Trace Interpolation using Model-constrained Minimum Weighted Norm Interpolation

모델 제약조건이 적용된 MWNI (Minimum Weighted Norm Interpolation)를 이용한 트레이스 내삽

  • Choi, Jihyun (Department of Earth Resources and Environmental Engineering, Hanyang University) ;
  • Song, Youngseok (Department of Earth Resources and Environmental Engineering, Hanyang University) ;
  • Choi, Jihun (Department of Earth Resources and Environmental Engineering, Hanyang University) ;
  • Byun, Joongmoo (Department of Earth Resources and Environmental Engineering, Hanyang University) ;
  • Seol, Soon Jee (Department of Earth Resources and Environmental Engineering, Hanyang University) ;
  • Kim, Kiyoung (Department of Geophysics, Kangwon National University) ;
  • Lee, Jeongmo (Department of Geology, Kyungpook National University)
  • 최지현 (한양대학교 자원환경공학과) ;
  • 송영석 (한양대학교 자원환경공학과) ;
  • 최지훈 (한양대학교 자원환경공학과) ;
  • 변중무 (한양대학교 자원환경공학과) ;
  • 설순지 (한양대학교 자원환경공학과) ;
  • 김기영 (강원대학교 지질.지구물리학부) ;
  • 이정모 (경북대학교 지구시스템과학부 지질학전공)
  • Received : 2017.03.09
  • Accepted : 2017.04.17
  • Published : 2017.05.31


For efficient data processing, trace interpolation and regularization techniques should be antecedently applied to the seismic data which were irregularly sampled with missing traces. Among many interpolation techniques, MWNI (Minimum Weighted Norm Interpolation) technique is one of the most versatile techniques and widely used to regularize seismic data because of easy extension to the high-order module and low computational cost. However, since it is difficult to interpolate spatially aliased data using this technique, model-constrained MWNI was suggested to compensate for this problem. In this paper, conventional MWNI and model-constrained MWNI modules have been developed in order to analyze their performance using synthetic data and validate the applicability to the field data. The result by using model-constrained MWNI was better in spatially aliased data. In order to verify the applicability to the field data, interpolation and regularization were performed for two field data sets, respectively. Firstly, the seismic data acquired in Ulleung Basin gas hydrate field was interpolated. Even though the data has very chaotic feature and complex structure due to the chimney, the developed module showed fairly good interpolation result. Secondly, very irregularly sampled and widely missing seismic data was regularized and the connectivity of events was quite improved. According to these experiments, we can confirm that the developed module can successfully interpolate and regularize the irregularly sampled field data.

MWNI (Minimum Weighted Norm Interpolation)를 이용한 내삽 방법은 고차원으로 확장이 용이하고 상대적으로 계산 속도가 빠르다는 장점을 가지고 있으나 알리아스 효과가 존재하는 자료의 내삽에 취약하다. 이런 문제의 개선을 위해 제안된 방법이 모델제약(model-constrained) MWNI이다. 이 논문에서는 MWNI를 이용한 방법과 모델제약 MWNI 방법의 두가지 모듈을 개발한 후 알리아스 효과가 존재하는 자료의 내삽 결과를 비교하였다. 시공간 영역(t-x domain)과 주파수-파수 영역(f-k domain)의 결과 그림을 통해서 모델제약 MWNI를 적용했을 때의 결과가 더 효과적임을 확인할 수 있었다. 동해 울릉분지의 가스 하이드레이트 부존 지역의 현장 자료에 내삽을 적용한 결과, 가스침니 구간 전후로 진폭이 급격하게 변하는 자료에서도 내삽이 가능함을 확인할 수 있었다. 또한 매우 불규칙하고 넓은 구간에서 누락된 인공지진파 자료의 정규화를 통해 신호의 연결성 향상이 가능함을 보일 수 있었다. 결과적으로 이 논문에서 개발된 모듈은 현장의 다양한 여건에 의해 불규칙하거나 넓은 간격으로 얻어진 탄성파 자료의 정규화나 내삽에 효율적으로 활용될 수 있음을 확인하였다.



Grant : 기상.지진See-At기술개발연구

Supported by : 기상청, KETEP


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