How Digital Twins Can Make Decarbonization a Reality in the Oil and Gas Industry
For today’s oil and gas companies, digital twins offer untapped potential to decarbonize the leading source of their emissions—field production.
Companies across industries and geographies have been tasked to decarbonize for decades. In recent years, however, net-zero commitments have spiked; according to the United Nations, decarbonization goals across the public and private sectors doubled in less than a year in 2020. And, while promising progress has been made, just one-third of all companies with net-zero targets met the UN’s Race to Net Zero “starting line” criteria in 2022. This means some organizations have not formally announced their 2050 promise, shared their long-term and short-term actions within a year of joining the campaign, acted accordingly to reach their interim net-zero targets, or formally published annual decarbonization reports detailing their short-term and long-term target progress.
For most enterprises across sectors, decarbonization methods go hand in hand with digital transformation tactics. Solutions such as advanced analytics, artificial intelligence, internet of things (IoT) sensors, and more can help organizations enhance their operational efficiency, leading to less waste, electricity consumption, fuel needed for transportation, and beyond. This collectively diminishes carbon footprints—not to mention improves cost reductions and profit margins.
In the energy industry, digital twins are particularly standing out for their ability to help reduce overall emissions and drive efficiencies. Specifically, digital twins of oil and gas fields have shown significant promise.
But where exactly do digital twins come into play in oil and gas field production, and how can they inherently help reduce carbon emissions? As virtual replicas of the physical oil and gas fields, digital twins can provide asset teams with invaluable details on real-time operations and optimize production such that companies can compile information and establish operational tactics to pinpoint areas of excessive emissions and curb them.
These digital twins must be developed with an integrated architecture and enabled with vast amounts of data tapping into an array of physical and digital assets. These highly specialized field-level twins provide field production teams with an accurate, holistic view of their field’s subsurface, wells, and surface infrastructure as well as the various interconnected intelligent solutions and equipment. They can simulate real-time scenarios such as fracturing to determine the well viability, identify associated costs, scheduling, increase production, ensure workplace safety, and analyze potential carbon emissions. Digital twins can also virtually test, monitor, and control equipment of artificial lift or injection operations.