ORCID Profile
0000-0002-9107-1925
Current Organisation
University of Calgary
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Publisher: Elsevier BV
Date: 2020
Publisher: Elsevier BV
Date: 07-2018
Publisher: Elsevier BV
Date: 07-2022
Publisher: SPE
Date: 09-11-2015
DOI: 10.2118/176886-MS
Abstract: Brittleness indices (BI) commonly used in the petroleum industry are based on elastic modulus or mineralogy that can be calculated from well logs. However, they both ignore the effect of confining pressure. Shale is usually distributed at different depth under different confining pressure. Models without considering the influence of confining pressure will directly lead to inaccuracy in BI calculation, thus resulting in the failure of hydraulic fracturing. In this work, we compared confining pressure with rock mechanics parameters and the microcrack quantity of a core, introduced "fracture toughness" to explain how confining pressure influences BI, and finally developed a new model to correct the effect of confining pressure in BI calculation. Fracture toughness is an important parameter that characterizing a rock’s resistance to a fracture. It increases with confining pressure, since an increase of confining pressure may close preexisting cracks and restrict the crack propagation. The results show that BI is usually larger at low confining pressure than at high pressure. Also, higher content in brittle mineral does not necessarily mean brittler. The results calculated by the new model, which considers the influence of Young’s modulus, Poisson’s ratio, tensile strength, confining pressure and fracture toughness in BI calculation, match well with experimental results.
Publisher: Elsevier BV
Date: 04-2019
Publisher: SPE
Date: 09-11-2015
DOI: 10.2118/177010-MS
Abstract: Brittleness indices (BI) commonly used in the petroleum industry are based on elastic modulus or mineralogy that can be calculated from well logs. However, they ignore the weights of these two factors. Also, it is imprecise to calculate BI by considering quartz (or dolomite) as the only brittle mineral in mineralogy-based BI prediction. Shale gas reservoirs like Eagle Ford are rich in carbonate minerals. If the carbonate minerals are ignored in those reservoirs, the value of BI will be greatly underestimated. On the other hand, brittle minerals like quartz, dolomite and calcite play different roles in BI calculation. If we equally treat them without weighting in BI prediction, the BI being calculated will be inaccurate as well. This paper analyzes the influence of calcite on rock mechanics parameters and BI comparing with quartz and clay. Then new models of BI prediction are built to characterize the weight of each brittle mineral and rock mechanics parameter. Based on the least squares method, optimal values of weight coefficients will be obtained by iteration. The results show that calcite improves rock brittleness and should be considered as a brittle mineral in BI prediction. However, the weight of calcite is less than quartz. From the statistics results, quartz & dolomite & calcite & clay occurs in improving BI. The results also show that Young's modulus plays a more important role in BI prediction than Poisson's ratio.
No related grants have been discovered for Zhangxin Chen.