The disciplines that describe a reservoir do not naturally agree. Seismic interpretation carries depth uncertainty of tens of metres and resolves layers no thinner than a wavelength. Petrophysics resolves centimetres at the wellbore and nothing between wells. Core describes millimetres in a sample of unknown representativeness. Well tests average over hundreds of metres and cannot see structure. Production history integrates everything over years and constrains volume and connectivity without saying where either resides. Each dataset is correct within its own resolution and uncertainty, and where they conflict something in one of them is being over-interpreted.

Integration is the process of resolving those conflicts explicitly. A model whose gross rock volume comes from a seismic interpretation that the material balance says is too large has a problem that must be addressed, not documented and passed on. A permeability distribution that honours core but produces a well productivity an order of magnitude below the test result has a scale problem that will not fix itself during history matching. Catching these conflicts early is far cheaper than discovering them after a simulation model has been built.

The alternative — sequential handover, where each discipline delivers its product and moves on — remains common and produces predictable failures. The geological model is built without knowing what resolution the simulation needs. The simulation is upscaled to something the geologist would not recognise. History matching adjusts properties into ranges that contradict the core data. Nobody updates the static model when production evidence contradicts it. The result is a model that satisfies no discipline and is trusted by none. This course covers both the technical workflow and the practice required to avoid that outcome.

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

• Assemble and quality control a multidisciplinary dataset and identify conflicts between data types
• Reconcile data of different scale, resolution and uncertainty into a consistent description
• Build a structural and stratigraphic framework that honours seismic and well evidence
• Apply seismic inversion and attribute data as a constraint on property distribution
• Develop rock types that link geological facies to petrophysical and dynamic behaviour
• Model saturation using height functions consistent with capillary pressure and log evaluation
• Distribute properties geostatistically with appropriate conditioning and trend control
• Transfer the static model to a dynamic grid and verify what upscaling has changed
• Use dynamic data to condition and revise the static model rather than to override it
• Propagate uncertainty through the full workflow into the forecast and the decision

The course is delivered as an integrated workflow programme, following a reservoir from data assembly through to a dynamic model and a decision. Each stage is developed with attention to what the preceding and following disciplines require from it. Cross-discipline conflicts are worked through explicitly, using field cases where seismic, petrophysical, engineering and production evidence disagreed and had to be reconciled. The course is intended for mixed audiences, and the exercises are structured so that participants encounter the constraints their neighbouring disciplines are working under.

Organisations sending participants to this training will:

• Produce reservoir models that all contributing disciplines accept and use
• Detect and resolve data conflicts early rather than during history matching
• Reduce rework and cycle time in reservoir studies
• Improve forecast reliability by carrying uncertainty through the workflow
• Strengthen multidisciplinary team working and reduce sequential handover losses
• Maintain a living reservoir description that is updated as new data arrives

Participants will:

• Work effectively across the geology, petrophysics and engineering interfaces
• Understand what each discipline can and cannot resolve and why they disagree
• Build models that survive the transition from static to dynamic
• Use production data to improve the reservoir description
• Carry uncertainty through a workflow rather than discarding it at each stage
• Lead or contribute confidently to integrated reservoir studies

• Reservoir engineers working with static models and simulation
• Geomodellers and reservoir geologists
• Petrophysicists supplying inputs to reservoir models
• Geophysicists working on reservoir characterisation and inversion
• Simulation engineers receiving and upscaling static models
• Subsurface team leads coordinating integrated studies
• Technical managers responsible for study quality and delivery

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.