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Levels of automation

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The oil and gas industry is becoming more technologically advanced every day. As automation, artificial intelligence (AI) and robotics improve, it may be increasingly tempting to employ automatic means to accomplish industry goals. The degree to which a task is automated is referred to as levels of automation (LOA). The most comprehensive list was developed by Thomas B. Sheridan and W. L. Verplank[1]. Levels of automation range from complete human control to complete computer control.


Automation levels

Sheridan & Verplanck (1978) were one of the first to publish that automation is not ‘all or nothing’, that is, automation is not only a matter of either automating a task entirely or not, but to decide on the extent of automating it.

Sheridan and Verplank’s Scale of Human-Machine Interaction (revised):

1 Whole task done by human except for actual operation by machine

2 Human asks computer to suggest options and selects from the options

3 Computer suggests options to human

4 Computer suggests options and proposes one of them

5 Computer chooses an action and performs it if human approves

6 Computer chooses an action and performs it unless human disapproves

7 Computer chooses an action, performs it, and informs human

8 Computer does everything autonomously

Four-stage model of human information processing

Parasuraman, Sheridan, and Wickens[2] went on to introduce the idea of associating levels of automation to functions.

The four-stage model of human information processing includes:

  1. Sensory processing
  2. Perception and/or working memory[3]
  3. Decision making
  4. Response selection
Sensory processing
Refers to the acquisition and registration of multiple sources of information. This stage includes the positioning and orienting of sensory receptors, sensory processing, initial pre-processing of data prior to full perception, and selective attention.
Perception and/or working memory
Involves conscious perception,and manipulation of processed and retrieved information in working memory. This includes cognitive operations such as rehearsal, integration and inference, but these operations occur prior to the point of decision.
Decision making
Decisions are reached based on such cognitive processing.
Response selection
Involves the implementation of a response or action consistent with the decision choice.

These functions are based on a four-stage model of human information processing and can be translated into equivalent system functions[4]:

  1. Information acquisition
  2. Information analysis
  3. Decision and action selection
  4. Action implementation

The four functions can provide an initial categorization for types of tasks in which automation can support the human operator.

Information acquisition
Automation of information acquisition applies to the sensing and registration of input data.[2]
Information analysis
Automation of information analysis involves cognitive functions such as working memory and inferential processes.[2]
Decision and action selection
This stage, decision and action selection, involves selection from among decision alternatives[2]
Action implementation
This final stage of action implementation refers to the actual execution of the action choice.[2]

Levels of automation across any of the above functional types do not need to be fixed at the system design stage. Instead, the level of automation could be designed to vary depending on production demands during operational use.[2]

Human-centered automation

Automation should be human-centered. Billings detailed this in his book "Aviation automation: The search for a human-centered approach."[4]

  • Automation systems should be comprehensible.
  • Automation should ensure operators are not removed from command role.
  • Automation should support situation awareness.
  • Automation should never perform or fail silently.
  • Management automation should improve system management.
  • Designers must assume that operators will become reliant on reliable automation.


  1. Sheridan, T. B., & Verplank, W. L. 1978. Human and computer control of undersea teleoperators. Cambridge, Mass: Massachusetts Institute of Technology, Man-Machine Systems Laboratory. PDF
  2. 2.0 2.1 2.2 2.3 2.4 2.5 Institute of Electrical and Electronics Engineers., & IEEE Systems, Man, and Cybernetics Society. 2000. A Model for Types and Levels of Human Interaction with Automation. IEEE transactions on systems, man, and cybernetics: A publication of the IEEE Systems, Man, and Cybernetics Society. New York, NY: Institute of Electrical and Electronics Engineers. Vol. 30. No. 3.
  3. Baddeley, A. D. 1986. Working memory. Oxford [Oxfordshire: Clarendon Press.
  4. 4.0 4.1 Billings, C. E. 1997. Aviation automation: The search for a human-centered approach. Mahwah, N.J: Lawrence Erlbaum Associates Publishers.

Noteworthy papers in OnePetro

Krome, J. D., Bloom, M. H., Swanson, A. B., Anthony, D., Derise, S., & Rightmire, L. (2015, September 28). Revealing the Benefits of the Intelligent Well Pad Program for Onshore Shale Assets. Society of Petroleum Engineers.

Martin, J. T. (1970, January 1). Low-level Automation For Marginal Leases. American Petroleum Institute.

Million, C. L., & Bowler, D. L. (1969, November 1). Feasibility Study of Oilfield Automation. Society of Petroleum Engineers.

External links

Calefato, Caterina, Roberto Montanari, and Francesco Tesauri. "The Adaptive Automation Design." Human Computer Interaction: New Developments. 2008. The Human Factors and Ergonomics Society. Web.

Endsley, Mica R. "Level of Automation Effects on Performance, Situation Awareness and Workload in a Dynamic Control Task." Ergonomics 42.3. 1999: 462-92. North Carolina State University.

"Human-Centered Systems Engineering Design Approaches." Human Supervisory Control. Massachusetts Institute of Technology.

See also

Automated drilling

Digital oilfields

Drilling automation

Human factors