The Management of Oil Industry Exploration & Production Data

Who are we? Purchase Options - B&W USA/World - B&W UK - B&W Germany - B&W France - Color USA/World - Color UK - Color Germany - Color France
1 Introduction 12 Physical data
2 Value of data 13 Documents
3 Subsurface data 14 Auditing
4 Current practice 15 Quality
5 DMBoK 16 Other elements
6 Governance 17 Assessing
7 Architecture 18 Glossary
8 Development 19 Figures
9 Operations 20 Bibliography
10 Security 21 Index
11 Corporate data 22 Further info
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Sample chapter Figures Bibliography Extra material Historical Papers

by Steve Hawtin
14 Sep 2013

Good and Bad Hype

Can of Hype

I once heard a great radio program about designing video recorders (this was long ago when people still bought video recorders). The question that the presenter was interested in was "these devices are jammed with so many features that they are confusing, why are they all so hard to use?" He talked to various users and consumer groups who all agreed that they were too complex, so he tracked down an engineer to talk to. This designer posed just one question "what made you buy your last video recorder?", as the presenter started to reel off a list of features the designer interrupted him, "my job is to create a product that sells, so I include bells and whistles because they help shift the product, whether users benefit from them or not doesn't matter".

I am often asked what impact I think "The Cloud" or "Big Data" will have on the future of sub-surface technical data handling. Cynically I suspect that in a few years' time neither will be seen as having been important. Both these terms, it appears to me, have been invented to sell product, not to solve user issues. Now don't get me wrong I'm sure there are valuable insights that using these terms have delivered and, in some specialised situations, I'm sure they have delivered fantastic benefits. It may even be that I'm wrong and that E&P data handling will be one of the industries that these techniques can be applied to, but my guess would be that the odds are against it.

Every so often the IT industry invents a new term, it goes through a cycle of evangelicalism, enthusiasm, application, disappointment and rediscovery. Gartner refer to this as the "hype cycle" and they will be happy to sell you reports on how the industry currently views more than 100 such topics from "Big Data" to "Web Computing". Of course Gartner only talks about terms that stand some chance of becoming fashionable again, terms like "GeoShare" whose disillusion phase was so strong that they will never come back get ignored.

The thing that each of these names share is an apparent simplicity, at first sight we think we know what the expression means. In the past this approach has delivered some notable and long lasting successes to our industry: the "integrated model" discussions of the early 1990s led directly into the success of Petrel; the miss-application of "six sigma" techniques has ended up radically improving the tools we employ to manage data quality; and I believe that the benefits from "change management" methods will continue to expand. So sometimes this understanding does deliver a real insight that helps us get our jobs done, but, for most hype terms closer inspection shows our improved comprehension to be an illusion.

The goal of this "hype based" approach is to generate the interest (and hence the funding) that is always required to convert a concept into a valuable implementation. In the majority of cases a hyped term doesn't end up delivering remarkable benefits to the users, the focus is to create sufficient revenue to keep construction going. Just as with the video recorder designer it could be that on the way something useful is produced, but that is not its primary objective.

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