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Australian Energy Producers Journal Australian Energy Producers Journal Society
Journal of Australian Energy Producers
RESEARCH ARTICLE

DRILL CUTTINGS ANALYSIS—A NEW APPROACH TO RESERVOIR DESCRIPTION AND CHARACTERISATION; EXAMPLES FROM THE COOPER BASIN, AUSTRALIA

S. Tiainen, H. King, C. Cubitt, E. Karalaus, T. Prater and B. Willis

The APPEA Journal 42(1) 495 - 509
Published: 2002

Abstract

In the absence of conventional core data, drill cuttings provide a continuous, independent and relatively inexpensive data source. Data collected from this often under-utilised resource can be used to determine permeability, provide information on diagenesis, stratigraphy and sedimentology, locate natural fractures, discriminate between genuinely poor reservoir and under performing assets and assist with petrophysical characterisation. Data can also be acquired in real time at the wellsite.

Drill cuttings analysis or rock typing is a visual method of semi-quantitatively describing rock and pore characteristics from drill cuttings. More specifically it partitions rocks into distinct permeability groups according to their petrophysical properties as observed under high-powered stereo microscope. Based on the observation of key visible attributes, the rocks are assigned to one of six rock types equivalent to the following permeability ranges; 1A (>100mD ambient), 1B (10-100 md ambient), 1C (1-10 mD ambient), 1D (0.5- 1 mD ambient), type II (0.5-0.07 mD ambient) and type III (<0.07 mD ambient).

One of the major strengths of rock typing is it can be used to provide an estimate of in-situ permeabilities. As rock type categories are related to ambient permeability classes an algorithm has been developed to take these ambient range estimates to single in-situ values for permeability and then taking into consideration the lithology in the sample, calculates a permeability height (kh) for the interval. The algorithm corrects for overburden, klinkenberg and relative permeability effects.

A comparison of kh derived from rock typing with kh derived from production and test data indicates a strong correlation between the two datasets. Results indicate that the kh sources are consistently similar and fall within one third of an order of magnitude of each other. As both of these data sources are independently derived it suggests both are realistic derivations of the actual kh of the reservoir interval. Consequently, once calibrated to all data sources, rock typing is considered capable of providing a robust estimate of in-situ kh for a specified reservoir interval.

https://doi.org/10.1071/AJ01027

© CSIRO 2002

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