Resources / Video Hub Library / Conneqt 2026 – Oil & Gas

Seeq for Oil & Gas - Seeq & Radix

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Category: #Conneqt 2026
Industry: #Oil & Gas
Topic: #Operational Efficiency #Seeq Product Capability

Shaista Mallik, Industry Principal, Oil & Gas, Seeq

Matt Sherick, Senior Analytics Engineer, Seeq

Josh Conroy, Vice President, Digital Products & Strategic Alliances, Radix

Seeq’s expanding oil and gas strategy takes center stage in this session, with a look at new upstream and asset health monitoring solutions built to reduce production deferment, optimize artificial lift, and scale analytics across upstream, midstream, downstream, and LNG operations. The presentation also features a compressor reliability example that shows how Seeq can identify lubrication-system degradation months before a critical alarm, explain the issue using transparent AI grounded in engineering context, and turn those insights into a governed maintenance workflow with evidence ready for action in SAP. Together, these examples position Seeq as a platform for combining asset data, packaged templates, and expert-led deployment to drive faster, more reliable operational decisions at scale.

Conneqt 2026 – Oil & Gas

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  • 1

    32:48

    Seeq for Oil & Gas – Seeq & Radix

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    15:06

    Quantifying Network Capacity and Risk in Crude Oil Gathering Networks Using Monte Carlo Simulation – Marathon Pipeline

  • 3

    Environmental Compliance with Seeq Vantage – Marathon Petroleum

  • 4

    20:55

    Energy Sustainability at Scale – PBF Energy

Resources / Video Hub Library / Quantifying Network Capacity and Risk in Crude Oil Gathering Networks Using Monte Carlo Simulation – Marathon Pipeline

Quantifying Network Capacity and Risk in Crude Oil Gathering Networks Using Monte Carlo Simulation - Marathon Pipeline

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Category: #Conneqt 2026
Industry: #Oil & Gas
Topic: #Asset Management

Andrew Foltz, Project Engineer, Marathon Pipeline

Learn how Seeq Datalab and Monte Carlo simulation can help operators understand pressure behavior across complex crude oil gathering networks, where constantly changing site activity makes traditional capacity analysis difficult. He explains how the approach uses real operating data to model thousands of possible conditions, score bottlenecks, and identify targeted solutions—including drag-reducing agents and variable-speed drives—that reduce high-pressure shutdown risk while preserving throughput. The session highlights practical results, including a roughly 90% reduction in projected high-pressure events, improved producer flexibility, lower chemical usage, and new opportunities to support pipeline forecasting, expansion, and network design.

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Resources / Video Hub Library / Conneqt 2025 – Food & Beverage + Power & Utilities

TVA - Elevating Combined Cycle Thermal Performance with Analytics

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Category: #Conneqt 2025
Industry: #Power & Utilities
Topic: #Statistical Process Control

David Tiffany, Engineer Performance Monitoring & Diagnostics, TVA

Conneqt 2025 – Food & Beverage + Power & Utilities

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    20:48

    TVA – Elevating Combined Cycle Thermal Performance with Analytics

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    16:33

    Ormat – Power Generation Forecasting with Seeq

  • 3

    18:18

    Chobani – Using Asset Groups to Easily Create Processing Metrics

  • 4

    17:50

    Cargill – From Data to Information to Action

Resources / Video Hub Library / Conneqt 2025 – Chemicals

Verdagy - Building a No User Learning Curve Internal Data Analysis Platform

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Category: #Conneqt 2025
Industry: #Chemicals & Petrochemicals

Emily Cole, ​Sr. Scientist, Verdagy

Verdagy developed a scalable monitoring tool for lab- and pilot-scale electrolyzers that automatically identifies and aggregates polarization curve parameters and summarizes other KPIs such as hydrogen production rate and total uptime metrics. Verdagy successfully implemented the tool across their technical teams to enable rapid results-sharing while maintaining uniform data analysis methodologies. The targeted scope of Verdagy’s tool enables widespread adoption and requires no learning curve to use. ​

Conneqt 2025 – Chemicals

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    20:56

    Verdagy – Building a No User Learning Curve Internal Data Analysis Platform

  • 2

    21:08

    Nutrien – Enhancing Ammonia Plant Reliability with Seeq

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    17:18

    Kaneka – Enhancing Polymer Reactor Productivity Using Seeq Analytics

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    16:55

    Indorama Ventures – Optimizing Data Science Deployment for Velocity

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    23:24

    Eastman Chemical Company – Machine Learning Analytics: Green is Good

Resources / Video Hub Library / Chobani – Using Asset Groups to Easily Create Processing Metrics

Chobani - Using Asset Groups to Easily Create Processing Metrics

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Category: #Conneqt 2025
Industry: #Food & Beverage
Topic: #Asset Management

Chloe Soejima, Process Engineer II, Chobani

Chobani used Seeq’s Asset Groups to streamline analysis across 20 yogurt separators — the “heartbeat” of their plant. By creating standardized templates, teams reduced reporting time, enabled cross-shift visibility, and improved fault root cause analysis. The improvements led to estimated savings of $10K–$20K per week.

