Bringing the Sucker Rod Pumping Unit into the Classroom with the Use of the Internet of Things

Abstract

Artificial lift and particularly sucker rod pumping units are the most applied technologies for oil wells. While the equipment as such requires strong mechanical background, the use of the equipment remains solely the responsibility of petroleum engineers. Teaching them the working principles and functions of the equipment could be a challenging process when using only classroom related tools such as multimedia, short pieces of equipment, etc. As a response to this shortcoming, a new laboratory has been developed at the University of Oklahoma, which includes a large-scale pumping unit that is capable to be programed to simulate any situation in real time and use the Internet of Things to gather real time data and create tailored diagnostic tools that students and laboratory staff can utilize for many applications. This paper focuses on the need to add a hands-on teaching experience to the classroom, and what type of data can be mined and used to accomplish specific objectives. It is required for our future petroleum engineers that they know how to apply basic industry principles and increase problem solving skills involving machinery. The proposed laboratory would be capable to deliver all standard monitored parameters of a sucker rod pumping unit to any classroom through a networked connection and allow the students to make decisions or experiment in real time with the setup. By being a large-scale setup, students can easily observe how the unit works, visualize downhole pumping operations, identify where the sensors are placed, and learn how to use raw data for any intended purpose. In other words, the entire artificial lifting process can be seen and operated from any classroom on campus remotely, and advanced analysis can be performed by the students or staff.