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Hosted with thanks to our Platinum sponsor Schlumberger
And Gold Sponsors Katalyst Data Management and Applied Geoscience
In recent years, major national and international E&P companies such as BP, ADNOC, Equinor, ENI, Shell among many others have been reporting enhanced operational efficiencies and substantial incremental production due to the implementation of digital technologies. Now, when we are emerging from a period of severe cost cutting, the capabilities of digital technologies to introduce significant Capex and Opex efficiencies are more compelling than ever.
This session will describe a recently developed workflow comprising of the latest high performance cloud computing technology, AI/ML algorithms and deep domain & data science to generate subsurface-to-economics “agile” digital models. The workflow enables a robust stochastic assessment of the impact of uncertainties associated with field development planning on asset economics and maximizes the value of data and the know-how of the asset team to optimize field production performance.
Agile subsurface-to-economic modeling has been applied in multiple fields around the globe reducing the time required for field development planning between 70 to 80%. An example of the workflow implementation in Australia involved running 12 subsurface production cases with 100 realizations each (1200 realizations in total) and utilizing them for the assessment of the economics of 24 field development scenarios in just 4 days. This allowed the field development team to have an almost-immediate insight into the development scenarios that would be most attractive to take forward for the next stages of the development process, while quickly discarding uneconomic options.
Ticket Prices:
Please note changes to the end of early bird pricing which now closes 1 week prior
Member (Early Bird): $69.00
Concession Member [Retired, Graduate or Hardship] (Early Bird): $59.00
Student Member (Early Bird): $39.00
Non-Member: $99.00
Member (Non-Early Bird): $79.00
Early bird pricing ends Thursday (1 week prior) at 5pm (AWST). All ticket sales close at 5pm Tuesday (2 days prior).