Problem Statement

The current climate in the upstream Oil and Gas industry is making us face up to the challenge of radically reducing our OPEX but how can we achieve this without compromising on safety.

Improvements in Technology and the tsunami of Big Data has left our decision makers Drowning in Data and Thirsting for Knowledge. How can we provide the necessary information for decisions to be taken and shorten the time from detection to implementation? Is near real-time decision making possible?


Demonstrate how the "Internet of Things" can be applied to the Human Machine Interface (HMI) to enable people to speed up responses.

Map out the route to decision making maturity by looking at where we start and what needs to be achieved along the road. We examine the basic components required for efficient decisions and discover how thing have changed over the years as pilot schemes have been developed into mature operational facilities.

Show how digital technology has speeded up decision making to near real-time and how it is paving the way for automatic processing of repetitive problems.

Finally we will look at where collaborative decision making is going and investigate the trends and advances in the industry.


  • Harnessing the power of big data and how we make sense of it

  • Using Exception Based Surveillance and how we can Increase Production and Reduce Deferment

  • Predictive Analytics and Risk Based Maintenance.

  • We will use examples from the Middle East where decisions were made "in the cloud."


  • Early attempts relied on technology and failed to develop the HMI.

  • Lessons were learned

  • Continuous improvement was evident

  • There is an appetite on the part of operators to embrace this way of working


What started out as an IT solution has now been focused on enabling people to work within automated processes to make decisions faster.

The tangible benefits of faster decision making include increased production and reduced deferment.

The intangible benefits have provided better working environments and a more motivated workforce.


This approach can be used for subsurface and surface teams and encourage cross functional cooperation. Examples are given for the Middle East, UK North Sea, Africa and the Far East.


  1. Monitor by exception and deliver better visualisation.

  2. Big data solutions in the connectivity of disparate databases.

  3. Data and information fed to the operator through automated workflows.

  4. Standard non critical decisions made automatically.

Significance of Subject Matter

This should be the normal way of working to take real-time data and translate it into meaningful information for managers to take key decisions.

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