Decarbonization journeys are accelerating across all industries. An expansion of wind and solar projects, a growing EV sector, and emerging climate-related regulations are changing the energy industry's calculus. Looking several decades into the future, major oil and gas companies are issuing ambitious climate targets and even net-zero pledges.

Many oil and gas companies focus on reducing the carbon intensity of their internal operations. Curbing carbon dioxide and methane emissions across the entire value chain is a priority. To advance these imperatives, new digital-first approaches — including the Internet of Things (IoT), digital twins, artificial intelligence, and predictive/prescriptive analytics — will play a crucial role in measuring emissions, modeling future scenarios, and advancing carbon-reduction interventions. These emerging digital capabilities will be particularly impactful in the carbon-intensive upstream domain.    

Upstream Decarbonization: A Technology-driven Pathway

The 2015 Paris Agreement—the most wide-reaching effort to address climate change and global warming to date—aims to restrict the global temperature rise to 1.5°C above pre-industrial levels. According to the World Economic Forum’s Global Risk Report, achieving this will require reducing human-caused CO2 emissions by 50% by 2030 relative to 2010 and to net zero by 2050.

In the long term, energy companies must address all their carbon emissions, including the Scope 3 emissions created when consumers and enterprises use oil and gas products. But even before those new low-carbon business models come fully into focus, energy companies can significantly reduce their Scope 1 and 2 emissions. According to the International Energy Agency, Scope 1 and 2 emissions of oil and gas production, transport, and processing are responsible for 15% of all global greenhouse gas emissions. Upstream oil and gas companies can make significant progress toward a net-zero future by achieving near-term reductions in these Scope 1 and 2 emissions.

A suite of emerging technologies will give energy companies the tools to address Scope 1 and 2 emissions rapidly. Fortunately, oil and gas companies are incorporating many of these tools — AI/ML, digital twins, IoT, robots/drones, augmented reality, and integrated data platforms — to address operational challenges like equipment maintenance and reliability, remote operations, and asset integrity. These technologies will enable concrete sustainability advancements by facilitating real-time, data-driven decision-making.

Three Decarbonization Priorities for Upstream

Three sequential capabilities will help energy companies leverage these technology tools to reduce emissions and advance their sustainability goals: Asset monitoring and surveillance, analysis and diagnosis, and optimization (see figure below).  

Digital-Led Upstream Decarbonization for Oil and Gas

These digital interventions will contribute to decarbonization goals in several ways. Improved asset health will reduce process emissions, optimize energy usage, and contribute to efficient maintenance (fewer field visits and less material use). Remote/digital inspection will eliminate field inspection visits and enable single-visit completion of maintenance work. Process improvements will reduce idle time, energy usage, material wastage, and asset productivity through optimum utilization. These digital interventions can and should be coupled with more straightforward interventions like replacing diesel generators in field operations with on-site renewable energy sources.

Digitalization will advance monitoring and surveillance across the upstream value chain, providing the raw data that energy companies will need to reduce the impact of emissions on compromised assets. Drones and robots will play a more significant role in monitoring asset integrity, while AR/VR will provide connected workers with new means of monitoring dispersed assets in real-time. In many cases, IoT and AI/ML will advance fully automated condition monitoring, reducing the need for frequent human intervention, particularly in inaccessible and high-risk contexts. In all these use cases, emissions monitoring will continue to rise toward the top of the priority list.

With the correct raw data, energy companies must leverage their data pipelines to service advanced analysis and diagnosis. Digital processes will dramatically improve the speed and accuracy of root cause analysis and drive a more efficient, automated approach to alerts and escalations. Image and video analytics, process variance analysis, and scenario modeling will continuously surface emerging opportunities to reduce operational and fugitive emissions. These analyses, in turn, will inform new approaches to sustainable equipment design.  

Finally, upstream leaders and operators will need to leverage data to fundamentally advance process optimization and rank the priority of optimization use cases by considering both cost and sustainability impact. This optimization can begin with Improved/Enhanced Oil Recovery (IOR/EOR) implementation plans. Highly viscous reservoirs, deep water, faulted, or high pressure/high temperature may become unfavorable for development in the future in terms of emission intensity. AI/ML-based reservoir modeling can help identify reservoir complexity and appropriate IOR/EOR methods while also considering the climate impacts of recovery operations and the potential to integrate CCUS (carbon capture, usage, and storage) techniques. These same optimization priorities will also impact the rollout of new energy value streams, such as solar and wind.

According to our analysis, addressing flaring, venting, and leaks with new technology could provide the industry with nearly $32.5 billion of additional revenue globally. The climate impact would be even more staggering. According to the IEA, rapid action to deploy all available abatement technologies over the next decade would have “the same effect on the global temperature rise by mid-century as immediately eliminating the GHG emissions from all of the world’s cars, trucks, buses and two- and three-wheelers.” As they leverage new digital capabilities to monitor, analyze, and optimize their upstream processes, energy companies will be able to reduce unplanned methane flaring/venting through IoT and predictive analytics, enable more precise operational data and tighter adherence to tolerances by increasing the connectivity of remote assets, and reduce routine flaring by leveraging AI models to assess processing and storage capabilities in real-time.  

Efficiency + Decarbonization: The New Energy Paradigm

Decarbonization is coming, but the energy transition will take time. Given the timelines required to transition to renewables, hydrocarbon energy sources will continue to be a necessary driver of global economic growth in the coming decades.

Emerging digital technologies will serve a dual purpose for global oil and gas enterprises: making current processes more efficient and less energy-intensive while paving the way for enterprise-wide decarbonization. These technologies will be particularly impactful in the upstream space, as enhanced connectivity and data availability bridge the distance between far-flung field assets, enabling numerous real-time insights and automated responses that reduce emissions. For oil and gas companies, decarbonization will be a complex multi-decade operation; the most successful players will be the ones that manage the energy transition with a digital-led effort to reduce emissions at every step of the journey.

About the Authors

Dr. Lakshmikantha Rao Hosur

Senior Partner – Energy, Resources, and Decarbonization

Lakshmikantha (Kantha) has more than 20 years of consulting experience related to energy and the energy transition across Europe and North America, and has worked with clients and assets all over the globe. Drawing on a deep knowledge of the energy value chain, Kantha is a strategist with a proven track record for delivering technology solutions — from ideation to go-to-market — and achieving delivery targets through consulting and portfolio management. Kantha holds a master’s degree in Geotechnical Engineering and a PhD in Soil and Rock Mechanics. He has previously worked with Repsol and SLB (Schlumberger) and is based in Amsterdam.

Anurag Kumar Srivastava

Global Upstream Lead & Consulting Partner

Anurag has over 21 years of industry experience, and has collaborated with energy industry majors across the globe to solve problems across the E&P value chain. His extensive experience from field to office has translated into innovative solutions addressing the industry pain points as well as patents, publications, and white papers. He holds master’s in Business Administration and a degree in Instrumentation and Control Engineering, and is based out of Gurugram, India.