Edge Detection of Fracturing Crack Morphology Image in Deep Shale Gas Horizontal Well Based on Dyadic Wavelet Enhancement
Aiming at the problem of low FOM(quality factor)in detection results caused by noise influence in the detection of fracturing crack morphology images.A deep shale gas horizontal well fracturing crack morphology image edge detection method based on dyadic wavelet enhancement is proposed.Convert the crack morphology image to be detected to a grayscale image and combine it with the Hough transform principle to calculate the edge direction of the crack morphology image.Using adaptive threshold method to segment the foreground area of the image,combined with Sobel operator,to extract the initial edge of the image target.Using the dyadic wavelet decomposition algorithm,fuzzy nonlinear denoising is applied to annotate the initial target edge of the image.The maximum value point of the dyadic wavelet transform modulus is calculated to locate the edge pixel points,and the image edge detection result is obtained.The experimental results show that under the condition of no noise interference,the FOM value of the proposed method's detection results is above 0.9.When the interference noise value reaches 40 dB,the FOM value of this method's detection results still remains above 0.7,indicating that this method effectively solves the problem of low FOM in detection results and has good detection performance.