Abstract: Application of a Novel High Resolution Object Recognition
Algorithm for Petrographic Image Analysis of Reservoir Facies from
the Rabbit Hills Oil Field, Montana
HENDRIX, M. S. and R. FORD, University of Montana-Missoula
In a series of ongoing experiments, we are applying a recently
developed object recognition
algorithm to the quantification of 2-D
pore networks in thin-section. Developed at the Distributed
Applications and Systems Lab (DASL) at University of Montana
(http://www.umt.edu/ MERGE), this algorithm has been already been
successfully applied to the analysis of large volume satellite
imagery. Key to our petrographic image analysis is the enhanced
resolution provided by the MERGE algorithm. Whereas most
petrographic image applications process images on the order of
1000x1000 pixels (i.e. 1,000,000 pixels), the MERGE algorithm has
been successfully applied to images as large as 625,000,000 pixels
using only well equipped local workstations. We are currently
modifying and applying this rule-based algorithm to the spatial
analysis of pore networks, framework grains, and
diagenetic
constituents in a suite of thin-sections cut from core samples of
the middle Jurassic upper Bowes Member (Piper Formation) from the
Rabbit Hills oil field in north-central Montana. The upper Bowes is
a bioclastic carbonate that comprises reservoir facies in the
Rabbit Hills field. Samples for thin-section were derived from the
Flynn Trust 7-15 well. Preliminary petrographic analysis of the
reservoir facies suggests that it should be ideal for this sort of
petrographic image application. Reservoir facies consist mainly of
quartz-bearing ooid and bioclastic grainstones. Shelter porosity
and moldic porosity after molluscan detritus are volumetrically the
most important porosity types. A fringing calcite cement has
partially occluded both primary and secondary porosity. Direct
porosity measurements of the reservoir facies average 16.8% (n=19).
Kmax measurements average 66 md (n=19). Both pores and pore throats
are easily resolved petrographically. We are currently conducting
spatial analysis of pore volumes,
diagenetic
constituents, and
framework components from this well, and we anticipate a reasonable
comparison between porosity and permeability values computed from
our petrographic image analysis and those obtained from direct
measurement.
AAPG Search and Discovery Article #90937©1998 AAPG Annual Convention and Exhibition, Salt Lake City, Utah