TY - JOUR
AU1 - Wang,, Y
AU2 - Li, C, H
AU3 - Hu, Y, Z
AB - Summary Plenty of mechanical experiments have been done to investigate the deformation and failure characteristics of shale; however, the anisotropic failure mechanism has not been well studied. Here, laboratory Uniaxial Compressive Strength tests on cylindrical shale samples obtained by drilling at different inclinations to bedding plane were performed. The failure behaviours of the shale samples were studied by real-time acoustic emission (AE) monitoring and post-test X-ray computer tomography (CT) analysis. The experimental results suggest that the pronounced bedding planes of shale have a great influence on the mechanical properties and AE patterns. The AE counts and AE cumulative energy release curves clearly demonstrate different morphology, and the ‘U’-shaped curve relationship between the AE counts, AE cumulative energy release and bedding inclination was first documented. The post-test CT image analysis shows the crack patterns via 2-D image reconstructions, an index of stimulated fracture density is defined to represent the anisotropic failure mode of shale. What is more, the most striking finding is that the AE monitoring results are in good agreement with the CT analysis. The structural difference in the shale sample is the controlling factor resulting in the anisotropy of AE patterns. The pronounced bedding structure in the shale formation results in an anisotropy of elasticity, strength and AE information from which the changes in strength dominate the entire failure pattern of the shale samples. Defects, Geomechanics, Geopotential theory 1 INTRODUCTION As a kind of very important unconventional energy resource, the exploitation of shale gas has spurred enthusiasm in many countries, and China is no exception. Due to the presence of cleavage, bedding planes, foliation, schistosity and natural fractures, shales often exhibit strong anisotropic properties. These inhomogeneous structural characteristics result in the different mechanical properties for shale with different bedding plane inclination, for example hydraulic properties, flow and transport properties, thermal properties and seismic properties. Therefore, through investigation of the mechanical properties and their anisotropy (strength, modulus, fracture toughness, brittleness, failure modes and stress–strain behaviours) in conducted in the context of oil-gas engineering (e.g. drilling, completion and hydraulic fracturing operations). The macroscopic and microscopic origins, such as the orientation of clay mineral platelets, or the layering or orientation of fractures, leads to the intrinsic anisotropy of shale. In recent years, the increasing fossil energy demand pushed the exploration and development of unconventional hydrocarbon reservoirs (e.g. gas shales, oil shales and tight gas sandstone). Especially, more and more wells are being drilled into shale because almost all of the sedimentary basins contain shale formations all over the world (Pei 2008; Sarout & Guéguen 2008a,b; King 2010). To be economically attractive, hydraulic fracturing treatment by stimulated reservoir volume (SRV) is viewed as the most prospective technology to realize commercial development of shale gas (Mayerhofer et al.2008; Cipolla et al.2009; Jeffrey et al.2010; Wang et al.2016). The key factors affecting the maximization of SRV include the natural fracture network, in-situ stress state, rock mechanical properties and fracturing operation factors (e.g. injection rate, volume of fracturing fluid, fracturing segment spacing and fracturing modes). Among the many factors, rock mechanical properties are important basic parameters not only for hydraulic fracturing, but also for borehole stability evaluation and for the assessment of stable mud weight windows during drilling (Rybacki et al.2015, 2016). As is widely known, the realization of fracture networks and improved production rates always depend on the mechanical properties of shale formations (Rybacki et al.2015). Shales in sedimentary basins are affected by the depositional environment, diagenetic process, tectonic disturbance and hydrocarbon charging, etc. The bedding plane and microfractures alter shale's physical and mechanical properties, and are the cause of their anisotropy and heterogeneity characteristics. A thorough literature review shows many scholars have conducted series of laboratory compressive tests (Masri et al.2014; Heng et al.2015a,b,c; Rybacki et al.2015, 2016), tensile tests (Mokhtari et al.2014), three-point bending tests (Heng et al.2015a), direct shear tests (Heng et al.2015b) and numerical simulations (Mokhtari et al.2013; Suarez-Rivera et al.2013) on shale outcrops and reservoir samples. They have not only studied the macroscopic failure mechanism of shale under small strain rate (Sone & Zoback 2013; Heng et al.2015a), but also under a medium strain rate of 10−4–10−2 s−1(Rybacki et al.2015), high strain rate of 10–102 s−1(Liu et al.2015), cyclic loading and unloading (Wei et al.2015), high temperature (Islam & Skalle 2013), variable saturation (Sarout et al.2014) and frequency (DellePiane et al.2014) conditions. These experiments are aimed at studying the geomechanical behaviour of various shales and clays, and showing that the failure mode, static elastic modulus, strength and ultrasonic velocities of these materials exhibit directional dependency (i.e. the sample bedding or the loading direction, Podioet al.1968; Johnston1987; Niandou et al.1997; Petley1999; Naumann et al.2007; Kuila et al.2011; Nadri et al.2012; Islam & Skalle 2013; Sarout et al.2015; Kovalyshen et al.2017), temperature dependency (Islam & Skalle 2013) and strain rate dependency(Liu et al.2015; Rybacki et al.2016). The outcomes of these results show a pronounced anisotropy of the tested shales due to the pronounced bedding planes (Speight 2013). The structural anisotropy and heterogeneity of shale also influence the creep and flow behaviours. Sone & Zoback (2013) have performed a series of triaxial creep experiments, and found that a strong correlation exists between the shale mineralogical compositions, the volume of clay plus kerogen and the intact rock strength, frictional strength and viscoplastic parameters. In addition, Guo et al. (2013) conducted plenty of permeability testingon shale cores taken from the Shengli Oilfield, and the experimental