Prediction of Subsurface Crack Propagation by the Acoustic Emission Moment Tensor Analysis

研究了矩张量分析在声发射中的应用，建立了裂纹扩展预测技术。采用基于P波振幅的矩量反演方法确定了6个独立的张量分量。开发了用于声发射反演分析的计算机代码SiGMA（简化格林矩张量分析函数）。为了从矩张量分量中划分裂纹类型和确定裂纹方向，提出了一种统一的特征值分解方法。分解的目的是确定声发射源中剪切和拉伸贡献的比例，并将裂缝分类为主导运动的裂缝类型。对现场水力压裂试验中探测到的声发射波形进行了SiGMA反演和统一分解。分析了水力压裂试验中部署的8个加速度计探测到的声发射波形。所确定的裂缝类型和方向与井眼电视观测预测的破坏面基本一致。结果表明：弱缝处先产生拉伸裂纹，张开缝处再产生剪切裂纹；对SiGMA方法进行了改进以解决二维问题，并将其应用于具有内狭缝的二维模型的实验。研究了单轴压缩下裂隙的混合模式裂纹扩展，并利用四通道声发射系统记录了声发射波形。基于矩张量分析，从声发射波形中确定裂纹位置、裂纹类型和裂纹方向。结果与模型中观察到的裂纹轨迹进行了比较。结果表明，σ分析方法可用于预测地下材料的破坏过程。

An application of a moment tensor analysis to acoustic emission (AE) is studied to develop a prediction technique of crack propagation. A moment tensor inversion based on P wave amplitude is employed to determine six independent tensor components. A computer code named SiGMA (simplified Green's functions for the moment tensor analysis) is developed for the AE inversion analysis. To classify crack type and to determine crack orientation from moment tensor components, a unified decomposition of eigenvalues is proposed. The aim of the decomposition is to determine the proportion of shear and tensile contribution on AE sources, and to classify cracks into a crack type of the dominant motion. The SiGMA inversion and the unified decomposition are applied to AE waveforms detected during an in-situ hydrofracturing test. AE waveforms detected by eight accelerometers deployed during the hydrofracturing test are analyzed. Crack types and orientations determined are in reasonable agreement with a predicted failure plane from bore-hole TV observation. The results suggest that tensile cracks are generated first at weak seams, and then shear cracks follow on the opened joints.The SiGMA procedure is modified to solve the 2-D problem and is applied to experiments of a 2-D model with an internal slit. Mixed-mode crack propagation from the slit under uniaxial-compression is investigated and AE waveforms are recorded by a four-channel AE system. Crack locations, crack types, and crack orientations are determined from AE waveforms, based on the moment tensor analysis. The results are compared with crack trajectory observed in the model. The results confirm that the SiGMA analysis is applicable to predicting failure process of subsurface materials.