Quantify static and dynamic subsurface uncertainty using geostatistical realisations and structured sensitivity analysis.
Oil, Gas & Energy
Subsurface Uncertainty Quantification and Decision Analysis for Field Development
Builds the technical and decision-making skills to quantify subsurface uncertainty, test its value against new data or flexible designs, and translate the results into defensible field development decisions.
🗓️Duration5 training days
📚Content4 modules · 8 sessions
🎓On completionAccredited attendance certificate
About the programme
Course Overview
Every field development decision is made before the reservoir is fully known, and the gap between what is measured and what is assumed drives much of the risk in a project's outcome. This course treats subsurface uncertainty as something to be measured and managed rather than avoided. Participants work through the static and dynamic sources of uncertainty in structure, facies, petrophysics and reservoir performance, then apply geostatistical realisations, Monte Carlo simulation and ensemble-based history matching to turn that uncertainty into defensible probability distributions consistent with recognised reserves reporting categories. The second half of the course moves into decision analysis: building decision trees and influence diagrams, calculating the value of information for a proposed well or survey, and comparing phased or flexible development concepts using real options thinking. Case exercises apply these tools to realistic field development choices so participants leave able to frame a subsurface decision, quantify what is and is not known, and recommend a course of action that a stage-gate review can act on with confidence.
Expected Learning Outcomes
Run Monte Carlo simulations that convert volumetric uncertainty into probability distributions aligned with PRMS reserve categories.
Apply ensemble-based history matching to update uncertain reservoir parameters against production and pressure data.
Build decision trees and influence diagrams that structure field development choices under subsurface uncertainty.
Calculate the value of information for a proposed appraisal well or seismic survey before committing to the spend.
Compare phased and flexible development concepts using real options analysis and risk-weighted economics.
Present decision recommendations and reserves classifications that hold up at stage-gate and audit review.
Who Should Attend
Subsurface engineers and geoscientists building static and dynamic models for field development projects.
Reservoir engineers responsible for reserves classification and probabilistic volumetric reporting.
Development planners and asset economists preparing stage-gate investment recommendations.
Decision analysts supporting exploration and production portfolio and appraisal investment choices.
Technical team leads who must communicate subsurface uncertainty clearly to non-technical management.
Reserves auditors and planning engineers reconciling deterministic and probabilistic volume estimates.
Course Modules
Select any module to see its sessions and points.
01Sources and Characterisation of Subsurface Uncertainty
2 sessions · 8 points
Session 1Static Uncertainty in Structure, Facies and Petrophysics
- Rank structural uncertainty from depth conversion and fault interpretation by testing alternative velocity models and fault seal scenarios against well control.
- Build multiple facies realisations using variogram-based or object-based geostatistical methods to capture reservoir heterogeneity away from well control.
- Propagate petrophysical uncertainty in porosity and permeability transforms through to original hydrocarbon in place using stochastic property modelling.
- Quality-check net-to-gross and saturation-height function uncertainty against core and log data from analogous fields to avoid unsupported ranges.
Session 2Dynamic Uncertainty in Reservoir Performance
- Identify dynamic uncertainty drivers such as aquifer strength, relative permeability hysteresis and fluid contact depth that control recovery forecasts.
- Screen uncertain parameters using tornado diagrams and sensitivity analysis to focus data acquisition and modelling effort on the variables that matter most.
- Assess reservoir connectivity uncertainty using pressure transient data, tracer results and production logging to test compartmentalisation scenarios.
- Document assumptions and uncertainty ranges in a live uncertainty register that is reviewed and updated as new well and production data arrive.
02Quantification Methods and Ensemble Modelling
2 sessions · 8 points
Session 1Geostatistical Realisations and Monte Carlo Analysis
- Generate multiple equiprobable geological realisations and rank them by hydrocarbon in place to select representative low, mid and high cases.
- Run Monte Carlo simulation over volumetric parameters to build a probabilistic in-place and recoverable resource distribution consistent with PRMS categories.
- Apply experimental design techniques to select a manageable number of simulation cases that span the uncertainty space efficiently.
- Build proxy or response surface models from simulation results to estimate production forecasts for combinations of parameters not explicitly run.
Session 2Ensemble-Based History Matching and Model Updating
- Configure an ensemble of reservoir models and apply ensemble-based history matching to update uncertain parameters against observed production and pressure data.
- Use Bayesian updating principles to narrow the uncertainty range on key parameters as new well results and 4D seismic data become available.
- Diagnose over-fitting and non-uniqueness in history matching by checking that matched models retain plausible geological and petrophysical properties.
- Communicate the reduction in uncertainty after history matching using updated probability distributions rather than a single deterministic match.
03Decision Analysis Frameworks for Development Choices
2 sessions · 8 points
Session 1Decision Trees, Influence Diagrams and Value of Information
- Structure a field development choice as a decision tree that captures sequential decisions, chance nodes and economic outcomes under uncertainty.
- Build an influence diagram to map the dependencies between subsurface uncertainty, development concept choices and commercial outcomes.
- Calculate the value of information for a proposed appraisal well or seismic survey to test whether the data acquisition cost is justified.
- Compare value of information against value of control to decide whether additional data or a flexible development concept better addresses the uncertainty.
Session 2Real Options and Flexible Development Planning
- Apply real options analysis to phased development concepts that allow expansion, deferral or abandonment as subsurface uncertainty resolves.
- Compare a phased development plan against a full-field development on a risk-weighted net present value basis under multiple subsurface scenarios.
- Design a well sequencing and appraisal programme that maximises early uncertainty reduction relative to its cost and schedule impact.
- Present decision recommendations using a clear framing of alternatives, information and value to support a stage-gate investment decision.
04Integrating Uncertainty into Investment and Portfolio Decisions
2 sessions · 8 points
Session 1Reserves and Resources Classification and Reporting
- Classify volumes into proved, probable and possible categories under the Petroleum Resources Management System based on the underlying uncertainty distribution.
- Reconcile deterministic and probabilistic reserves estimates when reporting to management and regulators to avoid inconsistent volume statements.
- Assess the impact of development plan changes and price assumptions on reserves bookings and the associated economic uncertainty.
- Prepare an audit-ready volumetric and economic uncertainty file that documents assumptions, methods and version history for external reserves auditors.
Session 2Portfolio Optimisation and Investment Governance
- Rank competing field development opportunities on a risk-weighted returns basis while accounting for correlated subsurface uncertainty across assets.
- Build a portfolio view that balances high-uncertainty exploration-linked developments against lower-uncertainty brownfield opportunities.
- Present uncertainty and decision analysis outputs at stage-gate reviews in a format that supports a clear go, no-go or hold recommendation.
- Track forecast versus actual performance after sanction to calibrate future uncertainty ranges and improve the quality of subsequent decisions.
What the participant receives
4 course modules
A structured syllabus
8 training sessions
across 5 days
32 detailed points
Applied, detailed content
Accredited attendance certificate
On completing the programme
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