A new gas lift allocation method in the IoT environment using a hybrid optimization algorithm
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View abstract on PubMed
Summary
This summary is machine-generated.This study optimizes gas injection for oil wells using a hybrid Particle Swarm Optimization and Atom Search Optimization algorithm with IoT data. The method improves energy efficiency and gas utilization, reducing costs.
Area Of Science
- Petroleum Engineering
- Artificial Intelligence
- Optimization Algorithms
Background
- Well productivity declines with reservoir depletion, necessitating artificial lift techniques like gas injection.
- Gas scarcity requires optimized allocation to balance oil production with minimal gas usage.
- Conventional gas allocation strategies struggle with real-world non-linear constraints and gas supply limitations.
Purpose Of The Study
- To develop an innovative, optimized gas allocation strategy for petroleum extraction.
- To leverage Internet of Things (IoT) technology for real-time data acquisition and adaptive optimization.
- To enhance oil recovery efficiency while minimizing gas consumption and energy usage.
Main Methods
- A hybrid optimization algorithm combining Particle Swarm Optimization (PSO) and Atom Search Optimization (ASO).
- Integration of IoT for real-time data acquisition and processing.
- Implementation of dynamic parameters and adaptive force constants for enhanced exploration and exploitation.
Main Results
- Significant improvements in energy efficiency (12.12% reduction) and gas utilization (18.05% reduction).
- Demonstrated enhancements in battery life (7.67%) and cost reduction (9.48%) compared to existing methods.
- The hybrid PSO-ASO approach provides precise and adaptive optimization for gas allocation.
Conclusions
- The proposed hybrid optimization technique effectively addresses gas scarcity in petroleum extraction.
- IoT integration enables adaptive and efficient real-time gas allocation strategies.
- The method offers substantial economic and operational benefits through improved resource management.
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