Enhanced cross-well seismic inversion by fuzzy c-means clustering

© 2019 24th European Meeting of Environmental and Engineering Geophysics. All rights reserved. A cross-well tomography with a geostatistical constraint via fuzzy C-means clustering (FCM) is proposed to extract geologically realistic velocity models for acquisition during mineral resource definition...

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Main Authors: Kieu, D., Jafarzadeh Rastin, Sepideh, Kepic, Anton
Format: Conference Paper
Published: 2019
Online Access:http://hdl.handle.net/20.500.11937/73904
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author Kieu, D.
Jafarzadeh Rastin, Sepideh
Kepic, Anton
author_facet Kieu, D.
Jafarzadeh Rastin, Sepideh
Kepic, Anton
author_sort Kieu, D.
building Curtin Institutional Repository
collection Online Access
description © 2019 24th European Meeting of Environmental and Engineering Geophysics. All rights reserved. A cross-well tomography with a geostatistical constraint via fuzzy C-means clustering (FCM) is proposed to extract geologically realistic velocity models for acquisition during mineral resource definition drilling. Constraining a damped least squares inversion process with the additional requirement to keep velocity values in clusters counters the smearing of geological boundaries by the addition of smoothing constraints, which are typically used . The FCM center values were either set as priori known values from borehole measurements or estimated from the data during the cross-well inversion process. We have applied our FCM constrained inversion to three synthetic models and then compared these results to a conventional smoothness constrained inversion result. The three models approximate three simple-to-challenging possible scenarios within a polymetallic deposit embedded in meta-sedimentary rocks. A significant improvement resulted using FCM constraints in the recovery of the true structure, particularly at the boundaries, and various artifacts were better damped. The additional accuracy can provide considerable benefits in improve the resource models in the mine planning stage, and optimize ground-support design and blasting parameter estimation during mining.
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spelling curtin-20.500.11937-739042019-02-19T04:27:46Z Enhanced cross-well seismic inversion by fuzzy c-means clustering Kieu, D. Jafarzadeh Rastin, Sepideh Kepic, Anton © 2019 24th European Meeting of Environmental and Engineering Geophysics. All rights reserved. A cross-well tomography with a geostatistical constraint via fuzzy C-means clustering (FCM) is proposed to extract geologically realistic velocity models for acquisition during mineral resource definition drilling. Constraining a damped least squares inversion process with the additional requirement to keep velocity values in clusters counters the smearing of geological boundaries by the addition of smoothing constraints, which are typically used . The FCM center values were either set as priori known values from borehole measurements or estimated from the data during the cross-well inversion process. We have applied our FCM constrained inversion to three synthetic models and then compared these results to a conventional smoothness constrained inversion result. The three models approximate three simple-to-challenging possible scenarios within a polymetallic deposit embedded in meta-sedimentary rocks. A significant improvement resulted using FCM constraints in the recovery of the true structure, particularly at the boundaries, and various artifacts were better damped. The additional accuracy can provide considerable benefits in improve the resource models in the mine planning stage, and optimize ground-support design and blasting parameter estimation during mining. 2019 Conference Paper http://hdl.handle.net/20.500.11937/73904 10.3997/2214-4609.201802636 restricted
spellingShingle Kieu, D.
Jafarzadeh Rastin, Sepideh
Kepic, Anton
Enhanced cross-well seismic inversion by fuzzy c-means clustering
title Enhanced cross-well seismic inversion by fuzzy c-means clustering
title_full Enhanced cross-well seismic inversion by fuzzy c-means clustering
title_fullStr Enhanced cross-well seismic inversion by fuzzy c-means clustering
title_full_unstemmed Enhanced cross-well seismic inversion by fuzzy c-means clustering
title_short Enhanced cross-well seismic inversion by fuzzy c-means clustering
title_sort enhanced cross-well seismic inversion by fuzzy c-means clustering
url http://hdl.handle.net/20.500.11937/73904