Application of support vector machine in drag reduction effect prediction of nanoparticles adsorption method on oil reservoir's micro-channels

作者：Di Qin-feng^*; Hua Shuai; Ding Wei-peng; Gong Wei; Cheng Yi-chong; Ye Feng

来源：Journal of Hydrodynamics, 2015, 27(1): 99-104.

DOI：10.1016/S1001-6058(15)60461-9

• nanoparticles adsorption method
• support vector machine (SVM)
• prediction model
• rapid evaluation
• enhanced oil recovery

Due to the complexity of influence factors in the nanoparticles adsorption method and the limitation of data samples, the support vector machine (SVM) was used in the prediction method for the drag reduction effect. The basic concept of SVM was introduced, and the epsilon - SVR programming for the kernel function on the radial basis was established firstly with the help of the MATLAB software. Then, an analysis was made for the influencing factors of the drag reduction effect in nanoparticles adsorption. Finally, a prediction model for the drag reduction effect of nanoparticles was established, and the accuracy of training sample and prediction sample was analyzed. The result shows that the SVM has good availability and can be used as a rapid evaluation method of the drag reduction effect prediction of nanoparticles adsorption method.

• 出版日期2015-2
• 单位上海大学