Study On Spatial Growth Law Of Tetrahydrofuran-Methane Binary Hydrate

Natural gas plays a major role in improving energy structure with its high-quality,highefficiency and high-cleanliness.However,most natural gas resources are far away from resource consumption areas.Therefore,technology of storing and transporting natural gas safely and efficiently will be the focus of natural gas industry research in future.Natural gas hydrate storage and transportation technology is expected to become the best choice for the natural gas storage and operation industry due to its advantages in safety,economy and technical reliability.Although the natural gas hydrate storage and transportation technology has considerable advantages as mentioned above,it still faces outstanding problems such as the slow hydrate formation process,which will hinder the development of this technology in practical applications.First of all,tetrahydrofuran-natural gas hydrate phase equilibrium prediction models were established in this paper and those models had been well tested and evaluated.Subsequently,visualization experiments on the growth characteristics of tetrahydrofuran（THF）-methane（CH₄）hydrate were launched on the basis of the established model.Finally,the spatial distribution of THF-CH₄ hydrate in the reactor was explored and experiments on the regulation of the spatial distribution of hydrate were carried out.In this paper,temperature prediction model of natural gas hydrate phase equilibrium with THF and NaCl additives were established based on ensemble learning algorithms.The prediction results show that the random forest temperature model has a higher generalization ability than gradient boosting decision tree and automatic machine learning temperature model.However,the gradient boosting decision tree temperature model has the most accurate prediction results for the experimental temperature.In addition,the Friedman test and Nemenyi’s follow-up test results demonstrated that the overall performance of the gradient boosting regression tree temperature model was the best one.Furthermore,there were no significant difference between random forest and automatic machine learning algorithms.Gradient boosting regression tree algorithm was used to predict the phase equilibrium of THFCH₄ hydrate where THF solution was under the concentration of 5.56% mol.After obtaining the THF-CH₄ hydrate phase equilibrium,this paper carried out a total of 9groups of visual experiments on the formation of THF-CH₄ hydrate under the conditions of experimental temperature and pressure of 283.2 K and 3 MPa,respectively.Through visual observation it can be found that the early stage of THF-CH₄ hydrate growth mainly includes three processes: firstly,THF and CH₄ form a saturated hydrate layer at the gas-liquid interface;then CH₄ passes through the hydrate layer and further reacts with the solution,and the hydrate layer begins to grow downward;at the same time the hydrate layer starts growing upward and the rate is much faster than downward growth.In addition,in the experiment with a solution volume of 250 mL,the hydrate growth rate was the fastest,the induction time and t₉0 were the shortest,which was the best gas-water ratio under the experimental conditions.The spatial distribution and evolution of THF-CH₄ hydrate in reactor were explored with two gas injection modes at relatively mild operating conditions.Three occurrences of THF-CH₄ hydrate in the reactor were observed in the mode of constant volume multiple gas injection mode.In the 3 MPa constant pressure gas injection mode,the THF-CH₄ hydrate column was composed of two layers of hydrates,a white layer and a transparent layer.Hydrate decomposition experiments confirmed that the white layer contained more methane molecules.In addition,in the constant pressure gas injection mode,the space utilization rate and gas storage capacity of the reactor reached 89% and 87.55（V/V）respectively.The growth control experiment of THF-CH₄ hydrate showed that the method of progressively decreasing liquid injection in batches can effectively control the hydrate column morphology and the space utilization rate of the reactor can reach 98.63%.