人工高导电体存在条件下的电阻率反演研究

因为技术成熟度高、成本较低等优势，电阻率法被广泛应用于各种勘查任务中。而由于城市、工业等环境中人工高导电体的存在，电阻率法的勘探效果受到很大影响。因此研究高导电体存在时电法数据的特征，开发高效的三维正反演算法以实现高导电体存在条件下的电阻率反演具有重要意义。钢筋混凝土地板是最常见的人工高导电体之一，混凝土层中内嵌的钢筋网会严重扰乱地下电流分布，使得电阻率法无法探测地下目标。通过对含钢筋混凝土地板的合成模型进行正演模拟，本文发现，钢筋网的存在使得电势差数据与视电阻率数据中出现了明显的异常。由于忽略钢筋混凝土地板的常规反演方法无法得到合理的结果，本文提出热启动反演法与地面-地下联合电极阵列这两种策略来改善反演结果。在热启动反演法中，首先找到能等效替代钢筋混凝土效应的分层模型；然后将该模型作为反演的初始模型和参考模型。该方法能有效恢复钢筋网与其他地质体之间的突变界面。 此外，本文改进了电极布设方式，成功提高了目标深度处的分辨率。本文使用这两种策略对某场地内被钢筋网干扰的实测数据集进行了反演。实测数据的反演结果验证了本文所提出策略的有效性。 为了实现对高导电体的高效建模，以及高导电体存在条件下的电阻率三维反 演，本文以三维高效多尺度等效电阻网络正演算法为基础，编写了高斯牛顿反演程序，实现了对体电导率、面电导率和线电导率这三种分别定义在体单元、面单元和棱单元上的电导率参数的反演成像。本文以实际监测场景为原型设计了三个数值模拟实验：在煤田采空区注浆监测中，使用线电导率对大量钢套管进行建模，实现了对体电导率的反演。本文发现正确模拟钢套管效应对于提升电法勘探深度的重要作用，相比于常规地面电法，长电极电法对深部地下电阻率的变化更加敏感。 在页岩气水力压裂压裂液监测中，本文使用线电导率模拟钢套管，同时使用面电导率模型来反演压裂液的分布。在钢筋腐蚀程度监测中，本文反演地面电法数据， 得到以线电导率表征的钢筋腐蚀程度。通过这三个数值实验，证明了本文算法能够对不同维度的高导电体进行高效模拟，并验证了对体电导率、面电导率和线电导率这三种电导率参数反演的有效性。

Due to the advantages of high technical maturity and low cost, electrical resistivity tomography (ERT) is widely used in various exploration tasks. However, because of the existence of artificial high-conductivity metallic infrastructures in urban and industrial environments, the exploration performance of ERT is greatly affected. So, it is of great significance to study the characteristics of the ERT dataset when metallic infrastructures exist and develop an efficient 3D forward and inversion algorithm. Reinforced concrete floors are one of the most common high-conductivity metallic infrastructures. The wire mesh embedded in the concrete layer will severely disturb the current distribution, making the ERT unable to detect subsurface targets. Through the forward simulation of the synthetic model with reinforced concrete floor, it is found that the existence of wire mesh makes the potential difference data and apparent resistivity data to exhibit obvious anomalies. The conventional inversion method that ignores the reinforced concrete floor cannot obtain reasonable results. In this paper, two strategies, the warm-start inversion method and the surface-underground combined electrode array, are proposed to improve the inversion results. In the warm-start inversion method, a layered model which can reproduce the effect of the reinforced concrete floor is found. Then this model is used as the initial and reference model for inversion. This method can restore the abrupt interface between the wire mesh and other geological bodies. In addition, the electrode arrangement is changed to improve the resolution at the target depth. This paper uses these two strategies to invert the observed data disturbed by the wire mesh. The inversion results demonstrate the effectiveness of our strategies. In order to develop the efficient and fast simulation of artificial high-conductivity metallic infrastructures and the 3D ERT inversion in the presence of high-conductivity structures, this paper writes the RESNet Gauss-Newton inversion program based on the 3D efficient multi-scale RESNet forward simulation algorithm, which can recover three different conductivity parameters: cellCon defined in cells, faceCon defined on faces, and edgeCon defined on edges. This paper designs three numerical experiments based on the actual monitoring scene. In the imaging of grouting monitoring in the mined-out area of the coalfield, this paper uses edgeCon to simulate a large number of steel casings and invert surface electrical data for cellCon. This paper found that the steel casing plays a vital role in improving the depth of electrical investigation. Compared with the conventional surface ERT method, the LEERT method is more sensitive to the change of subsurface resistivity. In the imaging of fracturing fluid monitoring in shale gas hydraulic fracturing, the LEERT can effectively image the fracturing fluid simulated by faceCon. In the imaging of monitoring steel corrosion in concrete structures, this paper proposes using surface ERT to monitor rebar corrosion. The inversion imaging accurately recovers the corroded areas in the rebar. These three synthetic model experiments prove that the inversion program can efficiently image high-conductivity infrastructures of different dimensions. Furthermore, the accuracy of the inversion of the three conductivity parameters is verified.

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