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고해상 탄성파 탐사자료에의 디고스팅 및 디시그니쳐 적용

Application of Deghosting and Designature for High-Resolution Seismic Data

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키워드

주제분류자원공학

초록

엔지니어링 목적의 고해상 탄성파 탐사는 석유탐사 목적의 탄성파 탐사에 비해 기본적인 자료처리기법을 사용하고 있다. 고해상 탐사자료의 해상도를 향상시키기 위한 추가적인 자료처리 기법이필요하기 때문에, 본 연구에서는 고해상 탄성파 탐사자료에 대해 고스트를 제거할 수 있는 디고스팅과 송신파형의 영향을 제거할 수 있는 디시그니쳐의 적용가능성을 알아보았다. 성공적인 디고스팅을 위해 고스트 지연시간을 L1-norm 목적함수를 활용하여 고스트 지연시간을 추정하였다. 디시그니쳐의 경우에는 효율적인 연산을 위하여 균질매질에서의 3차원 그린함수를 이용하여 음원을 추정하고, 새롭게 정의된 파형요소를 콘볼루션하여 기존 송신파형의 영향을 제거하였다. 합성자료와 현장자료에 대해 디고스팅과 디시그니쳐를 수행하였다. 디고스팅 적용 결과, L1-norm 목적함수를통해 고스트 지연시간을 추정할 수 있었으며 고스트 신호가 제거됨에 따라 왜곡된 주파수 성분이복원되어 진폭 스펙트럼 대역이 넓어짐을 확인하였다. 디시그니쳐의 경우, 기존 송신파형의 영향을 제거하고 새로운 영위상(zero-phase)의 파형요소를 콘볼루션함으로써 영위상 트레이스가 생성된 것을 확인할 수 있었다.

Abstract

In contrast to the seismic explorations for oil and gas development, elementary seismic data processing techniques have been applied to seismic surveys in engineering. Additional seismic data processing is required for high-resolution seismic data to enhance its resolution. Therefore, deghosting and designature methods on high-resolution seismic data were investigated to eliminate the ghost and the effects of the source signature. For successful deghosting, the objective function based on the L1-norm was used to estimate the ghost delay time. In the case of designature, the source signature with the homogeneous three-dimensional (3D) Green's function was efficiently estimated, and the effects of the source signature were eliminated by using a newly defined source wavelet. The deghosting and designature were implemented on synthetic seismic and field datasets. Through the deghosting, the ghost delay time can be estimated by the L1-norm based objective function, and the ghost signal can be eliminated. In addition, the bandwidth of the amplitude spectrum was broadened by resorting the distorted frequency components. The results of the designature showed that the zero-phased traces were generated by eliminating the effects of the original source signature and convolving the newly defined zero-phased source wavelet.

참고문헌 (18)

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