Course Overview

Day-by-Day Outline

Day 1 – Core Analysis and Laboratory Measurements

• Core acquisition and preservation techniques
• Routine core analysis (RCAL): porosity, permeability, grain density
• Special core analysis (SCAL): capillary pressure, relative permeability
• Scaling core data for reservoir conditions
• Exercise: Interpret RCAL and SCAL lab reports for petrophysical modeling

Day 2 – Log Interpretation for Petrophysical Properties

• Key open-hole logs: gamma ray, resistivity, density, neutron, sonic
• Clay volume estimation and shale corrections
• Porosity determination from density-neutron-sonic integration
• Water saturation calculations: Archie’s equation, shaly-sand models
• Workshop: Derive porosity and saturation from log suite

Day 3 – Integration of Core and Log Data

• Depth shifting and core-log reconciliation
• Comparing core-measured and log-derived porosity and permeability
• Generating rock type and electrofacies from integrated data
• Calibration of log interpretation with core data
• Exercise: Create crossplots comparing core and log data

Day 4 – Pressure Tests and Dynamic Data Integration

• Overview of well testing: RFT, MDT, DST
• Estimating permeability and fluid contacts from test data
• Reconciling static (log/core) and dynamic (pressure) measurements
• Incorporating test results into petrophysical models
• Workshop: Interpret test data and update net pay estimates

Day 5 – Petrophysical Modeling for Reservoir Simulation

• Upscaling petrophysical properties for reservoir grids
• Defining cut-offs for net-to-gross and net pay maps
• Estimating input property distributions for reservoir simulation
• Case studies: integration successes and pitfalls
• Capstone Project: Build integrated petrophysical model for a field case

Expected Learning Outcomes

• Interpret and reconcile core, log, and test data for petrophysical properties
• Estimate porosity, permeability, and saturation accurately
• Integrate static and dynamic data into consistent petrophysical models
• Build net pay maps and property distributions for reservoir simulation
• Enhance confidence in reservoir characterization and volumetric estimation