Journal of the Korean Institute of Gas (한국가스학회지)

The Korean Institute of GAS (한국가스학회)
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Analysis of Technical Trend for Drilling ROP Optimization with Artificial Intelligent

인공지능을 적용한 시추 굴진율 최적화 기술 동향 분석

  • 정지헌 ((주)아이에치케이) ;
  • 한동권 (동아대학교 에너지자원공학과) ;
  • 김상호 (동아대학교 에너지자원공학과) ;
  • 유인항 ((주)아이에치케이) ;
  • 권순일 (동아대학교 에너지자원공학과)
  • Received : 2019.12.12
  • Accepted : 2020.02.19
  • Published : 2020.02.28
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Abstract

Drilling operation is the most important and costly essential work in oil and gas exploration and development. Therefore, the studies about rate of penetration have been carried out continuously to improve drilling efficiency. In recent years, data-driven models have been developed by various researchers to overcome disadvantages of traditional mathematical models. For the data-driven models, selecting proper algorithms and parameters is very important. In addition, data-driven models should be retrained in real-time during continuous drilling operations in order to improve the model performance. In this paper, the latest studies are investigated to provide information about algorithms, drilling parameters and model retraining intervals that used in drilling optimization.

시추는 석유자원 탐사와 개발에서 가장 중요하며 많은 비용이 소요되는 필수 작업이다. 그래서 시추의 효율 향상을 위한 굴진율 연구가 지속적으로 진행되어왔다. 근래에는 전통적인 수학적 모델의 단점을 극복하기 위하여 새로운 방식의 자료기반 모델이 다양한 연구자들에 의해 개발되고 있다. 자료기반 모델은 알고리즘과 매개변수의 선택이 매우 중요하다. 또한 개발된 모델의 성능향상을 위하여 실시간으로 모델을 재훈련하여 연속적인 시추작업을 실현해야한다. 이 논문에서는 최신 연구들을 조사하여 시추 최적화에서 사용된 알고리즘, 시추 매개변수, 모델 재훈련 간격에 대한 정보를 제공하고자 한다.

Keywords

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