Read more on the impact of digitalization in the upcoming publication, “African Energy Road to Recovery: How the African Energy Industry Can Reshape Itself for a Post-COVID-19 Comeback,” developed in partnership between the African Energy Chamber (AEC) and Africa Oil & Power. Released in January 2021, the 200-page report maps out the productive recovery of the African energy sector, drawing upon the strength of the AEC’s thought leadership.
Big Data, automation, Internet of Things, Artificial Intelligence and other digital technologies can enable operators to extend the economic lifespan of maturing assets.
Legacy fields – or those that have been in operation for at least 25 years – account for 30% of African production. Digitalization is one of the most effective tools in an operator’s toolbox for managing this type of asset – which has already reached peak production – as it reduces operating costs, improves equipment reliability and augments efficiencies that have the ability to extend the economic life of the field.
In fact, optimizing production through the use of digital technologies is estimated to be able to generate up to $20 million in annualized cash flows on a 100-well project. Raw data, or ‘Big Data,’ plays a significant role in achieving cost-savings, which refers to the extensive amount of information acquired through 3D and 4D seismic surveys; drilling data; production data; environmental data; and monitoring data on pressures, flow rates, temperatures, humidity and more. In contrast with frontier acreage, mature fields
carry zero risk on whether large sums of data exist. Instead, mature field operators are focusing on developing the tools required for capturing high volumes of data – as well as those required to implement real-time decisions based on the data.
The Internet of Things (IoT) and electronic monitoring represents a key solution to both through implanting physical devices with sensors and extending Internet connectivity and communications among physical assets Within the oil and gas industry, IoT devices render real-time data on machinery, pipes, storage and transportation, among other infrastructure, which enables equipment lifespan and production controlling factors to be monitored remotely. An early adopter of this has been GE Digital, a subsidiary of General Electric Baker Hughes, which developed a digital platform known as ‘Predix’ to analyze vast quantities of data recorded by the sensors. As a result, GE and other companies utilizing Big Data analytics can implement predictive maintenance to service offshore installations, in turn enhancing productivity, reducing downtime and minimizing operating costs.
In addition to targeting efficiency and reduced cost management for fields in decline, digitalization can also help make improved drilling decisions for fields still being explored by tracking oil production in real time. This allows companies to adopt instantaneous drilling decisions by drawing comparisons between real-time downhole drilling data and production data from nearby wells. According to a study conducted by Bain & Company, such data collection and analysis can boost production by up to six to eight percent. A number of advances in seismic surveying have also enabled companies to expand existing discovery potential; subsurface imaging field-scale typically finds the size of the field to grow as additional 3D is collected.
Meanwhile, imaging at pore-scale in rocks can result in an enhanced understanding of pore structure, distribution and rock fabric at a micro-scale, enabling improved reservoir characterization, which is necessary for Enhanced Oil Recovery techniques. BP’s Wolfspar seismic source technology is a working example of this: the technology utilizes low frequency waves to study deeper, below salt layers, thereby identifying underlying, untapped reserves. Utilizing Wolfspar, BP discovered an additional one billion barrels of oil at its Thunder Horse field in the Gulf of Mexico, as well as 400 million additional barrels at the nearby Atlantis field.
Emerging technologies in automation, Artificial Intelligence, IoT and Big Data analytics serve to demonstrate how digitalization can be adopted and integrated to foster efficiencies and cut costs for the management of mature or low-volume fields. In fact, digital technologies are some of the only tools that can be used to effectively forecast the future in an effort to make better decisions in the present, while simultaneously leveraging incremental costs and efficiencies that remain to be discovered.