Digital Innovations in Oil and Gas with Geoffrey Cann

In energy and manufacturing, vast volumes of unstructured data (think OEM manuals, maintenance logs, shift notes, correspondence, procedures), sit largely untapped. For decades, experienced technicians have compensated by carrying critical knowledge in their heads. But with retirements accelerating and fewer seasoned workers on the front line, this model is breaking down.  New large language learning models that underpin technologies such as Grok and ChatGPT are being trained on this unstructured content to create context-relevant, queryable databases for industry. This technology, referred to as retrieval-augmented generation (RAG), could help unlock hidden knowledge across sprawling document sets. Early attempts at RAG have certainly improved search, a task that consumes hours of scarce engineering time. However, companies quickly learned that speed and accuracy fall apart at scale, context matters, and lack of trust in the output leaves users frustrated and skeptical.  The real opportunity lies in pairing RAG with agent-based AI systems designed for complex, asset-intensive environments. By reducing mean time to repair (MTTR), cutting rework, and extending the interval between failures, these solutions directly recover lost production capacity, which is an eight or nine-figure problem in many enterprises. For younger, less experienced workforces, AI tools are a critical equalizer, levelling the field against looming labor shortages. In this episode, I speak with Mark Fosdike, CEO and co-founder of Datch, about how his company is pioneering AI-driven diagnostic agents for manufacturing and industrial clients. We explore the realities of implementing RAG in high-stakes industries, the economic drivers behind adoption, and why obsessing about customers’ problems is the key to success. 👤 About the Guest Mark Fosdike is the CEO and co-founder of Datch, an AI company building agent-based diagnostic solutions for asset-intensive industries. With a background in aerospace engineering, shipbuilding, and manufacturing systems, Mark has spent his career navigating the complexities of the industrial value chain. His vision for Datch was born from frustration with traditional maintenance practices and a desire to put AI to work solving real-world challenges on the plant floor. LinkedIn Profile Company Website ⚒️ Additional Tools & Resources 🎙️ Go backstage and check out my studio: geoffreycann.com/mystudio 📘 Take my one-day digital strategy training course for oil and gas: Digital Strategy Training 🔗 Connect with Me 📚 Blog series: digitaloilgas.substack.com 🎧 Podcast: geoffreycann.com/broadcast 💼 LinkedIn: Geoffrey Cann 🐦 X: @geoffreycann 🎤 Contact for Lectures and Keynotes I speak regularly on these and other topics. Contact me to book a brief call about your upcoming event needs. Get in touch here. ⚠️ Disclaimer The views expressed in this podcast are my own and do not constitute professional advice.

Why is a pug named Phoebe likely more qualified than your frontline crew?  In the oil and gas industry, online training and certification have become the norm. Let's agree it's convenient, cost-effective, and scalable. But what if the people taking that training are subverting the training using AI, or aren’t people at all? Digital tools, especially generative AI, are now being misused to automate training completion, which undermines the entire compliance system. The same platforms designed to protect workers, assure reliability, comply with regulations, and safeguard the environment may be certifying untrained staff, putting lives at risk and exposing companies to severe legal and financial consequences. In this episode, Rob Day joins me on the podcast to discuss this hidden crisis. Rob is Managing Director at Cognisense, and a dedicated expert in risk mitigation. From court cases involving industrial explosions to training a pug to complete OSHA 10, Rob shares shocking and true stories from the frontlines of digital risk. He also outlines what companies can do right now to reclaim control over their training systems, ensure legal compliance, and reduce exposure. All managers and supervisors on the front line of industrial work need to be aware of the risks they face.  #RiskWashing #OHS #SafetyTraining #TrainingthatMatters #AI #WorkplaceSafety #RiskManagement #OilAndGas  👤 About the Guest Rob Day is Managing Director of Cognisense, a firm focused on risk mitigation and training validation for industrial operations. His background spans military firefighting, hazardous materials response, legal consulting, and refinery operations. Rob has advised on major incident investigations and regulatory risk across the energy sector. He’s now leading efforts to counter AI-enabled “risk washing” and bring integrity back to digital training systems. 🔗 Connect with Rob on LinkedIn 🌐 Connect with Cognisense 🧰 Additional Tools & Resources 📄 All about risk-washing by Rob Day 🎥 Go backstage and check out my studio: https://geoffreycann.com/mystudio/ 📘 Take my one-day digital strategy course for oil and gas: https://www.udemy.com/course/digital-oil-and-gas/?referralCode=0161D4D49AB75735A185 🔗 Connect with Me ✍ Blog: https://digitaloilgas.substack.com/ 🎙 Podcast: https://geoffreycann.com/broadcast/ 💼 LinkedIn: https://www.linkedin.com/in/advocate-digital-innovation-for-energy/ 🐦 X (Twitter): https://x.com/geoffreycann 🎤 Contact for Lectures and Keynotes I speak regularly on these and other topics. Contact me to book a brief call about your upcoming event needs. ⚠️ Disclaimer The views expressed in this podcast are my own and do not constitute professional advice.

