최소 사전정보틀 이용한 주파수 영역 항공 전자탐사 자료의 HOLISTIC 역산

Holistic inversion of frequency-domain airborne electromagnetic data with minimal prior information

  • Brodie, Ross (Australian National University & Geoscience Australia, Research School of Earth Sciences) ;
  • Sambridge, Malcolm (Australian National University, Research School of Earth Sciences)
  • 발행 : 2009.02.28

초록

주파수 영역 항공 전자탐사 자료의 holistic 역산은 사전정보가 충분한 경우에 측정 자료의 보정, 처리 및 역산을 동시에 진행하는 역산법으로 개발되었다. 이 연구에서는 사전정보가 없는 경우에도 적응 가능하도록 holistic 역산을 발전시킨다. 이 역산에서는 수직방향으로 전기적 물성이 부드럽게 변화하는 다층 구조를 가정하고, 시스템 오차로 인한 편향 매개변수를 단순화하며. 고도에 따른 수평 방향의 평활화 조건을 적용하고, 클러스터를 이용하여 병렬 계산을 수행한다. 사전정보를 전혀 이용하지 않고 holistic 역산법으로 800만 개의 자료를 340만 개의 매개댄수에 대해 역산한 결과, 이와는 별개로 계산된 보정 계수, 다운홀 로깅 자료 및 지하수위 자료와 잘 일치하는 결과를 굴을 수 있었다. 이로부터 holistic 역산의 성공 여부가 정교하게 작성된 초기 모형이나 탐사 지역의 특별한 사전정보와는 무관함을 알 수 있었다. 또한. holistic 역산은 높은 고도에서의 원점 측정을 필요로 하지 않으므로 자료 획득에 필요한 비용을 상당히 절감할 수 있을 것이다.

The holistic inversion approach for frequency domain airborne electromagnetic data has previously been employed to simultaneously calibrate, process and invert raw frequency-domain data where prior information was available. Analternative formulation has been developed, which is suitable in the case where explicit prior information is not available. It incorporates: a multi-layer vertically-smooth conductivity model; a simplified bias parameterisation; horizontal smoothing with respect to elevation; and cluster computer parallelisation. Without using any prior data, an inversion of 8.0 million data for 3.4 million parameters yields results that are consistent with independently derived calibration parameters, downhole logs and groundwater elevation data. We conclude that the success of the holistic inversion method is not dependent on a sophisticated conceptual model or the direct inclusion of survey-area specific prior information. In addition, acquisition costs could potentially be reduced by employing the holistic approach which largely eliminates the need for high altitude zero-level measurements.

키워드

참고문헌

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