A unified Bayesian framework for relative microseismic location

We study the problem of determining an unknown microseismic event location relative to previously located events using a single monitoring array in a monitoring well. We show that using the available information about the previously located events for locating new events is advantageous compared to...

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Main Authors: Poliannikov, Oleg V., Prange, Michael, Malcolm, Alison E., Djikpesse, Hugues
Other Authors: Massachusetts Institute of Technology. Department of Earth, Atmospheric, and Planetary Sciences
Format: Article
Language:en_US
Published: Oxford University Press on behalf of The Royal Astronomical Society 2014
Online Access:http://hdl.handle.net/1721.1/87682
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author Poliannikov, Oleg V.
Prange, Michael
Malcolm, Alison E.
Djikpesse, Hugues
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
Malcolm, Alison E.
Djikpesse, Hugues
author_sort Poliannikov, Oleg V.
collection MIT
description We study the problem of determining an unknown microseismic event location relative to previously located events using a single monitoring array in a monitoring well. We show that using the available information about the previously located events for locating new events is advantageous compared to locating each event independently. By analysing confidence regions, we compare the performance of two previously proposed location methods, double-difference and interferometry, for varying signal-to-noise ratio and uncertainty in the velocity model. We show that one method may have an advantage over another depending on the experiment geometry, assumptions about uncertainty in velocity and recorded signal, etc. We propose a unified approach to relative event location that includes double-difference and interferometry as special cases, and is applicable to velocity models and well geometries of arbitrary complexity, producing location estimators that are superior to those of double-difference and interferometry.
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spelling mit-1721.1/876822022-09-29T15:18:31Z A unified Bayesian framework for relative microseismic location Poliannikov, Oleg V. Prange, Michael Malcolm, Alison E. Djikpesse, Hugues Massachusetts Institute of Technology. Department of Earth, Atmospheric, and Planetary Sciences Massachusetts Institute of Technology. Earth Resources Laboratory Malcolm, Alison E. Poliannikov, Oleg V. Malcolm, Alison E. We study the problem of determining an unknown microseismic event location relative to previously located events using a single monitoring array in a monitoring well. We show that using the available information about the previously located events for locating new events is advantageous compared to locating each event independently. By analysing confidence regions, we compare the performance of two previously proposed location methods, double-difference and interferometry, for varying signal-to-noise ratio and uncertainty in the velocity model. We show that one method may have an advantage over another depending on the experiment geometry, assumptions about uncertainty in velocity and recorded signal, etc. We propose a unified approach to relative event location that includes double-difference and interferometry as special cases, and is applicable to velocity models and well geometries of arbitrary complexity, producing location estimators that are superior to those of double-difference and interferometry. 2014-06-06T15:57:11Z 2014-06-06T15:57:11Z 2013-04 2013-03 Article http://purl.org/eprint/type/JournalArticle 0956-540X 1365-246X http://hdl.handle.net/1721.1/87682 Poliannikov, Oleg V., Michael Prange, Alison Malcolm, and Hugues Djikpesse. "A unified Bayesian framework for relative microseismic location." Geophysical Journal International (July, 2013) 194 (1): 557-571. en_US http://dx.doi.org/10.1093/gji/ggt119 Geophysical Journal International Creative Commons Attribution-Noncommercial-Share Alike http://creativecommons.org/licenses/by-nc-sa/4.0/ application/pdf Oxford University Press on behalf of The Royal Astronomical Society Malcolm via Michael Noga
spellingShingle Poliannikov, Oleg V.
Prange, Michael
Malcolm, Alison E.
Djikpesse, Hugues
A unified Bayesian framework for relative microseismic location
title A unified Bayesian framework for relative microseismic location
title_full A unified Bayesian framework for relative microseismic location
title_fullStr A unified Bayesian framework for relative microseismic location
title_full_unstemmed A unified Bayesian framework for relative microseismic location
title_short A unified Bayesian framework for relative microseismic location
title_sort unified bayesian framework for relative microseismic location
url http://hdl.handle.net/1721.1/87682
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