Gulf of Mexico Data Analysis and Automation using GOM3 Data

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Gulf of Mexico Data Analysis and Automation using
GOM3 Data

• Charles Fried
• Doerte Steinhoff
• Nisha Punchavisuthi

GOM3 User ConferenceOctober 27, 2006 Houston, TX
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Summary

• Simple concept
• Less simple in reality
• GIS is indispensable
• GIS-ready data very helpful
• Presentation is critical
• But it can be done!

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Proprietary GoM Dataset

• Small but deep dataset
• Small number of rows (prospects)
• Large number of attributes
• Spatial distribution also very important
• Attributes need to be apportioned by spatial
  relationships
• Example Volumes by ownership from leases

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Multi-variate dataset
DataNeeded
Water depth
UnriskedVolume
Area
Volume Calc method
FluidType
RiskedVolume
UltimatePs
Interpretationmaturity
BPs Working Interest
DataQuality
PrimaryRisk
Relation to Salt
Seismic Definition
TrapType
Depth
Secondary Risk
Also KnownAs (AKA)
TargetAge
TrapConfiguration
Portfolio Action
DepositionalEnvironment
Playfairway
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GIS Data AutomationSimple concept
Ownership based on geometry
Intersection
Blocks Leases
Prospect Outlines
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GIS Data AutomationSimple concept
Each lease can have multiple owners with varied
working interest
Owner 1 Owner 2 Owner 3
60 30 10
Aggregate ownership recalculated with changes in
outlines and leases
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Simple ?

• "I have yet to see any problem, however
  complicated, which, when you looked at it in the
  right way, did not become still more
  complicated." -- Poul Anderson

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GIS model reality (not so simple)
Gather leases from state waters and onshore and
make them look like GOM3s federal offshore leases
Aggregate leases with blocks to capture open
areas where there are no leases
Pre-select only leases and blocks that intersect
prospect outlines to enhance performance
Calculate new category attributes (e.g.
Deepwater vs Shelf) and delete unwanted
attributes to reduce clutter
But it works!
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Now what?

• Ok, the calcuations are done
• What do we do with them?
• How can the trends, patterns, salient facts, and
  interrelationships be communicated?

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Edward Tuftes Principles

• Show all the data
• Present lots of visual detail
• Show context

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Applying Tuftes Principles

• Microsoft PowerPoint

• Poster not slides
• Large format
• Lots visual detail
• Non-linear

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Show your data

• "1. Never tell everything at once." --
  Ken Venturi

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Example Poster
Resource base
Maps of outlines and playfairways
Lease expiry predictions
YTF vs. discovered vs. inventory volumes
Top competitors and relative positions
Creaming curves
Inventory volumes vs. YTF by geologic age
Ranking of prospects by volumes and working
interest
Ranking of prospects by volumes and
interpretation maturity
Ranking of prospects by geologic age and volumes
Ranking of prospects by volumes and risk
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How we did it
Dynamic data queries and embedded charts
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The Joys of Automation

• "The computer allows you to make mistakes faster
  than any other invention, with the possible
  exception of handguns and tequila." - Mitch
  Ratcliffe

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Integration of data with GIS
Bathymetry contours
Leases
Fields
Air photos
Pipelines Platforms
GDE maps, Potential fields, playfairways,
competitor wells etc.
Shipping channels
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Acknowledgements

• Doerte Steinhoff Analysis and poster design
• Nisha Punchavisuthi Poster construction using
  Sharepoint, MS Access, Excel and ArcGIS

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Final thought

• "Courage is what it takes to stand up and speak
  courage is also what it takes to sit down and
  listen." -- Winston Churchill