The Modelling & Managing Uncertainty in the Subsurface training program is designed by Global Horizon Training Center to equip geoscientists, geomodellers, reservoir engineers, and subsurface professionals with the knowledge and practical skills required to identify, quantify, model, and effectively manage uncertainty throughout the subsurface evaluation and decision-making process. The course integrates geological, geophysical, petrophysical, and engineering data to develop robust uncertainty-aware subsurface models that support exploration, appraisal, field development, and production optimization.
By the end of this program, participants will be able to:
Understand the nature and sources of uncertainty in subsurface studies.
Differentiate between uncertainty, variability, and risk in geological and reservoir models.
Identify geological, geophysical, petrophysical, and dynamic uncertainties.
Apply uncertainty management throughout the subsurface modelling workflow.
Build multiple geological scenarios for uncertainty assessment.
Integrate seismic interpretation with geomodelling under uncertainty.
Perform sensitivity analyses to determine key uncertainty drivers.
Utilize probabilistic approaches for reservoir characterization.
Develop uncertainty-aware geomodels that support better business decisions.
Apply risk-based decision-making techniques during exploration and field development.
Communicate uncertainty effectively to multidisciplinary teams and management.
This highly interactive program combines:
Expert-led presentations
Practical geomodelling case studies
Real subsurface workflow demonstrations
Group discussions
Geological scenario-building workshops
Seismic interpretation exercises
Reservoir uncertainty evaluation
Risk assessment exercises
Integrated team-based problem solving
Interactive Q&A sessions
Upon completion of this program, organizations will benefit from:
More reliable subsurface models.
Improved exploration and development decisions.
Better management of geological uncertainty.
Reduced project risks.
Enhanced collaboration between geoscience and engineering disciplines.
Increased confidence in reservoir forecasting.
Improved reserve estimation accuracy.
Better investment decision support.
More efficient field development planning.
Stronger integration between seismic interpretation and geological modelling.
This program is designed for:
Geoscientists
Geomodellers
Seismic Interpreters
Reservoir Geologists
Petroleum Geologists
Reservoir Engineers
Petrophysicists
Exploration Geophysicists
Field Development Engineers
Asset Team Members
Subsurface Managers
Technical Specialists involved in exploration and production projects
Day 1: Fundamentals of Subsurface Uncertainty
Introduction to uncertainty in subsurface studies
Types and sources of uncertainty
Geological, geophysical, and petrophysical uncertainties
Data quality and uncertainty assessment
Risk versus uncertainty in decision-making
Building an uncertainty management framework
Industry standards and best practices
Day 2: Geological and Geophysical Modelling Under Uncertainty
Structural modelling and fault uncertainty
Seismic interpretation uncertainty
Stratigraphic and facies modelling
Property modelling and spatial variability
Deterministic versus probabilistic modelling approaches
Integrating geological and geophysical data
Developing alternative geological scenarios
Day 3: Quantifying and Analysing Uncertainty
Probabilistic modelling techniques
Sensitivity analysis methods
Stochastic simulation and multiple realizations
Uncertainty in reservoir properties
Volumetric uncertainty assessment
Model calibration and validation
Quantifying uncertainty for decision support
Day 4: Managing Uncertainty in Reservoir Development
Reservoir characterization under uncertainty
Risk assessment and mitigation strategies
Decision analysis and scenario evaluation
Uncertainty in field development planning
Well placement and production forecasting
Integrated subsurface workflows
Communicating uncertainty to stakeholders
Day 5: Advanced Applications and Industry Best Practices
Managing uncertainty throughout the asset lifecycle
Updating models with new data
Digital technologies for uncertainty management
Case studies in exploration and reservoir modelling
Lessons learned from industry projects
Best practices for integrated uncertainty management
Practical workshop and action planning
Course review and discussion