Abstract：
Brittleness is of great significance for deep rock engineering and resource development, especially for unconventional
oil and gas resources. Brittleness evaluation, fundamental principles of its prediction and research progress are summarized and
analyzed. The structural characteristics of rock such as lithologic composition, bedding and damage, pore fluid and its occurrence
characteristics, confining pressure, temperature, rock mass measurement scale, and stress path all impact brittleness. High
brittleness unconventional reservoirs are characterized by a high content of brittle minerals, high Young's modulus, small total
strain before fracture, dissipated energy in the pre-peak stage of the stress-strain curve, little fracture energy in the post-peak
stage, low ductility, large internal friction angle and easy formation of complex fracture network systems in hydraulic fracturing.
Unconventional reservoir brittleness research should focus on the formation frangibility and the ability to form complex fracture
network systems. According to the types of data, brittleness evaluation methods mainly include mechanical experiment evalua
tion and evaluation based on logging and drilling data. Brittleness prediction is mainly based on prestack seismic inversion. The
study of brittleness anisotropy and controlling factors help optimize and improve evaluation and prediction methods for different
types of unconventional reservoirs. Due to the different research ideas and data sources, the applicability of different methods
is also different. The integration and mutual verification of multiple data and methods is an important future development
direction. Artificial intelligence, including machine learning algorithms, can organically integrate multiple data, collate effective
information, and has the advantage of being more efficient and accurate. Artificial intelligence is promising in geological research
controlled by multiple nonlinear factors such as reservoir brittleness.
Key words：unconventional reservoir; factors affecting brittleness; brittleness evaluation method; brittleness prediction method; progress in brittleness research
Corresponding Authors： lbzeng@sina.com
Cite this article：CAO Dongsheng, ZENG Lianbo, LYU Wenya, XU Xiang, TIAN He. Progress in brittleness evaluation and prediction methods in unconventional reservoirs. Petroleum Science Bulletin, 2021, 01: 31-45.
