Review on Resistivity Inversion of Underground Abnormal Bodies

: With the development of petroleum in China, most oilfields have entered the stage of high water cut development. Well ground resistivity method as a new type of electric prospecting method, which have influence on the formation of small, measuring low cost advantages, gradually become one of the key technology of remaining oil distribution in the detection of resistivity inversion is through observation of the underground space apparent resistivity data reconstruction of the underground resistivity distribution, can realize the resistivity imaging of the underground space. In order to achieve the morphological characterization and spatial location of the abnormal area of underground resistivity, and then to carry out geological interpretation, the definition and properties of resistivity inversion are summarized, and the bottleneck problems encountered in practical engineering application are re-recognized and analyzed. On this basis, the theoretical method, numerical method and inversion method based on machine learning are introduced to solve the inverse resistivity problem of underground abnormal body. The inversion method based on deep learning is emphatically introduced, and its advantages and disadvantages and applicability are evaluated. It is pointed out that inversion is an ideal tool for data analysis. Then, it is pointed out that the development direction of resistivity inversion of underground abnormal body is to propose an optimized inversion network architecture based on deep learning.