Official Agenda 2026
Download agenda .pdfEvent will take place in Houston, TX, USA (GMT-5) time zone.
07:00 - 09:00
Registration & Refreshment Networking
09:00 - 09:30
One Governed Source of Truth: Reliable AI Across Construction, Commissioning, and Asset Operation
- Establishing a single, governed source of truth across construction, commissioning, and asset operations.
- Enabling reliable AI answers using the latest approved drawings, procedures, and SOPs.
- Automating document linking, revision comparison, and master document management to accelerate project delivery.
- Strengthening collaboration and secure information exchange between engineering teams, EPCs, and contractors.
- Reducing manual errors through version control, AI-driven quality checks, and end-to-end document traceability.
09:30 - 10:00
Beyond the Repository: Integrating Engineering Knowledge into a Living System
- Why fragmentation, not scarcity, is the real failure mode of engineering knowledge management
- The architecture of an integrated knowledge spine - connecting standards, deviations, conflicts, lessons, and experience so an insight in one propagates to all
- How an AI reasoning layer across integrated knowledge surfaces patterns, clashes, and needed standard changes no single silo could see
- A maturity path from document repositories? connected system? self-assuring, living knowledge
10:00 - 10:30
Bridging the Gap: Why Operational AI in Oil & Gas Starts at the Edge From Cloud Reliance to Edge Resilience Across the Distributed AI Factory
- Understanding why Edge AI is essential for real-time operational decision-making in oil and gas.
- Designing distributed AI architectures that balance edge, cloud, and centralized AI capabilities.
- Integrating Operational AI into existing OT environments while maintaining safety and reliability.
- Overcoming connectivity, latency, and infrastructure challenges to scale AI across industrial operations.
- Applying real-world lessons for moving AI initiatives from pilot deployments to enterprise-wide production.
10:30 - 11:00
Operational Intelligence: Turning Data into Business Growth
- Using LogistixIQ as a real-world case study, this presentation demonstrates how AI predicts supply chain risks that contribute to nonproductive time (NPT), automatically prioritizes recommendations, and supports operational decision-making throughout well execution. Attendees will see how AI-generated insights are embedded into daily field workflows to improve execution - not simply reported after the fact.
- The session will also explore how E&P operators can extend this approach by creating an operational data hub that enables AI agents to monitor multiple contractors, identify emerging execution risks across the supply chain, and recommend coordinated actions before performance degrades.
- Finally, the presentation will discuss the practical challenges of building an operational AI platform, including data quality, system integration, change management, and the methods used to transform fragmented operational data into trusted, actionable intelligence.
11:00 - 11:30
The Prediction Layer: Why the Future of BI Is Not a Better Dashboard Session
- Moving from descriptive analytics to predictive and prescriptive operational intelligence.
- Embedding AI-driven forecasting into existing BI and operational systems without replacing legacy infrastructure.
- Using predictive intelligence to anticipate equipment failures, supply chain disruptions, and capital allocation risks.
- Designing decision workflows that deliver the right insights to the right leaders in real time.
- Measuring the impact of AI through faster decisions, improved operational performance, and reduced downtime.
11:30 - 12:00
How Physics-Based Platforms Turn Operational Data into Real-Time Insights That Drive Efficiency, Reliability, and Enterprise-Wide Digital Transformation
- Why scaling digital transformation initiatives often stalls at pilot projects—and how physics-based, small-data AI enables enterprise-wide deployment across complex industrial assets.
- How operators can convert fragmented operational data into actionable intelligence to improve production, reliability, and emissions performance—without costly equipment upgrades or infrastructure overhauls.
- What real-world digital transformation looks like in heavy industry: integrating physics-native AI to continuously optimize operations, balance safety and environmental constraints, and unlock measurable ROI.
13:00 - 13:30
Implementing Digital Transformation with AI: How Agentic Systems Drive Execution, Automation, and Scalable Results Across Operations
- Moving beyond deterministic testing to validate autonomous AI in dynamic operational environments.
- Using digital twins and agent worlds to train, simulate, and test AI systems before deployment.
- Evaluating AI agents against complex scenarios, edge cases, and potential failure conditions.
- Reducing deployment risk while improving reliability, safety, and confidence in autonomous AI.
- Scaling AI-driven execution and automation across critical infrastructure through simulation-led validation.
13:30 - 14:00
The Technology Trinity (Item 3) Real-time Data, Next-Gen Communication & Blockchain
- Real-time 360 degree execution visibility
- A digital nervous system for containerised and contextualized advanced communication from doers’ to decision makers
- A future technology of a multi-cloud hybrid blockchain enabled EPC project delivery system for precision in management of scope and changes
14:00 - 14:30
From Markups to Intelligence: Using AI to Turn Engineering Documents into Faster, More Reliable Energy Project Decisions
- Learn how standardizing drawings, documents, markups, and review workflows creates the trusted information foundation AI needs to deliver useful, reliable project insights.
