--> --> Abstract: Distinguishing Legacy Dipmeters from Borehole Images in Oil Sands Geological Interpretations, by Satyaki Ray; #90075 (2008)

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Distinguishing Legacy Dipmeters from Borehole Images in Oil Sands Geological Interpretations

Satyaki Ray
ConocoPhillips, Canada, Calgary, Alberta, Canada

Historically dipmeter tools have been used in various ways for interpreting clastic reservoirs. Applications have ranged from paleocurrent patterns, stratal geometries, structure, stratigraphy and facies of oil sand reservoirs. Originally there were 3 or 4 button dipmeters increasing to 8 buttons over time and eventually to Borehole Images using up to 192 button electrodes for measuring azimuthal microconductivity data. As the number of buttons and pads increased, resolution and visualization of geological features improved. This led to the ability to build a more detailed and reliable interpretation. However still we have in the industry a lot of legacy dipmeter data which have been recorded by various companies prior to the imaging era. When we try to compare automatic dips from these legacy dipmeter microconductivity “fast channel” curves to the the high resolution image logs, there are certain interpretation skills which are required to make the transition. Historically the automated dipmeter data was coded into color dip patterns (green, blue, red, orange) by early processors and interpreters. Over time Borehole Imaging (FMI* Tool) led to the ability to hand pick and classify sinusoid dips from oriented and colored images. Both approaches result in dip patterns , however in the latter case (image based manual interpretation), the derived dip data is better quality checked , cleaner and not prone to processing artifacts such as mirror dips, bag of nail patterns and spurious dip patterns. Moreover it was possible to compare an image to a core photo, rather than wiggles. This is related to the fact that the traditional dipmeter microconductivity fast channel “wiggles” were very active in the shale dominated zones, whereas the conductivity contrast within massive or cross bedded sands was not that great. This was due to lack of borehole coverage and the lack of number of button electrodes (8 buttons verses 192 buttons). Further by incorporating static and dynamic histogram normalizations and color allocation, an image could be enhanced to bring out subtle geological features and facies (such as lateral accretions, cross beds, scour surfaces, mud clasts, mud sand couplets). The legacy dipmeter approach in the area of facies interpretation used educated “guesswork” which often may have been prone to error. In this paper a legacy approach and an image based approach from an oil sand dataset is presented to distinguish the dipmeter and image log applications in oil sand geology and facies analysis. The industry could use these approaches as screening tools for SAGD well placement.

* Mark of Schlumberger
FMI stands for Fullbore Formation MicroImager Tool

 

AAPG Search and Discovery Article #90075©2008 AAPG Hedberg Conference, Banff, Alberta, Canada