水力压裂微地震信号提取与裂缝反演研究

发布时间：2018-05-31 11:48

本文选题：微地震监测 + 振幅相关　；参考：《长安大学》2015年硕士论文

【摘要】：水力压裂微地震技术通过观测、分析微小的地震事件,能够很好地确定裂缝位置以及发震时间,从而对压裂过程中裂缝的空间分布以及几何形态进行监测。本文针对微地震数据处理中信号的提取与裂缝反演两个方面展开研究。首先,在实际地震资料中人工拾取信噪比低,数据量比较大拾取起来耗时又费力,因此,研究微地震事件的自动拾取与识别是至关重要的。本文通过瞬时频率法、振幅相关法、相位相关法对信号进行拾取。(1)在瞬时频率法中引入雷克子波与宽带子波对其进行拾取并比较其拾取效果,对比不同信噪比状态下的计算效果。(2)通过振幅相关法对微地震数据进行静校正、叠加、Hilbert变换、包络等计算对有效事件进行识别,并利用该方法完成初至拾取。(3)在相位相关法研究中通过傅里叶变换与逆变换等计算完成指纹、Lena图像的相似性研究,并在不同噪声下对微地震信号进行相位相关处理,验证其抗噪性。对比分析三种方法最终选取相位相关法进行微地震信号拾取。另一方面,利用模拟退火法以及遗传算法在微地震震源定位中展开研究。得出了(1)模拟退火法与遗传算法在计算过程中避免了局部极值,从而得到最优解,(2)两种方法并不需要非常精准的初始参数从而减小了工作难度。对一般函数数据以及模型数据进行最优化反演。对比分析两种方法最终选取模拟退火法对实际数据对进行震源定位。通过理论研究以及模型实现,对比分析不同的信号提取方法及反演方法的适用性,为各方法在微地震定位以及其他地球物理勘探中的应用提供指导。
[Abstract]:Through observation and analysis of small seismic events, hydraulic fracturing microseismic technology can determine fracture location and earthquake occurrence time well, and monitor the spatial distribution and geometric shape of fractures during fracturing. In this paper, two aspects of signal extraction and fracture inversion in microseismic data processing are studied. First of all, the signal-to-noise ratio (SNR) of artificial pickup is low and the large amount of data is time-consuming and laborious in the actual seismic data. Therefore, it is very important to study the automatic pickup and recognition of micro-seismic events. In this paper, the instantaneous frequency method, amplitude correlation method and phase correlation method are used to pick up the signal. Comparing the results of calculation in different SNR states. (2) using amplitude correlation method for static correction of microseismic data, superposition Hilbert transform, envelope calculation to identify effective events. The method is used to complete the similarity study of fingerprint Lena images by using phase correlation method, such as Fourier transform and inverse transform, and phase correlation processing of microseismic signal under different noise. Its noise resistance is verified. Finally, the phase correlation method is selected to pick up the microseismic signal. On the other hand, simulated annealing method and genetic algorithm are used to study the microseismic focal location. It is concluded that the simulated annealing method and the genetic algorithm avoid the local extremum in the calculation process, thus the optimal solution is obtained. The two methods do not need very accurate initial parameters to reduce the difficulty of work. The optimization inversion of general function data and model data is carried out. Comparing and analyzing the two methods, the simulated annealing method is selected to locate the source of the actual data pair. Through theoretical research and model implementation, the applicability of different signal extraction methods and inversion methods are compared and analyzed, which provides guidance for the application of these methods in micro-seismic location and other geophysical exploration.
【学位授予单位】：长安大学
【学位级别】：硕士
【学位授予年份】：2015
【分类号】：P631.4

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