Quest for Data Quality1 (QDQ) is not about ‘data quality’ as perceived by the IT community. It is about recording good logging data and understanding the pitfalls. QDQ sets out to ‘express real concerns’ about the data that is going from the logging truck into the ‘digital oilfield.’ After a disappointing first chapter on metrology, Theys gets into his subject, working through the logging tool suite, enumerating various gotchas. One of Theys’ hobby-horses is the repeat section. This should be an opportunity for on-the-spot QC. Unfortunately the trend today is for a ‘head in the sand’ approach, with no repeat section recorded in case it confuses the logger! Even worse, some LWD data is streamed straight into the corporate database, leaving potentially useful memory data behind.
An important job for the logger is the bringing of bad news—a dry hole or a poor cement job. The temptation to prefer ‘pleasant’ information needs to be avoided. One chapter compares logging company ‘brochure’ specs with reality to conclude that the evaluation of logging uncertainty is possible, but that a dialog with vendors is required to get behind their ‘simplistic’ public specs. Theys takes a swipe at remote supervision of the logging process noting that ‘reality’ can prove evasive to the remote observer. Theys suggests that logging engineers sign up to a ‘Hippocratic oath’ not to modify, hide or obfuscate the data they acquire. All in all, QDQ is an interesting collection of anecdotes, observations and entreaties. It does suffer from the absence of an index, from intrusive heading numbering, and rather idiosyncratic chapter titles that did not simplify the reviewer’s task!
1 Editions Technip 2011—www.oilit.com/links/1102_22.
This article originally appeared in Oil IT Journal 2011 Issue # 2.
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