An Interactive 5-Day Training Course
Mitigating Bias & Blind Spots in Subsurface Decision Making
Countering Bias in Subsurface Decision Making
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Duration
5 Days
Price
$ 3,500
Starting From
13 Sep 2027
Home Geology and Geoscience Mitigating Bias & Blind Spots in Subsurface Decision Making
Mitigating Bias & Blind Spots in Subsurface Decision Making
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Mitigating Bias & Blind Spots in Subsurface Decision Making - GG-BIAS-PEA27
| Code | Date | Time | Duration | Location | Currency | Early Bird Fee Per Person |
|---|---|---|---|---|---|---|
| GG-BIAS-PEA27 | 13 - 17 Sep 2027 | 10 AM CST | 4 Hours Per Day |
Online |
USD |
3500 |
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Mitigating Bias & Blind Spots in Subsurface Decision Making
This training covers bias and blind spots in subsurface decision making. It works through the evidence for systematic bias in the industry, overconfidence and calibration, anchoring and availability, confirmation bias in interpretation, motivational and organisational bias, group effects, the practical techniques that counter each, process design for debiasing, measurement of team calibration and the embedding of debiasing in technical workflows.
Description
Subsurface estimates are systematically biased, the direction of the bias is predictable, and the evidence for this is extensive: pre-drill ranges that fail to contain the outcome far more often than they should, reserves revised repeatedly in the same direction, and project costs and schedules that overrun with a regularity that cannot be chance. These are not failures of technical competence. They are cognitive and organisational effects that affect competent people and that can be partly countered by deliberate process.
This training covers both the effects and the countermeasures. The evidence for systematic bias in the industry is established first, so that the problem is treated as measured rather than theoretical. Overconfidence and calibration follow, covering the central and most consequential bias and how it is measured. Anchoring and availability are then developed. Confirmation bias in interpretation follows, covering its specific expressions in seismic interpretation, correlation and model building. Motivational and organisational bias are then addressed, covering the incentives that push estimates in particular directions. Group effects follow. The practical techniques that counter each are then developed. Process design for debiasing follows. Measurement of team calibration is addressed. The training closes with embedding.
Overconfidence cannot be felt and must be measured. The characteristic of a poorly calibrated estimator is that their ranges feel appropriately wide while being far too narrow, and no amount of care or experience corrects this by itself. The only reliable countermeasure is measurement: making estimates with stated confidence intervals, recording them, and scoring them against the outcomes. A team that discovers that only half of its outcomes fall within its stated eighty per cent ranges has information it cannot obtain any other way, and it will widen its ranges.
Seismic interpretation is particularly exposed to confirmation bias. An interpreter who expects a fault will see one in ambiguous data, and will pick the horizon in a way that is consistent with the expected structure. The data genuinely permits several interpretations and the expectation selects among them, without any conscious decision. Having a second interpreter work the same data without knowledge of the first interpretation, and comparing, reliably reveals how much of the interpretation was in the data and how much was in the interpreter.
Motivational bias is structural and is not resolved by integrity. A team that has worked on a prospect for two years, whose continuation depends on the prospect being drilled, will produce an assessment that is optimistic, and the individuals will be acting in good faith throughout. The same applies to a reserves estimate that supports a bonus, a cost estimate that must fit a budget and a schedule that must meet a licence date. Recognising the direction the incentives push, and building process that counteracts it, is more effective than relying on people to resist it.
Finally, a premortem is the single most effective and cheapest technique available. Before a decision is finalised, the team is asked to assume that the project has failed badly and to write down why. This simple inversion gives permission to voice concerns that would otherwise be withheld, surfaces risks that the risk register missed, and takes less than an hour. It works because it changes the social cost of raising a problem from being seen as obstructive to being asked to contribute.
By the end of this training, participants will be able to:
- Describe the evidence for systematic bias in subsurface estimation
- Measure and interpret calibration of probability estimates
- Recognise overconfidence and apply deliberate range widening
- Identify anchoring and availability effects in technical work
- Recognise confirmation bias in interpretation and counter it
- Identify motivational and organisational bias and its direction
- Recognise group effects that narrow ranges
- Apply premortem, reference class and red team techniques
- Design technical processes that counteract bias
- Measure and track team calibration over time
The training is largely experiential. Participants make estimates and have their calibration scored, interpret ambiguous data under different stated expectations and compare results, and run premortem and red team exercises on real decisions. The effect of each technique is measured within the course rather than asserted.
