Capture and act on lessons from incidents and near misses involving data-driven production optimisation.
Production Optimisation Using Big Data
A structured, applied course in data-driven production optimisation — designed to be used the week you return.
📍 Cairo🗓️ 5 training days📚 4 modules🎓 Accredited certificate
5intensive training days
4scientific modules
8training sessions
32detailed points
Course Overview
Regulators and insurers increasingly want documented evidence of how data-driven production optimisation is controlled. Deferred maintenance and deferred decisions on this area of energy and hydrocarbon operations both accrue interest. Plans for this part of energy and hydrocarbon operations often fail at the handover point between functions. Participants test their assumptions about data-driven production optimisation against scenarios designed to break weak ones. Across sectors, teams that rehearse this area of energy and hydrocarbon operations outperform teams that only plan it. It treats the energy and hydrocarbon operations discipline as an operating discipline and equips participants to run it as one. Participants develop a defensible line of reasoning for the choices they make about data-driven production optimisation. It is written for people who have to make this aspect of energy and hydrocarbon operations work with the resources they already have. The closing exercise tests whether the participant's plan for this part of energy and hydrocarbon operations survives a hostile question.
Expected Learning Outcomes
Verify that improvements to data-driven production optimisation have held six months after they were introduced.
Set acceptance criteria for data-driven production optimisation before work begins rather than after.
Assess the technical and commercial risk attaching to data-driven production optimisation across the asset life cycle.
Integrate data-driven production optimisation with the wider process safety management system.
Evaluate the environmental obligations arising from data-driven production optimisation.
Design a training and briefing approach that sustains competence in data-driven production optimisation.
Who Should Attend
Process safety and technical safety specialists reviewing data-driven production optimisation.
Operations staff who encounter the consequences of data-driven production optimisation directly.
Newly appointed managers taking on data-driven production optimisation for the first time.
Facility and plant managers accountable for data-driven production optimisation.
Commercial and planning analysts modelling data-driven production optimisation.
Inspection and integrity engineers assessing data-driven production optimisation.
Course Modules
Data-driven production optimisation: process safety, permits and isolation
2 sessions · 8 pointsSession 1Building the investment case for data-driven production optimisation that finance will accept
- Agree what will be standardised in data-driven production optimisation and what will not.
- Assess the emissions and discharge attributable to data-driven production optimisation.
- Model the economics of data-driven production optimisation at low, base and high price cases.
- Identify the failure modes of data-driven production optimisation with the highest consequence.
Session 2Moving data-driven production optimisation from approval to execution
- Confirm that lessons from data-driven production optimisation are shared beyond the team that learned them.
- Set escalation thresholds for data-driven production optimisation that work out of hours.
- Set out how exceptions to data-driven production optimisation are requested and approved.
- Define the trigger that would require data-driven production optimisation to be redesigned.
Data-driven production optimisation: economics, price exposure and investment case
2 sessions · 8 pointsSession 1Competence and handover on data-driven production optimisation when experienced staff leave
- Record the technical rationale for the chosen approach to data-driven production optimisation.
- Draft the minimum viable operating procedure for data-driven production optimisation.
- Compare the cost of data-driven production optimisation with the cost of its absence.
- Rank the weaknesses in data-driven production optimisation by consequence rather than by ease of fixing.
Session 2The environmental exposure created by data-driven production optimisation
- Build the competence framework that supports data-driven production optimisation.
- Anticipate the objections data-driven production optimisation will raise and prepare the answers.
- Identify the data already collected that bears on data-driven production optimisation.
- Distinguish symptoms from causes when data-driven production optimisation underperforms.
Data-driven production optimisation: competence, certification and handover
2 sessions · 8 pointsSession 1Reading condition data on data-driven production optimisation before failure, not after
- Confirm handover documentation for data-driven production optimisation is complete and current.
- Verify isolation points for data-driven production optimisation are proven and documented.
- Review the instrumentation on data-driven production optimisation for coverage gaps.
- Establish the alarm philosophy applying to data-driven production optimisation and remove nuisance alarms.
Session 2The permit and isolation regime that data-driven production optimisation actually requires
- Define the safe operating envelope for data-driven production optimisation and how deviations are detected.
- Review incident and near-miss history involving data-driven production optimisation.
- Close out actions on data-driven production optimisation rather than leaving them open indefinitely.
- Collect evidence on the present handling of data-driven production optimisation before proposing changes.
Data-driven production optimisation: incidents, lessons and continual improvement
2 sessions · 8 pointsSession 1Who answers for data-driven production optimisation, and to whom
- Confirm contractor competence records for anyone working on data-driven production optimisation.
- Verify emergency response arrangements cover the scenarios data-driven production optimisation can create.
- Check that management of change is applied to every modification of data-driven production optimisation.
- Set the trigger for a life-extension versus replacement study on data-driven production optimisation.
Session 2Comparing data-driven production optimisation with recognised practice
- Define acceptance criteria for data-driven production optimisation in advance.
- Establish what evidence demonstrates data-driven production optimisation is under control.
- Check that the permit regime covering data-driven production optimisation matches the actual hazard.
- Prepare the summary of data-driven production optimisation that senior management will read.
Choose the package that suits you
Silver Package
At least 3 people
USD1,250
- Workshop or Program Participation
- Airport Transfers
- Customized Badge
- Expert Mentorship (Private Sessions)
- Supervision & Secretarial Services
- Accredited Certificate of Participation
- Complete Training Kit
- Coffee Break
- Closing Ceremony
Gold Package
At least 3 people
USD1,850
- 5-night stay in a 5-star hotel
- Workshop or Program Participation
- Airport Transfers
- Customized Badge
- Expert Mentorship (Private Sessions)
- Supervision & Secretarial Services
- Accredited Certificate of Participation
- Complete Training Kit
- Coffee Break
- Closing Ceremony
Complete your registration
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