COURSE OVERVIEW:

Uncertainty quantification in prospect and reservoir geomodelling is a rigorous mathematical and geological discipline focused on assessing the range of possible outcomes in subsurface characterization. Given that subsurface data is inherently sparse and indirect, any single geological model represents only one possible reality. This course explores the methodologies used to move beyond "deterministic" modeling toward a "probabilistic" framework, where the risks associated with structural, stratigraphic, and petrophysical variables are systematically measured and managed.

The scope of this course covers the identification and categorization of uncertainties into primary drivers, such as gross rock volume, and secondary drivers, such as facies distribution and fluid contacts. Participants will learn how to implement Monte Carlo simulations, Experimental Design, and Latin Hypercube sampling to generate a distribution of outcomes. The curriculum emphasizes the transition from a single "best-case" model to a suite of realizations (P10, P50, P90) that define the economic and technical risk profile of an asset.

Coverage includes the practical application of geostatistical techniques to model spatial uncertainty and the integration of these results into decision-making workflows. The course details how to perform sensitivity analysis to identify which geological parameters most significantly impact the estimated ultimate recovery (EUR). By mastering these quantification tools, geoscientists can provide management with a transparent view of project risks, leading to better-informed investment decisions and more resilient field development strategies.

COURSE OBJECTIVES:

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

• Define the difference between uncertainty, risk, and bias in geological modeling.
• Identify the major sources of uncertainty in structural and stratigraphic interpretation.
• Utilize geostatistical methods such as Sequential Gaussian Simulation for property modeling.
• Perform sensitivity analysis using Tornado plots to rank uncertainty drivers.
• Apply Monte Carlo simulation techniques for volumetric resource assessment.
• Construct multiple structural realizations to assess gross rock volume (GRV) ranges.
• Evaluate the impact of facies modeling choices on reservoir connectivity.
• Use Experimental Design (DoE) to optimize the number of model realizations.
• Differentiate between aleatory and epistemic uncertainties in the subsurface.
• Integrate seismic inversion uncertainty into reservoir property distributions.
• Communicate probabilistic results (P10, P50, P90) effectively to stakeholders.
• Assess the impact of fluid contact uncertainty on reserve estimations.
• Formulate a risk-managed geomodelling workflow for exploration and development.

TARGET AUDIENCE:

Geomodellers, Reservoir Engineers, Exploration Geologists, and Asset Managers responsible for resource estimation and project valuation.

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.