- Identify where AI and connected document workflows can reduce review-cycle time, limit rework, surface changes faster, and improve collaboration across owners, EPCs, contractors, and field teams.
- Leave with a practical framework for governing AI-enabled workflows, driving adoption among project teams, and measuring value through faster decisions, stronger controls, and better continuity through handover.
BlueBeam
15:00 - 15:30
Fund the Business Case, Not the Pilot: Scaling Digital Twins to 7 Assets and $20-60MM/Year at a Supermajor
- Aligning digital transformation initiatives with business strategy and operational objectives
- Identifying high-value opportunities that deliver measurable business outcomes
- Applying best practices from large-scale engineering, operations, and capital projects
- Balancing technology innovation with practical business and operational requirements
- Driving sustainable, value-based digital transformation through proven implementation strategies
15:30 - 16:00
Industrial AI Without Accountability: Why AI Initiatives Fail to Scale and How Energy Leaders Can Turn Innovation Into Impact
- The energy industry is rapidly investing in AI, automation, and advanced analytics, but many organizations are discovering that successful transformation requires more than deploying new technology. Without clear ownership, governance, operational alignment, and measurable business outcomes, AI initiatives often remain disconnected pilots rather than enterprise-wide drivers of performance.
- Drawing from more than 30 years of leadership experience across energy, technology, and enterprise transformation, including global leadership roles at Halliburton Landmark Services, Steve Senterfit explores why industrial AI efforts stall and what leaders can do differently. This session will examine how oil and gas organizations can create accountability frameworks that connect AI investments to operational priorities, workforce adoption, and measurable value creation.
- Why AI initiatives fail when accountability and ownership are unclear
07:00 - 09:00
Registration & Refreshment Networking
09:00 - 09:30
The AI Field Manager: Building a Connected Operational Decision Intelligence Layer Across Wells, Water, Vendors, and OPEX.
- Reliable, real-time decision support across well performance, water management, and capital accountability remains an unsolved operational challenge for oil and gas operators - not because data is unavailable, but because the relationships between data are not queryable.
- Critical engineering decisions involving well prioritization, produced water disposal routing, vendor cost attribution, and AFE compliance monitoring require simultaneous access to information distributed across production databases, ERP systems, completions repositories, and AP platforms.
- In the absence of a connected data architecture, this integration burden falls on individual engineers, introducing hours of manual data assembly per query and systematically limiting the frequency and quality of operational analysis.
- The session presents the real-world deployment of the reView Intelligence Platform, a graph-native AI reasoning system, that unified well data, production history, financials, vendor records, AFEs, and water infrastructure into a single auditable, queryable knowledge graph for Civitas Resources with these results in the first six weeks: - $6.7M in annualized disposal cost savings from a 40% reduction in produced water trucking - $12M in avoided capital surprises through early AFE overrun detection - Complex cross-domain query time reduced from 2+ hours to under 10 second
09:30 - 10:00
Is There Such a Thing as Too Much Data?
- Understanding the distinction between data and information and why having more data is rarely the real problem.
- Exploring how data follows the same economic principles as inventory. It has costs to acquire, store, maintain, move, and transform, and its value is only realized when it is put to productive use.
- Reframing the objective of the data supply chain around the decision: what information does someone actually need to know to make the right decision at the right time?
- Using AI to rethink the relationship between data, information, and decisions - consuming more data while asking whether decision-makers actually need more information.
10:00 - 10:30
Business Transformation for Large Corporations – Where Testing Connects
- Testing as a Strategic Enabler
- Ensuring End-to-End Process Integrity
- Data Quality & Migration Readiness
- Connecting People, Process, and Technology
10:30 - 11:00
How to Deploy an AI Layer for Downstream Operations and Turnarounds
- Deploying an AI layer across permits, procedures, inspections, and maintenance workflows.
- Eliminating bottlenecks caused by paper-based processes and disconnected operational systems.
- Connecting frontline workflows and operational data for real-time field visibility and faster issue resolution.
- Scaling AI from pilot deployments to enterprise-wide adoption while achieving 85% field adoption.
- Delivering measurable value through lower administrative burden, stronger compliance, and faster turnaround execution.
11:00 - 11:30
From Remote Tanks to Real ROI: What Large-Scale Oilfield Monitoring Deployments Teach Us About Turning Simple Field Data into Real Savings
- Drawing on our major remote tank monitoring roll-outs with oil field service companies, look at what happens when thousands of previously “dumb” field assets become connected.
- Show where the real ROI comes from: fewer truck rolls, fewer manual tank checks, better replenishment, fewer run-outs and much better visibility of remote chemical inventories.
- Explore why getting simple, reliable data from the field is often more valuable than adding another sophisticated dashboard - and why platform agnostic monitoring matters at scale.
- Share the practical lessons learned from deploying remote monitoring across demanding oilfield applications: what works, what creates value, and where operators can achieve measurable savings quickly.
