Join Mark Smith and co-founder David Conley as they share the remarkable origin story of Empirical Energy, from sitting in a hot tub during oil field layoffs to revolutionizing how the energy industry measures and trades clean natural gas. This episode takes you behind the scenes of their journey from computer vision leak detection to creating the world's first empirically measured natural gas trading platform.

Tune in to discover how they're solving the massive data problem plaguing the oil and gas industry, why emission factors are fundamentally flawed, and how their technology is enabling producers to get premiums for truly clean energy production. David reveals how they built their first proof of concept in just 90 days and scaled from a single camera detecting fugitive emissions to a comprehensive platform that's changing how energy is measured, verified, and traded.

Key topics explored include the three major causes of emission events they've identified through millions of hours of AI monitoring, the difference between book and claim versus physical energy trading, and why vertical integration is crucial for solving the complexity problem that has plagued differentiated gas programs. Learn about their partnership with traders like Gunvor and how they're creating new markets for empirical natural gas and RNG blending.

Take away points: 

• The oil and gas industry relies on emission factors that can be 12 times higher than actual measured emissions 

• Computer vision and AI can automate leak detection and reduce the need for dangerous nighttime field visits 

• Three main emission events: cold venting, tank overpressuring, and loadout operations 

• Empirical measurement enables 40% carbon reduction for data centers switching from default factors 

• Book and claim trading allows clean gas premiums while physical infrastructure develops 

• Vertical integration reduces complexity and costs compared to multiple vendor solutions 

• Blending empirical natural gas with RNG can create net zero fuel products

Chapters: 

0:00 - Intro 

1:00 - The Hot Tub Moment: Origin Story of Empirical Energy 

4:48 - From Computer Vision to Leak Detection Technology 

8:15 - Remote Monitoring Revolution in Oil and Gas 

11:20 - Three Major Types of Emission Events Discovered 

14:40 - The Emission Factor Problem and Regulatory Issues 

18:02 - Community Relations and Environmental Stewardship 

20:26 - Data Integration Challenges and Solutions 

23:54 - ISCC Certification and Trading Mechanisms 

27:00 - Carbon Intensity Calculations and Data Center Applications 

31:14 - Book and Claim vs Physical Trading Explained 

34:39 - Vertical Integration Benefits and Cost Reduction 

37:03 - Premium Pricing and Market Opportunities 

39:28 - Outro

Quote of the show: "I've never seen a production facility produce an MMPTU of energy over one gram of CO2E per megajoule and they're reporting 12."

Ready to learn how empirical measurement is transforming energy markets? Subscribe for more insights into the intersection of AI, blockchain, and clean energy trading. Like this episode and share it with anyone interested in the future of energy verification and the technologies reshaping how we measure environmental impact.

#EmpiricalEnergy #CleanGas #EmissionMeasurement #OilAndGas #EnergyTrading #AI #ComputerVision #CarbonIntensity #NetZeroGas #EnergyInnovation #Blockchain #LNG #RNG #DataCenters #EnvironmentalTech