The key to unlocking innovation in the Upstream is standards. WHAT!? Does this sound backwards and non-intuitive? Don't we usually associate innovation with free-wheeling, no-boundaries kinds of approaches? How can people feel free to innovate if you tell them to "do it this way"? Well, it all depends on where you think the value comes from.

Technical computing in the Upstream oil and gas industry has evolved into extremely powerful, yet extremely complex systems. Varied and coagulated connectivity networks underlie a myriad of platforms, from UNIX to PC to mainframes to server farms, to thin clients and Blackberries, etc. At the other end of these systems, a multitude of user interfaces become the most visible aspect of these complexities to the user community. At the center of such complex technical computing system are the varieties of software applications: geoscience, engineering, operations, business, personal productivity, and IT, etc...usually supplemented out of necessity by a veritable foundry of line-coded "tools", "agents", or "macros". This software or line code is written by one of, or all of, several million developers, sometimes including end users themselves, in many different "languages". The fuel and lifeblood for this technical computing system is data. This data comes in a million different formats, sizes, and shapes. It comes in logarithmically increasing numbers making "a million" seem like a quaint and archaic term.

With the complications of these various elements and their inter-relationships in the systems, complexity has become the enemy of innovation. Too many engineers, geoscientists, field operators, accountants, and managers (not to mention IT specialists, and others) spend too much time dealing with the complexity and moving parts of the "system"...and so far too little time evaluating, analyzing, sciencing (is that a word?) and innovating in the environment.

While there are many targets for simplification in these technical computing systems, DATA rises to the top of the list as the most critical element. In this upstream environment, data is at the core of the systems - resting upon the networked infrastructure, and feeding the applications and user interfaces. Data is what the systems were built for and around. After all, scientific software applications without data are, in essence, just theory. And, I don't need computer infrastructure if I don't have any data or even software without data. Data is king. Yet data is probably in the worst shape of all the elements of the system in terms of its wild, complex nature.

Historically, geoscience based UNIX systems have involved large data file sizes (think seismic). Engineering and business productivity systems have grown from environments with relatively small data file size, but with numerically many more files. While the systems continue to evolve and converge, the Upstream industry is faced with a tidal wave of information; 2-D becomes 3-D, now 4-D seismic. Real-time data capture systems and others have led to an explosive exponential growth in data volumes and storage requirements. This reality has placed the technical user in the proverbial needle in the haystack situation.

Another reality of this information overload environment is that all data is not created equal. Some data have greater importance than others. Imagine looking for that needle in not just one haystack, but a field of haystacks. Maintaining data quality will require progressively better automation as data has entropy, always seeking a lower state.

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