## 1 Introduction  
Tight oil and gas reservoirs are an important part of mineral energy in China. However, their low permeability (<0.5 mD) makes it difficult to exploit them. Therefore, it is necessary to improve the reservoir and enhance oil recovery by hydraulic fracturing. The process of hydraulic fracturing involves not only solid deformation caused by fluid pressure before fracture, but also fracture initiation and propagation during fracture, as well as fluid flow and seepage after fracture [1]. If these key mechanical problems can be grasped and understood, the process of fracture development can be predicted and evaluated, thus providing important references for optimizing hydraulic fracturing plans and improving recovery efficiency. By conducting hydraulic fracturing experiments in the laboratory, the influence of environmental factors can be reduced, and the dynamic development process and distribution ranges of fractures can be obtained using multiple physical means, such as acoustic emission monitoring, ultrasonic velocity, and X-ray tomography [2; 3; 4; 5]. Acoustic emission events (AEs) originate from crack rupture induced by mechanical, thermal, or hydraulic factors [6; 7; 8; 9]. By investigating the AE characteristics (including count, amplitude, and location), we can obtain the failure law of hydraulic fracturing indirectly [10]. AE count is always used to quantify the AE activity [8], which represents the occurrence of the microcrack during the loading tests. AE peak amplitudes reflect the magnitude of fracture. The slope of the frequency magnitude distribution, b-value, is considered to represent the states of fracture [8; 11]. Numerous laboratory studies provide that the b-value always decreases when the stress increases [12; 13; 14; 15; 16], which makes it possible to predict failure using precursory changes in the b-value. Except for the AE amplitude, the characteristics of the AE waveform can be used to identify the fracture mode by moment tensor inversion [17; 18; 19; 20; 21]. Since the AE is associated with the fracture of the rocks, analyzing the spatiotemporal distribution of AE can capture the initiation and propagation of hydraulic fractures. In fact, AE location has been widely used to study the process of hydraulic fracturing in the laboratory [22; 23; 24; 25; 26; 27; 28; 29]. In addition, AE source localization could be used to determine the location of the fracture surface [22]. Although AE can explain the fracture process very well, it cannot fully reveal the fracture evolution of hydraulic fracturing, especially the mechanism of interaction between hydraulic fracturing and fluid flow. Therefore, to more fully understand the dynamic process of hydraulic fracturing, it is necessary to determine the distribution of fluid and flow process within the rock. As fluid could cause changes in the ultrasonic velocity of the rock [30; 31; 32; 33; 34; 35], the fluid distribution in the rock could be known if the 2D/3D rock velocity images can be obtained. For example, ref. [36] obtained the rock velocity structure using ultrasonic tomography (UT) and analyzed the process of fluid penetration in dry Oshima granite. Therefore, as a traditional means of studying rock deformation and fracture [7; 37; 38; 39; 40; 41], ultrasonic tomography can also be used to study the hydraulic fracturing of rocks. Joint analysis of AE and UT can help to understand the micromechanical response of rock to the stress field and fluid penetration effect [6]. AE and UT have brought us many interesting findings about the process of hydraulic fracturing. For example, a positive feedback mode between hydraulic fracturing and fluid flow was found in [42]. The investigation of [43] proved that the injected high-pressure oil would cause AE activities when the rock was at low-stress levels. A dynamic coupling process of fluid flow and rock deformation can also be found in [6; 44].