Enhancing Electrical Submersible Pump Operations: Leveraging Data-Driven Models Using Advanced Machine Learning and IoT Technologies for Effective Event Management

Electrical Submersible Pumps (ESPs) are widely used in the petroleum industry as an effective artificial lift method. ESP pumps are particularly effective in scenarios with reservoirs having low bottomhole pressure, low gas/oil ratio, high water cut, and low API gravity fluids. However, ESPs are very susceptible to issues depending on the well and reservoir conditions, requiring continuous monitoring and analysis of performance and failures of the ESP system. Despite their widespread application, operating ESP wells presents several challenges that can impact efficiency, reliability, and overall operational costs. Common issues include sand and solids production, gas interference, corrosion and scale formation, power supply inconsistencies, high reservoir temperatures, handling of viscous fluids, complications in deep and deviated wells, and mechanical failures due to vibration and stress. Addressing these challenges is crucial for optimizing ESP performance and ensuring economic viability. Under this context, Abu Dhabi Offshore Fields, as part of its field development plan, has adopted ESP as its artificial lift system. In consideration of this ambitious project, Abu Dhabi Offshore Fields is proactively engaged in laying the groundwork to manage these wells with the highest operational efficiency. This involves strategic planning for the installation, maintenance, and monitoring of the ESP systems to ensure they deliver optimal performance and longevity. Therefore, continuous surveillance of the system is a must, especially considering that common ESP failures are categorized as follows: Electrical Failures, which are the most prevalent, making up about 60% of all ESP failures, including power failures, under-voltage, voltage imbalances, and motor underload. Motor Failures can result from overheating, insulation breakdown, or mechanical wear and tear. Gas Locking occurs when gas accumulates in the pump, hindering its operation. Mechanical Failures include issues like impeller wear, shaft breakage, and seal failures. Operational Failures arise from improper installation, poor maintenance, and operational errors. Recent advancements in Artificial Intelligence (AI) offer promising solutions to mitigate these operational challenges. AI technologies, including machine learning and predictive analytics, can provide significant improvements in the management and optimization of ESP systems. For instance, predictive maintenance algorithms can analyze historical and real-time data to forecast equipment failures, allowing for proactive interventions that reduce downtime and extend the lifespan of ESP components. Similarly, AI models can predict sand production trends and recommend optimal operational parameters, minimizing sand ingress and associated issues.