SotaOG: ML + Physics to Drive Real-Time Value in O&G | Sarah Tamilarasan | CrowdField Podcast EP01

Welcome to Episode 1 of our brand-new CrowdField Podcast: O&G Builders, Agents & Workflows. In this debut episode, I sit down with Sarah Tamilarasan, CEO and Co-founder of SOTAOG, to explore how her team is blending machine learning and physics to deliver real-time insights and decision support for oil and gas operators. We walk through the SOTAOG platform, focusing on how it predicts bottomhole pressure, monitors wells in real time, flags issues, recommends actions, and even simulates outcomes — all in a clean, web-based interface designed for field teams and asset managers. What you'll learn in this episode: ✅ How ML + physics combine to produce accurate, engineer-trusted predictions ✅ What real-time nodal analysis looks like in the field ✅ How SOTAOG turns sensor data into actionable recommendations ✅ Why AI needs to be interpretable, auditable, and grounded in physics While we don’t go deep into the algorithmic weeds, this is a great real-world example of applied AI that delivers measurable value in upstream operations. 🎧 Note: You may notice some minor sound quality issues and some rough cuts. I’m still learning the ropes, and I appreciate your patience as I get better with each episode! Learn more about SOTAOG: https://www.sotaog.com/ Get in touch with Sarah:   / sarahchandrasekar   --- 🔧 Give the CrowdField LinkedIn page a follow. We regularly share tools, insights, and other O&G goodies you won't want to miss:   / crowdfield   🌐 Explore the CrowdField site for more tools and products built for subsurface professionals: https://www.crowdfield.net/ 🔔 Give us a hand by subscribing to the channel... you’ll get notified when new episodes drop. Are you working on a cool AI workflow? Anything you want to showcase? 👉 Reach out to me:   / alan-mourgues