자원환경지질 (Economic and Environmental Geology)

  • 제57권1호
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  • Pages.51-71
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  • 2024
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  • 1225-7281(pISSN)
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  • 2288-7962(eISSN)
대한자원환경지질학회 (The Korean Society of Economic and Environmental Geology)
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탄성파 속성 분석을 위한 탄성파 자료 무작위 잡음 제거 연구

Study on the Seismic Random Noise Attenuation for the Seismic Attribute Analysis

  • 원종필 (경북대학교 지질학과) ;
  • 신정균 (한국지질자원연구원 포항지질자원실증연구센터) ;
  • 하지호 (한국지질자원연구원 포항지질자원실증연구센터) ;
  • 전형구 (경북대학교 지질학과)
  • Jongpil Won (Department of Geology, Kyungpook National University) ;
  • Jungkyun Shin (Pohang Branch, Korea Institute of Geoscience and Mineral Resources (KIGAM)) ;
  • Jiho Ha (Pohang Branch, Korea Institute of Geoscience and Mineral Resources (KIGAM)) ;
  • Hyunggu Jun (Department of Geology, Kyungpook National University)
  • 투고 : 2023.09.15
  • 심사 : 2023.10.24
  • 발행 : 2024.02.29
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⟨ 이전 논문 다음 논문 ⟩

초록

탄성파 탐사는 지하자원 개발, 지반 조사, 지층 모니터링 등에 널리 사용되고 있는 지구물리탐사 방법으로 정확한 지층 구조 영상을 제공해주기 때문에 지층의 지질학적 특성 해석에 필수적으로 활용된다. 일반적으로는 탄성파 구조 보정 영상을 시각적으로 분석하여 지질학적 특성을 해석하지만 최근에는 탄성파 구조 보정 자료에 대한 정량적인 분석을 통해 원하는 지질학적 특성을 정확하게 추출하고 해석하는 탄성파 속성 분석이 널리 연구되고 있다. 탄성파 속성 분석은 탄성파 자료에 기반한 지질학적 해석에 정량적인 근거를 제시해줄 수 있기 때문에 석유 및 가스 저류층 분석, 단층 및 균열대 조사, 지층 가스 분포 파악 등의 다양한 분야에서 활용되고 있다. 하지만 탄성파 속성 분석은 탄성파 자료 내 잡음에 취약하므로 속성 분석의 정확도 향상을 위해서는 중합 후 탄성파 자료에 대한 추가적인 잡음 제거가 수반되어야 한다. 본 연구에서는 중합 후 탄성파 자료에 대한 무작위 잡음 제거 및 및 탄성파 속성 분석 정확도 개선을 위해 4가지의 잡음 제거 방법을 적용하고 비교한다. FX 디콘볼루션, DSMF, Noise2Noiose, DnCNN을 각각 포항 영일만 고해상 탄성파 자료에 적용하여 탄성파 무작위 잡음을 제거하고 잡음이 제거된 탄성파 자료로부터 에너지, 스위트니스, 유사도 속성을 계산한다. 그리고 각 잡음 제거 방법의 특성, 잡음 제거 결과, 탄성파 속성 분석 결과를 정성적 및 정량적으로 분석한 후, 이를 기반으로 탄성파 속성 분석 결과 향상을 위한 최적의 잡음 제거 방법을 제안한다.

Seismic exploration is one of the widely used geophysical exploration methods with various applications such as resource development, geotechnical investigation, and subsurface monitoring. It is essential for interpreting the geological characteristics of subsurface by providing accurate images of stratum structures. Typically, geological features are interpreted by visually analyzing seismic sections. However, recently, quantitative analysis of seismic data has been extensively researched to accurately extract and interpret target geological features. Seismic attribute analysis can provide quantitative information for geological interpretation based on seismic data. Therefore, it is widely used in various fields, including the analysis of oil and gas reservoirs, investigation of fault and fracture, and assessment of shallow gas distributions. However, seismic attribute analysis is sensitive to noise within the seismic data, thus additional noise attenuation is required to enhance the accuracy of the seismic attribute analysis. In this study, four kinds of seismic noise attenuation methods are applied and compared to mitigate random noise of poststack seismic data and enhance the attribute analysis results. FX deconvolution, DSMF, Noise2Noise, and DnCNN are applied to the Youngil Bay high-resolution seismic data to remove seismic random noise. Energy, sweetness, and similarity attributes are calculated from noise-removed seismic data. Subsequently, the characteristics of each noise attenuation method, noise removal results, and seismic attribute analysis results are qualitatively and quantitatively analyzed. Based on the advantages and disadvantages of each noise attenuation method and the characteristics of each seismic attribute analysis, we propose a suitable noise attenuation method to improve the result of seismic attribute analysis.

키워드

과제정보

이 논문은 2021학년도 경북대학교 신임교수정착연구비에 의하여 연구되었음. 본 연구에 사용된 자료는 한국지질자원연구원으로부터 제공받았음.

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