results demonstrate that the bedding and natural fractures have significant effects on the matrix permeability. In addition, some empirical relationships have been established between shale mechanical properties and well-logging results (Dewhurst et al.2015). Recently, many so-called brittleness indices have been proposed to assess the prospectivity and fracabilityof gas shale plays (Rickman et al.2008; Bruner & Smosna 2011; Jin et al.2014a,b; Zhang et al. 2016). Sarout et al. (2017) have used microseismic monitoring (location and focal mechanisms) to monitor the faulting and fault slip in shale with inclined bedding plane inclined with respect of the direction of maximum principal compressive stress. Almost all the testing techniques to investigate the mechanical properties of shale are based on macroscopic experiment and reports about monitoring the failure evolution are rarely published. As one of the most interesting techniques used for the non-destructive evaluation of rock behaviour during fracture evolution, the acoustic emission technique (AET) allows in-situ physical and mechanical monitoring during the formation and propagation of microcracks and/or macrofractures over a long duration. This makes the AE technique quite unique along with the ability to capture crack initiation and propagation on the surface or inside a tested object (Grosse & Ohtsu 2008). When cracks form in rocks under internal or external loading, several reasons may cause the occurrence of AE events, such as dislocations of minerals or twinning and grain boundary movements, or the initiation and propagation of cracks through and between mineral grains. Not only laboratory testing or in-situ experiment, such studies almost always focus on the AE locations, relationships between AE parameters and stress–strain curves for different rock types, the purpose of the AE technology is to quantify the rock strength, brittle damage and stability issues (Littke et al. 1988; Pradhan et al.2015). Sierra et al. (2010) conducted the Chevron Notched Semicircular Bend (CNSCB) tests on shale sample with the acoustic emissions (AE) recorded during the fracturing process to monitor the fracture initiation, and found that the AE prior to the uncontrollable fracture growth under CNSCB tests could only be observed for the lower clay samples. For shale under rapid unconfined compression, Amann et al. (2011) used AE monitoring for shale to help quantify the stress levels associated with crack initiation and propagation. Qiao et al. (2015) also used the AE technology to help identify the characteristic stress levels during sample deformation, the tested samples have pronounced horizontal bedding. Wu et al. (2017) performed a study of AE characteristics during the failure process in shale rocks and the changes of a- and b-values during sample deformation have been investigated. Although attempts have been made on a shale samples using AE technology, the tested sample had a single bedding orientation, and detailed studies use of AE technologyfor anisotropic shale is not common. Many previous experimental investigations have been done to investigate the strength and failure characteristics of shale with different structural patterns. However, the AE characteristics of anisotropic shale are not fully understood and still remain the subject of considerable scientific interest. In addition, studies of AE characteristics of shale can help us predict the internal failure mechanism in real time, and are pivotal for design of drilling and hydraulic fracturing operations. In addition, using AE to study the elastic energy accumulation and release during fracturing or the existing natural fractures are valuable for reservoir fracability evaluation, development of new microseismic monitoring techniques, prediction of the interaction between natural and hydraulic fractures and the evaluation of hydraulic fracturing effectiveness. This study presents a series of deformation experiments on well-characterized Longmaxi black shale during the whole deformation process under uniaxial compressive stress conditions. We investigate the AE response in combination with post-test computer tomography (CT) imaging analysis of specimens with varying inclination between bedding plane and drilling orientation, and the testing impact on mechanical properties and failure behaviour. In this work, two AE channels/sensors were used during shale deformation, focusing on the analysis of AE hit count and AE energy release during sample deformation. 2 MATERIAL STUDIED AND EXPERIMENTAL PROCEDURE 2.1 Material and sample preparation Samples were cored from Longmaxi formation in the Lower Silurian located in Shizhu County Chongqing, China (Fig. 1). The formation is a natural extension of the formations in shale gas block of Pengshui play. The geographical coordinates of the sampling site is N: 29°53΄0″, E:108°17΄16″. The Lower Silurian Longmaxi shale was buried at a depth ranging from 0 to 2500 m in this shale gas play. The typical shale cores, obtained from a depth interval of 10–20 m with alternating thin and thick layers, represent a kind of carbonate rich, mature gas shale with a vitrinite reflectance Ro of 0.93 per cent. The trend of the formation is 327°, and dip is about 36°. Two sets of natural fractures can be observed from outcrop. The mean density value of the shale samples is about 2.62 g cm−3. By mercury porosimetry measurement, we determine the porosity of shale as 2.2–7.5 per cent. Through X-ray diffraction analysis, the shale core is composed of clay, illite–smectite, kaolinite, quartz, carbonates, organic matter, pyrite and feldspar. All black-dark samples were very-fine grained with pronounced fabric anisotropy. By Focused ion beam (FIB) imaging and scanning electron microscope (SEM) analysis, distinct bedding planes were observed as well as plenty of organic matter with subparallel pyrite flakes and cadlcareous bands can be observed, as shown in Fig. 2. Cylindrical samples were drilled out of the shale blocks (Fig. 1), under dry conditions with bedding plane orientations of 0°, 15°, 30°, 45°, 60°, 75° and 90° (Fig. 3). Then, each cylindrical sample was prepared to achieve a length-to-diameter ratio, L/d = 2 (i.e. 50 mm in diameter and 100 mm in height). The sample end faces were ground to perpendicularto the sample axial to within 0.05 radian, with a flatness to within 