Advances in Key Technologies for Accurate Identification, Monitoring and Early Warning of Disaster Risks in Service Wellbores

4th International Conference on Advances in Energy Resources and Environment Engineering

能源学;生态环境科学

Song, Zhaoyang^1^2 ; Xu, Shuanxiang^3 ; Tan, Jie^1

Mine Construction Branch, China Coal Research Institute, Beijing

100013, China^1

School of Civil and Resource Engineering, University of Science and Technology Beijing, Beijing

100083, China^2

Shangdong Energy Xinwen Group Xin Julong Co. LTD., Heze

274918, China^3

关键词: Cloud computing platforms;    Deformation Characteristics;    Future coal productions;    Intelligence analysis;    Intelligent identification;    Multi-field coupling;    Real time monitoring;    Structural transformation;   

Others  :  https://iopscience.iop.org/article/10.1088/1755-1315/237/3/032113/pdf
DOI  :  10.1088/1755-1315/237/3/032113

学科分类：环境科学（综合）

来源: IOP

【 摘 要 】

Due to the structural transformation of the national macro-economic and policy adjustment of the supply-side structural reform, the number of new coal mine shaft has been sharply reduced. Future coal production capacity mainly focuses on the current mines in operation, therefore, accurate identification and monitoring warning of risk in the service wellbores has become a problem to be solved. This paper summarizes the current research and existing problems of wellbore and explores how to conduct wellbore risk identification and monitoring and early warning and how to handle multi-source disasters. Based on the theory of wellbore deformation system instability and regional geological multi-scale multi-phase multi-field coupling disaster mechanism, engineering risk identification and early warning theory, surrounding the scientific problems of accurate identification and monitoring and early warning of service wellbore risk, this paper puts forward the idea of multi-scale source risk monitoring of service wellbore, and summarizes 4 key scientific issues and 7 main research directions of accurate identification, monitoring, and warning of service wellbore risk. As for the stress source, corrosion source and physical property source that affect the safe service of the wellbore, for the risk hazard such as wellbore cracking, corrosion and deflection, this paper adopts multi-disciplinary and multi-method under the scale of "region-mining area-wellbore-key section" to study the multi-field coupling force and deformation characteristics of the service wellbore. Based on the precursor data collection, multi-network fusion transmission and scientific intelligence analysis technology of big data and cloud computing platform, a new model of future wellbore safety service featuring online real-time monitoring, intelligent identification, and accurate warning of the service wellbore risk can be established, thereby providing theoretical support and technical approach for the safety management and intelligent service of service wellbores in China.