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Resources / Video Hub Library / Nutrien – Enhancing Ammonia Plant Reliability with Seeq

Nutrien - Enhancing Ammonia Plant Reliability with Seeq

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Category: #Conneqt 2025
Industry: #Chemicals & Petrochemicals
Topic: #Asset Management #Downtime Reduction #Operational Efficiency

Dr. Nethika Suraweera PhD, Senior AI/Data Scientist, Nutrien

Adeyinka Opadeyi, Ammonia Process SME, Nutrien

Nutrien’s Real Time Operation Center (NROC) oversees operational efficiency of 10 Nitrogen Production Sites. NROC has utilized rapid data navigation and modeling during both the data exploration and analysis phases, enabling timely detection of failures and proactive interventions. We will review a few use cases illustrating the transformative impact of data monitoring and analytics in Nitrogen production, demonstrating how we leverage Seeq to ensure operational excellence.

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Resources / Video Hub Library / Bat Curtailment Compliance Reporting at Scale

Bat Curtailment Compliance Reporting at Scale

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Category: #Conneqt 2024
Industry: #Power & Utilities
Topic: #Asset Management

Jordan Rutledge, Data Analyst, Deriva Energy

Bat curtailment for wind turbines is required in order to be compliant with the guidelines of the U.S. Fish and Wildlife Service. Using Seeq Data Lab, in collaboration with a data science team, this project utilizes python code in order to create capsules for active bat curtailment and missed bat curtailment. The calculations for these capsules at turbine level are then scaled for the entire wind fleet in order to produce a scorecard metric for each wind site. The scorecard metric is achieved using an OData export of all capsules to Power BI. This project gives visibility to the accuracy of bat curtailment at each wind site and allows site engineers to identify events of missed bat curtailment.

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Resources / Video Hub Library / Advanced Asset Monitoring

Advanced Asset Monitoring

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Category: #Conneqt 2024
Industry: #Oil & Gas
Topic: #Asset Management

Jose Silvestre, Supervisor Operational Analytics, Enterprise Products

Matthew Richardson, Engineer Operational Analytics, Enterprise Products

In oil and gas operations, traditional equipment monitoring relies on physical checks and lacks the flexibility of current analytical tools. Our Advanced Asset Monitoring (AAM) program uses advanced data ingestion, anomaly detection, and signal processing to proactively identify equipment health issues. This allows our engineers to pinpoint root causes and predict failures, leading to improved maintenance planning and preventing costly downtime. AAM has successfully identified specific maintenance needs, like spark plug replacements, demonstrating its effectiveness in shifting from reactive to proactive maintenance.

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Resources / Video Hub Library / Brazed Aluminum Heat Exchanger Dashboards

Brazed Aluminum Heat Exchanger Dashboards

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Category: #Conneqt 2024
Industry: #Oil & Gas
Topic: #Asset Management

Sjoerd Hoogwater, Consulting Engineer, Phillips 66

Brazed aluminum heat exchangers (BAHX) allow high rates of heat transfer, but the equipment is susceptible to mechanical failures and internal/external leaks. As recognized by BAHX manufacturers, thermal cycling and high temperature differentials between adjacent streams can cause fatigue on the equipment and contribute to equipment failures. Seeq functionality was utilized to calculate the historical and current thermal cycling and temperature differential magnitudes on each BAHX across the fleet.

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Resources / Video Hub Library / Integration of Advanced Analytical Models in Value-Based

Integration of Advanced Analytical Models in Value-Based

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Category: #Conneqt 2024
Industry: #Power & Utilities
Topic: #Asset Management

Yanging Li, Lead Condition Monitoring Engineer, RWE Generation UK

RWE’s digitalization team aims to maximize existing asset value for a business edge. A key project, Value-Based Maintenance (VBM), uses advanced algorithms to predict failures and optimize maintenance plans based on real-time risk assessment. To achieve this, a cross-functional team built MARA (Maintenance & Asset Reliability Assistant) – a digital toolset with machine learning models that assess component health and predict failures. The presentation will showcase how MARA uses bespoke Seeq models to create health scores and how these scores are integrated into MARA for practical use. Real-world examples will demonstrate the value of these models in improving equipment reliability and availability.

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