Leveraging Alberta’s Oil & Gas Advantage to Support the Green Economy-Mike Kennedy


  • Alberta’s Oil & Gas Resource
  • Examine the current and future footprint
  • Strategies to leverage this footprint
  • BRIMS as a key Big Data resource for the province

Green Analytics Role

  • Leading the development of data and information systems
  • Identify key strategies and opportunities for governments and business to play a role in the green economy
  • Analyzing opportunities for socio-economic and environmental benefits
  • Communicating opportunities, benefits and challenges to a broad audience Green Analytics Role

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Analytics in the Oil and Gas Industry by Dean Wallace

Fallacies Arising from the Simplest Form of Analysis – The Infamous “Average”

An argument can be made on the same basis that the tree frog, on average, is black. However, this analysis is about as relevant as the knowledge drawn from overly-simplistic mathematical calculations that often are carried out on large data sets.


Analytics as the Solution – The Production Intelligence Suite of Analytics Solutions

  • Objective was to understand the effect of interactions on end-of-line measures (e.g. recovery) for the purpose of optimizing the process
  • It was necessary to consider a probabilistic solution in addition to deterministic solutions
  • Required a solution that was not biased by the individual doing the modeling
  • Association Discover*E was an appropriate tool for this application
  • Data-driven rule generation provides an unbiased perspective
  • Rule structure results in transparency so people can assimilate knowledge developed in the analytics process
  • Transparency also results in identification of correlation of supposedly independent variables
  • Allows for simultaneous analysis of quantitative and descriptive variables
  • Possibly a precursor to a control system without human intervention


Closing Comments

  • We have found that a statistically-based analytics approach has been able to unlock knowledge about the oil sand extraction process that was not possible using conventional statistical techniques and/or deterministic modeling
  • Elimination of bias during the process and transparency of the results are critical
  • Analytics has led in some cases and has collaborated in others with subject-matter expertise
  • The nature of the process being modelled determines if analytics can provide value
  • Frequency of the data must be much greater than the frequency of actions
  • The greater the influence of interactions on the process, the greater the value of or necessity for an analytics solution


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