Gas Hydrate Pipeline Is Optimized: Levy Flight, Cauchy Mechanism, and Perception Probability

Abstract

Pipelines used for the hydraulic lifting of gas hydrate particles in deep-sea gas hydrates consume a large quantity of energy, so the level of efficient resource exploitation is very low and it is challenging to meet an efficient gas supply. Therefore, the article aims to optimize and analyze a process used for rigid pipe hydraulic lifting, an essential part of a deep-sea gas hydrate extraction system. First, the objective function is constructed considering the relationship between the extraction system’s parameters, and a specific energy consumption is set when the deep-sea gas hydrate extraction is under consideration. Then, the range of each parameter is determined according to the extraction system's actual situation. Secondly, the improved crow search algorithm with a hybrid strategy covering dynamic perception probability, Levy flight, and Cauchy variation mechanism is employed to solve the optimization model. Finally, the improved crow search algorithm is applied to the experimental settings and compared with other optimization algorithms. The experimental results show that the proposed method, which is, the improved crow search algorithm, has a good computational efficiency, can effectively realize the optimization of the parameters of the deep-sea natural gas hydrate system, and is robust to numerical fluctuations of the parameters. Thus, the performance of the pipeline is improved and the energy consumption of the system is effectively reduced. Eventually, a theoretical reference is provided for the development of deep-sea gas hydrate. The proposed algorithm, I-CSA, can effectively deal with larger sample data and maintain high computational efficiency with fewer MAPE results when the sample sizes increase. Eventually, it is helpful for the deep exploitation and utilization of deep-sea gas hydrate.