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Postgraduate Petroleum Data Management 2017-2018

DM5001: PETROLEUM DATA MANAGEMENT TOOLS AND TECHNIQUES 1

15 credits

Level 5

First Term

 Data Sources, Types and Formats:

  • Spatial Data
  • Culture
  • Boundaries/Licenses/Leases
  • Licence history
  • Bathymetry/Topography
  • Surface images
  • Coordinate Systems
  • Subsea data (e.g. infrastructure and pipelines)

 

  • Geophysical Data
  • 2D/3D Navigation
  • Gravity & Magnetics
  • 3D Outlines
  • 2D/3D Seismic trace
  • 4D Seismic Time-Lapse data
  • Acquisition and Processing parameters
  • Velocities

 

  • Interpretation projects
  • Seismic Interpretation and Interpretation Studies
  • Horizon Time Grid and Depth Grid
  • Geologic and Simulation Models
  • Reserve calculations
  • Prospects

 

  • Well Data
  • Stratigraphic Columns
  • Identity: Headers, Directional
  • Drilling: Planning, Drilling, Completion, Events, Drilling / W-O treatment
  • Formation: Core description, Geochemistry, Surface picks, Intervals, Pressures
  • Logs: Curves, Petrophysical parameters, Zoned properties, Checkshots, VSP, Synthetic seismograms

 

  • Production Data
  • Configuration: External network, Network, Surface, Sub-surface
  • Regular: Measured volumes, Pump data, Other measurements, Operational, Allocated volumes
  • Occasional: Planned events, Unplanned events, Samples, Well tests

 

  • Reservoir Data
  • Porosity
  • Permeability
  • Fluids
  • “Problems”
  • Well tests (e.g. Drill stem test, Formation Integrity test)

 

  • Indexes
  • Physical assets
  • Scanned documents
  • Electronic Documents

 

  • The value of these different data types

 

  • Data sourcing workflows

 

  • Tools and techniques for
  • Using, loading, altering, and converting different data types and data sets
  • Data storage
  • Data archiving
  • Cataloguing data for effective search and retrieval
  • All of the above for Big Data
  • Introduction to regulatory reporting and data sharing between partners

 

  • Introduction to associated standards

 

  • Introduction to associated IT concepts

 

  • Introduction to Data Management Architecture and Data Management Models

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