Identification and Analysis of Long-duration Low-frequency Events from Microseismic Data
| dc.contributor.advisor | Li, Aibing | |
| dc.contributor.committeeMember | Hall, Stuart A. | |
| dc.contributor.committeeMember | Zhang, Jie | |
| dc.creator | Hu, Hongru 1989- | |
| dc.date.accessioned | 2017-06-22T14:37:07Z | |
| dc.date.available | 2017-06-22T14:37:07Z | |
| dc.date.created | May 2015 | |
| dc.date.issued | 2015-05 | |
| dc.date.submitted | May 2015 | |
| dc.date.updated | 2017-06-22T14:37:08Z | |
| dc.description.abstract | Hydraulic fracturing is commonly used to enhance rock permeability in unconventional reservoirs. Locating microseismic events has become a standard tool in monitoring the fracturing process. However, the relation between microseismicity and crack networks has not been well understood. In addition, microseismic energy is almost negligible compared with the total energy used in fracturing. Long-duration and low-frequency (LDLF) seismic events, which are often observed in volcanic fields, have been reported from the data recorded during hydraulic fracturing. Although the origin of low-frequency events could be complicated, fluid pressurization through cracks, which is a common source for volcanic tremors, could be one main mechanism for LDLF events during hydraulic fracturing. Therefore, investigating the LDLF events from microseismic data would help to understand different types of ground deformation and help to characterize the formation of fracture network. In this research, I have identified several LDLF events using frequency-time plots from a microseismic dataset acquired by surface receivers in the Eagle Ford Shale in Mexico. Seismograms are filtered and their envelopes are calculated. Arrivals from each energy pack are picked from the envelopes using a cross-correlation method. These arrivals are then used to locate the event through a grid-search approach. The LDLF events can be categorized in two types. Type 1 events are located at around 1500 m in depth, close to the horizontal well. The associated phase arrivals show typical P-wave moveout trends. In addition, these events tend to migrate away from the treatment well with time. Type 1 events are probably caused by fluid pressurization in fractures. Type 2 events are located near the surface and the waves travel at a Rayleigh wave speed. The source mechanism of type 2 events is not clear, but could be related to vibrations of the operation equipment. | |
| dc.description.department | Earth and Atmospheric Sciences, Department of | |
| dc.format.digitalOrigin | born digital | |
| dc.format.mimetype | application/pdf | |
| dc.identifier.uri | http://hdl.handle.net/10657/1806 | |
| dc.language.iso | eng | |
| dc.rights | The author of this work is the copyright owner. UH Libraries and the Texas Digital Library have their permission to store and provide access to this work. Further transmission, reproduction, or presentation of this work is prohibited except with permission of the author(s). | |
| dc.subject | Low-frequency | |
| dc.subject | Microseismic | |
| dc.title | Identification and Analysis of Long-duration Low-frequency Events from Microseismic Data | |
| dc.type.dcmi | text | |
| dc.type.genre | Thesis | |
| thesis.degree.college | College of Natural Sciences and Mathematics | |
| thesis.degree.department | Earth and Atmospheric Sciences, Department of | |
| thesis.degree.discipline | Geophysics | |
| thesis.degree.grantor | University of Houston | |
| thesis.degree.level | Masters | |
| thesis.degree.name | Master of Science |