improve well spacing with tibco spotfire and aws sagemaker · rds s3 efs sagemaker aws cloud public...
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October 29, 2019
Copyright © 2019 OAG Analytics
LutherBirdzellFounder&[email protected]
ImproveWellSpacingwithTIBCOSpotfireandAWSSageMaker
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The ChallengeParentWellA
ParentWellB
ChildWellC
PredictabilityofTightlySpacedUnconventionalWells
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WellA WellC WellB
|500’|800’| Neitherphysicsnormachinelearningaloneaccuratelyestimatestheproductionoftightlyspacedunconventionalwells
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Why is Well Spacing an Important Problem? $10B+EquityValueDestructioninH2-19
WellSpacingisaMakeorBreakProblemfortheU.S.Oil&GasIndustry
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WTISpotPrice LargeU.S.IndependentOperatorsStockPrice
Aug2019
Aug2019
Nov2018
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• Nonlinear function of rocks, well design, spacing and sequencing
• Distance between wells does not effectively describe depletion
• Binary parent / child classification lacks required details
• Modeling depletion requires combining reservoir physics with machine learning (this is really hard!)
Why is Well Spacing a Difficult Problem?
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Technology MilestonesAIEnablesNewCostSavingsandProductionUpliftOpportunities
1990s 2000s 2019
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SageMaker - Spotfire Integration
UpstreamAIPlatformApplication
Layer
Data
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EFSS3RDS
SageMaker
AWSCloud
Public Well Production Geo OtherDatabases
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OAG - Spotfire Integration
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Planning Drilling Units with Tight Well SpacingShouldWeDrill8or10Wells?WhichCompletionDesignsShouldweConsider?
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WellSpacingFeet
EURperF
oot
DSU-SpecificWellSpacingTrends
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Planning Drilling UnitsTraditionalAnalysis
OilProductionvsFluidPerFt.
360Cu
m.O
ilperF
oot
FluidperFoot
AdvancedAnalyticsInsightsOilProductionvsFluidPerFt.
PartialDependencyPlot(MonteCarloSimulation)
OAGAnalytics
Improve Correlations and Quantify Trends
FluidperFoot
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Planning Drilling Units
The production degradation of child Well C is a function of the distance and time between it and its parent Wells A & B
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6MonthDepletion
Area
12MonthDepletion
Area
WellAOct2018
WellBJune2019
WellCOct2019
6MonthDepletion
Area
HowMuchLessWillChildWellCProducethanParentWellsA&B?
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Why OAG?
Combiningphysicswithmachinelearningisrequiredtoimprovethepredictabilityoftightlyspacedwells
GuaranteedtoImprovethePredictabilityofTightlySpacedUnconventionalWells
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DEMO
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Q&AWhatWeDoWhoWeAre
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OAGImprovesthePredictabilityofUpstreamPlanningDecisions12
• Venture backed software company
• 100% focus on upstream oil & gas
• Founded in 2013
• Based in Houston
OAG Combines Physics with Machine Learning:
Well SpacingOffset production volumes and frac intensityParent / ChildFrac Hits
Completion DesignPerf Design (stage & cluster spacing)Slurry Design (proppant & fluid)