Book description
The oil and gas industry was one of the first aggregators of what we now call “big data,” but the amount of information these companies currently collect is truly unprecedented. In 1990, one square kilometer yielded 300 megabytes of seismic data; in 2015, it was 10 petabytes—33 million times more. This report features highlights from recent Strata+Hadoop World conferences to demonstrate how the petroleum industry uses data science in their operations today.
Oil companies use machine learning to mitigate short-term operational risk and to optimize long-term reservoir management. But, as author Naveen Viswanath explains, machine learning models alone can’t distinguish between good and bad data or reasonable and unreasonable results. Human intelligence—including a deep understanding of how data sources fit into business use cases—is crucial for making these distinctions.
With this report, you’ll learn the challenges these companies face when collecting a variety of data for seismic research, drilling, mechanical maintenance, worldwide logistics, and even gas station retail.
Publisher resources
Product information
- Title: Reducing Risk in the Petroleum Industry
- Author(s):
- Release date: August 2016
- Publisher(s): O'Reilly Media, Inc.
- ISBN: 9781491964705
You might also like
book
Dynamic Risk Analysis in the Chemical and Petroleum Industry
Dynamic Risk Analysis in the Chemical and Petroleum Industry focuses on bridging the gap between research …
book
Investing in Energy: A Primer on the Economics of the Energy Industry
An energy industry researcher and investment advisor provides a fresh perspective on the economics of energy …
book
Preparing for the Next Financial Crisis
The ramifications of the Global Financial Crisis, which erupted in 2007, continue to surprise not only …
book
A Profile of the Oil and Gas Industry, Second Edition
We know that the people of Mesopotamia were using crude oil as a tar for building …