Experimental Results and Analyses
Photographs of the cube after the fracturing tests are shown in Figure 19 and Figure 20. It is found that the geometry of the shale hydraulic fracture is more complex, which is different from the traditionally bi-winged, planar fracture. The morphology of the HF is strongly influenced by the opened NFs and sedimentary beddings.
Figure 19. Photographs of specimen Y-7-1 after conducting experiments.
The crack initiation and evolution can also be analyzed by the acoustic emission (AE) detection results during experiments. One red dot is defined as an AE event. For specimen Y-7-1 (shown in Figure 21), the HF firstly began to propagate along the overburden stress, lately extended to an inclined pre-existing natural fracture (fracture #1). Shortly, some acoustic emission events were gradually appeared along the natural fracture (fracture #2). These AE events were most probably generated by shear slippage along the NF surface since fluid that leaked off increased the pressure and reduced the cemented strength.
Figure 20. Photographs of specimen Y-7-3 after conducting experiments.
As time elapsed, the fluid pressure was sufficient to create a new secondary fracture at the weak location on the surface with the natural fracture. Thus, a step-like fracture with an obvious lateral offset was formed in the vertical direction (fracture #3). At the same time, some additional secondary fractures near the crack junction were also formed by the higher fluid pressure (fracture #4). Finally, the hydraulic fracture was arrested by a partially opened bedding fracture at the upper side and extended to the outer surface of the specimen at the lower left corner.
Figure 21. AE detection results for specimen Y-7-1 after conducting experiments.
For another specimen, labeled Y-7-3 (shown in Figure 22), the HF firstly propagated along the direction of the overburden stress (fracture #1), and thus turned into an opened bedding fracture (fracture #2). Soon afterwards, the partially opened bedding fracture near the wellbore was activated by the higher fluid pressure (fracture #3). As time elapsed, another pre-existing bedding fracture (fracture #4) was also activated by the main hydraulic fracture (fracture #1). Finally, a discrete fracture network was formed, but the complexity of the final fracture network was lower than that of specimen Y-7-1.
Figure 22. AE detection results of specimen Y-7-3 after conducting experiments.
The variation curves of the pump pressure and total injected volume during the tests are shown in Figure 23. It can be observed that there is a significant difference between the pump pressure curves of the two model blocks. In test Y-7-1, a typical pump pressure curve was recorded, and an obvious fracture breakdown was indicated by a sharp decline of the pump pressure. However, for specimen Y-7-3, it was difficult to see obvious fracture breakdown characteristics from the pump pressure curve, and the pump pressure continued to rise until a stable hydraulic flow channel had been fully formed.
Figure 23. Variation of pump pressure and total injected volume during the test. (a) Sample Y-7-1; (b) Sample Y-7-3.
This was because the hydraulic fractures were mainly propagating along the opened bedding fracture, and a higher fluid pressure was needed to overcome the overburden stress and stress shadow. In addition, the larger total injected volume and less AE events indicate that the specimen Y-7-3 was dominated by tensile failure and the sample Y-7-1 was mainly present in the form of shear failure.
Based on these experimental results, we found that the morphology of the shale hydraulic fracture was strongly influenced by the characteristics of the pre-existing natural fractures and sedimentary beddings. The density, orientation, and cemented strength of the pre-existing natural fractures are the three factors dominating the formation of complex fracture networks. The hydraulic fractures are either diverted or arrested by the NF. The experiment results are in good agreement with the numerical results.
Based on these numerical and experimental analyses, the following conclusions can be proposed:
(1) The hydraulic fracture morphology of shale was strongly influenced by the characteristics of its natural fractures. The NF density, orientation, and cemented strength, are three main factors dominating the formation of complex fracture networks.
(2) The cemented strength of the NF caused a noticeable nonlinear behavior for this problem. For an NF with a low strength, only shear failure occurred, and the HF was more likely to terminate. However, for an NF with a moderate strength, the hybrid failure model (tensile failure and shear failure co-existence, and conversion) may occur, and the HF is more inclined to step over at the contact.
(3) The displacements and stresses along the NF all changed in a highly dynamic manner. During the stage of approach of the HF to an NF, the HF tip could exert a remote compressional and shear stress on the NF interface, which could lead to the debonding of the natural fracture. Meanwhile, a maximum principal stress peak is generated at the end of the opening zone, where a new tensile crack is more likely to occur.
(4) The location and value of the stress is the function of NF inclination angle, far-field differential stress as well as HF net pressure. For small approaching angles, the stress peak is located farther from the intersection point, so a step over (offset) fracture is more likely to occur. The same effect can be found by a higher HF net pressure, because the stress perturbation ahead the NF is proportional to the fluid pressure in the HF.
(5) Meanwhile, the HF was found to be more prone to deviate from its original propagation path and reoriented near the NF because the deformation of the NF.
X.C. and C.Y. designed the theoretical framework; X.C. wrote the displacement discontinuity method code; Y.G. and X.S. designed the hydraulic fracturing tests; J.Z. prepared the shale samples and performed the hydraulic fracturing tests.
The research was funded by the National Science and Technology Major Project of China, grant numbers 2016ZX05060-004, 2017ZX05036-003; the National Natural Science Foundation of China, grant number 51574218; Strategic Priority Research Program of the Chinese Academy of Sciences, grant number XDB10040200.
Conflicts of Interest
The authors declare no conflict of interest.
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Xin Chang, Yintong Guo, Jun Zhou, Xuehang Song and Chunhe Yang
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