Organisations sending participants to this training will:
- Produce ranges that contain the eventual outcomes more often
- Measure and improve team calibration
- Counter confirmation bias in interpretation
- Recognise and offset motivational bias
- Run processes that surface concerns rather than suppress them
- Improve decision quality without additional technical work
Participants will:
- Recognise bias in their own work
- Measure their own calibration
- Widen ranges deliberately where justified
- Counter confirmation bias in interpretation
- Run premortem and red team exercises
- Contribute to better team decisions
- Geoscientists and engineers producing estimates
- Subsurface team leaders
- Exploration and development managers
- Technical assurance and review staff
- Planning and portfolio staff
- Reserves and resource staff
- Managers making subsurface investment decisions
Module 1 - Evidence for Systematic Bias
- Pre-drill prediction against outcome studies
- Frequency of outcomes outside stated ranges
- Volume prediction performance
- Reserves revision patterns
- Direction of revisions over time
- Project cost overrun statistics
- Schedule overrun statistics
- Exploration success rate against prediction
- Consistency across companies and basins
- Why experience does not correct it
- Treating bias as measured rather than theoretical
- Implications for technical practice
Module 2 - Overconfidence and Calibration
- Overconfidence definition
- Interval estimation and its failure
- Calibration concept
- Measuring calibration
- Calibration scoring methods
- Typical calibration performance
- Expertise and calibration relationship
- Why wide ranges feel wrong
- Deliberate range widening
- Extreme case consideration
- Testing ranges by stating the extremes
- Improving calibration through feedback
Module 3 - Anchoring and Availability
- Anchoring mechanism
- First number effects
- Previous estimates as anchors
- Analogue values as anchors
- Partner and management expectations as anchors
- Counteracting anchors
- Independent estimation before exposure
- Availability bias mechanism
- Recent events and their weight
- Memorable failures and successes
- Base rate neglect
- Reference class and outside view methods
Module 4 - Confirmation Bias in Interpretation
- Confirmation bias mechanism
- Ambiguous data and expectation
- Seismic interpretation and expectation
- Horizon picking consistency with the model
- Fault interpretation and expectation
- Correlation and the preferred framework
- Selective attention to supporting data
- Explaining away contradicting data
- Blind interpretation exercises
- Independent duplicate interpretation
- Seeking disconfirming evidence
- Falsification as a working discipline
Module 5 - Motivational and Organisational Bias
- Incentive effects on estimates
- Project continuation incentives
- Reserves and performance incentives
- Budget and schedule pressure
- Optimism in project advocacy
- Strategic misrepresentation
- Good faith optimism
- Direction of organisational pressure
- Hierarchy and deference effects
- Bad news suppression
- Structural countermeasures
- Separating advocacy from assessment
Module 6 - Group Effects
- Group convergence on estimates
- Range narrowing in discussion
- Social pressure to agree
- Dominant participant effects
- Groupthink characteristics
- Shared assumptions in long standing teams
- Diversity and its effect on estimation
- Independent estimation before discussion
- Discussing differences rather than negotiating
- Structured elicitation methods
- Delphi and estimate aggregation
- Preserving dissent in deliverables
Module 7 - Debiasing Techniques
- Premortem exercise conduct
- Why premortems surface hidden concerns
- Red team construction and remit
- Devil's advocate roles
- Reference class forecasting
- Base rate anchoring
- Checklists as debiasing tools
- Blind and independent review
- Consider the opposite technique
- Decomposition of estimates
- Calibration training and feedback
- Technique selection by situation
Module 8 - Process Design and Embedding
- Designing processes that counter bias
- Independent estimation requirements
- Review points and their design
- Documenting assumptions and falsifiers
- Recording predictions before outcomes
- Outcome tracking systems
- Calibration measurement over time
- Learning reviews and look-backs
- Rewarding accuracy rather than optimism
- Leadership behaviour and its effect
- Embedding techniques in workflows
- Measuring whether debiasing worked
Upon successful completion of this training course, delegates will be awarded an official Certificate of Completion issued by the Petroleum Engineers Association (PEA), an ISO 9001:2015 certified training organization. The certificate carries 10 Credits and formally records the total learning hours completed.
Each certificate is signed by the Course Facilitator and the CEO of the Petroleum Engineers Association, and serves as verifiable proof of professional training that delegates can present to employers and professional bodies worldwide.
Frequently Asked Questions
All course bookings made through PEA are strictly non-refundable. By registering for a course, you acknowledge and accept that all fees are payable in full and are not subject to refund under any circumstances, including changes in personal or professional commitments or partial attendance.
PEA reserves the right to make reasonable adjustments to course content, trainers, or schedules where necessary, without entitling delegates to a refund. Comprehensive details of each course — including objectives, target audience, and content — are clearly outlined before enrolment, and it is the responsibility of the delegate to ensure the course's suitability prior to booking.
For any inquiries related to cancellations or bookings, please contact our support team, who will be happy to assist you.
