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Type Curves Part 7: Survivor Bias

Omnira Software

Editor’s Note: With VERDAZO proudly joining Omnira Software in 2022, this blog is being re-published on the Omnira Software website.

 

A common issue with Type-well Curves is that they are “Survivor Biased”, and can provide an unrealistic (optimistic) production outlook.

Survivor Bias Definition: as depleted wells are excluded from the monthly average-production-per-well calculation, the Type-well Curve values are biased by the surviving wells (i.e. wells that are still producing). As such the Type-well Curve does not reflect the actual average production one might expect taking into account wells that are depleted (or shut-in permanently).

This chart illustrates how Survivor Bias can cause latter-life production increases in a Type-well Curve.

7-Survivor-Bias-1

Few software products provide Survivor-Bias Controls that allow you to include zeros in the production average after wells are identifiably depleted. The challenge when dealing with public production data is how to identify that a well is depleted. At VERDAZO we chose to use a “period of non-production” as the mechanism to identify a depleted well. The user can define the length of this period (e.g. if a well has not produced in the last 12 months, then consider it to be depleted … meaning it is not expected to come on production again).

The following chart illustrates how Survivor Bias Controls can provide a more realistic expectation of production when depleted wells are included in your Analogue Well Selection.

7-Survivor-Bias-2

Challenges of the Current Commodity Price Market

The current commodity price market will make identifying depleted wells more complicated. Increasingly companies are shutting-in wells until commodity prices recover to an economically acceptable level. This means that a larger window of non-production may need to be specified to identify a “depleted” well. Regardless, this is a poignant reminder that careful attention should be made to your Analogue Selection and every aspect of the choices you make when generating your Type-well Curve.

That concludes part 7 of this series. The remaining topics that you can look forward to include:

  • Truncation Using Sample Size Cut-off
  • Forecast the Average vs Average the Forecasts
  • Representing Uncertainty
  • Auto-forecast

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Production data: IHS Information Hub

Analysis: VERDAZO

Thanks for reading. We welcome your questions and suggestions for future blogs.

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