(1. 中南大学 地球科学与信息物理学院, 长沙 410083；
2. 中南大学 有色资源与地质灾害探查湖南省重点实验室, 长沙 410083)
摘 要: 利用模拟阻抗网络构建三维地电模型，方便快速正演计算。采用共轭梯度算法进行最小二乘反演迭代，迭代过程中不必完全计算灵敏度矩阵，大大节约了计算时间与存储空间，实现视电阻率监测数据的快速三维反演计算。在设计快速三维反演算法的基础上，利用模拟污染监测视电阻率数据对算法进行实验测试。测试结果表明：基于模拟阻抗网络模型的共轭梯度反演算法能有效实现对视电阻率数据的反演成像，算法收敛稳定，并且计算耗时少。进一步实验场地的实际监测数据反演测试还表明：该反演成像方法能有效反映追踪污染物质在地下介质中的扩散轨迹与具体影响范围，具有较好的实用性和时效性。
关键字: 三维反演；视电阻率；共轭梯度；污染监测
（1. School of Geosciences and Info-Physics, Central South University, Changsha 410083, China？
2. Hunan Key Laboratory of Non-ferrous Resources and Geological Hazard Detection, Central South University,
Changsha 410083, China）
Abstract:Based on impedances network analogy, 3D geo-electric model was built to perform numerical simulations more quickly. In the least square inversion, the conjugate gradient method was adopted to avoid calculating sensitivity matrix completely, which greatly decreases the time and memory space needed to do 3-D inversions. Then, it is practical to perform monitoring resistivity data inversion effectively to satisfy the requirements of engineering. Synthetic data was used to test the proposed inversion algorithm. The results show that the algorithm can perform resistivity data 3D inversion with fast convergence in short computation time. Further field data tests demonstrate that the fast 3D inversion can make good responses to the motion and range of underground contaminant plumes. And its exactness and effectiveness are very meaningful for interpreting field data in contaminant monitoring.
Key words: 3D inversion; apparent resistivity; conjugate gradient; contaminant monitoring
