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An Intelligent Early Warning Method Based on MWSPCA CBR Prediction Model

A prediction model and anomaly technology, applied in the field of intelligent early warning of CBR prediction model based on MWSPCA, can solve problems such as inaccurate identification of faults

Active Publication Date: 2021-11-02
BEIJING UNIV OF CHEM TECH
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  • Summary
  • Abstract
  • Description
  • Claims
  • Application Information

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Problems solved by technology

However, due to the limitations of the algorithm itself, it cannot accurately identify all types of faults

Method used

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  • An Intelligent Early Warning Method Based on MWSPCA CBR Prediction Model
  • An Intelligent Early Warning Method Based on MWSPCA CBR Prediction Model
  • An Intelligent Early Warning Method Based on MWSPCA CBR Prediction Model

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Embodiment 1

[0041] figure 1 It is an abnormality monitoring flow chart based on the moving window sparse principal component analysis method provided by Embodiment 1 of the present invention, figure 2 It is a flow chart of anomaly early warning of the case-based reasoning system provided by Embodiment 1 of the present invention. like figure 1 and figure 2 As shown, the present embodiment provides an intelligent early warning method for a case-based reasoning system (Case-based Reasoning, CBR) prediction model based on a moving window sparse principal component analysis method (Moving Window Sparse Principal Component Analysis, MWSPCA), including: using a moving window The sparse principal component analysis method monitors and analyzes the real-time drilling data, obtains the abnormal time period according to the monitoring and analysis results, calculates the contribution of each drilling-related variable in each abnormal time period to the abnormal time period, and uses the cosine s...

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Abstract

The invention discloses an intelligent early warning method based on MWSPCA CBR prediction model, which includes: monitoring and analyzing the real-time data of drilling, obtaining abnormal time periods according to the results of monitoring and analysis, and calculating the impact of each drilling-related variable in each abnormal time period on all The contribution degree of the abnormal time period is described, the fault type analysis is performed on the analysis results of the abnormal monitoring, and the abnormal early warning is carried out according to the analysis results. The technical solution provided by the invention uses the excellent reasoning and self-learning ability of the improved case reasoning early warning model to provide intelligent early warning for failures occurring during the drilling process, thereby reducing the probability of drilling failures and reducing the cost of non-productive time. The sparse principal component analysis algorithm provided by the present invention can reduce the dimensionality of the data in the drilling process, and the moving window sparse principal component analysis algorithm can process and analyze real-time data to quickly locate abnormalities in the drilling process.

Description

technical field [0001] The invention relates to the technical field of intelligent early warning, in particular to an intelligent early warning method based on MWSPCA CBR prediction model. Background technique [0002] Drilling engineering is an important part of the oil production process. With the progress of the times and the rapid development of drilling technology, reducing development costs and increasing production speed have become the goals pursued by the modern oil industry. However, the drilling project is a systematic project with many types of work, many procedures, and must be operated continuously, and it is also an underground project with strong concealment. There are huge risks and uncertainties in drilling engineering, and every step forward is accompanied by huge risks, which seriously threaten the safety of oil production, reduce production efficiency, increase production costs, and delay the development speed of oil fields. Statistics show that in the ...

Claims

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Application Information

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Patent Type & Authority Patents(China)
IPC IPC(8): G06K9/62G06N5/04G06Q10/04G06Q50/02
CPCG06N5/04G06Q10/04G06Q50/02G06F18/2135G06F18/22
Inventor 耿志强王仲凯韩永明朱群雄徐圆
Owner BEIJING UNIV OF CHEM TECH
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