0.01 mm. A total of seven shale samples were used in this experiment. Figure 1. Open in new tabDownload slide The Longmaxi shale outcrop in Shizhu Country, Chongqing city, China. Figure 1. Open in new tabDownload slide The Longmaxi shale outcrop in Shizhu Country, Chongqing city, China. Figure 2. Open in new tabDownload slide The FIB–SEM imaging of shale sample vertical to the bedding face. (a) and (b) plot the results with magnification of 200 and 8000 times, respectively. Figure 2. Open in new tabDownload slide The FIB–SEM imaging of shale sample vertical to the bedding face. (a) and (b) plot the results with magnification of 200 and 8000 times, respectively. Figure 3. Open in new tabDownload slide Obtaining of shale samples with bedding inclination of 0°, 15°, 30°, 45°, 60°, 75° and 90°, respectively. Figure 3. Open in new tabDownload slide Obtaining of shale samples with bedding inclination of 0°, 15°, 30°, 45°, 60°, 75° and 90°, respectively. 2.2 Experimental techniques 2.2.1 Unaxial compression test Uniaxial compressive tests were performed at a servo-hydraulically controlled deformation apparatus (GCTS RTR-2000), at the Institute of Acoustics, Chinese Academy of Sciences (Fig. 4). The maximum axial force and load frame stiffness are 4600 kN and 10.05 MN mm−1, respectively. The apparatus can provide a maximum confining pressure of 210 MPa. The dynamic frequency of cyclic loading of the machine is 0–10 Hz. It can test rock samples at a maximum temperature of 200°. During the whole deformation process, axial and circumferential strain gauges were attached to the sample surface. The axial strain rate was utilized as the servo-control feedback channel mode, with a constant strain rate of 10−5 s−1 for the studied shale samples. Linear variable displacement transformers (LVDTs) are used to measure the axial displacement of the rock samples. The axial stress, axial strain and circumferential strain are recorded simultaneously by a central computer at the same sampling frequency during the whole testing. Fig. 4 shows the experimental rock mechanical setup for the shale samples. Figure 4. Open in new tabDownload slide The GCTS-2000 rock mechanic system used in the test. Figure 4. Open in new tabDownload slide The GCTS-2000 rock mechanic system used in the test. 2.2.2 AE monitoring test During the Uniaxial Compressive Strength (UCS) test, the AET was used to monitor the crack initiation, propagation behaviours during sample deformation (Fig. 5). There are many advances to AE monitor comparing with some traditional non-destructive techniques. In addition, we can use relative less cost and time to conduct the testing during experiment. What is more, not in demand of human operating the instrumentations, monitoring of AE events and failure locations can be accurately accomplished during testing. In this work, a series of AE analysis approaches are used to explore the anisotropic shale failure mechanism under uniaxial compressive deformation. During real-time mechanical testing, we used a PAC AE monitoring system, made in the Physical Acoustic Corporation Ltd, USA. The components of the AE monitoring system include AE data acquisition, AE transducers, the pre-amplifiers and the recording, processing and display units, as shown in Fig. 5. During deformation of the shale sample, damage and (micro-) fracturing events occur and the released elastic energy is radiated toward the AE transducers, resulting in thevibration of the piezoelectric ceramics making up each AE sensor. When this phenomenon occurs, a change in output voltage of the sensors can be identified. The pre-amplifiers amplify this voltage signal and the resulting signal is then processed and recorded. In addition, this AE monitoring system has the ability to record entire AE waveforms and can achieve positioning of AE events during the deformation of the rock. A maximum of 1 mega per second (MSPS) sampling rate with resolution of 18 bits can be achieved using PAC AE monitoring system. The sampling bandpass filter frequency is 125–750 kHz. The AE system can record the whole AE waves and the associated AE parameters real time during the deformation of rock samples. The AE sensor Nano 30 is used to monitor the fracturing of shale sample. Two AE sensors were used and installed on the sample (at upper and lower, opposite positions), the sample interval is set to 50 μs, threshold value is set to 42 dB, frequency is set to 102–104 Hz. The size of the sensor is 6 mm × 6 mm, the working temperature is between −65 and 177 °C and the resonant frequency is 300 kHz. The hit limitation is 10 000, and peak sensitivity is −65 V·μbar. Figure 5. Open in new tabDownload slide AE system used in this work. (a) The AE system used in the experiment, two sensors (channels 3 and 4) were used in the experiment; (b) principle of acoustic emission monitoring; (c) positions of the AE sensors, axial and lateral strain gauges on shale sample and (d) Photo of AE sensors. Figure 5. Open in new tabDownload slide AE system used in this work. (a) The AE system used in the experiment, two sensors (channels 3 and 4) were used in the experiment; (b) principle of acoustic emission monitoring; (c) positions of the AE sensors, axial and lateral strain gauges on shale sample and (d) Photo of AE sensors. 2.2.3 CT scanning test In most cases, we can clearly observe the fractures generated during the test with the naked eye. However, to better investigate the internal fracture pattern, the high-resolution X-ray computed tomography technique with scans every 15 mm (Fig. 6), was performed after the UCS test. Based on the reconstructed CT images, we further extract the crack morphology and studied the crack density using a digital image processing method (e.g. threshold segmentation, region growing algorithm, edge detection algorithm and erosion process, etc) to separate the fractures from the background in the binary images. From the extracted crack results, we defined an index of fracture density, Df, to quantify the crack density, which is defined as the ratio of total crack area to the area of the CT image section, as below: \begin{equation}{D_f} = \sum\limits_{i = 1}^n {{A_i}} /S\end{equation} (1) where Ai is the area of each section of the fractures and S is the area of the CT image section. Figure 6. Open in new tabDownload slide The CT scanning positions for shale samples after the UCS test, taking the sample with inclination of 0° for example. Figure 6. Open in new tabDownload slide The CT scanning positions for shale samples after the UCS test, taking the sample with inclination of 0° for example. 