Eddy current detection of position and defect type of casing deformation section of oil and gas well

A eddy current detection method for position and defect type of casing deformation section of oil and gas well is proposed. According to the eddy current signals outputted by electromagnetic flaw detection imaging tool, the peak and features of signal are calculated, and an adaptive threshold is adopted to judge the deformation section. Differencial method is applied to process each deformation section. Successive groups of data are fusioned into multi-layer data. All data are dimensionally reduced by Fisher algorithm, and the dimensionally reduced multidimensional data are selected as the eigenvalue. The neural network algorithm is used for sample training and test data recognition. The experimental results show that the algorithm can identify the location of different deformation sections and the defect types in the deformation sections. The algorithm has certain practical value for applications.