• Quantifying Appalachia’s power needs for AI compute and mapping where new capacity can come online fastest.
• Positioning natural gas and LNG growth to support data center loads while balancing reliability and emissions.
• Translating DOE and NETL priorities into clear project timelines, interconnect steps, and funding routes.
• Coordinating operators and midstream to align deliverability, pipeline constraints, and grid buildouts for near-term wins.

• What “production ready” looks like for AI in upstream, midstream, and downstream
• Playbooks that move use cases past pilots, including data, guardrails, and change management
• Measuring business impact, safety, and reliability without slowing delivery
• Governance that keeps humans in the loop and meets regulatory and customer expectations

• Linking natural gas generation to AI data centers to deliver reliable behind the meter power in Appalachia while meeting cost and uptime targets.
• Integrating IT and OT for secure telemetry, controls, and audit ready operations across the plant and the network.
• Building digital twins for design to commissioning to day one operations so issues surface early and fixes repeat across sites.

• Cleaning priority tags for temperatures, pressures, and flows to remove noise and fill gaps.
• Contextualizing signals with unit, equipment, and mode metadata so trends make sense.
• Inferring key measurements from reconciled balances where instruments are limited.
• Standardizing access and visualization so supervisors see the same truths shift to shift.

• Consolidating scattered data and shadow warehouses into a governed model so teams stop living in Excel.
• Building future-state semantic models and warehouse tables first so reports migrate weeks before go live.
• Plumbing WellView and other streaming sources on Day 1 so analytics continue without disruption.
• Freeing stakeholders from rebuild churn with ready-to-use reports that scale cost and performance insights immediately.

• Confronting the shrinking window to adopt AI and digitalization before today’s opportunities become tomorrow’s constraints.
• Closing the “digital gap” by moving laggards toward proven practices from early adopters.
• Integrating online data with offline data to unlock insight.
• Delivering measurable gains in flow assurance, risk management, and reservoir characterization through midstream and upstream case examples.

Each round table covers a different topic, allowing attendees to select which one to join. Round table leaders will begin with a 5-minute introduction of themselves and a brief overview of the topic, which can include a case study, lessons learned log, or industry update. They will then facilitate a 40-minute discussion with the group, encouraging feedback and questions. The last 10 minutes will focus on agreeing on five industry recommendations.

1. Pilot to portfolio in gas operations
2. Production surveillance patterns that scale
3. Drilling and completions analytics that crews actually use
4. Compressor reliability quick wins for gathering networks
5. Control room practices that improve operator awareness and audit readiness
6. Cybersecurity architectures for pipelines and plants that operations accept
7. Metering and allocation practices that reduce billing disagreements
8. Integrity data flows that streamline reporting for gathering operators
9. Open Subsurface Data Universe patterns with existing historians so apps are portable
10. Managing models in operations without creating technical debt

• Aligning roles and rewards for supervisors, controllers, and technicians so adoption sticks.
• Measuring usage and value with a few simple metrics so leaders scale what works and stop what does not.
• Coaching digital fluency on the job so productivity rises without extra steps.

• Implementing AI-powered advanced process control to maximize NGL recovery and minimize energy consumption
• Building dynamic digital twins that allow operators to simulate plant upsets and test responses safely
• Calculating the hard dollar benefits of AI-driven optimization to secure project funding in a single budget cycle.

• Translating goals into shift checklists supervisors can coach every day.
• Running tight handovers so plans, alarms, and priorities carry across crews.
• Tracking two usage metrics and one outcome metric to prove value weekly.
• Resetting behaviours fast when turnover or outages hit.

•    Sharing production forecasts and constraints with gathering and plant teams so bottlenecks are solved before they bite.
•    Coordinating maintenance windows across the chain so planned work does not cause preventable rate cuts.
•    Using shared metrics that reward end-to-end flow, so local improvements do not reduce total throughput.
 

• Quantify production-signature patterns that reveal stimulated rock volume behaviour
• Apply a Viola Jones feature framework with AdaBoost to flag underperforming unconventional wells
• Prioritise restimulation targets with a repeatable workflow that links time series data to field action
• Show outcome metrics that translate analytics into uplift and cost per barrel saved

•    Providing controlled access to supervisory control and data systems so experts help fast which reduces downtime.
•    Recording and audit changes automatically so trust in remote work stays high.
•    Solving more issues from a distance so travel time and overtime fall.
 

•    Combining inspection records, geographic information, and operating signals to prioritize repairs that cut risk fastest.
•    Producing required reports with less manual effort by standardizing data flows so engineers win back time.
•    Closing the loop from field findings to permanent records so fixes are verified and searchable.
 

•    Versioning and monitoring models so performance holds in production environments.
•    Automating safe rollback and redeploy so change risk stays low.
•    Reusing features and components so new use cases deliver faster.

•    Plant-wide historian clean-up that unlocked better advanced control
•    Aerial and ground inspections tied to digital work orders
•    Digital twins and AI-driven control case.
 

•    Capturing tag and asset data during projects so handover to operations is clean and usable.
•    Standardizing testing and acceptance so analytics start on day one.
•    Sharing lessons between project and plant teams so future builds run faster.

•    Using open data standards to remove silos so analytics deploy faster across assets.
•    Leveraging a managed cloud service aligned to the standard so integration effort and run costs fall.
•    Shipping repeatable templates that multiple sites can deploy in weeks so value scales.
 

•    Defining clear roles and incentives for supervisors, controllers, and technicians so adoption improves.
•    Tracking usage and value with simple metrics so leaders know what to scale and what to stop.
•    Teaching digital fluency through on-the-job coaching so productivity rises without adding complexity.