Optimization of Gas Injection Network Using Genetic Algorithm: A Solution for Intermittent Gas Lift Wells

Multiple intermittent gas lift (IGL) wells are typically connected to a centralized high-pressure gas source, which can result in significant fluctuations in gas injection header pressure and subsequent liquid surges in the well fluid header when gas injection is initiated simultaneously in multiple wells. To address the challenge of gas injection interference among intermittent gas lift wells, we propose a mathematical model that utilizes genetic algorithm to optimize the staggering of time cycles, with the goal of achieving minimal interference. Genetic algorithms approach provides an effective optimization technique for addressing the time cycle staggering in intermittent gas lift wells. The algorithm involves creating a population of potential solutions, representing each solution as a set of genes or chromosome. In the context of this model, the gas injection time slots for each well are encoded as chromosomes. The developed model utilizes input gas injection time cycles, to compute the best possible time slots for each well. By leveraging the principles of natural selection and evolution, the model iteratively computes the best possible time slots for each well, continuously improving the solutions until convergence is reached. This approach minimizes gas injection interference and enhances the efficiency of gas lift operations. The current field practice involves manually staggering the time cycle slots to minimize interference among wells, which becomes impractical with increased well and time slot numbers. Our developed model based on genetic algorithm optimization approach offers an automated and efficient solution for time cycle staggering in intermittent gas lift wells. Despite the NP-hard (non-deterministic polynomial-time hardness) nature of the problem, genetic algorithms provide an effective means of generating near-optimal solutions within a reasonable computational time. By minimizing gas injection interference, this optimization technique enhances the overall efficiency of gas lift operations, preventing production losses. Application of the developed model in the onshore oil field of ONGC demonstrated a significant reduction in gas injection header pressure fluctuations which improved the overall performance of the gas lift system. In this study effect of manually staggered gas injection time cycle, on gas injection network pressure fluctuations is also analysed. The population of wells employing intermittent gas lift mode is progressively growing as oil fields undergo browning. This advancement in optimization methodology holds great promise for the oil and gas industry, facilitating the optimization of gas injection time cycle slots leading to reduced pressure fluctuations and improved production efficiency.