2.3 Experimental procedure During the UCS test, AE monitoring was always kept synchronous with the loading process. The tested shale sample was controlled by axial strain mode; the loading rate is set as a loading rate of 0.06 mm min−1 (strain rate is 10−5 s−1). The AE monitoring system operates during the whole deformation of samples, the recorded AE parameters include AE Hit, Count/Ring, Maximum amplitude of the waveform/event, Time duration, Rise time, Energy, Average frequency, Initial frequency and Reverberation frequency, etc. These parameters can help us analyse the crack initiation, propagation and coalescence behaviours of shale samples. The sensors were fixed on the sample surface by two rubber bands. We added Vaseline between the AE sensor and shale sample, in order to improve mechanical coupling at the interface. In order to minimize the risk of recording nose, a high acoustic signal trigger level was selected to be 4.5 mV. Doing so, we can only obtain the stable AE signals with high signal-to-noise ratio. In addition, the noise level was calibrated before loading, so as to eliminate the environmental noise of the loading system. The GCTS system carries out data collection at a rate of 0.5 Hz and record the corresponding stress, strains and loading time automatically. The axial, lateral and volume stress–strain curves can be drawn synchronously. After the test, we can read the AE parameters from the AE system, and study the relationships between AE parameter and the stress–strain curves. Post-test CT scanning analysis was also conducted to investigate the fracture pattern inside shale sample, and establish the relationship between the stimulated fracture density and bedding inclination. 3 EXPERIMENTAL RESULTS 3.1 Stress–strain behaviour We tested the Longmaxi shale samples with different bedding orientations under uniaxial compression at room temperature and pressure were conducted on. Table 1 shows the physical and mechanical parameters for shale samples. The typical stress–strain curves for sample with inclination of 0°, 15°, 30°, 45°, 60°, 75° and 90° are shown in Fig. 7(a). It can be seen that obvious brittle deformation occurs under uniaxial compression, the peak strain is below 1 per cent (Fig. 7b). In addition, because there is no lateral confining pressure restraint on sample, sudden failure occurs at peak strength and the post-peak curve cannot be recorded. The elasticity modulus exhibits lower value when the axial loading normal to bedding (i.e. inclination angle is 90°) compared to the other samples. In spite of different failure modes for the tested sample, the seven shale samples show brittle deformation, exhibit low peak strain and abrupt failure. The UCS, elasticity modulus and Poisson's ratio depend on the bedding inclination with respect to the applied stress, exhibiting that mechanical properties of the shale are anisotropic. Figure 7. Open in new tabDownload slide (a) Typical stress–strain curves black shales, (b) relationships of inclination and UCS, peak strain, (c) elasticity modulus and plot of the dynamic elastic modulus against static elasticity modulus. Figure 7. Open in new tabDownload slide (a) Typical stress–strain curves black shales, (b) relationships of inclination and UCS, peak strain, (c) elasticity modulus and plot of the dynamic elastic modulus against static elasticity modulus. Table 1. Strength and stiffness versus inclination for all tested shale samples. Test ID L × d (mm) Mass (g) Inclination (°) Density (g cm−3) Peak stress (MPa) Peak strain (per cent) Static elastic modulus (GPa) Static Poisson's ratio (v) P-wave velocity (m s−1) S-wave velocity (m s−1) S-0-1 98.61 × 48.91 500.07 0 2.700 191.47 0.626 42.31 0.352 4680 3012 S-0-2 99.31 × 49.92 500.11 0 2.574 174.78 0.612 40.87 0.344 4785 3087 S-15-1 100.04 × 49.68 503.78 15 2.599 164.45 0.542 32.32 0.316 4333 2784 S-15-1 99.96 × 50.01 500.65 15 2.551 158.22 0.532 35.43 0.307 4432 2795 S-30-1 99.97 × 49.79 502.67 30 2.583 84.04 0.272 31.34 0.287 4241 2608 S-30-1 99.79 × 49.83 503.78 30 2.590 90.32 0.344 30.83 0.292 4189 2633 S-45-1 99.96 × 49.80 503.84 45 2.589 122.79 0.501 27.23 0.345 3917 2557 S-45-1 100.02 × 49.89 502.44 45 2.570 119.32 0.532 28.67 0.266 4012 2561 S-60-1 100.03 × 49.84 503.36 60 2.580 131.93 0.608 26.22 0.253 3786 2412 S-60-1 99.98 × 49.67 503.37 60 2.599 129.33 0.642 25.72 0.261 3812 2430 S-75-1 100.22 × 49.93 504.12 75 2.570 135.72 0.674 25.04 0.363 3602 2284 S-75-1 99.96 × 49.87 504.23 75 2.583 140.22 0.702 24.98 0.345 3648 2272 S-90-1 99.63 × 49.95 502.91 90 2.577 146.66 0.867 23.12 0.385 3402 2241 S-90-1 99.96 × 50.01 504.21 90 2.569 155.01 0.812 22.22 0.392 3562 2196 Test ID L × d (mm) Mass (g) Inclination (°) Density (g cm−3) Peak stress (MPa) Peak strain (per cent) Static elastic modulus (GPa) Static Poisson's ratio (v) P-wave velocity (m s−1) S-wave velocity (m s−1) S-0-1 98.61 × 48.91 500.07 0 2.700 191.47 0.626 42.31 0.352 4680 3012 S-0-2 99.31 × 49.92 500.11 0 2.574 174.78 0.612 40.87 0.344 4785 3087 S-15-1 100.04 × 49.68 503.78 15 2.599 164.45 0.542 32.32 0.316 4333 2784 S-15-1 99.96 × 50.01 500.65 15 2.551 158.22 0.532 35.43 0.307 4432 2795 S-30-1 99.97 × 49.79 502.67 30 2.583 84.04 0.272 31.34 0.287 4241 2608 S-30-1 99.79 × 49.83 503.78 30 2.590 90.32 0.344 30.83 0.292 4189 2633 S-45-1 99.96 × 49.80 503.84 45 2.589 122.79 0.501 27.23 0.345 3917 2557 S-45-1 100.02 × 49.89 502.44 45 2.570 119.32 0.532 28.67 0.266 4012 2561 S-60-1 100.03 × 49.84 503.36 60 2.580 131.93 0.608 26.22 0.253 3786 2412 S-60-1 99.98 × 49.67 503.37 60 2.599 129.33 0.642 25.72 0.261 3812 2430 S-75-1 100.22 × 49.93 504.12 75 2.570 135.72 0.674 25.04 0.363 3602 2284 S-75-1 99.96 × 49.87 504.23 75 2.583 140.22 0.702 24.98 0.345 3648 2272 S-90-1 99.63 × 49.95 502.91 90 2.577 146.66 0.867 23.12 0.385 3402 2241 S-90-1 99.96 × 50.01 504.21 90 2.569 155.01 0.812 22.22 0.392 3562 2196 Open in new tab Table 1. Strength and stiffness versus inclination for all tested shale samples. Test ID L × d (mm) Mass (g) Inclination (°) Density (g cm−3) Peak stress (MPa) Peak strain (per cent) Static elastic modulus (GPa) Static Poisson's ratio (v) P-wave velocity (m s−1) S-wave velocity (m s−1) S-0-1 98.61 × 48.91 500.07 0 2.700 191.47 0.626 42.31 0.352 4680 3012 S-0-2 99.31 × 49.92 500.11 0 2.574 174.78 0.612 40.87 0.344 4785 3087 S-15-1 100.04 × 49.68 503.78 15 2.599 164.45 0.542 32.32 0.316 4333 2784 S-15-1 99.96 × 50.01 500.65 15 2.551 158.22 0.532 35.43 0.307 4432 2795 S-30-1 99.97 × 49.79 502.67 30 2.583 84.04 0.272 31.34 0.287 4241 2608 S-30-1 99.79 × 49.83 503.78 30 2.590 90.32 0.344 30.83 0.292 4189 2633 S-45-1 99.96 × 49.80 503.84 45 2.589 122.79 0.501 27.23 0.345 3917 2557 S-45-1 100.02 × 49.89 502.44 45 2.570 119.32 0.532 28.67 0.266 4012 2561 S-60-1 100.03 × 49.84 503.36 60 2.580 131.93 0.608 26.22 0.253 3786 2412 S-60-1 99.98 × 49.67 503.37 60 2.599 129.33 0.642 25.72 0.261 3812 2430 S-75-1 100.22 × 49.93 504.12 75 2.570 135.72 0.674 25.04 0.363 3602 2284 S-75-1 99.96 × 49.87 504.23 75 2.583 140.22 0.702 24.98 0.345 3648 2272 S-90-1 99.63 × 49.95 502.91 90 2.577 146.66 0.867 23.12 0.385 3402 2241 S-90-1 99.96 × 50.01 504.21 90 2.569 155.01 0.812 22.22 0.392 3562 2196 Test ID L × d (mm) Mass (g) Inclination (°) Density (g cm−3) Peak stress (MPa) Peak strain (per cent) Static elastic modulus (GPa) Static Poisson's ratio (v) P-wave velocity (m s−1) S-wave velocity (m s−1) S-0-1 98.61 × 48.91 500.07 0 2.700 191.47 0.626 42.31 0.352 4680 3012 S-0-2 99.31 × 49.92 500.11 0 2.574 174.78 0.612 40.87 0.344 4785 3087 S-15-1 100.04 × 49.68 503.78 15 2.599 164.45 0.542 32.32 0.316 4333 2784 S-15-1 99.96 × 50.01 500.65 15 2.551 158.22 0.532 35.43 0.307 4432 2795 S-30-1 99.97 × 49.79 502.67 30 2.583 84.04 0.272 31.34 0.287 4241 2608 S-30-1 99.79 × 49.83 503.78 30 2.590 90.32 0.344 30.83 0.292 4189 2633 S-45-1 99.96 × 49.80 503.84 45 2.589 122.79 0.501 27.23 0.345 3917 2557 S-45-1 100.02 × 49.89 502.44 45 2.570 119.32 0.532 28.67 0.266 4012 2561 S-60-1 100.03 × 49.84 503.36 60 2.580 131.93 0.608 26.22 0.253 3786 2412 S-60-1 99.98 × 49.67 503.37 60 2.599 129.33 0.642 25.72 0.261 3812 2430 S-75-1 100.22 × 49.93 504.12 75 2.570 135.72 0.674 25.04 0.363 3602 2284 S-75-1 99.96 × 49.87 504.23 75 2.583 140.22 0.702 24.98 0.345 3648 2272 S-90-1 99.63 × 49.95 502.91 90 2.577 146.66 0.867 23.12 0.385 3402 2241 S-90-1 99.96 × 50.01 504.21 90 2.569 155.01 0.812 22.22 0.392 3562 2196 Open in new tab The peak stress of samples ranges from 100 to 195 MPa, with higher stress value parallel to bedding face, whereas Young's modulus changes from 22.22 to 42.31 GPa, typically lower for bedding normal to the axial direction (Fig. 7c). The Poisson's ratio is calculated as the ratio of radial strain and axial strain in the linear elastic stage from the stress–strain curve, the axial and radial strains were measured using the LVDTs, and it was installed at the same position for all the tested sample. This value for samples with various inclinations is between 0.253 and 0.392. It can be seen that no obvious rule can be observed from the relationship between Poisson's ratio and inclination. This result may be attributed to the result of random decomposition of microfractures and pores among the bedding plane (Liu et al. 2002). The value of Poisson's ratio is a reflection of the lateral deformation, which affects the volumetric strain to some extent. The change of Poisson's ratio further shows that the bond strength of bedding is relatively weak, shale sample can be easily stimulated during hydraulic fracturing treatment. The lower value for UCS occurs when inclination angle is 30°; however, for elasticity modulus, the lower value corresponding to shale with an inclination bedding angel of 90° (Table 1). Before the UCS test, the P-wave velocity was measured. The classical ultrasonic pulse transmission technique is used to conduct velocity measurements between an emitting and a receiving transducer. It consists of measuring the traveltime of an ultrasonic pulse through the shale sample for a known propagation path. Velocity was calculated as the ratio of travel distance to traveltime. Interestingly, P-wave velocities of the studied Longmaxi shale in laboratory from the Shizhu County, clearly present anisotropy characteristic and correlate well with elasticity modulus (Fig. 7d). This result also suggests that the physical and mechanical properties of the Longmaxi shale are consistent, that is, the quasi-static and dynamic elasticity moduli are well correlated. 3.2 AE counts response During AE monitoring, we can obtain the waveform of every AE event, the parameters of AE counts and energy release can be calculated from the waveform. Fig. 8 shows the typical waveform for shale samples with different inclinations, the waveform corresponds to the last AE event for the tested sample. From the axial stress strain curve, four deformation stages can be devised (Martin & Chandler 1994; Nicksiar & Martin 2012): crack closure stage, elastic deformation stage, crack stable propagation stage and the crack unstable propagation stage, as shown in Fig. 9. The change of AE pattern is closely related to the mechanical properties of shale. Fig. 10 plots the AE rate–AE accumulation–Loading time curves. During the AE monitoring, two sensors were used to record the AE event; however, we use the mean value data from the two AE sensors to study the pattern of AE rate. During the compression process, AE counts together with the rapid release of elastic energy with the shale are used by the AE system to assess fracture evolution. The variation of AE rate and AE accumulation during compressive loading indirectly reflects the influence of the bedding orientation on failure modes, and the associated mechanical anisotropy. From Fig. 10, the main results can be drawn as below: The overall trend for the tested samples is similar. At the beginning of the loading, no significant AE counts were recorded, while the rock is in its crack closure stage, this stage is also called silent zone. At the linear elastic stage, AE counts were at a constant level. When the AE counts increase gradually with increasing axial stress, the shale sample reaches the stable crack propagation stage. This stage, no significant damage occurs and the macroscopic failure plane forms. When unstable crack propagation occurs, the AE count rate exhibits an exponential increase and finally the rock fails. Affected by the bedding plane in shale samples, the specific morphology of the curves in Fig. 10 is different. For samples with inclination of 0° and 15°, after the crack closure stage, the AE