- by mik63, Prospector
- 10/26/2012 4:35:38 PM
I think there are at least 2 areas worth mentioning:
1) the amount of prospects and related data, both in exploration as well as in drilling and production is so much larger and broader than all the resources in the industry, that an automated analytics/AI model is probably the only way for the industry to handle the data tsunami and improve discovery, production, etc...; this cannot be solved with the traditional way of working. A combination of stocastic distribution, simulations, automatic detection, etc.., has to become the frontend before the few human experts are involved.
2) the ability to visualiza multiple data types is a great step and Petrel has been a shot of fresh air from this perspective. But as most of the data we are looking at is a remote reflection of reality, with a lot of uncertainty and aberrations, the need now is to enable users to do what if scenarios in real time. This requires a major shot of computation while people visualize. This new trend of combined interactive visualization and computation will enable the value extraction out of the concurrent visualization of different data types.
- by BethSchultz, Blogger
- 9/14/2012 8:54:24 AM
@Joe, so in other words, whether out in the oil field or stuck in a cubicle, employees share the burden of finding the time to do more with less and instilling new thinking at their companies!
- by Joe Gimenez, Blogger
- 9/13/2012 12:06:44 PM
Well, Ken is a journalist and not necessarily an industry expert. He's good at synthesizing what's going on at a higher level but can't see the trees below.
I also think that there is a lack of knowledge about analytics and their capabilities in the industry. Those working their day jobs focus on performing the core mission of extracting hydrocarbons from below surfaces. Theirs is a very difficult job already. Add on yet another level of 'thinking requirements' and it becomes a matter of "How many hours are in a day?" and "What's my job, exactly?"
The question then becomes when will job promotion be linked to the accomplishment of defined markers for increased use of analytics? Will there be an executive who takes the lead on introducing such a cultural change so that it becomes a core part of the everyday worker's job? To offer some cliches here: It's greenfield stuff and most people know that the pioneers are the ones who take the first arrows.
- by Broadway0474, Blogger
- 9/12/2012 10:09:28 PM
@Alexis, I agree with you. From what I know about how energy companies try to minimize fluctuations -- for instance, due to weather -- they apply highly sophisticated models to arrange derivatives and other hedging tools to transfer the risk of, say, low rain (if they're a hydroelectic dam) or unseasonably warm temperatures in the winter (if they're a gas utility). That's just one example.
- by BethSchultz, Blogger
- 9/12/2012 9:31:29 AM
Hi Joe, I guess I do find it surprising that the word "analytics" never appears as a critical piece of the business strategy, even if plenty of analysis takes place. Now is the time for companies in all industries to be thinking outside the box on how they might better take advantage of ever-more sophisticated analytic techniques and technologies and the ability to finesse the mining and analysis of ever-greater amounts of data. In this case, do you think that analytics was taken as a given, and therefore not mentioned. Or was this writer and his sources being short-sighted?
- by Alexis, Data Doctor
- 9/12/2012 9:02:09 AM
I don't think the problem is a lack of analytical thinking in the energy industry. I think it is a tendency to push the limits of the analysis to maximimze profit, and sometimes take shortcuts with safety and environmental issues.
- by Noreen Seebacher, Blogger
- 9/12/2012 8:53:05 AM
It seems to me that formal analytics programs are already deeply entrenched in the oil and gas industry, as evidenced by the widespread use of options like Petrell, a Schlumberger owned Windows PC software application intended to aggregate oil reservoir data from multiple sources. It allows the user to interpret seismic data, perform well correlation, build reservoir models suitable for simulation, submit and visualize simulation results, calculate volumes, produce maps and design development strategies to maximize reservoir exploitation.
And you can find throngs of data analysts among the ranks at virtually any energy company. At Hess, for instance, The Global Technical Data Management Group is united under a single Global Data Manager but functionally split in to primary two sub-groups, Enterprise Data Management (EDM) and Departmental Data Management (DDM).
· The EDM group are primarily responsible for the Master Data Solutions and technical data entering and leaving the company.
· The DDM group are primarily responsible for managing the technical data flows from the Master Databases to active asset team applications and/or projects and for the ongoing data managemen support throughout the entire project life-cycle. The Data Analysts will typically be co-resident with the Asset Teams.