Application of Artificial Neural Network to Pump Card Diagnosis

Abstract

Beam pumping is the most frequently used artificial-lift technique for oil production. Downhole pump cards are used to evaluate performance of the pumping unit. Pump cards can be generated from surface dynamometer cards using a 1D wave equation with viscous damping, as suggested by Gibbs and Neely. Pump cards contain significant information describing the behavior of the pump. However, interpretation of these cards is tedious and time-consuming; hence, an automated system capable of interpreting these cards could speed interpretation and warn of pump failures. This work presents the results of a DOS-based computer program capable of correctly classifying pump cards. The program uses a hybrid artificial neural network (ANN) to identify significant features of the pump card. The hybrid ANN uses classical and sinusoidal perceptrons. The network is trained using an error-back-propagation technique. The program correctly identified pump problems for more than 180 different training and test pump cards. The ANN takes a total of 80 data points as input. Sixty data points are collected from the pump card perimeter, and the remaining 20 data points represent the slope at selected points on the pump card perimeter. Pump problem conditions are grouped into 11 distinct classes. The network is capablemore » of identifying one or more of these problem conditions for each pump card. Eight examples are presented and discussed.« less