WES Trainings

Reservoir Engineer: Reservoir Characterization & Monitoring Strategies

Course Outline

Day - 1

Introduction to Reservoir Characterization

  • Overview of Reservoir Engineering
    • The role of reservoir engineering in exploration and production
    • Key concepts in reservoir characterization
    • Types of reservoirs: Conventional vs. unconventional
  • Geological Characterization
    • Introduction to geological and geophysical data in reservoir characterization
    • Lithology, stratigraphy, and structural interpretation
    • Understanding facies models and reservoir heterogeneity
  • Petrophysical Properties
    • Key petrophysical properties: Porosity, permeability, fluid saturation
    • Tools for petrophysical analysis: Well logs and core data
    • Building petrophysical models from data
Day - 2

Static Reservoir Modeling

  • Building Static Reservoir Models
    • Introduction to static modeling and its importance
    • Integrating geological, petrophysical, and seismic data
    • Mapping reservoir properties: Porosity, permeability, and structural features
  • Data Integration Techniques
    • Integrating well data, seismic data, and geological maps into 3D models
    • Understanding and managing reservoir heterogeneity
    • Creating geocellular models for reservoir representation
  • Reservoir Property Distribution
    • How to interpret and model the distribution of reservoir properties
    • Dealing with uncertainty in static models
    • Using static models to assess reservoir volume and initial reserves
Day - 3

Dynamic Reservoir Modeling & Simulation

  • Introduction to Reservoir Simulation
    • The role of dynamic modeling in reservoir management
    • Understanding fluid flow equations and modeling techniques
    • Types of reservoir simulations: black oil, compositional, and thermal models
  • Building Dynamic Reservoir Models
    • Integrating static models with dynamic simulation tools
    • Understanding reservoir fluid behavior, pressure, and temperature dynamics
    • History matching: Comparing model predictions with actual production data
  • Production Forecasting
    • Using reservoir simulation to forecast future production
    • Impact of different recovery methods: Primary, secondary, and enhanced oil recovery (EOR)
Day - 4

Monitoring Strategies & Data Analysis

  • Monitoring Techniques
    • Overview of monitoring tools: Pressure monitoring, production data analysis, and well testing
    • Real-time reservoir monitoring: Surface and downhole tools
    • Using pressure transient analysis (PTA) for well performance assessment
  • Well Test Analysis
    • Interpreting well test data to assess reservoir properties
    • Well testing methods: Drill stem testing (DST), production tests, and interference tests
    • History matching and analysis of transient flow data
  • Data Integration for Monitoring
    • Integrating monitoring data with reservoir models for real-time optimization
    • Using production data to update and improve reservoir models
    • Managing data uncertainty and noise in monitoring systems
Day - 5

Advanced Topics & Risk Management

  • Enhanced Oil Recovery (EOR) Characterization
    • Reservoir characterization for EOR: Water flooding, CO2 injection, and chemical flooding
    • Modeling the impact of EOR on reservoir performance
    • Understanding the geology and reservoir conditions required for EOR success
  • Uncertainty and Risk Analysis
    • Managing uncertainty in reservoir models: Sensitivity analysis and Monte Carlo simulations
    • Risk management in reservoir engineering: Addressing geological, operational, and economic risks
    • Best practices for decision-making under uncertainty
  • Optimizing Reservoir Management
    • Using reservoir characterization and monitoring strategies to maximize recovery and minimize costs
    • Design of reservoir management strategies based on monitoring data
    • Case studies of successful reservoir management using integrated modeling and monitoring techniques
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