基于GA-SVR算法的CO_(2)在地层水中溶解度模型研究  

Study on CO_(2)solubility model based on GA-SVR algorithm in formation water

作　　者：刘洋[1] 王长权[1,2] 石立红 龙震宇[1] LIU Yang;WANG Chang-quan;SHI Li-hong;LONG Zhen-yu(Department of Petroleum Engineering,Yangtze University,Wuhan 430100,China;Hubei Key Laboratory of Oil and Gas Drilling and Production Engineering,Wuhan 430100,China)

机构地区：[1]长江大学石油工程系,湖北武汉430100 [2]油气钻采工程湖北省重点实验室,湖北武汉430100

出　　处：《应用化工》2021年第S01期18-23,共6页Applied Chemical Industry

基　　金：国家自然科学基金(51404037)。

摘　　要：利用高温高压反应釜开展了不同温度、压力条件下CO_(2)在不同矿化度地层水中的溶解度实验,采用支持向量回归(SVR)和遗传算法(GA)建立模型(GA-SVR)来计算CO_(2)在地层水中的溶解度大小,利用实验溶解度数据对GA-SVR模型进行训练和验证。结果表明,GA-SVR模型预测结果的相对误差最小为1.60%,最大为3.73%,平均为2.46%,均方根误差为0.094,与其他3种模型(Chang模型、Furnival模型和PR-HV模型)计算结果相比,GA-SVR模型具有更高的精度。该研究成果为CO_(2)在地层水溶解度的计算提供了一种新方法。Using high temperature and high pressure reaction kettle carried out under different conditions of temperature and pressure of CO_(2)in different salinity formation water solubility experiment,using support vector regression(SVR)and genetic algorithm(GA)to establish a model(GA-SVR)to calculate the solubility of CO_(2)in the formation water size,solubility data of experiment is used to analyse the GA-SVR model training and validation.The results show that the relative error of GA-SVR model is 1.60%,3.73%at most,2.46%on average,and 0.094 at root mean square.Compared with the calculation results of the other three models(Chang model,Furnival model and PR-HV model),the GA-SVR model has higher accuracy.The research results provide a new method for the calculation of the solubility of CO_(2)in formation water.

关 键 词：CO_(2) 地层水 高温高压反应釜 溶解度 支持向量回归 遗传算法 

分 类 号：TE357[石油与天然气工程—油气田开发工程]