期刊名称：IOP Conference Series: Earth and Environmental Science
印刷版ISSN：1755-1307
电子版ISSN：1755-1315
出版年度：2019
卷号：310
期号：3
页码：1-9
DOI：10.1088/1755-1315/310/3/032032
出版社：IOP Publishing
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.
