Experimental investigation on the fracture behaviour of black shale by acoustic emission monitoring and CT image analysis during uniaxial compression

Feng²,

et al. 2019

Water

The deterioration of rock geomechanical behaviors subjected to freeze–thaw (F–T) action is a determining factor for rock engineering and rock structures in cold regions. In this work, taking six groups of granite obtained from an open pit mine as the research object, F–T cycle treatment, in-situ AE (acoustic emission) monitoring and ultrasonic detection techniques were performed to experimentally reveal the effects of F–T fatigue damage on the mechanical and acoustic properties of granite. The results indicate that the F–T action impacts the rock’s mesoscopic structure, deformation, strength, P and S-wave velocities, AE pattern and energy release. The accumulated AE counts and accumulated AE energy show a decreasing trend as the F–T cycle increases. The frequency spectrum revealed that the width of the low frequency band decreases and the high frequency band increases with increasing F–T cycles, indicating that there is an increase in large-scale cracks for a sample with high F–T treatment. In addition, energy balance analysis further illustrates the energy dissipation and release mechanism. The energy proportion used to drive the crack propagation is relatively small with high F–T treatment, and the final released energy becomes the minimum. The energy evolution characteristics analyzed by the energy balance approach is in good agreement with AE results. It is suggested that the F–T fatigue damage influences the rock energy storage and release characteristics and the instability of rock in the cold regions.

Section: Ae Energy Characteristicsmentioning

confidence: 99%

Geomechanical and Acoustic Properties of Intact Granite Subjected to Freeze–Thaw Cycles during Water-Ice Phase Transformation in Beizhan’s Open Pit Mine Slope, Xinjiang, China

Feng²,

et al. 2019

Water

“…The first type is to study the crack evolution and failure mechanism under different loading patterns based on AE. The brittle failure of shale occurs during loading progress [24], and the bedding planes of shale have a significant effect on its mechanical behavior [25]. Tensile cracks along with the bedding dominate the failure of shale with the axis parallel to the bedding.…”

Section: Introductionmentioning

confidence: 99%

Experimental Studies on Shale Cracks and Permeability Evolution Based on Acoustic Emission Monitoring

Chen

et al. 2021

Geofluids

The matrix permeability of shale reservoirs is extremely low. Therefore, massive volume fracturing is needed to form a complex crack network and get adequate sufficient capacity during the well completion. After fracturing, the effective stimulated reservoir volume (ESRV) is vital for developing shale reservoirs, mainly determined by stimulated reservoir volume (SRV) and the increase in permeability. Microseismic monitoring is widely used in the field to describe the crack shape and determine the SRV, to evaluate the stimulation effect. However, no studies have been conducted on the relationship between microseismic parameters and permeability. Thereby, we conducted uniaxial compression tests on Longmaxi shale samples and measured their changes in porosity and permeability before and after loading combining the microseismic monitoring under a laboratory scale (acoustic emission (AE)). Results show that porosity has little influence on the permeability before and after loading, while the propagation and connection of cracks are the most critical factors. As the loading stress increases, the crack volume and sample connectivity both grow. Besides, for the Longmaxi shale, when the stress is loaded to 30~50% of uniaxial compressive strength (UCS), the cracks start to propagate steadily (dilation), the permeability begins to increase rapidly, and percolation occurs, which indicates that the dilation point is closely related to the percolation threshold. The AE rate and accumulative ringing number both increase when it is larger than the percolation threshold value. The variation of AE characteristics can be used to identify the percolation threshold. Finally, the graphic model including AE parameters, crack, and permeability evolution is established based on the experimental results, which could help us understand the relationship between microseismic parameters and permeability and provide a methodological basis for the ESRV evaluation in the field.

“…By analyzing the AE characteristics of rock fractures, it is helpful to understand the rock fracturing mechanism and provide a theoretical and technical basis for field HF monitoring [14]. Numerous studies have reported laboratory-scale rock fracture analysis using AE monitoring, including the rupture process of brittle rock [15,16], the mechanical and acoustic properties of shale rocks [17,18], the characteristics of fracture propagation with bedding planes at different directions [19], and the focal mechanism of AEs during laboratory-scale HF experiments [20,21].…”

Section: Introductionmentioning

confidence: 99%

Multifractal Analysis of Acoustic Emissions during Hydraulic Fracturing Experiments under Uniaxial Loading Conditions: A Niutitang Shale Example

Tan

Xie

et al. 2020

Geofluids

Fracture characterization is essential for estimating the stimulated reservoir volume and guiding subsequent hydraulic fracturing stimulations in shale reservoirs. Laboratory fracturing experiments can help provide theoretical and technical guidance for field operations. In this study, hydraulic fracturing experiments on the shale samples from Niutitang Formation in Hunan Province (China) under a uniaxial loading condition are conducted. The multifractal method is used to analyze the acoustic emission (AE) signals and characterize fracture initiation and propagation. The hydraulic fracturing process can be divided into three stages based on the characteristics of AE signals: the initial stage, the quite stage, and the fracturing stage. The multifractal analysis results showed that: (1) the value of the spectrum width, Δα, continues to increase as the energy accumulates until the fracturing stage starts; and (2) the difference in the multifractal spectrum values, Δf, reflects the relationship between small and large signal frequencies and can quantify the fracture scale, i.e., the lower the Δf, the larger the fracture scale and vice versa. The results were further verified using a time-frequency analysis of the AE signals and micro-CT scanning of the samples. This study demonstrates that the multifractal method is feasible for quantitatively characterizing hydraulic fractures and can aid field hydraulic fracturing operations.