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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

Abstract

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.

Acknowledgement

Grant : 기상.지진See-At기술개발연구

Supported by : 기상청, KETEP

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