Abstract
With high temporal resolution demand under noise contamination, the travel time estimation for the pulse-echo is noticed in the acoustic logging instrument design. To this end, an intelligent ultrasonic logging system is built to collect borehole information, and a framework with domain adaptation theory is proposed. The modified maximum mean discrepancy minimization combined with spatial pyramid pooling is constructed on different deep neural networks, where the transfer from the microseismic P-wave picking to the estimation of echo travel time is achieved. Versus the conventional travel time extraction algorithms, the proposed scheme improves the picking accuracy to 83.55% of the 10-dB signal-to-noise ratio. Experiments over the ultrasonic logging tool demonstrate the feasibility of the confusion domain, the effectiveness of travel time estimation, and the versatility of algorithm application.
Sign-in/Register to access full text options 
Talk to us
Join us for a 30 min session where you can share your feedback and ask us any queries you have
Schedule a callMore From: IEEE Transactions on Instrumentation and Measurement
Disclaimer: All third-party content on this website/platform is and will remain the property of their respective owners and is provided on "as is" basis without any warranties, express or implied. Use of third-party content does not indicate any affiliation, sponsorship with or endorsement by them. Any references to third-party content is to identify the corresponding services and shall be considered fair use under The CopyrightLaw.
