| LDR | | 02876nam u200433 4500 |
| 001 | | 000000421698 |
| 005 | | 20190215165529 |
| 008 | | 181129s2018 |||||||||||||||||c||eng d |
| 020 | |
▼a 9780438079656 |
| 035 | |
▼a (MiAaPQ)AAI10821775 |
| 035 | |
▼a (MiAaPQ)mines:11541 |
| 040 | |
▼a MiAaPQ
▼c MiAaPQ
▼d 247004 |
| 082 | 0 |
▼a 550 |
| 100 | 1 |
▼a Bray, Matthew P. |
| 245 | 10 |
▼a Velocity, Attenuation, and Microseismic Uncertainty Analysis of the Niobrara and Montney Reservoirs. |
| 260 | |
▼a [S.l.]:
▼b Colorado School of Mines.,
▼c 2018. |
| 260 | 1 |
▼a Ann Arbor:
▼b ProQuest Dissertations & Theses,
▼c 2018. |
| 300 | |
▼a 162 p. |
| 500 | |
▼a Source: Dissertation Abstracts International, Volume: 79-10(E), Section: B. |
| 500 | |
▼a Adviser: Thomas L. Davis. |
| 502 | 1 |
▼a Thesis (Ph.D.)--Colorado School of Mines, 2018. |
| 520 | |
▼a Time-lapse reservoir characterization with surface seismic provides greater spatial information about reservoir physical properties, and delineates reservoir scale changes. Identification of reservoir deformation due to hydraulic fracturing and |
| 520 | |
▼a In Wattenberg Field, the Reservoir Characterization Project (RCP) at the Colorado School of Mines (CSM) and Anadarko Petroleum Corporation (APC) collected time-lapse, multicomponent seismic data in order to characterize the reservoir fracture ch |
| 520 | |
▼a Time-lapse velocity and attenuation results are integrated with image logs, surface microseismic, tracer data, and production information to analyze how faults, joint sets, and well spacing, affect stimulation, early term production, and late te |
| 520 | |
▼a Borehole microseismic is a common tool used to evaluate hydraulic stimulation. A challenge in microseismic monitoring is quantification of survey acquisition and processing error, and how these errors jointly affect estimated locations. Quantify |
| 520 | |
▼a Processing steps are applied to a downhole microseismic dataset from Pouce Coupe, Alberta, Canada. A probabilistic location approach is implemented to identify the optimal bottom well location based upon known source locations. Probability densi |
| 520 | |
▼a The overall research illustrates that reservoir heterogeneity significantly affects hydraulic stimulation and production. Integration of multi-disciplinary data is vital for reservoir characterization in shale reservoirs. Additionally, this work |
| 590 | |
▼a School code: 0052. |
| 650 | 4 |
▼a Geophysics. |
| 690 | |
▼a 0373 |
| 710 | 20 |
▼a Colorado School of Mines.
▼b Geophysics. |
| 773 | 0 |
▼t Dissertation Abstracts International
▼g 79-10B(E). |
| 773 | |
▼t Dissertation Abstract International |
| 790 | |
▼a 0052 |
| 791 | |
▼a Ph.D. |
| 792 | |
▼a 2018 |
| 793 | |
▼a English |
| 856 | 40 |
▼u http://www.riss.kr/pdu/ddodLink.do?id=T14998411
▼n KERIS
▼z 이 자료의 원문은 한국교육학술정보원에서 제공합니다. |
| 980 | |
▼a 201812
▼f 2019 |
| 990 | |
▼a ***1012033 |