Until a decade ago, the practice of data analytics and artificial intelligence in upstream was sporadic, and that was only possible through research organizations and individual effort. Nowadays, we see an increasing trend of image-classification applications for reducing subsurface studies from months to days and time-series analytics for recommending actions and preventing failures in real time.
Despite all efforts, the hydrocarbon industry continues to be perceived by many as the black sheep of all the energy supplies; its sustainability is jeopardized by environmental concerns and the net unit cost. In addition, operating companies are charged by shareholders to increase profitability continuously, leading to longer-than-usual working periods and less-safe working sites.
Digital transformation supported by data analytics and artificial intelligence can be the differentiator that allows the upstream industry to persist in the next 100 years, providing a unique foundation for innovation to enhance general public awareness and life quality.
Because automated machines yield more results per unit time and less unit cost, genuine concerns have arisen about artificial intelligence reducing the number of jobs or making some positions obsolete. Numerous cases exist in which automated oilfield operations have delivered safer workplaces with fewer human-intensive decision-making processes. These operations and processes run 24/7 with very high availability, reducing people-power requirements by 80% or more.
