Webinar on Reservoir Modeling Workflow

Introduction

• Presenter: Abdullah, Business Developer at Reservoir Solutions.
• Company Overview: Reservoir Solutions provides technical studies and courses for oil and gas companies and professionals.
  • Services include technical reservoir studies, field development planning, reservoir static and dynamic modeling, economic feasibility studies, and technical support for academic researchers.
  • Announced an upcoming course: Static and Dynamic Reservoir Modeling starting on July 25 for two weeks.
    • Lifetime access to recorded sessions.
    • Application data sets and workshops.
    • Course material provided.
    • Certificate with online identification ID.

Webinar Overview

• Presenter: Engineer Muhammad Amin, Senior Reservoir Engineer at General Auditorium Company, Egypt.
• Experience: 9+ years in asset evaluation, reserve characterization, and simulation.
• Agenda: Reservoir Modeling Workflow for Static and Dynamic Models.

Reservoir Production and Exploration Lifecycle

• Steps: Exploration, Evaluation, Production, Secondary Recovery, Abandonment.

Importance of Reservoir Modeling

• General Definitions: Mathematical representation of natural phenomena.
• When to use: When traditional methods (decline curve analysis, material balance) are insufficient.

Static Modeling Workflow

1. Data Preparation and Interpretation: Seismic data, well logs, core data.
2. Structural Modeling: Fault modeling, X-Y and vertical gridding.
3. Property Modeling: Facies and petrophysical modeling.
4. Uncertainty Analysis: For original oil in place (OOIP) calculation.
5. Up-scaling: Converting high resolution geological model to lower resolution for simulation.

Dynamic Modeling Workflow

1. QC Static Model: Quality check on static model.
2. Traditional RE Tools: Material balance, well tests, decline curve analysis.
3. PVT and SCAL Data Input: Modify lab data for simulation.
4. History Matching: Compare simulated production with actual production.
   • Levels: Pressure match, saturation match, well productivity index match.
5. Production Prediction and Field Development Planning: Main goal of reservoir modeling.
6. Uncertainty and Optimization Analysis: For parameters affecting production forecasts.

History Matching

• Concept: Matching simulated production to actual production.
• Process: Modify reservoir model parameters until match is achieved.

Sensitivity, Uncertainty, and Optimization Analysis

• Sensitivity Analysis: Identify key parameters affecting production outcomes.
• Uncertainty Analysis: Determine effect of parameter ranges on production forecasts.
• Optimization: Automate history matching and predict optimal production scenarios.

Questions & Answers

• Streamlines: Used to identify flow direction and cell orientation matching.
• Classical vs. Modeling Workflow: Traditional tools vs. 3D reservoir modeling.
• Upscaled Data QC: Compare well-log values against upscaled values.
• Reducing Uncertainty: Integrate multiple data sources and more data collection.
• Importance to Geologists: Helps in predicting new well locations.
• Aquifer Modeling: Analytical and numerical methods.
• Forward vs. Inverse Modeling: Solving problems vs. adjusting models to match observed data.
• Core Data vs. Well Logs: Accuracy considerations.

Conclusion

• Summary: Detailed steps and considerations for both static and dynamic reservoir modeling workflows.
• Next Steps: Look forward to the next webinar and further questions via LinkedIn or other channels.

End of Webinar.