The Impact of Styles of Thinking and Cognitive Bias on How People Assess Risk and Make Real-World Decisions in Oil and Gas Operations
Awareness of the psychological realities of different styles of thinking can provide deep understanding of the choices people make and the actions they take when they are faced with assessing risk and making decisions in real time under operational conditions. At a time when the industry is striving to achieve more with fewer staff and resources, there is a compelling need to understand better how these psychological processes actually influence real-world operations, and to develop practical approaches to mitigating the associated risks.
While there have been previous attempts to apply this area of knowledge to the analysis of real-world incidents and to develop operational interventions, such attempts have been limited to date, and have lacked the necessary research evidence. Written from a psychological perspective, the purpose of this paper is to illustrate how such knowledge can be operationalized and used to gain deeper understanding of the nature of human error in real-world oil and gas operations.
Establishing Data Ethics in Oil and Gas Operations
The use of data-intensive decision making and smart risk-management solutions has resulted in the improvement of the ethical foundations underlying the industry. These digital tools and machine-based cognitive processes for risk-avoidance have also helped restore the public’s trust in the industry.
Should Cybersecurity Drive Business Decisions?
Cyberattacks are often seen as an IT issue, but the intelligence gained during the development of an effective cybersecurity protocol may serve a broader role as a business driver for energy. What should companies look for in assessing threats?
AI Aims To Predict Operational Behaviors, Alert of Potential Hazards
Unstructured data, such as process logs, safety reports, and public records, make up the bulk of data produced from the oil field. Emerging NLP technology has been designed to help make sense of this data, enabling better insights into near-accidents.
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