会议论文详细信息
2019 2nd International Conference of Green Buildings and Environmental Management
Research on energy saving of Coalbed Methane Field pumping wells based on Data Mining
生态环境科学
Li, Xueqin^1^2
Petrochina Huabei Oilfield CBM Branch Company, Jincheng, Shanxi Province
048000, China^1
CBM Pilot Test Base of China National Petroleum Corporation, Jincheng, Shanxi Province
048000, China^2
关键词: Energy consumption datum;    Energy consumption index;    High energy consumption;    Mechanical production wells;    Optimization strategy;    Production parameters;    Southern qinshui basins;    Theoretical calculations;   
Others  :  https://iopscience.iop.org/article/10.1088/1755-1315/310/3/032032/pdf
DOI  :  10.1088/1755-1315/310/3/032032
学科分类:环境科学(综合)
来源: IOP
PDF
【 摘 要 】

Generally, the CBM well has the characteristics of large variation of the water rate and unstable pumping load, corresponding equipment type, status and parameters adjusted frequently, the utilization rate of energy is generally low, however, the energy transfer relationship of pumping unit system is complex and the coupling between parameters is strong, the theoretical calculation method requires high energy consumption calculation parameters for each node, and the effective dynamic analysis cannot be realized; the experience analysis method has high workload and high requirement for analysts. In southern Qinshui basin CBM Wells, for example, by analyzing the relationship between production parameters and the energy consumption of each node, a multi variable data mining algorithm is constructed for the energy consumption index of the common pumping unit system, according to the energy consumption data characteristics of pumping unit, the single well is classified, and the adjustment optimization strategy of pump replacement, pumping-unit replacement, intermittent pumping and equipment maintenance is put forward according to the different types of energy consumption bias. Verified by practice, the application of this technology can improve the timeliness and accuracy of energy consumption data analysis of CBM pumping well, effectively reduce the cost of energy consumption analysis on mechanical production Wells, and is helpful to improve the intelligent level of CBM gas field production.

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