Identification of Indicator Diagram Type in the Oil Well by BP Neural Network

Abstract

Wax sticking in oil wells has always been a difficult problem in oil exploitation. Wax sticking in oil wells exists not only in the exploitation stage, but also in every link of oil production. Accurate identification of indicator diagram type is very important to prevent oil well wax sticking. In this paper, a BP neural network method is proposed to identify indicator diagram types. This model makes full use of indicator diagram data, simplifies complex mechanism research, and has wider practicability. Through the calculation of an example, the BP neural network established in this paper can accurately identify the type of indicator diagram.