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A CNX news hub highlighting all aspects of our Appalachia First vision. Subscribe for insights on energy innovation, advocacy, and community...

Quality Data, Better Operations: CNX’s Austin Blake on Digital Transformation

CNX’s approach to quality data is more than a back-office metric—it is the engine that drives operational efficiency, excellence in execution, and long-term value for shareholders. 

Across CNX’s footprint, the same disciplined approach to data that improves uptime and lowers emissions parallels the company’s industry-leading 

In the EnergyTech Podcast episode below, “

The ROI of Clean Data: Unlocking Value Across Drilling, Completions & Midstream,”

 CNX Director of Data Austin Blake shares how CNX is transforming its data foundation. 

Watch and listen as Austin explains how clean, consistent operational data enables better, faster decision-making.

In this episode of the Energy Tech Podcast, Mike Flores sits down with Austin Blake — Director of Data at CNX Resources — for one of our deepest, most comprehensive conversations yet on data quality, machine learning, edge computing, anomaly detection, and what real digital transformation looks like inside a major upstream operator. This conversation pulls back the curtain on how CNX is rebuilding its entire data foundation, streaming real-time operational data from the field, and applying advanced machine learning models to critical equipment like fracture fleets, flowback operations, and multi-stage compressor stations.
WHAT YOU’LL LEARN IN THIS EPISODE
1. Modernizing Oilfield Data
How CNX moved from siloed spreadsheets to a governed Snowflake data lake with clean, consistent, ML-ready data.
2. Real-Time Edge Visibility
How MQTT + AWS IoT Core deliver sub-second frac, flowback, and drilling data—and how offset-well monitoring helps prevent frac hits.
3. Machine Learning That Works
How CNX built practical anomaly detection models using 1-second SCADA data to improve compressor uptime and maintenance planning.
4. AI vs. Reality
Why GenAI won’t fix bad data—and why traditional time-series ML still delivers the most value in oil & gas operations.
5. Austin’s Career Path
How a completions engineer became CNX’s Director of Data and what he’s learned about failing fast and delivering real value.
Chapters
00:00 – Welcome to the Energy Tech Podcast
00:16 – Introducing Austin Blake (Director of Data, CNX)
00:48 – CNX’s digital transformation and Austin’s role
01:30 – Fixing siloed data with a modern Snowflake architecture
03:05 – Data governance, medallion layers, and eliminating Excel chaos
04:05 – Austin’s background: field engineering → completions → data
06:00 – Why completions lacked real-time data historically
07:03 – Rise of Python, analytics, and why engineers must learn data
08:30 – When CNX realized it needed to fix data before ML
12:00 – Why ML fails without clean data
13:30 – The well-naming problem in oil & gas
15:00 – Misconceptions about AI “orchestrating” bad data
16:02 – Aligning drilling, completions, production & midstream around data
17:10 – CNX’s edge journey: Red Lion, vendors, and protocol challenges
18:30 – Building the edge → AWS IoT Core → MQTT pipeline
20:04 – Why sandbox environments accelerate innovation
21:30 – Hot vs cold data paths: real-time vs long-term reporting
24:00 – Real example: completions dashboards in Grafana
25:20 – Preventing frack hits with offset-well observability
28:00 – Demo walkthrough: real-time frack visualization
32:50 – Why smaller operators can do this themselves
34:00 – Building context at the edge (MQTT/Sparkplug)
35:20 – Machine learning on compression fleets
37:30 – Using 1-second SCADA for anomaly detection
39:50 – Deploying ML models + measuring success via uptime
42:00 – Austin’s personal approach: iterate fast, fail fast, deliver value
44:30 – AI vs ML: what matters in oil & gas
47:00 – Closing thoughts + subscribe
Music: Uygar Duzgun / “Fast Life” / courtesy of www.epidemicsound.com

The ROI of Clean Data: Unlocking Value Across Drilling, Completions & Midstream - EP 051

CNX is rebuilding its data foundation from the wellhead up—transitioning from siloed, spreadsheet-based systems and toward governed, cloud-based architecture designed for clean, consistent, machine-learning-ready data.

Internally, CNX uses high-frequency data monitoring and advanced analytics to spot trends, refine operating practices, and identify opportunities to cut emissions and improve reliability across the asset base. 

Externally, transparent, verifiable data is at the core of the company’s environmental stewardship, including Radical Transparency—providing policymakers, communities, and investors a clear, evidence-based view of how responsible natural gas development performs against science-based air quality and emissions benchmarks.

“Radical” in Radical Transparency does not refer to rhetoric; it refers to radically higher standards for data integrity and accountability. 

By investing in rigorous data collection, modern digital infrastructure, and practical machine learning at the edge of operations, CNX is building a model where operational excellence, environmental performance, and shareholder value are all grounded in the same uncompromising foundation: quality data that anyone can see and test for themselves.

Quality Data, Better Operations: CNX’s Austin Blake on Digital Transformation

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