Learning Objectives

Upon successful completion of this course, participants will be able to:

1. Introduction to Rock Typing in Carbonate Reservoirs

• Understand the significance of rock typing in reservoir characterization.
• Differentiate between deterministic and probabilistic rock typing methods.
• Identify factors influencing rock types in carbonate formations (diagenesis, depositional environment, porosity evolution, etc.).

2. Fundamentals of Deterministic Rock Typing

• Classify carbonates based on Dunham and Lucia classifications.
• Define pore geometry, connectivity, and permeability variations in carbonate systems.
• Understand the impact of vuggy, interparticle, and intraparticle porosity on fluid flow.
• Apply thin-section petrography, SEM imaging, and CT scanning for rock type identification.

3. Mercury Injection Capillary Pressure (MICP) Analysis

• Understand MICP principles and how it characterizes pore throat distributions.
• Conduct MICP data acquisition and laboratory procedures.
• Interpret capillary pressure curves and their implications on fluid saturation.
• Analyze entry pressure, pore size distribution, and relative permeability estimation.

4. Integration of MICP with Petrophysical and Geological Data

• Correlate MICP results with NMR, well log, and routine core analysis data.
• Use MICP to refine permeability models in carbonate reservoirs.
• Identify flow zones and reservoir heterogeneity using MICP-derived rock typing.

5. Applications of Deterministic Rock Typing and MICP in Reservoir Studies

• Improve reservoir simulation models by integrating rock types.
• Predict water breakthrough and recovery efficiency in carbonate formations.
• Enhance reservoir management strategies for waterflooding and EOR applications.

6. Practical Considerations and Case Studies

• Review real-world applications of deterministic rock typing and MICP analysis.
• Participate in hands-on exercises for MICP data interpretation.
• Develop a rock typing framework for a carbonate reservoir study.

7. Advanced Techniques and Future Trends

• Explore digital rock physics for pore-scale modeling.
• Apply machine learning techniques for automated rock classification.
• Investigate the impact of wettability on capillary pressure in carbonates.

Target Audience

• Reservoir engineers and geologists
• Petrophysicists and core analysts
• Laboratory specialists in rock property characterization
• Reservoir simulation and modeling professionals