Rochester Sensors - an Amphenol Company
11:30 - 12:00
“Q“ Quantum Opportunities in the Oil and Gas Industry
- Overview of D-Wave’s quantum technology available in production today
- Discussion and Proof points of Quantum Annealing out performing classical solutions.
- Opportunities in the industry where Quantum Annealing can deliver real value.
13:00 - 13:30
AI Agents at Enterprise Scale: Petrobras’ Real-World Journey in Intelligent Automation, Regulatory Compliance, and Operational Excellence in Oil & Gas
- How Petrobras architected and deployed an enterprise-wide intelligent automation framework using SAP S/4HANA, delivering a 47% reduction in process cycle times and 31% improvement in decision accuracy across upstream, midstream, and downstream operations.
- Pioneering implementation of an AI Agents platform specifically designed for regulatory compliance in the oil and gas industry, enabling real-time monitoring, risk mitigation, and automated audit processes at global scale.
- Design and integration of AI-driven financial systems (New Cash Flow Analyzer, TM-TRM, BPC) that increased forecast accuracy by 37%, combined with an enterprise-wide agile transformation that accelerated product delivery 3.5x while boosting employee engagement by 42%.
- Practical lessons learned from building a comprehensive digital skills acceleration program that upskilled over 3,000 employees and created sustainable ecosystem partnerships for continuous innovation.
13:30 - 14:00
From Pilots to Production: Scaling Trustworthy AI Across the Oil & Gas Value Chain for Real Operational and Business Impact
- Artificial Intelligence is no longer a future promise for Oil & Gas — but scaling it beyond pilots remains a leadership challenge. This session explores how AI can be effectively operationalized across the O&G value chain, from upstream exploration and predictive maintenance to downstream optimization and commercial decision-making.
- Drawing from real enterprise-scale transformations in highly regulated and asset-intensive environments, the talk addresses three critical dimensions: (1) aligning AI initiatives with core business value and operational KPIs; (2) building trust through governance, data integrity, and responsible AI practices; and (3) enabling organizational adoption by integrating people, processes, and technology.
- Attendees will leave with a pragmatic framework to move from experimentation to sustainable AI-driven performance, reducing risk while accelerating impact
14:00 - 14:30
A practical path to safer, more resilient, data-driven operations using edge computing, sovereign AI, and a proven cloud partner.
- Using edge computing and sovereign AI to strengthen safety, resilience, and operational efficiency.
- Aligning digital technologies with existing processes and organizational culture.
- Applying a connect, compute, protect, and learn approach to unlock real-time operational insights.
- Improving decision-making through integrated, secure, and data-driven operations.
- Building scalable digital operations through proven cloud capabilities and predictable economics.
14:30 - 15:00
The Invisible Intelligence Layer: Engineering Real-Time AI Systems That Serve Billions Without Breaking
- Amazon's real-time AI infrastructure—systems processing millions of decisions per second while maintaining sub-millisecond latency.
- Practical architectural principles for distributed inference optimization, adaptive ranking systems, and federated learning at scale.
- Framework for engineering graceful degradation and extending Zero Trust principles into AI governance.
- Insight into production AI systems operating at global scale—the engineering trade-offs, failure modes, and architectural decisions that determine whether AI infrastructure thrives or breaks under pressure.
15:00 - 15:30
From Sandface to Topsides: How Cross-Disciplinary Teams Can Turn Fragmented Production Data into Clear, Practical, and Defensible Digital Investment Priorities for Offshore Assets
- Production losses rarely belong to one discipline. The session begins with a practical way to frame problems jointly across subsurface, wells, subsea, flow assurance, and topsides.
- It shows how operational data and engineering judgment can be brought together to separate measurement gaps, equipment constraints, process issues, and genuine optimization opportunities.
- Rather than producing another long opportunity list, the method ranks actions by production value, technical feasibility, implementation effort, operational risk, and readiness.
- The closing discussion covers ownership after the assessment, keeping disciplines engaged, converting findings into funded work, and tracking whether the expected operational value is delivered.
15:30 - 16:00
Beyond Digitalization: Transforming the End-to-End Contract Procurement Lifecycle Through an Integrated Enterprise Platform
- Transforming the end-to-end contract procurement lifecycle through integrated enterprise platforms
- Redesigning procurement processes to improve governance, efficiency, and compliance
- Enhancing collaboration through unified digital workflows and cross-functional integration
- Applying lessons learned and best practices for successful procurement transformation
- Leveraging AI-enabled automation and intelligent decision support to optimize procurement performance and business value
YASREF (Yanbu Aramco Sinopec Refining Company),
16:30 - 17:00
Next-Gen AI-Powered Real-Time Operations Center
- Unify real-time operational data, domain intelligence, and AI-driven insights into a single decision-making platform.
- Leverage predictive and prescriptive AI to identify risks, optimize performance, and recommend actions proactively.
- Enable continuous monitoring and autonomous workflows across drilling, production, and field operations.
- Accelerate decision cycles through contextualized data, digital twins, and real-time collaboration environments.
