Please use this identifier to cite or link to this item:
Scopus Web of Science® Altmetric
Type: Journal article
Title: Optimisation of a stochastic rock fracture model using Markov Chain Monte Carlo simulation
Author: Xu, C.
Dowd, P.
Wyborn, D.
Citation: Transactions of the Institutions of Mining and Metallurgy Section A: Mining Technology, 2013; 122(3):153-158
Publisher: Maney Publishing
Issue Date: 2013
ISSN: 1474-9009
Statement of
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.
Keywords: Fracture modelling
Markov Chain Monte Carlo
Geothermal energy
Rights: ©2013 The Australian Institute of Mining and Metalurgy
DOI: 10.1179/1743286312Y.0000000023
Published version:
Appears in Collections:Aurora harvest
Civil and Environmental Engineering publications

Files in This Item:
There are no files associated with this item.

Items in DSpace are protected by copyright, with all rights reserved, unless otherwise indicated.