Electrical Engineering
      and Computer Sciences

Electrical Engineering and Computer Sciences

COLLEGE OF ENGINEERING

UC Berkeley

Supervisory Control and Data Acquisition System Design for CO2 Enhanced Oil Recovery

XIE LU

EECS Department
University of California, Berkeley
Technical Report No. UCB/EECS-2014-123
May 21, 2014

http://www.eecs.berkeley.edu/Pubs/TechRpts/2014/EECS-2014-123.pdf

Supervisory control and data acquisition (SCADA) are essential for oilfield operations. Currently available SCADA systems often do not incorporate recent technological advances that allow efficient network administration, over-the-air (OTA) programmability, and easy scalability to thousands of locations. Additionally, today's SCADA systems are not cost-effective for wells with low production rates such as CO2 enhanced oil recovery (EOR). This paper proposes a SCADA system design that is based on a popular hybrid single-board computer. The controller is connected to a local wireless Ethernet/IP network with a secure IP-addressable radio and subsequently to the corporate intranet at the field central processing facility. The hybrid acts as a powerful and low-cost core for the controller. It is programmable in Python, and it is flexible, with provisions for digital outputs and most sensor inputs, as well as wireless sensor connections over Wi-Fi or Xbee radio standards. Sensor data are acquired and processed prior to being uploaded to a central database. To access the wellhead data, users log into a web-based graphical user interface (GUI). Similarly, the network structure allows users with proper permissions to send commands to, reprogram, and access the file system of individual controllers. Furthermore, the system applies an optimized control algorithm for sucker-rod pumps based on the Everitt-Jennings algorithm. A prototype unit was deployed in a North Dakota oilfield with a total material cost of less than $1000. The system has applications in the oilfield beyond artificial lift control and wellhead sensing. With appropriate programming, the same hardware can be used for tank level monitoring, process condition monitoring, and alarming. The high level of control and programmability allows for efficient responses to dynamic oilfield conditions.

Advisor: Ruzena Bajcsy and Donald Wroblewski


BibTeX citation:

@mastersthesis{LU:EECS-2014-123,
    Author = {LU, XIE},
    Title = {Supervisory Control and Data Acquisition System Design for CO2 Enhanced Oil Recovery},
    School = {EECS Department, University of California, Berkeley},
    Year = {2014},
    Month = {May},
    URL = {http://www.eecs.berkeley.edu/Pubs/TechRpts/2014/EECS-2014-123.html},
    Number = {UCB/EECS-2014-123},
    Abstract = {Supervisory control and data acquisition (SCADA) are essential for oilfield operations. Currently available SCADA systems often do not incorporate recent technological advances that allow efficient network administration, over-the-air (OTA) programmability, and easy scalability to thousands of locations. Additionally, today's SCADA systems are not cost-effective for wells with low production rates such as CO2 enhanced oil recovery (EOR). This paper proposes a SCADA system design that is based on a popular hybrid single-board computer. The controller is connected to a local wireless Ethernet/IP network with a secure IP-addressable radio and subsequently to the corporate intranet at the field central processing facility. The hybrid acts as a powerful and low-cost core for the controller. It is programmable in Python, and it is flexible, with provisions for digital outputs and most sensor inputs, as well as wireless sensor connections over Wi-Fi or Xbee radio standards. Sensor data are acquired and processed prior to being uploaded to a central database. To access the wellhead data, users log into a web-based graphical user interface (GUI). Similarly, the network structure allows users with proper permissions to send commands to, reprogram, and access the file system of individual controllers. Furthermore, the system applies an optimized control algorithm for sucker-rod pumps based on the Everitt-Jennings algorithm. A prototype unit was deployed in a North Dakota oilfield with a total material cost of less than $1000. The system has applications in the oilfield beyond artificial lift control and wellhead sensing. With appropriate programming, the same hardware can be used for tank level monitoring, process condition monitoring, and alarming. The high level of control and programmability allows for efficient responses to dynamic oilfield conditions.}
}

EndNote citation:

%0 Thesis
%A LU, XIE
%T Supervisory Control and Data Acquisition System Design for CO2 Enhanced Oil Recovery
%I EECS Department, University of California, Berkeley
%D 2014
%8 May 21
%@ UCB/EECS-2014-123
%U http://www.eecs.berkeley.edu/Pubs/TechRpts/2014/EECS-2014-123.html
%F LU:EECS-2014-123