The oil and gas industry has invested heavily in new digital technologies, but too many efforts fall short in value delivery. However compelling digital initiatives may seem, they will assuredly flounder if workers are unable or unwilling to adopt them.  The challenge lies in the way asset centric organizations tend to approach change. Leaders often seek rapid results that will contribute to current earnings, while frontline teams struggle with clunky processes and data silos ill-suited for AI, analytics, robotics, connected workers, and many other innovations. Rolling out new tools at scale without winning hearts and minds often leads to resistance, “pilot project hell,” and failed implementations.  So how can energy companies unlock real value from digital transformation? What are the overlooked success factors that determine whether AI and digital deployments thrive or falter? In this episode, I’m joined by David Moore, a digital advisor and AI delivery lead, who reflects on the five critical lessons he wishes he had known earlier in his career. From the power of storytelling, to focusing on people before technology, to the need to start small and scale, to leveraging vendors as partners, and finally the hard truth that data is the real currency, David shares practical insights drawn from frontline experience. ⸻ 👤 About the Guest   David Moore is a well engineer by background with a PhD in mechanical engineering and now a digital advisor and AI leader. Over the past nine years, he has worked on digital transformation across upstream oil and gas, leading projects from Microsoft Teams deployments to AI-driven planning and real-time operations. David brings a unique perspective from seeing the industry’s challenges from both the operator and service company side, with deep experience in building adoption, scaling pilots and designing data foundations all on a global scale.    🌐 Website: www.davidjmoore.com 🛠️ Additional Tools & Resources 🎙️ Go backstage and check out my studio: https://geoffreycann.com/mystudio/ 📘 Take my one-day digital strategy training course for oil and gas: https://www.udemy.com/course/digital-oil-and-gas/?referralCode=0161D4D49AB75735A185 🔗 Connect with Me 📚 Blog series: https://digitaloilgas.substack.com/ 🎧 Podcast: https://geoffreycann.com/broadcast/ 💼 LinkedIn: https://www.linkedin.com/in/advocate-digital-innovation-for-energy/ 🐦 X: https://x.com/geoffreycann 🎤 Contact for Lectures and Keynotes I speak regularly on these and other topics. Contact me to book a brief call about your upcoming event needs: 👉 https://geoffreycann.com/contact/ ⚠️ Disclaimer The views expressed in this podcast are my own and do not constitute professional advice.

The energy industry is having a moment. As assets become digitized, operations increasingly automated, molecules displaced for electrons, and capital more discerning, the biggest challenge is now people, instead of engineering. Specifically, where will the next generation of digitally fluent energy professionals come from?   At the same time, academic institutions, whose mission is to deliver qualified talent, are under grave financial pressure. International student revenue is collapsing, and many programs are out of step with the real-world digital needs of industry. Meanwhile, the workforce is retiring, and young professionals are turning away from careers in oil and gas.   In this episode, Doug Cronk, an investment committee advisor, and former Academic Chair of Financial Services and Fintech at SAIT, sets out how the energy sector can seize this moment. By repackaging existing academic offerings, combining them with data analytics, AI, and energy domain knowledge, and co-creating programs that reflect the needs of a digital energy economy, the energy sector can secure its future talent needs.   Doug argues that industry must lead, by articulating exactly what skills are needed, and why energy companies should present themselves as data-driven innovation platforms, not just extractive enterprises. This episode offers a clear-eyed assessment of the education-industry disconnect, the talent crisis looming over the sector, and the strategic opportunity to build the next generation of digital energy leaders.      👤 About the Guest   Doug Cronk is an experienced board member, investment committee advisor, and former Academic Chair of Financial Services and Fintech at SAIT. His career spans banking, pension fund management, and education, with a specialty in helping institutions adapt to technological and demographic disruption. Today, he sits on multiple boards where he evaluates long-term investment strategies and talent risk in capital-intensive sectors, including energy.   🔗 Doug Cronk on LinkedIn 🛠️ Additional Tools & Resources 🎙️ Go backstage and check out my studio: https://geoffreycann.com/mystudio/ 📘 Take my one-day digital strategy training course for oil and gas: https://www.udemy.com/course/digital-oil-and-gas/?referralCode=0161D4D49AB75735A185 🔗 Connect with Me 📚 Blog series: https://digitaloilgas.substack.com/ 🎧 Podcast: https://geoffreycann.com/broadcast/ 💼 LinkedIn: https://www.linkedin.com/in/advocate-digital-innovation-for-energy/ 🐦 X: https://x.com/geoffreycann 🎤 Contact for Lectures and Keynotes I speak regularly on these and other topics. Contact me to book a brief call about your upcoming event needs: 👉 https://geoffreycann.com/contact/ ⚠️ Disclaimer The views expressed in this podcast are my own and do not constitute professional advice.

