ESP Startup Scheduling With MPC and Choke Opening Control
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Solution Overview
Problem
Existing methods for controlling electric submersible pumps (ESPs) lack optimization in startup sequences, leading to inefficient operation and potential damage to reservoirs, pumps, and processing facilities due to inadequate control over motor frequency and choke opening.
Innovation Solution
A model-based approach that develops offline and real-time optimized startup schedules using physical models and model-predictive control (MPC) to dictate optimal operation of ESPs and wellhead chokes, ensuring compliance with operational constraints and objectives such as avoiding formation damage and maintaining pump efficiency.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Reliability
If traditional startup methods are used for ESPs, then the startup process is simple to implement, but the operation efficiency is poor and potential damage may occur to reservoirs, pumps, and processing facilities
Solution Approach 1:
The patent applies preliminary action by developing optimized startup schedules offline before actual ESP startup. The system pre-calculates optimal motor frequency and choke opening sequences based on physical models, storing these schedules for execution during startup. This eliminates the need for complex real-time calculations during actual startup while ensuring reliable, damage-free operation through pre-planned control sequences.
2Productivity
If optimized startup schedules are implemented, then the operation efficiency and safety are improved, but the control system complexity increases
Solution Approach 1:
The system performs all complex optimization calculations offline before startup, generating pre-optimized schedules that are stored and executed during actual startup. This transfers computational complexity from real-time operation to offline preparation, achieving high startup efficiency without requiring complex real-time control systems.
Solution Approach 2:
The patent creates simplified copies of the optimal startup sequences from complex physical models. Instead of executing complex model calculations in real-time, the system stores simplified control schedules (copies of optimal behavior) that can be executed directly during startup, maintaining efficiency while reducing real-time system complexity.
3Adaptability or versatility
If real-time optimization is performed during startup, then the adaptability to changing conditions is improved, but the computational time and system response delay increase
Solution Approach 1:
The system pre-calculates startup schedules considering various operational conditions and constraints offline. These pre-computed schedules are stored and executed during actual startup, eliminating real-time computational delays while maintaining adaptability through pre-planned optimization for different scenarios.
Solution Approach 2:
The patent implements dynamic adaptability by allowing the offline optimization process to incorporate various operational scenarios and constraints. The system can generate different optimized schedules for different conditions, selecting the appropriate pre-computed schedule based on actual startup conditions without requiring real-time recalculation.
Data Source
AI summary
A method for controlling an ESP-lifted well in an optimal fashion using the ESP speed and choke opening as actuators subject to operational constraints.