Bayesian inversion of pressure diffusivity from microseismicity
We have considered the problem of using microseismic data to characterize the flow of injected fluid during hydraulic fracturing. We have developed a simple probabilistic physical model that directly ties the fluid pressure in the subsurface during the injection to observations of induced microseism...
| Main Authors: | , , , , |
|---|---|
| Andre forfattere: | |
| Format: | Article |
| Sprog: | en_US |
| Udgivet: |
Society of Exploration Geophysicists
2015
|
| Online adgang: | http://hdl.handle.net/1721.1/98499 https://orcid.org/0000-0002-8814-5495 |
| _version_ | 1826196675040903168 |
|---|---|
| author | Poliannikov, Oleg V. Prange, Michael Djikpesse, Hugues Malcolm, Alison E. Fehler, Michael |
| author2 | Massachusetts Institute of Technology. Department of Earth, Atmospheric, and Planetary Sciences |
| author_facet | Massachusetts Institute of Technology. Department of Earth, Atmospheric, and Planetary Sciences Poliannikov, Oleg V. Prange, Michael Djikpesse, Hugues Malcolm, Alison E. Fehler, Michael |
| author_sort | Poliannikov, Oleg V. |
| collection | MIT |
| description | We have considered the problem of using microseismic data to characterize the flow of injected fluid during hydraulic fracturing. We have developed a simple probabilistic physical model that directly ties the fluid pressure in the subsurface during the injection to observations of induced microseismicity. This tractable model includes key physical parameters that affect fluid pressure, rock failure, and seismic wave propagation. It is also amenable to a rigorous uncertainty quantification analysis of the forward model and the inversion. We have used this probabilistic rock failure model to invert for fluid pressure during injection from synthetically generated microseismicity and to quantify the uncertainty of this inversion. The results of our analysis can be used to assess the effectiveness of microseismic monitoring in a given experiment and even to suggest ways to improve the quality and value of monitoring. |
| first_indexed | 2024-09-23T10:34:11Z |
| format | Article |
| id | mit-1721.1/98499 |
| institution | Massachusetts Institute of Technology |
| language | en_US |
| last_indexed | 2024-09-23T10:34:11Z |
| publishDate | 2015 |
| publisher | Society of Exploration Geophysicists |
| record_format | dspace |
| spelling | mit-1721.1/984992022-09-30T21:40:00Z Bayesian inversion of pressure diffusivity from microseismicity Poliannikov, Oleg V. Prange, Michael Djikpesse, Hugues Malcolm, Alison E. Fehler, Michael Massachusetts Institute of Technology. Department of Earth, Atmospheric, and Planetary Sciences Massachusetts Institute of Technology. Earth Resources Laboratory Poliannikov, Oleg V. Malcolm, Alison E. Fehler, Michael We have considered the problem of using microseismic data to characterize the flow of injected fluid during hydraulic fracturing. We have developed a simple probabilistic physical model that directly ties the fluid pressure in the subsurface during the injection to observations of induced microseismicity. This tractable model includes key physical parameters that affect fluid pressure, rock failure, and seismic wave propagation. It is also amenable to a rigorous uncertainty quantification analysis of the forward model and the inversion. We have used this probabilistic rock failure model to invert for fluid pressure during injection from synthetically generated microseismicity and to quantify the uncertainty of this inversion. The results of our analysis can be used to assess the effectiveness of microseismic monitoring in a given experiment and even to suggest ways to improve the quality and value of monitoring. National Science Foundation (U.S.). Division of Mathematical Sciences (Grant 1115406) 2015-09-15T15:05:15Z 2015-09-15T15:05:15Z 2015-06 2015-01 Article http://purl.org/eprint/type/JournalArticle 0016-8033 1942-2156 http://hdl.handle.net/1721.1/98499 Poliannikov, Oleg V., Michael Prange, Hugues Djikpesse, Alison E. Malcolm, and Michael Fehler. “Bayesian Inversion of Pressure Diffusivity from Microseismicity.” Geophysics 80, no. 4 (June 22, 2015): M43–M52. © 2015 Society of Exploration Geophysicists https://orcid.org/0000-0002-8814-5495 en_US http://dx.doi.org/10.1190/GEO2014-0374.1 Geophysics Article is made available in accordance with the publisher's policy and may be subject to US copyright law. Please refer to the publisher's site for terms of use. application/pdf Society of Exploration Geophysicists Society of Exploration Geophysicists |
| spellingShingle | Poliannikov, Oleg V. Prange, Michael Djikpesse, Hugues Malcolm, Alison E. Fehler, Michael Bayesian inversion of pressure diffusivity from microseismicity |
| title | Bayesian inversion of pressure diffusivity from microseismicity |
| title_full | Bayesian inversion of pressure diffusivity from microseismicity |
| title_fullStr | Bayesian inversion of pressure diffusivity from microseismicity |
| title_full_unstemmed | Bayesian inversion of pressure diffusivity from microseismicity |
| title_short | Bayesian inversion of pressure diffusivity from microseismicity |
| title_sort | bayesian inversion of pressure diffusivity from microseismicity |
| url | http://hdl.handle.net/1721.1/98499 https://orcid.org/0000-0002-8814-5495 |
| work_keys_str_mv | AT poliannikovolegv bayesianinversionofpressurediffusivityfrommicroseismicity AT prangemichael bayesianinversionofpressurediffusivityfrommicroseismicity AT djikpessehugues bayesianinversionofpressurediffusivityfrommicroseismicity AT malcolmalisone bayesianinversionofpressurediffusivityfrommicroseismicity AT fehlermichael bayesianinversionofpressurediffusivityfrommicroseismicity |