Research on Intensive Management Mode of Oil and Gas Metering in Long-distance Pipeline Based on Ant Colony Optimization Algorithm

In recent years, China's social and economic growth is very rapid, and people's production and living standards are constantly improving. In this context, the demand for oil and gas energy is increasing day by day. In order to ensure the safety and stability of oil and gas energy supply, it is necessary to improve the intensive management quality of oil and gas metering in long-distance pipelines. Therefore, this paper constructs an intensive management model of oil and gas metering in long-distance pipeline based on ACO (Ant Colony Optimization) algorithm. The algorithm model takes the pipe network as individual particles, and searches for the optimal solution by constantly updating the positions of particles. By controlling the ant state transition process, constraints such as well type, gathering and transfer radius, and throughput of metering station are ensured, which effectively avoids the generation of infeasible solutions. The final test results show that the accuracy of the ACO algorithm proposed in this paper can reach 95.84%, which is about 11 % higher than that of the traditional method. This shows that the optimization results based on ACO algorithm are improved compared with the existing traditional algorithms in the intensive management of oil and gas metering in long-distance pipelines. In order to provide some technical support for the intensive management mode of oil and gas metering and the optimal design of oil and gas gathering and transfer pipeline network in the future.