COURSE OVERVIEW:

Uncertainty quantification in reservoir modeling and forecasting is a vital technical discipline that allows energy companies to make informed investment decisions under geological and economic ambiguity. This course provides a robust framework for identifying, characterizing, and mitigating the risks inherent in subsurface evaluations. The scope includes the transition from traditional deterministic "best estimate" modeling to modern probabilistic workflows that capture a range of possible outcomes for reserves and production profiles.

The technical core of the training focuses on the sources of uncertainty in the static and dynamic modeling process, including structural interpretation, petrophysical properties, and fluid behavior. Participants will explore advanced statistical methods, such as Monte Carlo simulations and experimental design, to evaluate how variations in input parameters propagate through the model to affect the final forecast. The coverage emphasizes the importance of sensitivity analysis in determining which variables have the greatest impact on project value.

The final portion of the course addresses the practical application of uncertainty quantification in field development planning and history matching. It details the methodologies for integrating real-time production data to narrow the range of uncertainty over the life of the asset. By mastering these techniques, engineers and geoscientists can communicate risk more effectively to stakeholders and design more resilient development strategies that account for the unpredictable nature of subsurface reservoirs.

COURSE OBJECTIVES:

After completion of this course, the participants will be able to:

1. Define the fundamental differences between deterministic and probabilistic modeling approaches.
2. Identify the primary sources of uncertainty in structural and stratigraphic interpretations.
3. Quantify the impact of petrophysical property distribution on reservoir volume estimates.
4. Utilize Monte Carlo simulation techniques to generate a range of production forecasts.
5. Apply Experimental Design (DoE) to identify the most sensitive model parameters.
6. Evaluate the uncertainty associated with fluid properties and PVT characterization.
7. Integrate seismic uncertainty into the static reservoir modeling workflow.
8. Assess the role of history matching in reducing uncertainty for mature assets.
9. Perform a robust sensitivity analysis using Tornado and Spider diagrams.
10. Formulate risk-based decision-making criteria for capital-intensive projects.
11. Develop P10, P50, and P90 reserves estimates following industry standards.
12. Communicate complex uncertainty and risk profiles to non-technical management.
13. Utilize advanced software tools for automated ensemble-based modeling.

TARGET AUDIENCE:

Reservoir Engineers, Geologists, Petrophysicists, Asset Managers, and Decision Analysts are involved in reservoir characterization and field development.

TRAINING COURSE METHODOLOGY:

A highly interactive combination of lectures, discussion sessions, and case studies will be employed to maximise the transfer of information, knowledge, and experience. The course will be intensive, practical, and highly interactive. The sessions will start by raising the most relevant questions and motivating everybody to find the right answers. The attendants will also be encouraged to raise more of their questions and to share in developing the right answers using their analysis and experience. There will also be some indoor experiential activities to enhance the learning experience. Course material will be provided in PowerPoint, with necessary animations, learning videos, and general discussions.

The course participants shall be evaluated before, during, and at the end of the course.

COURSE CERTIFICATE:

National Consultant Centre for Training LLC (NCC) will issue an Attendance Certificate to all participants completing a minimum of 80% of the total attendance time requirement.