Neural Network Control for Column Processing System of the Four-Single Pipe Rig

Abstract

With the oil and gas exploration, the drilling is developed toward the deeper and more complex stratigraphic, the number of super deep well has been continued growth. In order to improve the tripping efficiency of deep wells and complex wells, equipment manufacturers develop four-single pipe rig to reduce the times of make-and-break during tripping, tripping operations efficiency is greatly improved. The four-single pipe rig is 10 meter higher than three single pipe conventional rig, pipe rack size of four-single pipe rig is smaller which be decision by K type derrick structure, so it is asked the control precision of the pipe string processing system is more higher, the conventional PID control precision cannot meet the requirements of the pipe string movement system. Combined with PID control in real-time data, pipe string position data and pipe string moving model, embedded in the physical model of artificial neural network adaptive control algorithm is established, and the model error sensitivity of propagation equation is derived. Simulation results show that the model has higher accuracy, robust adaptable, can meet the pipe moving automatic control system requirements of the four-single pipe rig.