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OPTIMIZATION OF THE END-TO-END OIL & GAS VALUE CHAIN FOR UPSTREAM INDUSTRY
- 1. Overcome siloed approach for optimization to improve End-to-End production Prediction-Optimization Framework
- 2. Introductions Crystal Lui, P.Eng Senior Analytics Manager & Data Scientist Cognitive & Analytics, IBM
- 3. The Opportunity Optimizing end-to-end System of Systems Optimization Rapid Decision-Making Real-time data driving business decisions New Ways of Working Explore how AI can amplify human expertise
- 4. Today’s Case Study: Canada’s leading integrated energy company $75B+ Enterprise value ~900 mbpd Oil production capacity ~500 mbpd Upgrading capacity ~1750 Retail sites
- 5. As operations are increasingly more integrated, so does the complexity of the system How do we integrate the world of data science with the physical complexities of industrial production? 80,000 sensor readings 30+ Plants 130,000+ Measurements ~1000 Key metrics…
- 6. Orchestrating upstream oil sands production holistically 6 What if we could… Optimize across siloes? Flag upsets early for timely response? Identify and action opportunities in real-time? Mine & In-Situ Feed, Primary Extraction, Secondary Extraction, Upgrading, E&U, Tank Farms
- 7. Solution: Production Optimization Advisor KEY CAPABILITIES • Upset Flagging • Scenario Generation (System of Systems Optimization) • Opportunity Awareness Production Optimization Advisor Production Optimization Solution productionoptimization.mybluemix.net “This is an exemplar of how AI and Optimization can herald some of the promise of AI in Industry 4.0… An advisor that is at par with some of our best area managers” – Director of Site Wide Ops Advisor
- 9. The Challenge: Real-time, and AI driven early- warning notifications for user defined process upsets PROCESS UPSET FLAGGING Production Optimization Solution THE SOLUTION: I want to be notified if a key inventory level is dropping! There are too many processes to track at once! How can I know something is going to fail before it happens? How can have access to information while I’m on the move?
- 10. Machine learning models provide early warnings for high value process upsets Early warning flag triggered @ 5pm Threshold-based flag triggered @ 6pm Quality Quality Threshold • Mitigates risk by improving situational awareness and allowing for preventative action • Predictive flags and timely threshold alerts improve upset response time Value:
- 12. The Challenge: End-to-end optimization model integrates machine learning and real-time mass balancing to generate new production plan within minutes SCENARIO GENERATION THE SOLUTION: How can I reset my production plan after a process upset? I want to know what I can do to maximize production. How can I compare the outcomes of different production strategies? How can I manage tank inventories?
- 13. Optimization model that breaks down silos between business areas to form a System of Systems
- 14. Layers of models to recommend actions by integrating machine learning and real-time mass balancing Flow Interdependencies Constraints Min/Max Constraints Tanks Goals Objective Function Restrictions Predictive Models Process Upsets Quality Constraints Maximize Production Targets Achieve Inventory Targets Standard linear regression Decision tree regression Multivariate adaptive regression splines (MARS) Mass-Balance Models Minimize Expensive Inputs Maintenance Events Flows
- 15. Generate production plans based on dynamic events and operational objectives Production Optimization Solution • Informs decision making by suggesting unbiased approaches and allowing comparison of multiple strategies • Improves process upset response or find room for optimization by creating a new production plan in 5 minutes Value:
- 17. The Challenge: Applying machine learning and streaming analytics to real-time data to bring awareness to high value opportunities as they occur OPPORTUNITY AWARENESS THE SOLUTION: How can I not miss opportunities even when we are busy? I need to investigate too many data sources to see if there is room for improvement. Can we maximize utilization of key assets? How can I be sure there are actions I can take?
- 18. Opportunity Awareness Example: Improve plant asset utilization • Models generate simple recommendations for actions that users can take to close the identified operation gap. • Actioned opportunities can maximize asset availability, improve product quality, minimize energy use, etc. Value:
- 19. 19 19 19 The human aspects of the on-going journey
- 20. Catalyst for Digital Transformation Digital Sponsorship Stakeholder Commitment Transformation Partners Opportunity Prioritization Business Case & Cultural Change Cognitive & Industry Consultants Asset & Applied Researchers End-User Ownership and Involvement
- 21. Human centered design and SME engagement are essential for sustainable value creation “Data Scientists. Meet Process engineers” Co-creation between data scientists and domain experts is essential to build models that create real value. “Design AI around humans” (not the other way round) Human Centered Design is even more important for AI-driven tools than it is for conventional systems. “Data science support is not the same as app. mgmt.” Data science based solutions require active monitoring and regular tuning in response to operational changes. The teams maintaining these models need expertise at the intersection of production processes and data science.
- 22. Production Optimization Advisor delivers value by augmenting human decision making This [Production Optimization Advisor] initiative has the potential to generate business value in the order of millions of dollars per year by turning complex and big data into actionable insights - “Building the layers of a Cognitive Enterprise” article “ ” ~ 5 mins to generate multi-plant production optimization scenario 30+ mins lead time warnings provided to users prior to dynamic process upsets 82% average accuracy for machine learning based process upset models Along with identifying opportunities for operations to increase production, increase sales, maximize asset utilization, and improve energy efficiencies.
- 23. 23 Thank You!