In the oil industry you can make or lose money based on how good your forecasts are, so I’ve pulled together six papers that discuss different ways in which you can leverage analytics to optimize your output and more accurately predict your production performance. Written by employees at oil and
As traditional reserves deplete and oil prices rise, market analysts predict that the global demand for petroleum products will increasingly be met with oil extracted from non-traditional resources in more challenging and harsher environments. Therefore, companies across the oil & gas industry are evaluating technologies and processes that can deliver
In an increasingly complicated operating environment, the global oil and gas industry struggles to optimize their asset portfolio. Producers combat severe challenges inherent to aging facilities in the context of pricing volatility. Change is the new constant, as the cyclical nature of the oil and gas industry means that producers
The dramatic drop in crude oil prices from the highs above $100USD per barrel down to levels around $50 per barrel is one of the drivers behind the industry’s march towards improved operating efficiency. Along the corridors of Independent Oil Companies (IOCs) and National Oil Companies (NOCs), machine learning and
“Analytics” and “data scientist” aren’t new terms, but they are trending buzzwords. The popularity of these concepts has created a false impression: Analytics are mysterious abstractions that can only be decoded if you have a white lab coat and an advanced degree in computer science. The reality couldn’t be more different.
Under-utilized technology creates a drag on an organization. The ability to get more out of the tools you already use can increase the value of an existing investment, and that value grows as processes become more efficient and decisions are based on firmer foundations. Consider the facilities engineer at an
The Barnett Shale in North Texas hit a historic mark on April 25: Its rig count fell to zero. Two hundred rigs once harvested the 40 trillion cubic feet of natural gas in this massive basin, stretching beneath 17 Texas counties. Today, nothing. This dramatic silence in North America’s second-largest
Small causes can have large effects; or how a discovery in the Barnett Shale can spike some interest in the rest of the world and change the face of the industry. This article is co-written by Sylvie Jacquet-Faucillon, Senior Analytics Presales Consultant, SAS France; and David Dozoul, Senior Adviser
Year-end outlooks from most analysts project the low-price environment in the oil market will continue for most of next year, but some pundits emphasize that the market has bottomed out and suggest recovery, though gradual, may be seen if increasing demand outpaces supply growth and sops up some of the
Times have changed. As the oil industry shutters and sheds investments that made sense during the two-year period in which oil rode comfortably above $90, the market is establishing a new equilibrium at $40/barrel. This despite the fact that the Baker Hughes domestic rig count is down 64 percent. It’s
Though crude oil prices edged up last week, the market remains well below VirtualOil’s original $50 strike price, meaning the hypothetical portfolio’s production is shut in in the spot market again. Oversupply continues while China GDP forecasted growth is slowing. Given the market outlook, the VirtualOil board has decided to
Over my career, I've attended many events where the audience was blasted with the value of analytics -- and the pitch usually fell on deaf ears. The 2015 SAS Energy Analytics Forum (which doubled in size from last year) was vastly different. The attendees had more questions and more urgency to take
Since our last VirtualOil update in May, oil prices have continued to take a beating. As the chart of the rolling five-year portfolio shows, much of our strip of options is now out-of-the-money and the average value per barrel of that optionality has sunk below $7. No surprise then that
I enjoy watching TV crime series like Law and Order, Crime Series Investigation (CSI), CriminalMinds, Numb3rs, Person of Interest, as well as real-life mystery stories on shows like 20/20 and others. Obviously, the popularity of these types of shows means I'm not the only one who enjoys this type of entertainment. Here at SAS,
I'm not just talking about all the energy put in planning, scheduling, and supporting this great event, which is in Dallas, TX next week, April 26-29. I'm talking about all the presentations about using analytics in energy related industries, particularly in Utilities and in Oil and Gas. There is a
In the Cold War techno-thriller WarGames, a marine monitoring a nuclear missile silo deep under the Nevada desert sees a red warning light blink on his console. “Just flick it with your finger,” his colleague tells him. He does, and the bulb goes out. Problem solved. But what will their
When do analytics really provide value? All the time, of course. However, one of the best times for analytics to prove their value is when you are asked to do more with less. Often, the reason we are asked to do more with less is because of an economic downturn
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
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
Drilling a well is costly, risky and fraught with hazards for both man and machine. So why does most well behavior surveillance rely solely on historical data? Why not include a data driven approach that can also predict what might happen next? One great example is wellbore breathing. Annular pressure
Yes, we have all heard about the 3 V's of big data by now. Or the 4 V's or possibly 5 V's, depending on who you ask. However, I would argue the value of data isn't necessarily tied to the "volume" part of big data (unless of course you are a
Our perceptions can impact others and influence decisions. As a result, I always like to understand each customer's perception of what SAS is and what we do. There is no right or wrong answer to this question, however the response provides me with a chance to listen to our customers.
Engineers who implement process control can use analytics to think outside the of box. Better yet, they can use analytics to help solve the issues and risks associated with being inside the box or outside the box in the first place. Read on to learn what box I'm referring to
The value of analytics to solve multiple business problems really makes analytics the ultimate reusable business investment, or as they say in the energy industry, it may be called a renewable resource. As I've commented before, organizations spend billions of dollars on storing data, and unless you happen to be a