Heavy industry runs on complex systems and distributed assets, but frontline workers are often still armed with paper manuals and radios. It works, but yields an unacceptably high level of inconsistencies, safety incidents, and productivity bottlenecks. And as experienced workers retire, critical knowledge about systems, assets, and good practice disappears. The shift to digital work execution is now both viable and urgent. Smartphones are everywhere. AI is mainstream. And yet many organizations still struggle to digitize even basic workflows. In this episode, Liam Scanlan, co-founder and managing director of HINDSITE, reveals how his technology is addressing this challenge head-on. HINDSITE equips frontline workers with just-in-time digital instructions, visual training, and live process documentation. Companies that leverage this technology report fewer errors, faster onboarding, improved safety, and lower costs. Whether it’s inline inspections, sensor maintenance, or tire bay procedures, HINDSITE brings consistency and governance to the last mile of industrial work. 👤 About the Guest: Liam Scanlan is the co-founder and managing director of HINDSITE, a field operations platform built to support complex, safety-critical tasks in heavy industry. Liam has worked in digital transformation projects around the world with BHP. He has worked across the Energy sector in work management solutions for over a decade and set out to solve the particular challenges of Industry around Work Management and Service Delivery. He has degrees in Mining Engineering, Law, Finance and Economics. ✉️ liam@hindsiteind.com 🌐 www.hindsiteind.com ⚒️ Additional Tools & Resources: 🎥 Go backstage at my studio 📘 Digital Strategy Training 🔗 Connect with Me: Resources Blog Podcast LinkedIn X (Twitter) ☎️ Contact for Lectures and Keynotes: Book a Call ⚠️ Disclaimer: The views expressed in this podcast are my own and do not constitute professional advice.

The traditional model of hydrocarbon exploration has transitioned in much of North America, replaced by exploitation of known shale and tight resources. For shale players, exploration is seen as more risky, expensive, and slow than pursuing resource play.  Classic geochemical methods, reliant on sample collection and lab analysis, can’t keep up with the need for real-time decision-making. Helium—a light, inert, and upwardly mobile gas—offers potential as an indicator of subsurface resources, but its volatile nature makes it difficult to measure accurately and reliably using conventional approaches. Helium, when measured digitally and interpreted with AI, can provide a new high quality and reliable signal for the presence of valuable subsurface resources, reducing costs, time, and risk. In this episode, Denis Krysanov, founder of Heologic, explains how helium-based digital exploration can help identify oil, gas, lithium, geothermal energy, and even natural hydrogen deposits. By capturing helium anomalies in real-time, and layering them with AI and geoscience data, Heologic creates a digital twin of subsurface conditions. With field-proven success from Argentina to Malaysia, this technique has already delivered remarkable predictive power, improving hit rates and opening new plays.  👤 About the Guest Denis Krysanov is the founder and CEO of Heologic, a geoscience innovation company pioneering helium-based exploration. With over two decades of experience at the intersection of automation, robotics, and energy systems, Denis combines technical depth with entrepreneurial leadership. His career began in offshore oil and gas technology in Finland, and has since expanded globally with breakthrough applications in digital geochemistry, particularly in helium sensing and AI integration. Heologic now operates across multiple continents and energy sectors, working with companies such as Petronas and YPF. 🧰 Additional Tools & Resources 🛠 Visit My Studio 🎓 One-Day Digital Strategy Course for Oil and Gas   🔗 Connect with Me 📚 Resources 📰 Substack Newsletter 🎧 Podcast Archive 💼 LinkedIn 🐦 X / Twitter 🎤 Contact for Lectures and Keynotes I speak regularly on these and related topics. Contact me to book a call about your next event. ⚠️ Disclaimer The views expressed in this podcast are my own and do not constitute professional advice.

