Quantitative seismic interpretation of rock brittleness based on statistical rock physics

Wang, Lin; Zhang, Feng; Li, Xiang-Yang; Di, Bang-Rang; Zeng, Lian-Bo. 2019 Quantitative seismic interpretation of rock brittleness based on statistical rock physics. Geophysics, 84 (4). IM63-IM75. 10.1190/geo2018-0094.1

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Official URL: http://dx.doi.org/10.1190/geo2018-0094.1

Abstract/Summary

Rock brittleness is one of the important properties for fracability evaluation, and it can be represented by different physical properties. The mineralogy-based brittleness index (BIM) builds a simple relationship between mineralogy and brittleness, but it may be ambiguous for rocks with a complex microstructure; whereas the elastic moduli-based brittleness index (BIE) is applicable in the field, but BIE interpretation needs to be constrained by lithofacies information. We have developed a new workflow for quantitative seismic interpretation of rock brittleness: Lithofacies are defined by a criterion combining BIM and BIE for comprehensive brittleness evaluation; statistical rock-physics methods are applied for quantitative interpretation by using inverted elastic parameters; acoustic impedance and elastic impedance are selected as the optimized pair of attributes for lithofacies classification. To improve the continuity and accuracy of the interpreted results, a Markov random field is applied in the Bayesian rule as the spatial constraint. A 2D synthetic test demonstrates the feasibility of the Bayesian classification with a Markov random field. This new interpretation framework is also applied to a shale reservoir formation from China. Comparison analysis indicates that brittle shale sections can be efficiently discriminated from ductile shale sections and tight sand sections by using the inverted elastic parameters.

Item Type:	Publication - Article
Digital Object Identifier (DOI):	10.1190/geo2018-0094.1
ISSN:	0016-8033
Date made live:	24 Sep 2019 14:29 +0 (UTC)
URI:	https://nora.nerc.ac.uk/id/eprint/525181

Item Type:

Publication - Article

Digital Object Identifier (DOI):

10.1190/geo2018-0094.1

ISSN:

0016-8033

Date made live:

24 Sep 2019 14:29 +0 (UTC)

URI:

https://nora.nerc.ac.uk/id/eprint/525181