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Fracturing index-based brittleness prediction from geophysical logging data: application to Longmaxi shale

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Abstract

Understanding of brittle and ductile behavior in low permeability shale formation is essential for optimizing the completion and stimulation treatment in a shale play. For the quantification of brittleness in shale, several methods for estimating fracability index have been proposed in the literature. However, uncertainties still exist in the interpretation of fracability to decide where to place perforation clusters, what magnitude of fracability index mean to hydraulic fracture initiation and propagation, and how brittleness is best defined. This study aims to clarify these unresolved issues by introducing improved fracturing-index (FI) model after modifying Yuan et al. (SPE J 2017:1–9, 2007) fracability-evaluation model (Frac). Comparing with the use of Frac, the improved FI accurately predicts the brittle and ductile regions and provide a comparatively better idea about favorable fracturing sweet spots at TOC rich zones with added advantages of estimating efficient fracture initiation and propagation, and resistant to proppant embedment. In this study, mechanical rock properties were derived through acoustic logging data to develop mechanical earth models and designed brittleness templates for differentiating brittle and ductile regions in Longmaxi gas shale reservoir. The effectiveness of designed brittleness templates was verified through improved FI evaluation model and pre-existing fractures. The obtained result revealed that the points of high FI fall exactly into the predicted brittle regions and the points of low FI fall exactly into the predicted ductile regions. The applicability of the designed brittleness templates was further verified through the data from offset Well J-3, laboratory testing of several outcrop samples, and shale sample from different origin with varying composition.

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(Modified from Huang et al. 2012)

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Abbreviations

TOC:

Total organic carbon

BI:

Brittleness index

BIm :

Mineralogy based brittleness index

FI:

Fracturing index

Frac:

Fracability-evaluation model

XRD:

X-ray diffraction

ECS:

Elemental capture spectroscopy

FE-SEM:

Field emission scanning electron microscopy

E:

Young’s modulus

ν:

Poisson’s ratio

G:

Shear modulus

K:

Bulk modulus

σt :

Tensile strength

KIC :

Mode-1 fracture toughness

KIIC :

Mode-II fracture Toughness

σh :

Minimum horizontal stress

λ:

Lamè’s parameters

µ:

Lamè’s parameters

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Acknowledgements

We greatly appreciate the support of National key research & development plan programs (2017YFB0202900), the National Science Foundation of China (41574125, 41774139) and the Strategic Priority Research of the Chinese Academy of Sciences (XDA14010303). We also acknowledge school of Geosciences, China University of Petroleum (East China) and Rock Mechanic Laboratory, University of Saskatchewan, Saskatoon, Canada for providing lab facilities and technical support.

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Authors and Affiliations

  1. School of Geosciences, China University of Petroleum (East China), Huangdao district, Qingdao, People’s Republic of China

    Qamar Yasin & Qizhen Du

  2. Department of Civil, Geological and Environmental Engineering, University of Saskatchewan, Saskatoon, Canada

    Ghulam M. Sohail

  3. Department of Petroleum and Gas Engineering, University of Engineering and Technology, Lahore, Pakistan

    Atif Ismail

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  1. Qamar Yasin
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Correspondence to Qizhen Du.

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Yasin, Q., Du, Q., Sohail, G.M. et al. Fracturing index-based brittleness prediction from geophysical logging data: application to Longmaxi shale. Geomech. Geophys. Geo-energ. Geo-resour. 4, 301–325 (2018). https://doi.org/10.1007/s40948-018-0088-4

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