Microcrack Damage Observations near Coalesced Fractures Using Acoustic Emission

Hampton, Jesse; Gutierrez, Marte; Matzar, Luis

doi:10.1007/s00603-019-01818-4

Cited by 28 publications

(29 citation statements)

References 8 publications

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“…The test data of 5 single flaw tests, which are used for validating the modified and the serendipity methods, are available through previous publication: Wong and Xiong (2018). The test data for the hydraulic fracturing test has partially been available through previous publications: Hampton et al (2019), and Xiong and Hampton (2021), and an organized data set is available through Zenodo (Xiong & Hampton, 2022). The coding and code manual for the algorithms are on MATLAB platform and can be available through reasonable contact to the authors.…”

Section: Data Availability Statementmentioning

confidence: 99%

“…We apply the serendipity method to the data set of the hydraulic fracturing test (Hampton et al., 2019). To note, the delineation of any structure caused by hydraulic fracturing is in principle in 3D space, which introduces new challenges in the AE data analysis and interpretation.…”

Section: Application To a Hydraulic Fracturing Testmentioning

confidence: 99%

“…At the laboratory‐scale, strategies for improving the global source location accuracy often, unfortunately, would also inevitably involve the systematic discarding of low‐quality sources, to illustrate a few, Hampton et al. (2019); Xiong and Hampton (2021a); Zang et al. (1998).…”

Section: Introductionmentioning

confidence: 99%

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Semi‐Empirical Error Ellipsoid Clustering for Identifying the Second‐Order Structural Features From a Laboratory AE Source Location Cloud: Method, Validation, and Application to a Hydraulic Fracturing Test

Xiong

Hampton

2022

Earth and Space Science

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Point cloud of sources in the form of acoustic emission (AE) or seismicity at both field‐ and laboratory‐scales are indicative of causative structures. The error ellipsoid clustering (EC) method, whose underlying premise is reducing the amount of discarded data, is helpful for seeking the causative structure(s) from field‐scale seismic sources. However, a proper EC method does not exist for laboratory sources. Interpretation of laboratory AE sources usually involves systematic discarding of the assumed “low‐quality” data. We seek the successful transfer of the field‐scale EC method into the investigation of laboratory‐scale sources. For that, a new semi‐empirical EC method (serendipity method) is devised, and we have systematically modified the previous EC method (standard method) in (1) error ellipsoid formation, (2) iterative clustering algorithm, and (3) clustering stopping criterion. In the literature, the standard method and its limitations were validated using synthetic data. We validate the modifications by comparing its post‐clustering results with the original source locations and with the in‐situ and post‐mortem inspections of the laboratory rock fractures; and similarly for the serendipity method. We apply the serendipity method to a laboratory hydraulic fracturing test. The serendipity method implies the existence of a 3D damage zone as the second‐order feature caused by the hydraulic fracturing in addition to the primary hydraulic fracture. This complex damage zone provides a logical explanation to the previously observed reverse permeability‐distance relationship for hydraulic fracture.

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Section: Data Availability Statementmentioning

confidence: 99%

Section: Application To a Hydraulic Fracturing Testmentioning

confidence: 99%

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Semi‐Empirical Error Ellipsoid Clustering for Identifying the Second‐Order Structural Features From a Laboratory AE Source Location Cloud: Method, Validation, and Application to a Hydraulic Fracturing Test

Xiong

Hampton

2022

Earth and Space Science

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“…Reservoir permeability enhancement through injection-based hydraulic fracturing is widely studied for improved oil production and shale gas development as well as coal bed methane (CBM) and other unconventional oil and gas recovery [1][2][3][4]. Less attention is paid to natural fracture reactivation induced during oil and gas production processes and its implication on reservoir permeability, despite its relatively common occurrence [5] During production, an oil or gas reservoir shrinks (−ΔV) as the effective stresses increase.…”