In the world of oil and gas operations, edge devices are  mission-critical. These compact, intelligent sensors operate in  the most extreme of environments, such as remote drill sites, deep wells, and hostile landscapes, where they continuously collect operational data. Best in class operators don't just throw digital at the field. They prioritize efficiency, reliability, and integrity at the edge, where human oversight is limited, infrequent, and mostly absent. But the drive to digitize oilfield infrastructure raises major challenges: reliable power, cyber threats, temperature extremes, and real-time decision-making without cloud access. David Smith, VP of Innovation at Black Pearl Technology, shares how his team builds micro-powered, field-tough sensors that handle pre-processing on-site, sip power in microamps, and run mission-critical code on the edge to avoid failures. MEMS (Micro-Electro-Mechanical Systems) is enabling a new era of industrial sensing, complete with cyber-safe hardware that controls every component. Innovation must always serve a real-world problem—not just be a shiny gadget. From strain gauges to AI-at-the-edge, David offers an inside look into the future of smarter, safer, and smaller industrial tech. 👤 About the Guest: David Smith is Vice President of Innovation and co-founder at Black Pearl Technology, where he leads the development of ruggedized, ultra-efficient sensing devices for industrial and energy sectors. With a background spanning biomedical, aerospace, and energy tech, David brings decades of experience in building purpose-driven edge innovations that survive the toughest conditions on earth. 💼 Linkedin: https://www.linkedin.com/in/techpirate/ 🔗 Black Pearl Technology Website 🛠️ Additional Tools & Resources: 🎛️ Go backstage and check out my studio: https://geoffreycann.com/mystudio 🧠 Take my one day digital strategy training course for oil and gas: https://www.udemy.com/course/digital-oil-and-gas 🤝 Connect with Me: 🧾 Resources: https://geoffreycann.com/resources 📚 Blog: https://digitaloilgas.substack.com 🎧 Podcast: https://geoffreycann.com/broadcast 💼 LinkedIn: https://www.linkedin.com/in/advocate-digital-innovation-for-energy 🐦 X: https://x.com/geoffreycann 🎤 Contact for Lectures and Keynotes: I speak regularly on these and other topics. Contact me to book a call for your upcoming event: 👉 https://geoffreycann.com/contact ⚠️ Disclaimer: The views expressed in this podcast are my own and do not constitute professional advice.

The global upstream oil and gas sector is confronting a mounting crisis—access to capital. For over a decade, international producers, especially small- and mid-cap firms, have faced shrinking pools of funding as banks exit the space and public equity markets falter. Traditional sources of capital have dwindled, leaving many promising ventures stranded without the financial fuel they need to grow. As capital constraints tighten, the sector’s self-depleting business model—where every produced barrel reduces tomorrow’s inventory—becomes unsustainable. The result? A looming risk of supply shortfalls, price shocks, and widening energy inequity, especially in underdeveloped economies. With traditional financing off the table, how can energy producers bridge this capital chasm? In this episode, I sit down with Richard Naden, a seasoned executive and co-founder of Atlas Energy, to explore a breakthrough model inspired by royalty and streaming structures from mining and North American energy. Richard shares how Atlas provides not only innovative capital but also operational and technical expertise to its partners, creating an aligned and scalable funding approach. With a lean asset-light model, heavy on analytics and trust in data, Atlas aims to build a multi-billion dollar portfolio that could reshape how energy projects are financed around the world.  👤 About the Guest Richard Naden is a senior executive with Atlas Energy Corp., bringing nearly four decades of experience in engineering, operations, acquisitions, and executive leadership roles in the global energy industry. Raised on the gas fields of Alberta and trained as a mechanical engineer, Richard’s international career has spanned the Americas, Europe, North Africa, the Middle East, and Asia. His latest venture, Atlas Energy, combines his depth of industry knowledge with a passion for innovation and sustainable energy finance. atlas-corp.ca rwnaden@gmail.com 🧰 Additional Tools & Resources 🔗 Visit My Studio 📘 Digital Strategy Course for Oil and Gas 🔗 Connect with Me Resources Digital Oil and Gas Blog Podcast Archive LinkedIn X / Twitter 🎤 Contact for Lectures and Keynotes I speak regularly on these topics. Book a call to discuss your event. ⚠️ Disclaimer The views expressed in this podcast are my own and do not constitute professional advice.

