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
Upcoming events New articles Extra material Links
Sample chapter Figures Bibliography Extra material Historical Papers

by Steve Hawtin
22 Apr 2014

Corporate strategy models

For the CDA report we created a model of an oil company in order to examine the relationship between financial results and the technical data held within the organisation. In that case we had to incorporate a range of assumptions, for example that sub-surface data affected projects related to exploration, development and production. I remain happy with all the assumptions made. There were some short-cuts over the more complex oil company activities, I continue to believe that without those we could not have completed our report.

The oil industry model used in the CDA study

Previously I've claimed that there are two distinct types of business process models "corporate" and "process" ones. What I mean by this is that some models take a holistic approach and focus on a strategic view, while others concentrate on the details and enumerate as many facets as they can. A similar thing occurs in atmospheric modelling: "weather" models provide a picture that is accurate but only valid over a limited time frame; "climate" models, because they average weather over time, have results that are usually a much more reliable guide but isolated from specific incidents.

In the same way high-level corporate models rely on smoothing out the linkages between the components and the results. Like a climate model they can't predict if a particular project will succeed or fail, but they can indicate the overall influence that a new corporate strategy can be expected to deliver in the long term. Of course this distinction just highlights two ends of a spectrum, every model has to be a compromise between encapsulating enough detail to exhibit realistic responses and having so many parts that creating and using it is a challenge. For the CDA work, we started from the assumption that there was such a thing as "sub-surface technical data" and that this was of sufficient influence to significantly impact a company's overall results. Not a single one of the oil company executives questioned the existence of such a thing, or that it has a major effect on their business. Had they felt inclined to explore the details of what we meant by the term, and whether their definition was consistent with ours I'm sure there would have been quite a bit of a discussion, and maybe some disagreement.

Now don't misunderstand me, I am absolutely certain that this data exists and has a major impact on company results, but spending time exploring the exact scope of the term would have wasted the participants valuable time and distracted us from getting the input that we actually needed. Sometimes skipping over detail can help illuminate the real issues.

"The business value case for data management - a study" is available from Common Data Access Ltd for free from if you have not yet downloaded it you should.

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