Calculation on hanging-point dynamometer card characteristic parameters of sucker-rod pumping unit in a directional well based on ANN

Calculation of hanging-point dynamometer card characteristic parameters is important to the selection of mechanical and electrical equipment for sucker-rod pumping system. However, it is difficult to obtain an accurate result by way of the traditional method of solving high-dimensional and time-variable nonlinear equations, because of the unpredictability of down-hole working condition and the difficulty of determining some parameters such as friction force and viscous damping parameters in directional well. In this paper, a method combining the traditional means and the artificial neural network (AAN) is put forward to calculate the hanging-point dynamometer card characteristic parameters of sucker-rod pumping system in directional well, which avoids establishing and solving nonlinear equations. First, the simplified dynamometer card is calculated based on the traditional method. Then, by means of the BP and RBF artificial neural network, a model is established for calculating the hanging-point dynamometer card characteristic parameters for different working conditions, which takes into account the influences of elastic vibration of rod-string, coulomb friction and viscous damping between rod and tube, as well as gas effect. The network is trained and validated with the system's working condition monitoring data, which shows that the present method is correct and effective.