In the upstream oil and gas sector, frontline operations have long depended on manual methods for information management, such as clipboards, spreadsheets, and disconnected tools. These outdated processes persist despite mounting pressure to improve efficiency and cut costs. But with today’s margin compression, regulatory scrutiny, and demographic changes, that operational model is no longer sustainable. Field operators are expected to do more with less, but lack integrated, user-friendly tools that align with their daily work activities. In this episode, I chat with Philip Richard, CEO of Porosity, about how his company is tackling these very challenges. Leveraging his personal background in production engineering and startup leadership, Philip explains how Porosity is building software designed for the field, not just the back office. Key moves such as streamlining leak detection, maintenance, and safety workflows through a single, mobile-first platform really help the field directly address its challenges.  This episode is all about how oilfield digitization actually happens. 👤About the Guest: Philip Richard is the CEO of Porosity, a software company focused on improving field operations in oil and gas. With a background in petroleum engineering and leadership roles in methane detection and SaaS startups, Philip brings a rare blend of field experience and entrepreneurial drive. Connect with Philip on LinkedIn. Additional Tools & Resources: 🎙 Podcast: https://geoffreycann.com/broadcast/ 📚 Blog Series: https://digitaloilgas.substack.com/ 🎓 Digital Strategy Course: Udemy – Digital Oil and Gas 📷 Backstage Tour: https://geoffreycann.com/mystudio/ Connect with Me: 🔗 LinkedIn ✖ X (Twitter) 💬 Contact Contact for Lectures and Keynotes: “I speak regularly on these and other topics. Contact me to book a brief call about your upcoming event needs.” 👉 Click here to schedule Disclaimer: The views expressed in this podcast are my own and do not constitute professional advice.

Mid-sized oil and gas companies are now at a digital crossroads. While supermajors have pushed forward with large-scale transformation programs, many mid-market firms are only beginning to explore how digital innovation can improve performance. Their operational processes—budgeting, forecasting, asset planning—tend to mirror those of larger firms but constrained by fewer resources and less internal capability. Unfortunately, mid-sized companies cannot simply copy the big-company playbook. They lack dedicated data teams, struggle with legacy systems, and must handle all the integration hassles with bespoke coding. At the same time, they are under the same pressure to lower costs, improve transparency, and make faster, better decisions. Is a pragmatic and impactful digital transformation even possible in this context? Absolutely. In this episode, I speak with Lewis Gillhespy, Executive Advisor at Rockflow, on practical solutions that work with mid-sized firms. By focusing on core business processes—particularly budgeting and production forecasting—smaller firms can drive efficiency through better data quality, increased transparency, and dashboard-driven decision-making. A bonus outcome is that improved data transparency leads to a self-reinforcing data stewardship culture, and why starting with business needs (not technology hype) is the key to lasting change. 👤 About the Guest Lewis Gillhespy is an Executive Advisor at Rockflow, a UK-based consultancy focused on oil and gas strategy, technical excellence, and expert witness services. A former transformation leader at Suncor, Lewis now advises global mid-sized energy companies across Europe, the Middle East, and Asia. He brings deep operational experience and a keen understanding of how to turn digital ambition into practical execution. Connect with Lewis Gillhespy 🔗 Rockflow 🔗 LinkedIn - Lewis Gillhespy Additional Tools & Resources 🎙 Go backstage: My Podcast Studio 🎓 Take the course: Digital Strategy for Oil and Gas Connect with Me 🌐 Resources 📝 Substack 🔗 LinkedIn ✖️ X (Twitter) Contact for Lectures and Keynotes I speak regularly on these and other topics. Book a brief call about your event. Disclaimer The views expressed in this podcast are my own and do not constitute professional advice.