Workshop 18
Improving Subsurface Decision Quality Friday, June 12th|
Convenors
- Jeff Parke (BP)
Description
- Learn methods to structure and validate subsurface predictions, reducing cognitive biases.
- Conduct risk assessments early to identify relevant reference class analogues, enabling more realistic forecasting and robust decisions.
- Use practical tools such as scenario planning, reference class forecasting, and probabilistic modelling to counter overconfidence and anchoring.
Sub-Topics that will be covered in the workshop:
Role of subsurface teams in decision-making processes.
Understanding Bias in Subsurface Predictions
- Common cognitive biases: overconfidence, anchoring, and confirmation bias.
- Impact of bias on volumetric estimates and risk profiles.
De-biasing Techniques
- Scenario planning and structured uncertainty ranges.
- Pre-mortem analysis to anticipate failure modes.
- Reference class forecasting: principles and application.
Risk Assessment and Analogue Identification
- Building risk matrices for exploration and development projects.
- Identifying and validating reference class analogues using historical data.
- Linking analogue insights to probabilistic forecasts.
Practical Exercises
- Case studies on bias reduction in volumetric estimation.
- Hands-on analogue benchmarking and scenario modelling.
- Group discussion: improving input quality for high-stakes decisions.
Participant Profile
Geoscientists, Reservoir Engineers, and Decision makers involved in exploration and development projects.
Experience Level: Mid-career professionals with 5–15 years of experience in subsurface evaluation, risk analysis, or project planning.
Responsibilities:
- Provide technical input for investment decisions.
- Assess uncertainty and risk in subsurface models.
- Communicate forecasts and recommendations to decision makers.
Motivation: Improve the reliability and clarity of predictions, reduce bias in evaluations, and strengthen decision quality under uncertainty.
Prerequisites: Familiarity with subsurface workflows, basic probabilistic concepts, and project economics.
Workshop Programme
Coming Soon!
| Time | Activity |
|---|---|
| 09:25 | Start |
| Session 1: Foundations | |
| 09:30 | Lecture 1: Decision Quality Framework for Subsurface Decisions:
- Six elements of DQ: appropriate frame, creative alternatives, meaningful information, clear values, logically correct reasoning, commitment to action - Common DQ failures in subsurface workflows - The value of imperfect information vs. perfect models |
| Quiz | |
| 09:55 | Lecture 2: Inside View vs. Outside View:
- Kahneman’s planning fallacy and expert prediction failures - Why subsurface professionals default to inside view - Reference class forecasting: principles and requirements - Case study |
| 10:20 | Breakout Exercise 1 |
| 10:35 | Feedback |
| 10:50 | Break |
| Session 2: Reference Class Forecasting in Practice | |
| 11:05 | Lecture 3: Using Risk to Define Reference Classes
- Risk analysis to support reference class identification (pre-mortems and analogues) - Building reference class databases from analogue populations - Combining inside and outside views: Bayesian approaches - Example: Adjusting EUR distributions for prospect-specific features |
| 11:25 | Breakout Exercise 2 |
| 11:40 | Group Presentations & Discussion |
| 12:55 | Lunch |
| Session 3: Model Complexity and the Inference Problem | |
| 13:55 | Lecture 4: When Complexity Undermines Decisions
- The inference problem: underdetermined subsurface systems - Overfitting in reservoir models, seismic inversions, and basin modelling - Calibration vs. prediction: why history-matched models often fail - Complexity as false confidence: psychological appeal of detailed models - Fit-for-purpose modelling: matching complexity to decision needs |
| 14:25 | Breakout Exercise 3 |
| Session 4: Integration and Action Planning | |
| 14:55 | Lecture 5: Implementing DQ in Subsurface Workflows
- Practical barriers to reference class forecasting in organizations - When to invest in model complexity vs. gathering more analogues - Checklist for subsurface decision quality - Quick wins: low-effort, high-impact DQ improvements |
| 15:20 | Breakout Exercise 4 |
| 15:45 | Final Share-Out & Wrap-Up |