Most information acquired in subsurface work has no value, in the specific technical sense that it cannot change a decision. An appraisal well that will confirm a development is viable when the development would proceed anyway, a seismic survey that will refine a volume estimate within a range where the decision does not change, a core programme that will improve a parameter the outcome is insensitive to: each of these costs money and produces knowledge, and none of them produces value. Value of information analysis identifies which data acquisition actually earns its cost, and applying it routinely changes appraisal spending substantially.

Framing errors are the most expensive and the least examined. A team asked to determine the optimal well count for a fixed facility design will produce a good answer to that question, and may never consider that a different facility concept would produce more value. A team asked whether to develop a discovery may not consider selling it. Framing determines the space within which alternatives are sought, and a frame set too narrowly excludes the best option before analysis begins.

Alternatives are usually too similar to each other. A development study presenting three options that differ in well count is presenting one alternative at three scales. Genuinely distinct alternatives differ in concept, in timing, in scale, in ownership structure or in technology, and generating them requires deliberate effort against the natural tendency to converge early on a preferred approach. The value difference between distinct alternatives is normally far larger than the value difference between variants of one.

Finally, bias operates systematically and predictably. Anchoring on initial estimates, overconfidence in narrow ranges, confirmation bias in evidence selection, motivational bias where estimates serve an interest, and the tendency of groups to converge prematurely are all documented, all present in subsurface work, and all partly correctable by process. Recognising them is more useful than exhorting people to avoid them.

By the end of this training, participants will be able to:

• Apply the elements of decision quality and assess a decision against them
• Frame decisions appropriately and recognise when a frame is too narrow
• Generate genuinely distinct alternatives rather than variants
• Characterise uncertainty and conduct expert elicitation while managing bias
• Construct and evaluate decision trees including expected value calculation
• Calculate value of information and determine whether data acquisition is justified
• Calculate value of control and identify where influence rather than information creates value
• Apply real options thinking to staged and flexible development decisions
• Recognise cognitive and motivational bias and apply process countermeasures
• Establish organisational practice that produces consistently good decisions

The training is worked through decision problems drawn from subsurface practice: appraisal decisions, development concept selection, data acquisition, and staged development. Participants frame the decisions, generate alternatives, characterise uncertainty, build decision trees and calculate expected value, value of information and value of control numerically. Elicitation is practised directly, with the resulting ranges tested for overconfidence. Real decisions and their outcomes are examined, separating decision quality from outcome quality.

Organisations sending participants to this training will:

• Reduce appraisal and data acquisition spend that cannot change a decision
• Improve development concept selection through better framing and alternative generation
• Improve the calibration of subsurface uncertainty ranges
• Reduce the effect of bias on technical estimates and recommendations
• Establish a common decision language across technical and commercial functions
• Judge decisions by their quality rather than by their outcomes

Participants will:

• Frame decisions properly before analysing them
• Generate alternatives that differ in ways that matter
• Calculate whether proposed data acquisition is worth its cost
• Build and evaluate decision trees
• Recognise bias in their own and others' estimates
• Build a capability that improves every technical recommendation they make

• Reservoir, production and development engineers
• Geoscientists working on appraisal and development decisions
• Development planners and asset engineers
• Reserves, evaluation and portfolio staff
• Technical and commercial managers making investment decisions
• Project and study leaders framing technical work
• Anyone specifying or approving data acquisition programmes

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.