Predicting sweet spots in shale plays by DNA fingerprinting and machine learning
conference paper
Topics
Artificial intelligenceBacteriaDNAHydrocarbonsInfill drillingIterative methodsLearning systemsOil shaleResource valuationSeepageShaleSoil surveysSoilsComplex compositionsDNA fingerprintingHaynesville shalesHydrocarbon accumulationHydrocarbon-oxidizing bacteriaMachine learning applicationsMicrobial speciesOil and gas pricesBig data
TNO Identifier
842151
ISBN
9781613995433
Publisher
Unconventional Resources Technology Conference (URTEC)
Article nr.
2671117
Source title
SPE/AAPG/SEG Unconventional Resources Technology Conference 2017. 24 July 2017 through 26 July 2017
Pages
126
Files
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