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Indexed by:会议论文

Date of Publication:2015-01-01

Included Journals:CPCI-S

Page Number:308-314

Key Words:Coal bed methane gas; Time series; Grey Theory; Fault Diagnosis; Trend Change; Prediction

Abstract:As a new type of energy, coalbed gas plays an important role in the national resource structure. With the large-scale production, high security requirement is necessary to the development of coalbed gas single well. We hope a rapid, correct prediction and fault diagnosis to save the property and lives. According to the actual survey of the single-well site, we find that the wells located in different site has different natural environment and sometimes we can't acquire enough datas in different working status. There exists correlation between gas producing parameters and the parameters have abnormal trend change in different fault, which requires us to find a new fault diagnosis method to solve this problem. Aimed at the new problems, this paper proposes a method based on grey theory and time series theory. We create the corresponding parameters' time series model to make the prediction and fault diagnosis. The innovation of this paper is the use of multi-parameters time series model to measure the working state of the single well. The simulation results show that this method has good practicality, and can be applied to both parameters' prediction and fault diagnosis of single well.