Application of acidification parameter optimization method. Issue 5 (February 2020)

• Record Type: Journal Article
• Authors: Liu, Qilun; Cao, Jiefeng; Long, Changjun; Zeng, Zhiguo; Liu, Wenge; Zhang, Yingying; Su, Dandan; Zhang, Xu; Jia, Jiangfen; Huang, Bohua
• Is Part Of: IOP conference series. Volume 446:Issue 5(2020)
• Publication Date: 2020-02
• Subjects: Earth sciences -- Periodicals; Environmental sciences -- Congresses; Environmental sciences -- Periodicals; 550.5
• DOI: 10.1088/1755-1315/446/5/052032
• Languages: English
• ISSNs: 1755-1307

Abstract

Abstract: The acidification technology is an important measure to increase the production and increase the injection of oil and water wells. However, due to the complicated working conditions of the acidification measures and the difficulty in determining the construction parameters, it is necessary to establish the acidification model of the injection wells and optimize the parameters. The paper uses the grey correlation analysis method to find the correlation between each construction parameter and the daily injection volume of the injection well, establishes the BP neural network program, trains it according to the existing data and predicts the artificial controllable parameters in turn to find the best construction parameter combination. Taking a single well as an example to predict the parameters and guide the on-site construction. The results show that combining the mathematical method with the acidification construction technology of the injection well and establishing the model prediction parameters can significantly improve the injection efficiency of the injection well.