Direct hydrocarbon indicators analysis informed by machine learning processes

Various embodiments described herein provide methods of hydrocarbon management and associated systems and/or computer readable media including executable instructions. Such methods (and by extension their associated systems and/or computer readable media for implementing such methods) may include ob...

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Bibliographische Detailangaben
Hauptverfasser: Steffen, Kurt J, Zhang, Jie, MacDonald, Cody J
Format: Patent
Sprache:eng
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Beschreibung
Zusammenfassung:Various embodiments described herein provide methods of hydrocarbon management and associated systems and/or computer readable media including executable instructions. Such methods (and by extension their associated systems and/or computer readable media for implementing such methods) may include obtaining geophysical data (e.g., seismic or other geophysical data) from a prospective subsurface formation (that is, a potential formation or other subsurface region of interest for any of various reasons, but in particular due to potential for production of hydrocarbons) and using a trained machine learning (ML) system for direct hydrocarbon indicators (DHI) analysis of the obtained geophysical data. Hydrocarbon management decisions may be guided by the DHI analysis.