The Green's function for the diffusion coefficient

Thesis: S.B., Massachusetts Institute of Technology, Department of Earth, Atmospheric, and Planetary Sciences, 2012.

Bibliographic Details
Main Author: Hess, Clarion Hadleigh
Other Authors: Alison Malcolm.
Format: Thesis
Language:eng
Published: Massachusetts Institute of Technology 2018
Subjects:
Online Access:http://hdl.handle.net/1721.1/114353
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author Hess, Clarion Hadleigh
author2 Alison Malcolm.
author_facet Alison Malcolm.
Hess, Clarion Hadleigh
author_sort Hess, Clarion Hadleigh
collection MIT
description Thesis: S.B., Massachusetts Institute of Technology, Department of Earth, Atmospheric, and Planetary Sciences, 2012.
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spelling mit-1721.1/1143532019-04-11T13:30:23Z The Green's function for the diffusion coefficient Hess, Clarion Hadleigh Alison Malcolm. Massachusetts Institute of Technology. Department of Earth, Atmospheric, and Planetary Sciences. Massachusetts Institute of Technology. Department of Earth, Atmospheric, and Planetary Sciences. Earth, Atmospheric, and Planetary Sciences. Thesis: S.B., Massachusetts Institute of Technology, Department of Earth, Atmospheric, and Planetary Sciences, 2012. Cataloged from PDF version of thesis. Includes bibliographical references (pages 53-54). The scattering diffusion coefficient between two points can theoretically be extracted from a random distribution of sources. An improved ability to measure the diffusion coefficient of the Earth's crust would simplify the process of characterizing the fracture network for applications in geothermal energy. This has the potential to make geothermal wells more economical to make, more efficient to operate, and longer lived. Previous work has shown the diffusion coefficient can be extracted from synthetic datasets in both one dimension and three dimensions using seismic interferometry. This paper attempts to recover the diffusion coefficient for a realistic source distribution taken from a microseismic dataset from a geothermal field in Indonesia. This dataset did not have an ideal distribution of sources, so the estimated diffusion coefficient did not match the expected value. A better estimate of the expected diffusion coefficient and an improved dataset with sources more evenly distributed in all directions around the receivers would likely give a better result. by Clarion Hadleigh Hess. S.B. 2018-03-27T14:18:49Z 2018-03-27T14:18:49Z 2012 2012 Thesis http://hdl.handle.net/1721.1/114353 1028979427 eng MIT theses are protected by copyright. They may be viewed, downloaded, or printed from this source but further reproduction or distribution in any format is prohibited without written permission. http://dspace.mit.edu/handle/1721.1/7582 54 pages application/pdf Massachusetts Institute of Technology
spellingShingle Earth, Atmospheric, and Planetary Sciences.
Hess, Clarion Hadleigh
The Green's function for the diffusion coefficient
title The Green's function for the diffusion coefficient
title_full The Green's function for the diffusion coefficient
title_fullStr The Green's function for the diffusion coefficient
title_full_unstemmed The Green's function for the diffusion coefficient
title_short The Green's function for the diffusion coefficient
title_sort green s function for the diffusion coefficient
topic Earth, Atmospheric, and Planetary Sciences.
url http://hdl.handle.net/1721.1/114353
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