Articles | Volume 10, issue 2
Research article
17 Apr 2019
Research article |  | 17 Apr 2019

A new methodology to train fracture network simulation using multiple-point statistics

Pierre-Olivier Bruna, Julien Straubhaar, Rahul Prabhakaran, Giovanni Bertotti, Kevin Bisdom, Grégoire Mariethoz, and Marco Meda

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Cited articles

Agar, S. M. and Geiger, S.: Fundamental controls on fluid flow in carbonates: current workflows to emerging technologies, Geological Society, London, Special Publications, 406, 60,, 2015. 
Angelim, L. A. A., Medeiros, V. C., and Nesi, J. R.: Mapa geológico do Estado do Rio Grande do Norte, CPRM/FAPERN, Recife, Projeto Geologia e Recursos Minerais do Estado do Rio Grande do Norte, 2006. 
Bemis, S. P., Micklethwaite, S., Turner, D., James, M. R., Akciz, S., Thiele, S. T., and Bangash, H. A.: Ground-based and UAV-Based photogrammetry: A multi-scale, high-resolution mapping tool for structural geology and paleoseismology, J. Struct. Geol., 69, 163–178, 2014. 
Berkowitz, B.: Characterizing flow and transport in fractured geological media: A review, Adv. Water Resour., 25, 861–884, 2002. 
Bertotti, G., de Graaf, S., Bisdom, K., Oskam, B., Vonhof, H. B., Bezerra, F. H. R., Reijmer, J. J. G., and Cazarin, C. L.: Fracturing and fluid-flow during post-rift subsidence in carbonates of the Jandaira Formation, Potiguar Basin, NE Brazil, Basin Res., 29, 18,, 2017. 
Short summary
Natural fractures influence fluid flow in subsurface reservoirs. Our research presents a new methodology to predict the arrangement of these fractures in rocks. Contrary to the commonly used statistical models, our approach integrates more geology into the simulation process. The method is simply based on the drawing of images, can be applied to any type of rocks in various geological contexts, and is suited for fracture network prediction in water, geothermal, or hydrocarbon reservoirs.