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Main control factors affecting mechanical oil recovery efficiency in complex blocks identified using the improved
Qiuyu Lu1, Suling Wang1, Minzheng Jiang1
1School of Mechanics Science & Engineering, Northeast Petroleum University, Daqing, Heilongjiang, China.
Plos One
|May 4, 2021
Summary
An improved k-means algorithm enhances oil recovery efficiency by identifying key factors like motor utilization and pump efficiency. This method optimizes well performance and increases oil output in mature fields.
Area of Science:
- Petroleum Engineering
- Data Science
- Artificial Intelligence
Background:
- System efficiency in oil recovery pumping units is complex, with varying control factors across different blocks.
- Traditional k-means clustering is limited by its assumption of equal factor influence and sensitivity to initial cluster points.
- Accurate identification of factors affecting efficiency is crucial for optimizing oil production in mature fields.
Purpose of the Study:
- To develop and apply an improved clustering algorithm for analyzing factors influencing mechanical production efficiency in oil recovery.
- To overcome the limitations of the standard k-means algorithm in handling complex, multi-factor data in oil production.
- To identify specific operational adjustments for enhancing system efficiency in oil production blocks.
Main Methods:
- Calculated correlation coefficients and standardized system efficiency indicators.
- Developed a weighted k-means algorithm incorporating factor weights derived from moisture values.
- Combined DBSCAN and weighted k-means to address initial center point selection issues in k-means clustering.
- Applied both standard and improved algorithms to an oil production block in the Daqing Oilfield.
Main Results:
- The improved algorithm identified motor utilization, pump efficiency, and daily fluid production as positively correlated with system efficiency.
- Low-efficiency wells showed significantly lower pump diameter, power consumption, water content, daily fluid production, oil pressure, and casing pressure compared to the block average.
- High-efficiency wells were characterized by pump depths lower than the block average.
Conclusions:
- The improved weighted k-means algorithm effectively analyzes complex factors influencing oil production system efficiency.
- Operational adjustments, such as optimizing pump depth and enhancing water injection, can significantly improve system efficiency.
- This approach provides a unified and accurate method for assessing block-specific efficiency characteristics in oil fields.
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