Section: Introductionmentioning

confidence: 99%

Fracture Reactivation Modeling in a Depleted Reservoir

Cao¹,

Yin²,

Liang³

et al. 2021

Computer Modeling in Engineering &Amp; Sciences

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Injection-induced fracture reactivation during hydraulic fracturing processes in shale gas development as well as coal bed methane (CBM) and other unconventional oil and gas recovery is widely investigated because of potential permeability enhancement impacts. Less attention is paid to induced fracture reactivation during oil and gas production and its impacts on reservoir permeability, despite its relatively common occurrence. During production, a reservoir tends to shrink as effective stresses increase, and the deviatoric effective stresses also increase. These changes in the principal effective stresses may cause Coulomb fracture slip in existing natural fractures, depending on their strength, orientation, and initial stress conditions. In this work, an extended finite element model with contact constraints is used to investigate different fracture slip scenarios induced by general reservoir pressure depletion. The numerical experiments assess the effect of Young's modulus, the crack orientation, and the frictional coefficient of the crack surface on the distribution of stress and displacement after some reservoir depletion. Results show that the crack orientation significantly affects the state of stress and displacement, particularly in the vicinity of the crack. Slip can only occur in permitted directions, as determined by the magnitudes of the principal stresses and the frictional coefficient. Lastly, a larger frictional coefficient (i.e., a rougher natural fracture surface) makes the crack less prone to shear slip.

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“…e acoustic character can effectively reflect the developing and extending situation of the internal structure of rock masses. e acoustic wave detecting technology has already been widely applied in studying the damaging evolution law and the damaging extent evaluation in rock masses [33][34][35]. Based on this, aiming at the coal and rock masses in the working face 8512 in the Chenjiagou Coal Mine in China, this study used the acoustic character to reflect the generating and developing state of the internal fractures in coal and rock masses.…”

Section: Introductionmentioning

confidence: 99%

State Judgement Model of the Coal and Rock Medium and Its Engineering Application

Zhu

Wang

Han

2020

Advances in Civil Engineering

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In the loading and failure process of the coal and rock medium, with the increasing of the damaging and failure extent, the medium state gradually changed from the continuous, the quasicontinuous, and the discontinuous to the loose successively. To evaluate the damaging failure extent of the coal and rock mass and distinguish the state of the coal and rock mass medium, first, the medium state index was defined based on the acoustic wave propagation model. Then, based on the coal mass in the working face 8512 in the Chenjiagou Coal Mine in China, the acoustic character and the mechanical character experiments were conducted. Through experiments, the variation law of the ultrasonic wave velocity and the medium state index of the coal mass with the strain under the compressive state were acquired; with the increasing of the strain, the medium state indexes successively experienced the variation process including stabilising around 0, slow increasing, dramatic increasing, and stabilising around 1. Then, based on the variation law of the medium state index, the coal and rock mass medium state judgement model was constructed. This model was applied to judge the coal mass medium state. After it, the mudstones in the roof of the same working face were regarded as the research object, the mudstone medium state was divided into 4 types according to the medium state judgement model, namely, continuous, quasicontinuous, discontinuous, and bulk solid, and the mudstone failure state was basically consistent with the continuous, quasicontinuous, discontinuous, and bulk solid state. The adaptability and rationality of the judgement model was verified. Finally, engineering application of the judgement model was conducted. The distribution law of the top coal with different medium state was acquired. In the top coal that was 186 m away from the working face, it belonged to the continuous medium state. As for the top coal that was 6 m to 186 m far away from the working face, it was under the quasicontinuous medium state. For the top coal that was 3 m to 6 m far away from the working face, it was under the discontinuous medium state. For the top coal that was less than 3 m far away from the working face and behind the working face, it belonged to the bulk solid medium state. The state judgement model can successfully distinguish the medium state of the coal seam and mudstones in the roof in the working face 8512. This provided a new approach to evaluate the damaging failure extent of the coal and rock medium in the Chenjiagou Coal Mine.

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Microcrack Damage Observations near Coalesced Fractures Using Acoustic Emission

Cited by 28 publications

References 8 publications

Semi‐Empirical Error Ellipsoid Clustering for Identifying the Second‐Order Structural Features From a Laboratory AE Source Location Cloud: Method, Validation, and Application to a Hydraulic Fracturing Test

Semi‐Empirical Error Ellipsoid Clustering for Identifying the Second‐Order Structural Features From a Laboratory AE Source Location Cloud: Method, Validation, and Application to a Hydraulic Fracturing Test

Fracture Reactivation Modeling in a Depleted Reservoir

State Judgement Model of the Coal and Rock Medium and Its Engineering Application

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