首页|Accurate determination of the first arrival time of elastic wave traveled through rock sample by machine learning
Accurate determination of the first arrival time of elastic wave traveled through rock sample by machine learning
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NSTL
Elsevier
To automate time-consuming and experience-based analysis of elastic wave velocities in rock samples, we propose a method of determining the arrival time of experimental waveform data using machine learning. Our model is one-dimensional semantic segmentation based on U-net utilizing ResNet and attention mechanisms. The results demonstrate high accuracy of travel time estimation (0.0125 mu s) of two types of waves (P- and S-waves). Our approach can estimate the travel time in any experimental device. This method reduces the interpretation time and human biases in analyzing laboratory data of elastic waves. Therefore, this approach contributes to the efficient evaluation of subsurface structure from seismic properties.
First arrival timeElastic waveRock sampleMachine learningSemantic segmentationAttentionDRYVELOCITIES
NSTL
Elsevier
