钻孔雷达探测地下不良地质体的正演模拟及其复信号分析

Forward simulation and complex signal analysis of borehole radar detection for underground adverse geological bodies

在工程建设中经常会遇到诸如溶洞、裂隙带和断层破碎带等不良地质体,如果不能提前探明地下是否存在不良地质体及其含水情况,将会埋下严重的安全隐患。钻孔雷达是一种十分有效的探测方法,但迄今,尚未见有针对典型不良地质体进行正演模拟并进行复信号分析的工作。结合复信号分析技术,利用振幅、相位和频率等瞬时信息对钻孔雷达探测结果进行综合分析,能够提高解译的精度和准确性。针对溶洞、裂隙和断层等典型不良地质体无水和含水的情况分别建立了数值模型,利用地质雷达正演软件GprMax对数值模型进行了正演模拟,并使用复信号分析技术对正演结果进行了分析,获取了典型不良地质体的响应特征,且当不良地质体含水时,反射信号振幅增强、相位反转、频率降低。结合工程实例对钻孔雷达探测数据进行了复信号分析,正演模拟和工程实例都表明,利用复信号分析技术,可以更加方便地对地质异常体的形态分布及其含水情况进行分析,提高了钻孔雷达解译的精度和准确性。

Engineering construction usually encounters adverse geological phenomena such as karst caves, fractures and faults. Thus, it is extremely significant for maintaining security to ascertain the adverse geological bodies in particular the conditions containing water. Borehole radar is an effective detecting method, however the issues in terms of forward simulation and complex signal analysis of adverse geological bodies have not been well addressed. To improve the precision and accuracy of interpretation, the complex signal analysis technique which utilizes instant information including amplitude, phase and frequency is adopted to analyze detected results. A numerical model is developed for adverse geological bodies with water and without water, and then GprMax, a ground penetration radar forward simulation software, is applied to implement the forward simulation. Numerical results are further analyzed by a complex signal analysis technique to obtain the response characteristics of adverse geological bodies. In particular, adverse geological bodies containing water enhance the amplitude of reflected signal, reverse the phase, and reduce the frequency. Finally, detected results from a case study are analyzed by using the borehole radar with the complex signal analysis technique. Numerical and field detecting results demonstrate that the complex signal analysis technique has the advantage to analyzing the morphological distribution and the water situation in adverse geological bodies. In addition, it increases the precision and accuracy of the data interpretation.