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The AAPG/Datapages Combined Publications Database
AAPG Special Volumes
Abstract
DOI:10.1306/13181276M923404
Data
Management and Quality Control of Dipmeter and Borehole Image Log Data
Data Management and Quality Control of Dipmeter and Borehole Image Log Data
Carmen Garcia-Carballido,1 Jeannette Boon,2 Nancy Tso3
1Maersk Oil North Sea UK Ltd., Aberdeen, Scotland, United Kingdom; Present address: CEPSA E
P, Madrid, Spain
2NAM, Shell EP Europe, Assen, Netherlands
3Shell International Exploration and Production, Houston, Texas, U.S.A.
ACKNOWLEDGMENTS
The authors of this article are grateful for constructive comments by Christine McKay (Maersk Oil North Sea UK Ltd.), Stuart Buck (Task Geoscience), Heike Delius (Task Geoscience), and Michael Poppelreiter (Shell).
ABSTRACT
Numerous dipmeter and borehole image log data sets have been acquired over the years and are being used to build subsurface models. Dealing with dipmeter and image log data remains a niche skill within the petroleum industry, and because these are not conventional log data sets, they tend to be neglected in the way data are stored and quality controlled. A variety of wireline and logging-while-drilling tools exist, and each logging run contains a variety of curves with tool-specific mnemonics. For a particular data set, there may be several tens of curves from the raw data set and hundreds from the processed and interpreted data sets. Data quality control (QC) is an essential procedure that has to be conducted to assure dipmeter and image log data integrity in the subsurface models. Data QC should be performed iteratively during data acquisition, data management, processing, and interpretation. This chapter presents standard and globally applicable corporate guidelines for data management and data QC of dipmeter and image log data
sets.
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