accumulation curves present a fluctuation growth trend with an arrow range until the failure of the samples. For samples with an inclination of 30°, 45° and 60°, after the crack closure stage, the shape of the AE accumulation kept relatively level until the crack initiation stage; of the stable crack propagation stage is short. For samples with an inclination of 75° and 90°, the curve morphology of the AE accumulation presents an obvious step skip shape compared to samples with other inclination. The shape differences of the curves (level, skip and fluctuation shapes) suggest that the damage failure mechanism of shale samples is different. The crack initiation and propagation are strongly influenced by the interactions between shale matrix and bedding plane. These results are closely related to the inclination angle of the bedding in shale samples. By comparing AE accumulation counts against inclination bedding, as shown in Fig. 11, it can be seen that AE accumulation count first decreases and then increases, with increasing bedding inclination. It reaches a minimum when the bedding inclination equals 30°. This result indicates that at this inclination, the failure pattern of the sample is quite simple. From Fig. 6(a), we can also see that the UCS at a bedding inclination of 30° is also the lowest. The maximum cumulative AE count emerges when the bedding orientation is 90° (i.e. vertical structural bedding sample), much more microfractures form than other cases. Their unstable propagation and coalescence result in the formation of macrocracks (this result can be validated from the CT images). The accumulative AE analysis is consistent with the peak strength of shale samples with different bedding inclinations. The characteristic of the AE count presents a directional dependency, which can indirectly reflect the anisotropic failure mode of shale. Therefore, the term anisotropic AE counts refer to different AE response of the shale sample with various bedding face inclination. Figure 8. Open in new tabDownload slide Typical waveform of the last AE events during sample deformation (a–g: the inclination of the shale sample is 0°, 15°, 30°, 45°, 60°, 75° and 90°, respectively). Figure 8. Open in new tabDownload slide Typical waveform of the last AE events during sample deformation (a–g: the inclination of the shale sample is 0°, 15°, 30°, 45°, 60°, 75° and 90°, respectively). Figure 9. Open in new tabDownload slide Method used to obtain the four characteristic stress from the completed stress strain curves. (a) Crack evolution process in the stress–strain diagram (modified after Martin, 1994); (b) obtaining the four characteristic stress for shale sample with 15° inclination. Figure 9. Open in new tabDownload slide Method used to obtain the four characteristic stress from the completed stress strain curves. (a) Crack evolution process in the stress–strain diagram (modified after Martin, 1994); (b) obtaining the four characteristic stress for shale sample with 15° inclination. Figure 10. Open in new tabDownload slide Representive plots of AE rate, AE accumunation against loading time. (a)–(g) correspond to the inlination of 0°, 15°, 30°, 45°, 60°, 75° and 90°, respectively. Figure 10. Open in new tabDownload slide Representive plots of AE rate, AE accumunation against loading time. (a)–(g) correspond to the inlination of 0°, 15°, 30°, 45°, 60°, 75° and 90°, respectively. Figure 11. Open in new tabDownload slide Plot of the comparison of the AE accumulation counts against inclination for shale samples with different inclination. Figure 11. Open in new tabDownload slide Plot of the comparison of the AE accumulation counts against inclination for shale samples with different inclination. 3.3 AE accumulated energy release response The relationships between the accumulated AE energy release (here it refers to a multiplication of the received amplitude by the timespan of the event, we use the mean data of the two sensors, the unit is mv·μs.), axial stress and axial strain of shale samples with different bedding inclination are presented in Fig. 12. The AE energy is generally defined as a measured area under the rectified signal envelope. The energy is preferred to interpret the magnitude of source event over counts because it is sensitive to the amplitude as well as the duration, and less dependent on the voltage threshold and operating frequencies (Grosse & Ohtsu 2008). It can be seen that at the initial loading stage, the energy release exists for all the samples. This phenomenon has been commonly observed for almost all materials; the shale material is no exception (He et al. 2010). The pre-existing naturally developed microcracks, voids and defects inside the shale sample before experiment will develop and connect with each other and lead to the formation of macrocracks. Under a lower stress level, in spite of the low AE energy release, it increases continuously and quickly until failure of the rock. However, the index of AE energy release shows surge increment in a very short period (for example, 10–40 s for the studied shale samples, during between points ‘b’ and ‘c’, as shown in Fig. 12), accompanied by the unstable crack propagation. Figure 12. Open in new tabDownload slide Typical plots of the relationship of axial stress, AE accumunlative energy release and axial strain. (a)–(g) correspond to the inlination of 0°, 15°, 30°, 45°, 60°, 75° and 90°, respectively. Figure 12. Open in new tabDownload slide Typical plots of the relationship of axial stress, AE accumunlative energy release and axial strain. (a)–(g) correspond to the inlination of 0°, 15°, 30°, 45°, 60°, 75° and 90°, respectively. According to the rock mechanics principle (Martin & Chandler 1994; Nicksiar & Martin 2012), generally, four typical stages of AE behaviour based on the accumulated release energy can be found for shale. (i) Little AE energy release. This stage is characterized by the closing of microcracks, friction on the loading platens, modifications or re-arrangements of the rock grains. The present experimental results combined with these observations reveal that during the first stage, AE event is relatively small, which implies a balance period for the shale sample after initial loading, although some microcavities and microcracks are weakly activated. (ii) Low AE energy release is recorded under compressive loading. Weak AE