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Upgrading Of Carbonate Classifications By Digital Image Analysis And Multivariate StatisticsNormal access

Author: E. Kiefer
Event name: First EAGE Workshop on Evaluation and Drilling of Carbonate Reservoirs
Session: Geomechanics and Rock Properties of Carbonates
Publication date: 04 October 2017
DOI: 10.3997/2214-4609.201702366
Organisations: EAGE
Language: English
Info: Extended abstract, PDF ( 566.76Kb )
Price: € 20

Carbonate classifications and petrophysical rock typing are popular in reservoir characterization, core-log-calibration, seismic inversion, and petrophysical modeling for reservoir simulation. They rely on visual comparison charts and semi-quantitative estimations. This paper outlines the potentials of advanced digital image analysis tools in combination with agglomerative hierarchical cluster analysis (AHC) to define rock types. This approach has been tested in a tight oil reservoir using more than 500 petrophysical plug measurements and petrographic thin section analyses from 6 wells. The case study resulted in 11 rock types, which clearly seperate in terms of porosity, permeability and density.

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