Three-Dimensional Ultrasonic Imaging and Acoustic Emission Monitoring of Hydraulic Fractures in Tight Sandstone

Zhu, Wei; Wang, Shangxu; Chang, Xu; Zhai, Hongchen; Wu, He-Zhen

doi:10.3390/app11199352

Cited by 6 publications

(2 citation statements)

References 55 publications

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“…Similarly, active acoustic characterization such as the pulse-echo and pulse-transmission techniques has allowed us to quantify rock properties and detect inhomogeneities (Lockner et al, 1977;Pyrak-Nolte et al, 1990;Espinoza and Santamarina, 2011;Knuth et al, 2013;Modiriasari et al, 2017;Geremia and David, 2021). Laboratory-scale velocity tomography, although quite challenging, has provided a precious opportunity to observe deformation over time (Falls et al, 1992;Brantut, 2018;Aben et al, 2019;Zhu et al, 2021). These findings have enhanced the interpretation of seismic data from the field (Meadows and Winterstein, 1994;Verdon and Wüstefeld, 2013;Cai et al, 2014).…”

Section: Introductionmentioning

confidence: 99%

Integrating laboratory acoustic measurements, deep neural networks, and micro-CT imaging for characterizing rock brittle deformation

2023

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Brittle deformation is prevalent in both geological processes and engineered structures, so probing its actions is an important task as much for Earth materials and engineered ones. To characterize brittle deformation, acoustic waves are especially useful in revealing deformation processes. To promote the use of acoustic techniques, we present an integrated characterization approach that includes both acoustic data collection and analysis. By customizing a rock sample and acoustic sensor assembly, we incorporate acoustic data acquisition into a core holder system that accommodates relatively small samples (2.54 cm diameter) under triaxial loading. Along with fast and high-resolution acoustic waveform recording, the compact design facilitates convenient collection of high-quality acoustic data. To meet the challenge of efficiently and accurately picking P-wave arrivals for hundreds of thousands of acoustic waveforms, we modified and implemented a deep neural network model from the seismology literature called PhaseNet. After training with an augmented dataset of manually-picked arrivals (a total of around 50,000 waveforms), the modified PhaseNet model achieved more than 88% (96%) picking accuracy within ±1 μs (±2 μs) time residual relative to manual picks. This demonstrates the potential of integrating deep learning techniques into the workflow of acoustic data analysis for rapid and accurate extraction of valuable information from a large acoustic dataset. Finally, we conducted high-resolution micro-computed tomography (micro-CT) to inform and complement acoustic characterization at micron- and centimeter-scales. Microscopic observations validate the spatial development of two macroscopic fractures, and suggest that deformation-induced changes in velocity need to be incorporated for accurately locating microcracking events. Thus, integrating acoustic monitoring, a deep neural network, and micro-CT imaging offers an effective means to understand brittle deformation from micro to centimeter scales.

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Section: Introductionmentioning

confidence: 99%

Integrating laboratory acoustic measurements, deep neural networks, and micro-CT imaging for characterizing rock brittle deformation

2023

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“…Fracture detection and characterization are very important in the context of oil/gas exploration and production [3,4]. As a result, analyses of fracture physical characteristics (scale, aperture, orientation) and their influences on seismic propagation have attracted considerable interest in academia and industry [5][6][7].…”

Section: Introductionmentioning

confidence: 99%

Experimental Validation and Calibration of the Galvin Model with Artificial Tight Sandstones with Controlled Fractures

Zhang

2023

Applied Sciences

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The study of fractures in the subsurface is very important in unconventional reservoirs since they are the main conduits for hydrocarbon flow. For this reason, a variety of equivalent medium theories have been proposed for the estimation of fracture and fluid properties within reservoir rocks. Recently, the Galvin model has been put forward to model the frequency-dependent elastic moduli in fractured porous rocks and has been widely used to research seismic wave propagation in fractured rocks. We experimentally investigated the feasibility of applying the Galvin model in fractured tight stones. For this proposal, three artificial fractured tight sandstone samples with the same background porosity (11.7% ± 1.2%) but different fracture densities of 0.00, 0.0312, and 0.0624 were manufactured. The fracture thickness was 0.06 mm and the fracture diameter was 3 mm in all the fractured samples. Ultrasonic P- and S-wave velocities were measured at 0.5 MHz in a laboratory setting in dry and water-saturated conditions in directions at 0°, 45°, and 90° to the fracture normal. The results were compared with theoretical predictions of the Galvin model. The comparison showed that model predictions significantly underestimated P- and S- wave velocities as well as P-wave anisotropy in water-saturated conditions, but overestimated P-wave anisotropy in dry conditions. By analyzing the differences between the measured results and theoretical predictions, we modified the Galvin model by adding the squirt flow mechanism to it and used the Thomsen model to obtain the elastic moduli in high- and low-frequency limits. The modified model predictions showed good fits with the measured results. To the best of our knowledge, this is the first study to validate and calibrate the frequency-dependent equivalent medium theories in tight fractured rocks experimentally.

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Tomography with sparseness regularisation for ultrasonic velocity imaging

Zhu

Wang

Chang

et al. 2022

Journal of Geophysics and Engineering

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Ultrasonic tomography, which is widely used in the study of the fracturing process of rocks, often exhibits low resolution due to insufficient ray coverage, particularly while evaluating the three-dimensional (3D) fractures. To resolve this issue, we adopted sparseness regularisation in tomography to reconstruct the ultrasonic velocity of rocks. Both numerical and laboratory experiments demonstrate that tomography with sparseness regularisation generates velocity images with clear fracture morphology than that with Tikhonov regularisation. Dynamic monitoring of the fracturing process of a granite slab with two-dimensional (2D) velocity images can reveal the accurate development of the fracturing process. The experiment on the internal structure of tight sandstone after hydraulic fracturing reveals demarcated low-velocity regions in the 3D ultrasonic velocity images of tomography with sparseness regularisation. These low-velocity regions correspond to the positions of the fractures when compared to the X-ray scanning images. Thus, tomography with sparseness regularisation can improve the resolution of ultrasonic velocity images, which can be used to accurately describe the fracture development and strain localisation during rock deformation.

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Three-Dimensional Ultrasonic Imaging and Acoustic Emission Monitoring of Hydraulic Fractures in Tight Sandstone

Cited by 6 publications

References 55 publications

Integrating laboratory acoustic measurements, deep neural networks, and micro-CT imaging for characterizing rock brittle deformation

Integrating laboratory acoustic measurements, deep neural networks, and micro-CT imaging for characterizing rock brittle deformation

Experimental Validation and Calibration of the Galvin Model with Artificial Tight Sandstones with Controlled Fractures

Tomography with sparseness regularisation for ultrasonic velocity imaging

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