Hydrocarbon and offshore exploration are expanding beyond Texan oil fields and choppy Gulf waters. Funding is now being focused on leveraging text analytics to optimize processes like well discovery, re-bidding, and tapping into geopolitical contexts. Increasingly, the oil and gas industry is turning their drills to big data and mining actionable insights from a trove of unstructured text.
Utilizing a tool like Lexalytics’ Concept Matrix™ gives oil and gas companies the ability to nimbly respond to complex petroleum news announcements, keeping them at the front of the space.
Another important and well-studied area of text analytics is classification: sorting documents by topic. Those in the petroleum industry could utilize classification for patent analysis, among other tasks. One study of classification combines statistical methods with linguistics. It demonstrates the combination yields results superior to using statistics alone (Vanderwilt, 2016).
Another widely researched application of text analytics is sentiment analysis and reputation analysis. This is particularly germane to the recent controversies surrounding offshore exploration. Baking sentiment analysis into the reputation management strategy of a company like BP works on many levels. It ensures all criticism is accounted for, at a PR level. But it also helps the company gauge the results of a response effort (like the Gulf clean up) by extracting granular insights from thousands of residents across social platforms.