Optimizing the hydrocarbon value chain means the business of extracting value from each point in the chain from feed to production to client delivery. There are opportunities to leverage recent advances in digital technologies, AI and ML to significantly enhance profitability and allow companies to confidently face the future.
2. DIGITALIZATION
AIMS FOR A
WORLD OF:
Proprietary Information 2
No safety incidents
Net zero emissions
No unplanned outages
Nimble response to market
changes and plan disturbances
A culture of profitability
A motivated and informed workforce
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Commercial Excellence
DAYS
Ahead
HOURS
Ahead
MINUTES
Ahead
WEEKS
Ahead
MONTHS
Ahead
YEARS
Ahead
SECONDS
Ahead
NOW
THE
PAST
BACKCASTING
EXECUTION
SCHEDULING
PLANNING
HYDROCARBON VALUE CHAIN
HYDROCARBONMANAGEMENTTIMEHORIZON
Window of Optimization
6. Proprietary InformationProprietary Information
Process and Offsites
Control & RTO
Reconciliation &
Variance Analysis
Production
Accounting
Rigorous
Simulation
Scheduling
Planning
Corrected
model
Corrected
data
Corrected
model
Plant
Raw
data
- 1 MONTH - 1 WEEK NOW
Today’s Challenges
• Limited integration between tools
• Linear models have limited validity
• Plan does not reflect logistic
constraints
• Sub optimal schedule
• Updating models is time-
consuming and SME dependent
• Largely heuristic data reconciliation
• Data siloed, poor quality
• Slow recognition of opportunities to
open constraints
• Control strategies not updated with
schedule changes
7. Proprietary Information 7
Process and Offsites
Control & RTO
Reconciliation &
Variance Analysis
Production
Accounting
Rigorous
Simulation
Scheduling
Planning
Corrected
model
Corrected
data
Corrected
model
Plant
Raw
data
- 1 MONTH - 1 WEEK NOW
Digital Future
• Data driven, automated
identification of optimization
using AI
• Intelligent, automated work
processes
• Automated data management
and tool integration
• Cloud enabled to facilitate;
• Scalability
• Collaboration
• Support
• Rapid enhancements
• Knowledge management
• Integration
• Visualization
8. Proprietary Information
Process and Offsites
Control & RTO
Reconciliation &
Variance Analysis
Production
Accounting
Rigorous
Simulation
Scheduling
Planning
Corrected
model
Corrected
data
Corrected
model
Plant
Raw
data
Optimization with AI
Use Cases
Plant-wide
optimization
Demand and
price forecasting
Reconciliation
and variance
analysis
Automation of
model updates
Automation of
production
scheduling
Knowledge Graph
9. 9Proprietary Information
Value Chain Knowledge Graph
Global optimization
Visualize and manage entire
supply chain
Connect data silos – Linked Data
Add structure and context
ML, text mining & NLP
Semantic search and AI
Automation, classification
Reporting, personalization
Provide agility
Model complexity
Business Taxonomy and Ontology – Meta Data
Partner
2
Partner
1
Plant
2
Plant
1
Place
2
Place
3
Place
1
Product
3
Product
1
Distance
Cost
Time
Mode
Feed
Production
Cost
Product
2
Production
Database
Simulation Database
Scheduling
Database
Planning
Database
ERP
Database
Unstructured
Data
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Opportunity
Engine
Base
Case
Profit
Opportunities
KBC
PIP
- Market Conditions
- Site Operating Conditions
Reconciliation and Variance Analysis
Scheduling
Optimal Targets
Expected
Benefit
Actual
Benefit
Schedule Constraint Set
Historical
Information
Optimal SolutionPlanning/Scheduling
Model
Actual Realization
Planning
Plan Constraint Set
Actual Actions
Desired Actions
Operation
Planning
Forecasts
Programs on > 150 sites
Rigorous Site Model
to Validate
Proposed
Improvements
Finding improvement opportunities automatically
12. 12Proprietary Information
Combining Simulation and Machine Learning
First
Principles
Model
Plant Data
Inputs
Model
Outputs
Feed quality and flow
Product Yields
Product Compositions
Fuel flow
Feed quality and flow
Operating parameters
Product Yields
Product Compositions
Energy consumption
Catalyst activity
Heat exchanger coefficients
KPIs
KPI analysis and model errors
Multiple indices
indicating process
and model status
Profit improvement opportunities
Yield
Energy
Example
On-line ML
(Multivariate analysis)
Process issues and model
inaccuracies can be
obtained
Parameters
- Tray Efficiencies
- Calibration Factors
13. 13Proprietary Information
Early detection of operational problems
Identify ‘potential’ opportunities by monitoring the index in real time
Normal Caution
Abnorm
al
Simulation and Measured Data
Time
Improvement opportunity index
14. 14Proprietary Information
Automation of Production Scheduling using AI
Crude
Scheduling
Refinery
Scheduling
Blending
Scheduling
Shipping
Scheduling
Task updates
Nomination
updates
Violated constraints
Deviations from plan
Economics
Baseline
Update
Explained
AI Classifier
Opening
inventory
discrepancies
Inventory
and past
task updates
MCTS,
Supervised and
Reinforcement
Learning
18. www.kbc.global
Simon Rogers
Simon.Rogers@jp.yokogawa.com
Excellence
is never an accident. It is always the result of high
intention, sincere effort, and intelligent execution; it
represents the wise choice of many alternatives -
choice, not chance, determines your destiny.
Optimizing an
integrated, agile and
accurate value chain.