Quantitative safety evaluation of drilling engineering by combining analytic hierarchy process with alternating condition expectation

Kunkun Fan, Fangxiang Wang, Chunguang Wang, Shaojie Chen, Hai Lin, Jia He, Zhongwei Chen

Research output: Contribution to journalConference articlepeer-review

1 Scopus citations

Abstract

Drilling engineering is important for development of underground resources. There are many potential risks in the process of drilling engineering. If the drilling safety is not effectively managed, it will lead to great loss. In order to predicate and prevent safety accidents, a safety evaluation index system is established and an AHP-ACE method is proposed. 23 groups of original drilling data are collected from a block of Xinjiang oil field, and the safety levels are quantitatively analyzed by characteristic values. First, the AHP method is applied to relate direct observation variables to potential variables by calculating weight and determining membership function of each index. Second, three potential variables are chosen as the input of the ACE model and a training set containing 17 groups of data is used to establish the mathematical relationship between the potential variables and drilling safety value. Finally, the validity of the proposed model is examined by matching it to the other 6 groups of data. This study provides a new and effective way to quantitatively evaluate the safety of drilling engineering.

Original languageEnglish
Article number01038
JournalE3S Web of Conferences
Volume303
DOIs
StatePublished - 17 Sep 2021
Externally publishedYes
Event10th Anniversary Russian-Chinese Symposium on Clean Coal Technologies: Mining, Processing, Safety, and Ecology 2021 - Kemerovo, Russian Federation
Duration: 19 Oct 202121 Oct 2021

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