A Signal Processing Approach for Fracture Inversion Technique Utilizing Acoustic Emission Signal in Shale Hydraulic Fracturing Experiment

In order to detect the fracture information inside the material, solve the problem of static flaw detection and dynamic monitoring of the material, this paper studies the processing method of acoustic emission signal based on the active excitation signal of shale surface and the data output from hydraulic fracturing test. Event detection is the preliminary signal processing, to obtain the event information conveyed by acoustic emission signal and capture the information of shale internal materials carried in signal transmission. Sound source location is calculated by dividing the unit and fitting the signal source position. Both spectrum analysis and tomography are used to locate static natural fractures. Through the analysis of signal data, the positioning situation of different methods is compared. Based on experimental data from laboratory shale hydraulic fracturing, this study uses Julia language to construct a processing model for acoustic emission signals. Through the research context of this paper, we hope to provide reference for Julia language in the field of acoustic emission signal processing.