一种基于数据驱动的注采井关联分析调控方法及系统
By acquiring the load and water cut data of oil wells, generating a daily load difference sequence, constructing a sliding time window, and identifying the water injection response lag cycle, the problem of difficulty in capturing injection-production response fluctuations in existing technologies is solved, achieving high efficiency and accuracy in the coordinated control of injection and production wells.
Patent Information
- Authority / Receiving Office
- CN · China
- Patent Type
- Patents(China)
- Current Assignee / Owner
- BEIJING DIHANG TIMES TECH CO LTD
- Filing Date
- 2026-03-04
- Publication Date
- 2026-07-17
AI Technical Summary
In existing technologies, it is difficult to accurately capture injection-production response fluctuations and lag times using low-frequency, discrete production data, which makes it difficult to accurately capture the pressure transmission relationship between injection wells and production wells, resulting in low efficiency of injection-production well correlation control.
By acquiring the maximum load sequence, minimum load sequence, actual water cut data, and fitted water cut data of the target oil well, and combining them with the daily water injection data of the injection well, a daily load difference sequence is generated. A sliding time window is constructed to shift the time axis, generating multiple sets of lag water injection sequences. The correlation coefficient is calculated, the water injection response lag period is identified, and the model parameters are corrected to generate water injection control commands.
It enables continuous quantification of the dynamic operating characteristics of oil wells without relying on production monitoring equipment, improves the ability to perceive the trend of state changes in the injection and production system, accurately identifies the lag period of water injection response, generates highly reliable water cut prediction results, and improves the efficiency of injection and production well correlation control.
Smart Images
Figure CN121765445B_ABST