Dynamic change in dominant factor controls the injection-induced slip behaviors of rock fractures.

In the geo-energy industry, fluid injection induces different slip behaviors of a rock fracture, from aseismic creep to dynamic slip. The transition from aseismic creep to dynamic slip is explained by the ratio of the stiffness of surrounding rock and the critical stiffness of the fracture. However, numerous studies suggest multiple controls affecting the slip behaviors, and their joint influences on the slip transition remain unclear. Here we trained a dual-stage attention-based recurrent neural network model using fluid injection experimental data to explore the dominant factor controlling the slip behaviors. Our results showed that the dominant factor changes during fluid injection, and the attention to shear stress dominates the occurrence of dynamic slip. We found that high fluctuations of the attentions to normal stress, shear stress, and water pressure gradient promote the slip transition. Our model was applied to explore the competing process between water pressure front and aseismic creep front while gradually increasing the injection pressure and to reveal the dynamic change in the dominant factor during the growth of cumulative moment release. • A recurrent neural network is built to explore the dominant factor controlling slip behaviors. • The attention mechanism reveals the dynamic change in dominant factor during fluid injection. • High fluctuations of attentions to controlling factors promote the slip transition of rock fracture. [ABSTRACT FROM AUTHOR]