activity is associated with the stress distribution within the sample. In this stage, after the cracks are compacted, the energy release due to stress concentration of some gains would be balanced by gain slipping and deformation of crystal boundary. (iii) High AE energy release is recorded under the sudden formation of microcracks. The released energy by stable propagation of microcracks is monitored by the skip of the AE accumulative energy curve. (iv) A rapid associated with unstable crack propagation corresponds to the fourth stage. In this stage, due to the appearance of larger cracks generated by the abrupt change of sample shape, the growth and coalescence of the cracks causes the AE release to reach a maximum. In addition, shear within the sample leads to plastic deformation. The points labeled a, b, c and d in the curves in Fig. 9 refer to the crack closure stress, crack initiation stress, crack damage stress and peak stress (Martin & Chandler 1994; Nicksiar & Martin 2012). In addition, the morphology of the AE accumulation energy curves presents an obvious difference. For samples with inclination of 0° and 15°, the curves show an evident inflection point at the characteristics stress (e.g. close stress, initiation stress and crack damage stress); and the curve displays a weak fluctuation growth with increasing strain. For samples with inclination of 30° and 45°, the interval of the initiation stress point and crack damage stress point is very close, and the violent skip occurs at a crack damage point until failure of the sample occurs. For shale samples with an inclination of 60°, 75° and 90°, multistage skip phenomenon can be observed from the curves. Especially for the sample with an inclination of 75°, the skip range is larger than the other samples. This may be in close relation to the internal structure of the shale sample. The analysis of the relationship between accumulative AE energy release and the bedding inclination is shown in Fig. 13. Interestingly, the AE energy release first decreases and then increases with the increase of inclination, and the curve appears as a U shape. The change is in consistent with the variation of UCS (Fig. 7a), Young's modulus (Fig. 7b) and AE counts (Fig. 11) and for samples with an inclination of 30°, the AE energy release reaches a minimum. This result indicates that fewer microcracks form and coalesce to form a macroscopic failure plane. The anisotropy of the AE energy release is the result of the structural anisotropy and heterogeneity of shales. The difference of AE energy release reflects the different failure mode of shale samples. Figure 13. Open in new tabDownload slide Plot of the relationship between AE accumulative energy release and inclination for typical shale samples. Figure 13. Open in new tabDownload slide Plot of the relationship between AE accumulative energy release and inclination for typical shale samples. 3.4 Fracture pattern visualization analysis Fig. 14 shows the 2-D image reconstruction for all the shale samples with different bedding inclinations. These figures clearly show the fracture morphology and their spatial distribution. The CT images can help us interpret the failure characteristics of shale. For the 30° inclination sample, fracture occurs along the bedding plane, and the number of cracks is the least compared to the other cases. For the 90° inclination sample, the number of fractures can be observed, and the fracture density and scale in the sample are at a maximum. Therefore, combined with the AE analysis above, the AE counts and AE accumulative energy release for the 30° inclination sample is less than the other samples. For samples with a 90° inclination, due to the complex failure modes, multicracks cross the layered structured shale matrix and communication with the bedding planes, the fracture pattern is the most complicated. The crack density in the CT images first increases and then decreases with increasing bedding inclination, and this result is also consistent with the response observed by AE monitoring. Figure 14. Open in new tabDownload slide Fracture morphology visualized by CT imaging. Image 2-D reconstructions of shale samples with different inclination, CT scans at different positions, at 80, 65, 50, 35 and 20 mm, from the top of the samples. Figure 14. Open in new tabDownload slide Fracture morphology visualized by CT imaging. Image 2-D reconstructions of shale samples with different inclination, CT scans at different positions, at 80, 65, 50, 35 and 20 mm, from the top of the samples. Using digital imaging process method, taking the shale samples with 0°, 30°, 45° and 90° for example, the crack extraction results are shown in Fig. 15. From Fig. 15, the pattern of fracture after UCS test can be clearly observed; the scale of fracture varies with bedding orientation. We plot the relationship between fracture density and sample orientation, as shown in Fig. 16. It can be seen that the fracture density is at the maximum for the 90° orientation sample; however, it is the minimum for the 30° inclination sample, which is consistent with the AE count. The fracture density shows strong anisotropy, which is determined by the sample structure. Figure 15. Open in new tabDownload slide Crack morphology visualized by CT imaging. Image 2-D reconstructions of shale samples with different inclination, CT scans at different positions, at 80, 50 and 20 mm, from the top of the samples. Figure 15. Open in new tabDownload slide Crack morphology visualized by CT imaging. Image 2-D reconstructions of shale samples with different inclination, CT scans at different positions, at 80, 50 and 20 mm, from the top of the samples. Figure 16. Open in new tabDownload slide Plot of fracture density against bedding face orientation. Figure 16. Open in new tabDownload slide Plot of fracture density against bedding face orientation. 