QuickField.ai
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Engineering Power Without the Complexity

New week - new updates!

Strong engineering does not always require overcomplicated interface and workflow. We bet, those who had an experience of creating field development plan from scratch will be expert in QuickField.ai for 10 min (and as a bonus, will get much more detailed insights than with traditionally used analog based approach).

#MachineLearning#OilAndGas#ReservoirEngineering#DataScience#RecoveryFactor#DigitalTwin#FDP#ProductionForecast#OilProduction

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Hi everyone! We're happy to share some new updates:

  1. Scenarios can now be calculated in tons or barrels.
  2. The interactive well planning tool now includes an option to visualize infrastructure capacity constraints.
  3. Attribute distributions now support different types: normal and uniform.
  4. Monte Carlo analysis and sensitivity charts now incorporate the impact of petrophysical properties on the recovery factor and cumulative oil production at the well level.
  5. We have fixed several bugs related to scenario export, and ton/barrel units are now fully supported.

We're truly inspired by the feedback we receive, which keeps QuickField.ai moving forward. It's exciting to see how small improvements can make the entire workflow easier and more intuitive.

For those who haven't heard about us yet, we are building an application that offers an alternative to the traditional analog-based approach to evaluating oil reservoirs, even before production starts.

With QuickField.ai, you can skip time-consuming steps such as exploring raw, unstructured data, performing manual analysis, and searching for the best analogs. To begin an assessment, you only need a few petrophysical parameters.

Create an account and see how it works!

#MachineLearning#OilAndGas#ReservoirEngineering#DataScience#RecoveryFactor#DigitalTwin#FDP#ProductionForecast#OilProduction

QuickField engineering results
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