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The AAPG/Datapages Combined Publications Database

Journal of Sedimentary Research (SEPM)

Abstract


Journal of Sedimentary Research
Vol. 87 (2017), No. 5. (May), Pages 460-485
Research Articles
DOI: 10.2110/jsr.2017.25

Quantitative Image Analysis For Geologic Previous HitCoreNext Hit Previous HitDescriptionNext Hit

Roger J. Barnaby

Abstract

Many basic rock properties—such as lithology, bedding, grain size, sorting, and porosity—are expressed in geologic cores by changes in color, brightness, and texture. Quantitative descriptive rock properties can thus be derived from digital Previous HitcoreNext Hit images. Despite the widespread availability of high-resolution Previous HitcoreNext Hit images and image analysis software, these data are underutilized by geoscientists tasked with describing Previous HitcoreNext Hit.

This paper demonstrates the application of image analysis for quantitative Previous HitcoreNext Hit Previous HitdescriptionNext Hit using examples from three different carbonate reservoirs: (1) evaporite-rich dolostone from the First Eocene, Kuwait–Saudi Arabia Partitioned Zone, (2) vuggy dolostone from the Cretaceous Toca Formation, offshore Angola, (3) thin-bedded limestone and mudrock from the Ordovician Utica Formation, Ohio, USA. In each example, quantitative data are extracted from Previous HitcoreNext Hit images using ImageJ or WellCAD software. The image-derived descriptive parameters are consistent with petrophysical log and Previous HitcoreNext Hit data, supporting the validity of this approach to Previous HitcoreNext Hit Previous HitdescriptionNext Hit.

Image-analysis-guided Previous HitcoreNext Hit Previous HitdescriptionNext Hit offers many advantages over traditional hand-drawn Previous HitcoreNext Hit Previous HitdescriptionNext Hit: 1) hand-drawn Previous HitcoreNext Hit descriptions tend to be qualitative and Previous HitcoreNext Hit-log integration is difficult and imprecise, whereas image analysis generates quantitative descriptive data that are directly comparable with petrophysical datasets; 2) image analysis can characterize fine-scale geologic heterogeneity that is difficult or impossible to resolve using log and Previous HitcoreNext Hit plug data and hand-drawn Previous HitcoreNext Hit descriptions; 3) image analysis allows geologists to generate preliminary descriptions prior to actual Previous HitcoreNext Hit viewing, a more efficient workflow that minimizes time expended in offsite Previous HitcoreNext Hit viewing, perhaps in remote locations with limited time available; 4) integration of image-derived Previous HitcoreNext Hit data with petrophysical log and Previous HitcoreNext Hit data allows rigorous evaluation of Previous HitcoreNext Hit data quality—before, during, and after the process of Previous HitcoreNext Hit Previous HitdescriptionNext Hit.

Image analysis thus provides a valuable tool for geoscientists to efficiently generate quantitative, petrophysically significant Previous HitcoreTop descriptions.


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