Kyle Miller, Automation Manager, Marathon Pipe line

Marathon Pipe Line leverages Seeq to analyze pipeline pressure cycles, critical for predicting pipeline fatigue and ensuring operational integrity. Using Seeq Data Lab, they automate the process of pressure cycle counting, significantly reducing analysis from multiple days to mere minutes. This approach eliminates dependency on third-party tools, improving data reliability and saving approximately $50,000 annually. By quickly assessing cumulative pipeline damage, they enhance safety and operational efficiency.

Sjoerd Hoogwater, Consulting Engineer, Phillips 66

Phillips 66 employs Seeq to detect and analyze coke drum blowouts, a significant safety concern in refinery operations, particularly at their Borger Refinery. Previously unnoticed minor blowouts are quickly identified using Seeq’s advanced analytics capabilities, providing greater clarity on incident patterns and occurrences. Through rapid statistical analysis, they confirmed that blowouts occur in clusters rather than randomly, guiding more effective mitigation strategies. This implementation drastically reduces manual analysis time, enabling faster operational improvements and enhancing overall safety.

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John Spelic, Manager Automation & Equipment Analysis, Tallgrass

Tallgrass Energy uses Seeq to optimize the overhaul scheduling of turbines across multiple compressor stations, addressing the challenge of managing unpredictable runtimes and fluctuating pipeline conditions. The integration of Seeq provides real-time visualization of turbine operating hours and status, simplifying monitoring and enabling rapid response to undesirable configurations. Automating the scheduling process has already delivered substantial financial benefits, saving approximately $6 million immediately, with projected additional savings of up to $12 million. This strategic capability ensures predictable maintenance costs, stable financial planning, and enhances long-term operational reliability.

Albert Swalha, Staff OSI PI Engineer, Western Midstream

Western Midstream significantly streamlined regulatory reporting of Saltwater Disposal (SWD) wells by implementing a robust analytics solution using Seeq. Previously, regulatory reporting involved extensive manual Excel workbook preparations, which were labor-intensive and error-prone, consuming nearly 24 hours monthly. Using Seeq’s combined applications—Workbench, Data Lab, and Organizer—they automated data cleansing, analysis, and report generation, reducing monthly effort to only 1-2 hours. This scalable solution improves data accuracy, proactively highlights operational exceptions, and significantly reduces administrative burden, enabling analysts to focus on more strategic tasks.

Trey Morris, Principal Specialist – Operational Data Analytics, Energy Transfer

​Patrick Weber, Analytics Engineer, Seeq

Energy Transfer enhanced its operational analytics by implementing Seeq’s Vantage platform, significantly improving predictive maintenance and proactive asset management capabilities across their extensive pipeline network. They replaced reactive monitoring with a flexible, condition-agnostic system that supports real-time operational alerts, machine learning predictions, and anomaly detection. Seeq’s centralized “Vantage Room” improved cross-functional collaboration and provided a unified, reliable source of actionable insights. This solution delivered notable reductions in asset downtime and maintenance costs, increased operational efficiency, and fostered scalable growth to meet evolving operational complexity

Kyle Miller, Innovation Manager, Marathon Pipe Line

Tim Sandford, Refining PI Coordinator, Marathon Petroleum

Serge Ibarra, Environmental Engineer, Marathon Petroleum

Todd Dixon, Refining Services Senior Director, Marathon Petroleum

A quartet of Seeq champions across Marathon Petroleum and Marathon Pipe Line share how they are maximizing the value of Seeq across the business by pushing adoption and enhanced use cases.

Don Morrison, Real Time Data Architect, Devon Energy

Justin Milton, Data Scientist, Devon Energy

Discover how a strong strategic partnership with Seeq led to the successful scaling of advanced use cases across thousands of assets. This presentation reveals how aligning on a shared success plan drove real results, with practical insights for teams looking to achieve impactful, scalable analytics.

Brent Railey, Manager of Data Science, Chevron Phillips Chemical

Chris Herrera, Head of API & Interoperability, Seeq

Jai Karve, Solutions Architect, Databricks

As the concept of the “cloud lakehouse” matures and develops, Databricks has emerged as a key player in this space. Databricks is excellent at applying large-scale compute to data engineering, data science, and AI problems. However, Databricks is not a specialized time-series analytics tool, and does possess not out-the-box connectivity to industrial data sources.

On the other hand, Databricks has become a common store of IIoT data, with many companies landing the time-series data in their lakehouses and cloud datastore that Databricks compute engines can access.

Combining Seeq with Databricks together can have tremendous benefits–with Seeq being both a provider and a customer to Databricks. This session with outline patterns and practices, along with lessons learned, for Seeq and Databricks customers to scale-up their machine learning, IIoT, etc capability by conneqting (see what I did there?) Seeq and Databricks together.