Research on Oil Well Production Prediction Based on Radial Basis Function Network

¹ Engineering Technology Research Institute, Xinjiang Oilfield Company, 834000, China
² School of Sciences, Southwest Petroleum University, Chengdu, Sichuan, 610500, China

^* Corresponding Author: Yunwei Kang; email: kangyunweiSWPU@163.com; phone:15281856277

Abstract

Selection of well and reservoir is an important step in the process of stimulation and transformation of oil fields. Good measures can effectively save the cost in the process of oil field development and greatly increase the production of oil fields. Aiming at the problem of well and reservoir selection in petroleum engineering, a method of oil well production prediction based on radial basis function network is proposed in this paper. According to the field data of Xinjiang oilfield, the main controlling factors with greater influence are selected by correlation analysis after data pretreatment. Then we randomly divide the data into training data set and prediction data set, and use the training data set to create a radial basis function network. Finally, we use the radial basis function network to predict the prediction data set, and the final prediction accuracy reaches 80%.