Please use this identifier to cite or link to this item: https://hdl.handle.net/2440/72053
Type: Conference paper
Title: Optimisation of a stochastic rock fracture model using Markov Chain Monte Carlo simulation
Author: Xu, C.
Dowd, P.
Wyborn, D.
Citation: 35th APCOM symposium: application of computers and operations research in the minerals industry, 24-30 September 2011, University of Wollongong, New South Wales, Australia: proceedings /​ E.Y. Baafi, R.J. Kininmonth and I. Porter (eds.), pp.635-642
Publisher: The Australasian Institute of Mining and Metallurgy
Publisher Place: CD
Issue Date: 2011
Series/Report no.: Publication /​ Australasian Institute of Mining and Metallurgy ; 11/​2011
ISBN: 9781921522512
Conference Name: International Symposium of Application of Computers and Operations Research in the Minerals Industry Symposium (35th : 2011 : Wollongong, N.S.W.)
Statement of
Responsibility: 
C. Xu, P.A. Dowd and D. Wyborn
Abstract: The characterisation of rock fracture networks is an important component of rock engineering applications involving stability assessment or fluid flow analysis. However, the derivation of a reliable rock fracture model remains a very challenging problem in practice. This paper describes a Bayesian framework, in the form of Markov Chain Monte Carlo (MCMC) simulation, for the construction of such a model. Model conditioning using different data sources is discussed including seismic events recorded during hydraulic fracture stimulation, rock face fracture mapping data and downhole geophysical survey data. The freeware FracSim3D is used for the simulations.
Rights: © Copyright 2012 - The Australasian Institute of Mining and Metallurgy
Description (link): http://www.ausimm.com.au/publications/epublication.aspx?ID=13004
Appears in Collections:Aurora harvest 5
Civil and Environmental Engineering publications

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