Optimisation of a stochastic rock fracture model using Markov Chain Monte Carlo simulation
Date
2011
Authors
Xu, C.
Dowd, P.
Wyborn, D.
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Conference paper
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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
Statement of Responsibility
C. Xu, P.A. Dowd and D. Wyborn
Conference Name
International Symposium of Application of Computers and Operations Research in the Minerals Industry Symposium (35th : 2011 : Wollongong, N.S.W.)
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.
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© Copyright 2012 - The Australasian Institute of Mining and Metallurgy