Analytics Firms Explore Oil and Gas Market

Abstract

The oil and gas industry is facing an invasion of data analytics startups who saw a wide-open gap in the market a few years ago when talk of big data first began. Many of these young companies vying for attention from producers are focused on alleviating the headaches associated with artificial lift systems. There are also a number of software products designed to handle difficult computations such as production forecasting and reserve estimation. Some are selling analytics as a way to combat the growing threat of cyber attacks. Other programs interpret human semantics to extract valuable information out of the entirety of a company’s document library. Below is a closer look at what several of these analytics startups are offering to the industry—only there will be no deep dive into the layer cake of terminology that dominates this emerging software arena, e.g., artificial intelligence, machine learning, edge computing, etc. Power of Integration A sign of the industry’s accelerating uptake of analytics came in May when a number of the world’s largest producers made a USD-26 million investment in an industrial-focused analytics startup from Silicon Valley called Maana. The list of financiers includes the venture arms of Saudi Aramco, Chevron, Shell, and GE. This may be a leading indicator of things to come because rather than focusing on any particular niche solution, Maana is a big-picture analytics platform. Able to reach between different silos within an organization, the program analyzes seemingly disparate sets of operational data and ties them all together. Donald Thompson, cofounder and president of Maana, said such data integration is able to generate “new knowledge” that oil and gas producers can leverage to drive performance in the field. “Most projects involve going and tackling a single isolated problem, but everything in a business tends to be highly interrelated,” he explained. “So the failure of an individual pump is very interesting to understand, but its impact on production schedules is also interesting … if one pump fails, how should you adjust all the other pumps in order to still meet your production requirements?” Thompson, who pioneered knowledge- and semantic-based search engine tools during his 15 years at Microsoft, gave another example of an oil and gas project involving malfunctioning field sensors.