Oil and gas communication terminal data acquisition and format conversion method

By standardizing and performing deep correlation analysis on the sensor data streams of oil and gas communication terminals, a fused feature tensor is generated and semantic integrity is verified, which solves the problems of fragmented sensor data features and missing verification, and improves the coherence and reliability of the data.

CN122364653APending Publication Date: 2026-07-10CHINA UNIV OF PETROLEUM (EAST CHINA)
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Patent Information

Authority / Receiving Office
CN · China
Patent Type
Applications(China)
Current Assignee / Owner
CHINA UNIV OF PETROLEUM (EAST CHINA)
Filing Date
2026-04-16
Publication Date
2026-07-10

AI Technical Summary

Technical Problem

In existing technologies, the sensor data features of oil and gas communication terminals lack deep correlation analysis, resulting in fragmented feature information. After format conversion, there is a lack of effective semantic integrity verification, leading to data waste and insufficient reliability.

Method used

By standardizing and aligning the original sensor data stream, correcting trend drift, filtering out impulse noise, and eliminating jitter, pressure fluctuations, flow changes, and valve status features are extracted, deep correlation analysis is performed, a fused feature tensor is generated, and a data format template engine is used for structured filling and semantic integrity verification.

Benefits of technology

This achieves deep coupling of sensor data features, improves data coherence and reliability, reduces data waste, and enhances the accuracy and reliability of standardized data recording.

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Abstract

This invention discloses a method for data acquisition and format conversion of oil and gas communication terminals, relating to the field of oil and gas communication terminal data processing technology. The method includes: acquiring raw sensor data streams containing well pressure, pipeline flow rate, valve status, and acquisition timestamps from the target oil and gas communication terminal; generating a data point sequence with a unified time reference through standardized time-series alignment; forming a time-series data set through quality enhancement processing; extracting three types of features and inputting them into a preset feature fusion architecture for deep correlation analysis to obtain a fused feature tensor; generating standardized data records through structured filling using a data format template engine; and performing semantic integrity verification on the records, with those failing the verification being returned for feature re-extraction. This method avoids feature fragmentation and data waste, improves the effectiveness and reliability of standardized data, and achieves efficient collaboration between data acquisition, processing, conversion, and verification.
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