Ortiz, Alvaro Andres2021-08-302021-08-3020102010https://hdl.handle.net/11244/330760Thesis (M.S.)--University of Oklahoma, 2010.Includes bibliographical references (leaves 160-163).Accurate automatic classification and picking of arrival times of events from acoustic emission (AE) signals is of considerable importance for rapid identification and location of seismic events. Due to the large number of digital signals that could be acquired during a simple experiment, manual classification and arrival picking become impractical and subjective. A system that detects and stores seismic signals generated during hydraulic fracturing (HF) experiments has been used in laboratory experiments to study the mechanism of HF. This system employs a combination of sensors, preamplifiers, signal conditioning unit and a data acquisition (DAQ) module attached to a personal computer (PC). The system captures the AE signals using a simple threshold value. External and internal noise due to the electronics, sensor coupling, reflections and echoes from the microseismic signals (MS) are captured too. In order to reduce the number of false AE signals, improve the processing time and obtain the most information from the HF processes, an automated solution has been developed to classify, pick the first arrival, and the polarization of AE signals that have been previously captured by the AE monitoring system.xxi, 163 leavesxxi, 163 leaves : ill. (some col.) ; 29 cm.engAcoustic emissionHydraulic fracturingSeismic wavesMicroseismsText