4 DISCUSSIONS Although some scholars have studied the strength anisotropy of shale through macroscopic compressive testing, the fracturing mechanism has not been discussed in detail. We have laboratory studied the anisotropic failure characteristics of the Longmaxi shale with different bedding inclinations through real-time AE monitoring tests and CT imaging. The anisotropic AE counts and AE accumulative energy are strongly affected by the bedding orientation. From the results, the relationships between the AE count and AE energy and bedding orientation present U-shaped, and this result is first demonstrated in this work. From the macrofailure morphology of the shale sample (Fig. 17), the failure morphology of samples with different inclinations can be obtained. When the inclination equals 0° and 15°, the failure mode is mainly the tension splitting along the bedding plane, and the properties of the bedding plane control the overall strength of the shale sample. When the inclination equals to 30°, it the shear sliding failure that controls the life of shale sample, in this case, the UCS is at a minimum. When the inclination equals to 45° and 60°, the shale matrix and bedding plane simultaneously control the failure mode; failure mode presents shear failure of crossing and along bedding. When the inclination equals to 75° and 90°, the failure mode of shale shows a combination of tension failure cross the matrix and shear sliding along the bedding plane. For those typical failure modes, the bedding plane plays an important role in controlling the overall strength of the shale sample. The source of the failure-mode anisotropy is the combined action of the layered sedimentary structure and bonding of the bedding planes. Meanwhile, the anisotropic AE response is the result of the differential failure mode. Different failure modes result in the different AE responses, which are well reflected by the variation in AE counts and AE energy release. The AE results show the failure anisotropic characteristics of shale, and it can be further observed from the failure morphology. Figure 17. Open in new tabDownload slide Failure morphology of shale samples after UCS test. Figure 17. Open in new tabDownload slide Failure morphology of shale samples after UCS test. As mentioned above, the anisotropy of the strength, elasticity modulus, AE counts and AE accumulative energy are strongly related to the structure of shale samples. The structural heterogeneity of the shale is attributed to the orientation distribution of minerals and organic matter, typically resulting in the formation of weak-bedding planes and a pronounced elastic transverse isotropy (Vernik & Liu 1997; Dewhurst & Siggins 2006; Gallant et al.2007), meaning that properties, for example strength properties and elastic constants, within the bedding are isotropic but vary across them (Chong Smith1984; Meier et al.2015). In anisotropic shales, bedding plane inclination has a significant effect on the crack distribution in the sample. Through CT imaging, we have visualized the fracture patterns, their density and width, etc. The fracture density is the maximum for the shale sample with a 90° orientation; however, it is the minimum for the sample with a 30° orientation. Fracture density in the samples after the UCS test reflects the fracability under mechanical force by an experimental apparatus. Fracture morphology description and CT images analysis indicate that rock fracability has a certain internal relationship to the sample structure. For the anisotropic shale studied in this work, the fracture density is the minimum for the sample with a 30° orientation. For the sample with a 90° orientation, a larger fracture density occurs, which is consistent with the results of AE counts and AE accumulative energy. The bedding plane is the weak plane in shale formations, the layered deposited structural and weak cementation between layers are the main factors controlling the anisotropy of mechanical properties, AE response and its failure mechanism. When conducting hydraulic fracturing treatment, the role of the bedding plane on hydraulic fracture propagation should be given much more attention. The interaction between natural fracture and the bedding plane should be given full consideration. 5 CONCLUSIONS Here, we study the failure characteristics of a Longmaxi formation shale through laboratory UCS test, AE monitoring and post-test CT image analysis. The characteristics of AE counts and AE energy release well reflect the fracturing information of shale samples under compressive loading. The differential shape of those associated curves indicates different failure modes of shale, owing to the existence of the bedding plane. CT image analysis also helps us observe the internal crack morphology and grasp the failure mechanism of anisotropic shale. The pronounced bedding planes of shale have significant influence on its mechanical behaviours. For hydraulic fracturing treatment, how to stimulate the bedding plane and communicate natural fractures, are crucial to improving the gas production. We noted that the intensity and energy of an acoustic event is the minimum at a bedding inclination of 30°, and in this case, shear sliding failure occurs in shale. This observation implies that when the intersection angle of the bedding plane and the maximum principle stress is 30°, slippage behaviours along bedding face results in the initial damage and failure of the sample. Presentation of the initial failure accelerates the formation of more and more severe breakouts either as tensile or shear failure. This result would be used as a reliable alarm of judging stability of drilling borehole. The plots of AE responses depend on the bedding inclination. This indicates differences in the fracturing evolution process between different structured shale. AE studies show the failure anisotropy from energy mechanism analysis. Using X-ray CT imaging, 2-D reconstructed images after sample failure reveal the crack geometry and pattern and the failure anisotropy. Using these two independent analyses methods, good agreement has been found between the observations which prove the reliability of the results and also confirm the demand to develop a corresponding failure constructive equation for shale. Acknowledgements The authors would like to thank the editors and the anonymous reviewers for their helpful and constructive comments. 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TI - Experimental investigation on the fracture behaviour of black shale by acoustic emission monitoring and CT image analysis during uniaxial compression
JF - Geophysical Journal International
DO - 10.1093/gji/ggy011
DA - 2018-04-01
UR - https://www.deepdyve.com/lp/oxford-university-press/experimental-investigation-on-the-fracture-behaviour-of-black-shale-by-a8ZcBWkLJW
SP - 660
VL - 213
IS - 1
DP - DeepDyve
ER -