内容：
 天然气水合物(以下简称水合物)具有高储气率和高可靠性等优点,在天然气储存及运输方面具有广泛的应用前景,同时水合物的存在也会给输气管道带来堵塞等严重影响,因此对水合物的生成研究具有重要意义。为此,对Ⅰ型水合物在无添加剂条件下的静态生成规律进行了研究。首先基于水合物动力学实验装置进行一系列实验,然后利用支持向量机(SVM)结合遗传算法(GA)建立了水合物生成预测模型(SVM+GA)。据此将实验中得到的温度和压力数据进行预测和优化处理,并对上述数据进行非线性拟合,得出了相平衡曲线及其方程,计算得出了常温下生成水合物的相平衡压力为33.5 MPa,常压下生成水合物的相平衡温度为237.1 K。将分别由SVM+GA模型、Chen-Guo模型和vd W-P热力学模型所得到的数据与经典的实验数据进行了对比,其平均相对误差分别为2.678%、1.447%和3.249%。结论认为:SVM+GA模型具有较高的计算准确度,比Chen-Guo模型和vd W-P热力学模型更为简便,可为水合物开发研究提供更多的数据。 Natural gas hydrate (hereinafter referred to as hydrate) has the advantages of high gas storage rate and high reliability, and has wide application prospect in natural gas storage and transportation, and the presence of hydrate can cause serious obstruction to gas pipeline , So the formation of hydrate research is of great significance. In this paper, the static generation of type I hydrate in the absence of additive was studied. (SVM + GA) was established by using support vector machine (SVM) combined with genetic algorithm (GA), based on a series of experiments on hydrate kinetic experiment. According to this, the temperature and pressure data obtained in the experiment are predicted and optimized, and the data is nonlinearly fitted. The phase equilibrium curve and its equation are obtained. The equilibrium equilibrium pressure of hydrate formation at room temperature is calculated Is 33.5 MPa, and the phase equilibrium temperature of the hydrate formed under normal pressure is 237.1 K. The data obtained by SVM + GA model, Chen-Guo model and vd W-P thermodynamics model are compared with the classical experimental data, the average relative error is 2.678%, 1.447% and 3.249% respectively. It is concluded that the SVM + GA model has higher computational accuracy than the Chen-Guo model and the vd W-P thermodynamic model, which can provide more data for hydrate development research.

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