, we describe the theory and characteristics of the methods by systematizing them in the order of advancements. In the early days of DL-based FWI, the DL model predicted the velocity model by preparing a large training data set to adopt faithfully the basic principles of data science and apply a pure data-based prediction model. The current research trend is to supplement the shortcomings of the pure data-based approach using the loss function consisting of seismic data or physical information from the wave equation itself in deep neural networks. Based on these developments, DL-based FWI has evolved to not require a large amount of learning data, alleviating the cycle-skipping problem, which is an intrinsic limitation of FWI, and reducing computation times dramatically. The value of DL-based FWI is expected to increase continually in the processing of seismic data.

High-resolution shallow marine seismic survey using an air gun and 6 channel streamer (에어건과 6채널 스트리머를 이용한 고해상 천부 해저 탄성파탐사)

  • Lee Ho-Young;Park Keun-Pil;Koo Nam-Hyung;Park Young-Soo;Kim Young-Gun;Seo Gab-Seok;Kang Dong-Hyo;Hwang Kyu-Duk;Kim Jong-Chon
    • 한국지구물리탐사학회:학술대회논문집
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    • 2002.09a
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    • pp.24-45
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    • 2002
  • For the last several decades, high-resolution shallow marine seismic technique has been used for various resources, engineering and geological surveys. Even though the multichannel method is powerful to image subsurface structures, single channel analog survey has been more frequently employed in shallow water exploration, because it is more expedient and economical. To improve the quality of the high-resolution seismic data economically, we acquired digital seismic data using a small air gun, 6 channel streamer and PC-based system, performed data processing and produced high-resolution seismic sections. For many years, such test acquisitions were performed with other studies which have different purposes in the area of off Pohang, Yellow Sea and Gyeonggi-bay. Basic data processing was applied to the acquired data and the processing sequence included gain recovery, deconvolution, filtering, normal moveout, static corrections, CMP gathering and stacking. Examples of digitally processed sections were shown and compared with analog sections. Digital seismic sections have a much higher resolution after data processing. The results of acquisition and processing show that the high-resolution shallow marine seismic surveys using a small air gun, 6 channel streamer and PC-based system may be an effective way to image shallow subsurface structures precisely.

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Seismic Data Processing Suited for Stratigraphic Interpretation in the Domi Basin, South Sea, Korea (남해 대륙붕 도미분지 탄성파자료의 층서해석을 고려한 전산처리)

  • Cheong, Snons;Kim, Won-Sik;Koo, Nam-Hyung;Lee, Ho-Young;Shin, Won-Chul;Park, Keun-Pil
    • Economic and Environmental Geology
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    • v.43 no.6
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    • pp.603-613
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    • 2010
  • The Domi Basin in the South Sea of Korea is located between the Jeju Basin and Ulleung Basins, and is characterized by several sediment sags that are interested to have formed by crustal extension. This paper aims to derive an optimized seismic data processing procedure which helps stratigraphic interpretation of the Domi Basin. In particular, our data processing flow incorporated horizon velocity analysis (HVA) and surface-relative wave equation multiple rejection (SRWEMR) to improve the quality of stack section by enhancing the continuity of reflection events and suppressing peg-leg multiples respectively. As a result of processing procedures in this study, unconformities were recognized in the stack section that defines the early and middle Miocene, Eocene-Oligocene sequences. In addition, the overall quality of the stack section was increased as essential data to investigate the evolution of the basin. The suppression of multiple resulted in the identification of the Cretaceous basement. The data processing scheme evaluated through this study is expected to improve the standardization of processing sequences for seismic data from the Domi and adjacent Sora and north-Sora Basins.

Seismic Traveltime Tomography in Inhomogeneous Anisotropic Media (불균질 이방성 매질에서의 탄성파 주시 토모그래피)

  • Jeong, Chang-Ho;Suh, Jung-Hee
    • 한국지구물리탐사학회:학술대회논문집
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    • 2007.06a
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    • pp.209-214
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    • 2007
  • In Korean geology that crystalline rock is dominant, the properties of subsurface including the anisotropy are distributed complexly and changed abruptly. Because of such geological environments, cross-hole seismic traveltime tomography is widely used to obtain the high resolution image of the subsurface for the engineering purposes in the geotechnical sites. However, because the cross-hole tomography has a wide propagation angle coverage relatively, its data tend to include the seismic velocity anisotropy comparing with the surface seismic methods. It can cause the misinterpretation that the cross-hole seismic data including the anisotropic effects are analyzed and treated with the general processing techniques assuming the isotropy. Therefore, we need to consider the seismic anisotropy in cross-hole seismic traveltime tomography. The seismic anisotropic tomography algorithm, which is developed for evaluation of the velocity anisotropy, includes several inversion schemes in order to make the inversion process stable and robust. First of all, the set of the inversion parameters is limited to one slowness, two ratios of slowness and one direction of the anisotropy symmetric axis. The ranges of the inversion parameters are localized by the pseudo-beta transform to obtain the reasonable inversion results and the inversion constraints are controlled efficiently by ACB(Active Constraint Balancing) method. Especially, the inversion using the Fresnel volume is applied to the anisotropic tomography and it can make the anisotropic tomography more stable than ray tomography as it widens the propagation angle coverage.

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Shallow Marine Seismic Refraction Data Acquisition and Interpretation Using digital Technique (디지털 技法을 이용한 淺海底 屈折法 彈性波 探査資料의 取得과 解析)

  • 이호영;김철민
    • 한국해양학회지
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    • v.27 no.1
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    • pp.19-34
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    • 1992
  • Marine seismic refraction surveys have been carried out by Korea Institute of Geology, Mining and Materials(KIGAM) since 1984. The recording of refraction data was based on analog instrumentation. Therefore the resolution of refraction data was not good enough to distinguish many layers. The objective of the interpretation of seismic refraction data is the determination of intervals and critically refracted seismic wave propagation velocities through the layers beneath the sea floor. To determine intervals and velocities precisely, the resolution of refraction data should be enhanced. The intent of the study is to improve the quality of shallow marine refraction data by the digital technique using microcomputer- based acquisition and processing system. The system consists of an IBM AT microcomputer clone, an analog-digital(A/D) converter. A mass storage unit and a parallel processing board. The A/D converter has 12 bits of precision and 250 kHz of conversion rate. The magneto-optical disk drive is used for the mass storage of seismic refraction data. Shallow marine seismic refraction surveys have been carried out using the system at 6 locations off Ulsan and Pusan area. The refraction data were acquired by the radio sonobuoy. The refraction profiles have been produced by the laser printer with 300 dpi resolution after the basic computer processing. 5-9 layers were interpreted from digital refraction profiles, whereas 2-4 layers were interpreted from analog refraction profiles. the propagation velocities of sediments were interpreted as 1.6-2.1 km/sec. The propagation velocities of acoustic basement were interpreted as 2.4-2.7 km/sec off Ulsan area, 4.8 km/sec off Pusan area.

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