页岩层理结构对超声波特性响应分析及应用

Response analysis of shale bedding structure to ultrasonic characteristics and its application

基于波动理论,建立渝东南地区下志留统龙马溪组页岩的不同层理结构模型,利用时间二阶、空间四阶的交错网格有限差分法,实现页岩不同层理结构对超声波特性响应的数值模拟计算,利用灰色系统理论筛选层理结构的声学参数敏感因子建立针对层理发育页岩的动态力学参数模型,利用ZY1、YY1井下岩心超声波透射实验结果与ZY2井测井资料对模型进行了验证。结果表明:(1)模拟波形与实验波形相关系数大于80%,数值模拟方法可有效模拟超声波透射实验;(2)声学参数中声波速度是表征页岩层理结构的常规敏感因子,而衰减系数对层理厚度的变化较为敏感,关联系数可达0.89,因此利用衰减系数的归一化结果来综合描述页岩层理可使结果更加准确;(3)模型计算得到的动、静力学参数相关性优于传统模型,利用模型和测井资料反演而获取的岩石力学剖面预测值与实验值吻合较好。研究结果为进一步利用声波测井资料准确预测岩石力学参数奠定基础。

Based on the wave theory,different bedding structure models for shales in Lower Silurian Longmaxi Formation of southeastern Chongqing area were established,numerical simulations of responses of different bedding structures of shale to ultrasonic wave were carried out by using the second order in time and fourth order in space grid finite difference method,based on the grey system theory,sensitive factors of acoustic parameters of bedding structure were selected,and the dynamic mechanical parameter model of bedded shale was established,which was verified by the ultrasonic transmission experiment results on core down Well ZY1 and YY1 and the logging data of Well ZY2.The results show that:(1)The correlation coefficient between analog and experimental waveforms is greater than 80%,indicating that the numerical simulation method can effectively simulate ultrasonic transmission experiment.(2)Acoustic velocity is a conventional sensitive factor used to characterize shale bedding structure,whereas the attenuation coefficient is sensitive to the change of bedding thickness,with correlation coefficient of 0.89,therefore,using the normalized results of attenuation coefficient to comprehensively describe the shale bedding can make the results more accurate.(3)The correlation between the dynamic and static parameters calculated by the model is better than that of the traditional model;and the predicted values of rock mechanics obtained by using the model and logging data inversion are in good agreement with the experimental values.The research results lay the foundation for further accurate prediction of rock mechanic parameters using sonic logging data.