The need to understand the future trends of the oil industry has never been greater than it is today. Throughout the history of the oil industry, technology and innovation have made a significant contribution by pushing the boundaries to enable a continuous expansion in production, increasing reserves, and capital efficiency. In the years to come, with the world’s conventional reserves declining, energy companies will inevitably have to move into more challenging and remote locations to explore and produce hydrocarbons. Therefore, the role of innovation and, more specifically, data-science-derived technologies will likely become the key to shaping the future of the oil and gas sector.
In fact, there are ample opportunities for oil and gas companies to use Big Data to get more oil and gas out of hydrocarbon reservoirs, reduce capital and operational expenses, increase the speed and accuracy of investment decisions, and improve health and safety while mitigating environmental risks. It is worth mentioning that although the so-called “disruption mandate” faced in every industry, including oil and gas, is not new, its current speed and complexity will foster an adaptive mindset while maintaining its business practices—the key not only for success but also for survival in the age of the digital transformation.
Technological advances, such as increased use of Web-based platforms and cutting-edge data-acquisition technologies such as sensors, have made it possible to generate a staggering amount of data in the industry—the aforementioned Big Data—often which is not used efficiently or effectively. One of the key enablers of the data-science-driven technologies for the industry is its ability to convert Big Data into “smart” data. New technologies such as deep learning, cognitive computing, and augmented and virtual reality in general provide a set of tools and techniques to integrate various types of data, quantify uncertainties, identify hidden patterns, and extract useful information. This information is used to predict future trends, foresee behaviors, and answer questions which are often difficult or even impossible to answer through conventional models.
Automation, which is derived from Big Data analytics, is a huge step in the direction of improving data science in the immediate future. This evolution holds added benefits such as improving operational efficiency, reducing operational costs, increasing speed, and enhancing self-service modules. The need to automate business processes with the goal of improving functionality and increasing efficiency will be the main driver for the increased adoption of data sciences in the industry. A significant potential for automation exists because it can serve as an ideal aid to daily operations. Many areas where automation can make an immediate and lasting difference for the oil and gas sector include identifying new well targets, improving drilling efficiency, optimizing artificial-lift systems, and monitoring onshore and offshore pipelines and other relevant facilities.
Modernizing internal processes with automation, along with better access to information about operations and maintenance, will help the industry boost production while increasing capital efficiency. It is expected that soon there will be more automated equipment at all stages of the oil and gas value chain. This transformation will lead to many current jobs becoming obsolete. However, this will also create many new roles that organizations will need to fill. Therefore, for young professionals in the industry, it is prudent to add a data-science skill set; this will enable them to make better and faster decisions, broaden their career choices, and ultimately improve their respective company’s operational efficiency.
Simultaneously, the most recent Global Energy Talent Index report confirms that the graduate-recruitment cuts during the industry downturn led to a skilled labor shortage for the sector, which is expected to worsen over the next few years. Hence, without skilled workers in the required positions, it has now become essential for the energy industry to reconsider its operations and include the use of data analytics and automation tools. These technologies can increase productivity and efficiency dramatically while coping with the skilled labor shortage and maintaining an acceptable profitability.
For Further Reading
SPE 190812 “Status of Data-Driven Methods and Their Application in the Oil and Gas Industry,” by Karthik Balaji, University of North Dakota, et al.
SPE 192460 “Rapid and Comprehensive Artificial-Lift-Systems Performance Analysis Through Data Analytics, Diagnostics, and Solution Evaluation,” by Lichi Deng, Quantum Reservoir Impact, et al.
| Vural Sander Suicmez is regional manager for the Middle East at Quantum Reservoir Impact (QRI), a Houston-based technology and advisory company. Before joining QRI, he worked at Maersk Oil & Gas in Copenhagen, Denmark; Brunei Shell Petroleum in Seria, Brunei Darussalam; Shell International E&P in The Hague, The Netherlands; and Saudi Aramco in Dhahran, Saudi Arabia. He has been an industry guest lecturer and advisor at Imperial College London and the editor-in-chief of the Journal of Petroleum Science and Engineering. He holds PhD, MSc, and BSc degrees, all in petroleum engineering, from Imperial College London, Stanford University, and Middle East Technical University, respectively, and an MBA degree from the University of Cambridge. |