Optimization of the depressurization rate and stepwise strategy for hydrate exploitation using a genetic algorithm-based depressurization method

Abstract

Depressurization is one of the most effective methods for hydrate exploitation. Optimization of the pressure-drop strategy for improving the exploitation efficiency requires immediate attention. In this study, a hydrate decomposition model was for the first time combined with a genetic algorithm. The pressure-drop rate and strategy were optimized based on the exploitation efficiency. The depressurization rate of the continuous slow depressurization method was optimized. Subsequently, the best pressure-drop rate for stepwise depressurization was hypothesized and validated. In addition, the stepwise strategy was optimized. For the two depressurization methods, increasing the pressure-drop rate increased the exploitation efficiency, while increasing the number of pressure-drop stages in the stepwise depressurization method adversely impacted the exploitation efficiency. Prolonged constant-pressure intervals reduced the efficiency when there were few pressure-drop stages; however, the opposite trend emerged for a high number of depressurization steps. This study provides guidance for optimizing the production efficiency of hydrate exploitation via depressurization.