As a simulation exercise, SAS has created a fictitious oil portfolio, VirtualOil, which readers can use as a generic benchmark against their physical oil commodity book’s performance. Each month, we reflect on what the visual analytics can tell us about the portfolio’s movement, with additional commentary and granular chart views
Volatility. It’s a business reality for energy market participants and it’s been a wild ride for the oil marketing business over the past few weeks. How has your energy risk data helped you navigate the recent increase in volatility and precipitous price drop? This month, we are launching a recurring
You may have heard the phase that big data is the new oil. Well (pun intended), if that is the case, then analytics should be thought of as the fracking technique used on data to improve the value you get from this new oil. Fracking is actually just one
I’ve been told I have rocks for brains before, but right now I have rocks on the brain – the kind that are millions of years old and contain precious stores of oil and gas. One reason I have petroleum on my mind is that I’ve just returned from Brazil, where
In the energy industry, oil and gas companies as well as utilities are struggling with many changes at once. First, they're facing what the oil and gas industry has coined "the big crew change," meaning the retirement of those with the most skills and experience on how to run their
Oil companies are being forced to explore in geologically complex and remote areas to exploit more unconventional hydrocarbon deposits. New engineering technology has pushed the envelope of previous upstream experience. No guidebook existed on how computing methodologies can contribute to E&P performance at reduced risk. Until now. A new book
At SAS Global Forum 2014 customers were asked to describe SAS in one word and they came up with quite a few including awesome, powerful, data, fun, easy, and of course statistics, analytics, and PROC. Then I gave it some thought on what one word would I choose to describe SAS. This
What's the differences between predictive analytics and basic reporting? Predictive analytics provides insight about what will happen in the future. Basic reporting only looks at past performance. Why is this difference difficult to grasp? It's partly because transitioning to predictive analytics requires change. And most people don't embrace change. Take
Acronyms are funny things. Need an example? Try decoding this sentence: How is event stream processing (ESP), applied to electrical submersible pumps (ESP) in the oil and gas industry, like extrasensory perception (ESP)? Even if you had extrasensory perception you would still need some clarification if that sentence contained acronyms only.
As more and more data is being collected and analyzed, it becomes even more important to have a strategy in place that will allow you to get value out of your data. Since it's humanly impossible for your brain alone to process fast streaming data, an event stream processing (ESP) engine
