Multi-objective optimization of oilfield water injection operations under dynamic electricity prices: For equivalent reduction of carbon emissions

Abstract

Low-carbon oilfield requires the water injection system with huge electricity consumption to reduce carbon emissions, and there is an urgent need to establish an operation optimization method with low-carbon goals. This paper constructs a multi-objective optimization model of time-segmented water injection in oilfield water injection systems considering time-of-use electricity pricing that minimizes carbon emissions and electricity cost under time-of-use electricity pricing. The model comprehensively considers local head losses, pipeline network hydraulic balance, water balance constraint, pressure constraint of water injection well, pump flow rate constraint, water injection volume constraint, and time period priority constraint. Traditional solvers are prone to falling into local optima when solving the water injection optimization model. This paper proposes the innovative algorithm named Quantum Leader-Follower Formation Optimization Algorithm (QLFFOA). Compared with 10 classical algorithms, QLFFOA exhibits better solution performance. Finally, the proposed method was applied to a real oilfield water injection system containing 131 water injection wells and 2 water injection stations, and time-segmented water injection optimization was performed for 4 injection pumps over 13 independent time periods throughout the day under the time-of-use (TOU) electricity pricing mechanism. Under the premise of satisfying the core constraints of the water injection system, the optimized schedule decreased system energy consumption by about 7.3%, saved electricity costs by 10.8%, decreased carbon emissions by 7.2%, decreased unit energy consumption by 0.4 kWh/m³, and raised the system average pump efficiency by 1.84%. The optimized scheme avoided night-time peak periods, effectively reduced electrical energy consumption and correspondingly decreased CO₂ emissions. The results indicate that this model and algorithm can scientifically guide the time-segmented operation management of oilfield water injection systems, thereby reducing harmful gas emissions from the electricity demand side.