Education Days Houston 2019
|November 2019||Mitigating Bias, Blindness and Illusion in E&P|| Creties Jenkins, Texas USA
|November 2019||Integrated Seismic Acquisition and Processing||Jack Bouska, Calgary, Canada||2 Days|
|November 2019||Challenges and Solutions in Stochastic Reservoir Modelling - Geostatistics, Machine Learning, Uncertainty Prediction||Vasily Demyanov, UK||2 Days|
|November 2019||Seismic Fracture Characterization: Concepts and Practical Applications||Enru Liu, Texas, USA||1 Day|
Mitigating Bias, Blindness and Illusion in E&P Decision Making
Creties JenkinsCourse description
Decisions in E&P ventures are affected by cognitive bias, perceptual blindness, and various forms of illusion which permeate our analyses, interpretations and decisions. This two-day course examines the influence of these cognitive pitfalls and presents techniques that can be used to mitigate their impact.
"Bias" refers to errors in thinking whereby interpretations and judgments are drawn in an illogical fashion. "Blindness" is the condition where we fail to see an unexpected event in plain sight. "Illusion" refers to misleading beliefs based on a false impression of reality.
All three—Bias, Blindness, and Illusion--can lead to poor decisions regarding which work to undertake, what issues to focus on, and whether to continue investing time, effort, and money in a given project.
The course begins by examining how these cognitive errors affect us. Several different errors are discussed, including: Perceptual Blindness; Illusions of Potential, Knowledge and Objectivity; and Anchoring, Availability, Confirmation, Framing, Information, Overconfidence and Motivational Biases. Exercises, videos, and examples help illustrate how these manifest themselves in our daily activities and affect our judgment, often without us realizing it. We then focus on the oil and gas industry where drilling portfolios, production forecasts, resource assessments, and other activities are regularly impacted. Techniques are presented that can be used to mitigate cognitive errors and examples are shown where these techniques have worked.
A key element of the course are the mitigation exercises which give participants a chance to apply what’s been learned to real-life situations. For example, what elements of the “anchoring bias” led to the belief that the exploration potential of a prospect offshore Brazil was much greater than it turned out to be? Or, what elements of the “confirmation bias” led to a decision regarding which analogous data should be used to predict the outcome of a new drilling project?
The second day includes a series of exploration and appraisal case studies resulting in both positive and negative outcomes. Participants are asked to identify cognitive errors contributing to the project results, and which of these had the greatest impact. This is followed by a 3-hour, real-world exercise using project data to give participants practice in addressing cognitive errors. The exercise requires participants to list all of their assumptions followed by a list of the contrary assumptions. This is followed by an assessment of the impacts if the contrary assumptions are true, and what key types of data / analyses will be required to determine which set of assumptions are correct. Finally, the participants identify cognitive errors leading to the actual project outcome.
The course concludes by presenting a summary ‘toolkit’ with mitigation techniques that can immediately be applied to project work and decisions. This includes a laminated card listing the various types of bias, blindness and illusion on one side, and the six key steps to mitigate these cognitive errors on the flip side. This helps participants immediately apply the concepts to their daily work.
This course is designed to have broad appeal to all levels and disciplines within an organization: junior to senior level geoscientists, junior to senior level engineers, analysts, landmen, HSE, HR, etc. And mid-level to senior managers and executives.
Integrated Seismic Acquisition and Processing
Mr Jack Bouska
Challenges and Solutions in Sctochastic Reservoir Modelling - Geostatistics, Machine Learning, Uncertainty Prediction
Dr Vasily Demyanov
For more information and tailored advice, please visit our Education portal.