The most common failure in reservoir engineering is applying a method beyond the data that supports it. Material balance on a field with three pressure points and questionable production allocation produces a number, and that number will be used, but it carries no information. A simulation history matched to twenty years of production with fifteen adjustable parameters can reproduce the past without predicting anything. In both cases the calculation is correct and the conclusion is worthless, and the difference is only visible to someone who understands the method's requirements.

Data quality therefore deserves the attention it rarely receives. Pressure measurements taken during flowing conditions, production allocated by outdated well tests, PVT samples taken below bubble point, core measurements made on unrepresentative plugs and log-derived saturations from an unvalidated model all enter reservoir calculations as facts and leave as errors. Establishing what the data can support is the first step of any reservoir engineering study, not an optional preliminary.

Method redundancy is the practical defence. Volumetric in-place, material balance connected volume and simulation model volume should be compared, and where they disagree the disagreement is information. Decline extrapolation, material balance recovery and analogue recovery factors should be compared for the same field. Independent methods converging on similar answers is the strongest evidence available in a discipline where nothing can be measured directly.

Finally, reservoir engineering exists to support decisions about money. Well count, facility size, injection strategy, development phasing and reserves bookings all rest on reservoir engineering output, and the value of that output lies in how well it characterises uncertainty rather than in the precision of a single number. Presenting a range with its basis is more useful to a decision maker than presenting a point estimate with unstated assumptions.

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

• Characterise reservoir rock and fluid properties and assess the quality of the data behind them
• Estimate hydrocarbon in place volumetrically and construct defensible uncertainty ranges
• Apply material balance to oil, gas and gas condensate systems and identify the operating drive mechanism
• Interpret well test and production analysis results and integrate them into reservoir description
• Apply displacement theory, relative permeability and sweep efficiency concepts to recovery estimation
• Evaluate waterflooding, gas injection and enhanced recovery options against reservoir and fluid characteristics
• Determine when reservoir simulation is justified and specify a study that will answer the question asked
• Forecast production and classify reserves against recognised definitions
• Design surveillance programmes that reduce the uncertainties that matter to decisions
• Select methods appropriate to available data and present results with their uncertainty

The training works through the reservoir engineering toolkit in the order it is normally applied, with each method developed through its assumptions, data requirements and calculation procedure, then applied numerically to field data. Multiple methods are applied to the same field so that participants see where they agree and where they diverge, and what the divergence indicates. Data sets with quality problems are used deliberately. Field case histories are examined for the analysis that led to a good or poor development decision, and participants are encouraged to bring reservoir problems from their own assets for group work.

Organisations sending participants to this training will:

• Improve the technical quality and consistency of reservoir engineering work across the organisation
• Reduce development decisions taken on inadequately supported reservoir analysis
• Improve reserves reliability and reduce the frequency of significant revision
• Strengthen internal review of reservoir studies produced by consultants and partners
• Improve surveillance design so that data collection targets the uncertainties that matter
• Build a common technical standard and vocabulary across reservoir engineering staff

Participants will:

• Select and apply the reservoir engineering method appropriate to the available data
• Recognise when a calculation is not supported by its inputs and say so
• Cross-check results between independent methods and interpret disagreement
• Present reservoir engineering conclusions with appropriate uncertainty
• Contribute to development planning and reserves work with confidence
• Consolidate scattered reservoir engineering knowledge into a coherent working practice

• Reservoir engineers at all levels seeking a consolidated technical foundation
• Production and petroleum engineers moving into reservoir roles
• Geoscientists working closely with reservoir engineering teams
• Reserves and evaluation engineers
• Simulation engineers requiring stronger analytical grounding
• Asset managers and technical supervisors reviewing reservoir engineering work
• Graduate engineers entering subsurface roles

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.