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Abstract

Summary

Big Geo Data and cloud computing are a real E&P game changer taking us from Geosciences to Geo DATA sciences. Probability theory offers a consistent mathematical framework for developing specific “kriging based” machine learning algorithms for automating reservoir modelling and updating in real time. This is the season 3 of the Kriging algorithm saga in the oil industry, after season 1, kriging as an interpolator, and season 2, kriging as a geophysical workflow optimizer. In season 3, kriging-based software packages give way to kriging-based software apps for operating digital E&P projects

© EAGE Publications BV
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/content/papers/10.3997/2214-4609.202032025
2020-11-30
2024-04-26

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References

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  2. (2)L.Sandjivy, A.Shtuka & F.A.Merer EAGE 2014: Plea for Consistent Uncertainty Management in Geophysical Workflows to Better Support E&P Decision-making
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http://instance.metastore.ingenta.com/content/papers/10.3997/2214-4609.202032025
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Kriging Season 3: From Geosciences to Geo_DATA_Sciences
Conference Proceedings 2020, 1 (2020); https://doi.org/10.3997/2214-4609.202032025
/content/papers/10.3997/2214-4609.202032025
/content/papers/10.3997/2214-4609.202032025
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