Multi-scale fracture network characterisation on carbonate platforms

Loza Espejel, Roberto ORCID: https://orcid.org/0000-0001-8502-0083, Alves, Tiago M. ORCID: https://orcid.org/0000-0002-2765-3760 and Blenkinsop, Tom G. ORCID: https://orcid.org/0000-0001-9684-0749 2020. Multi-scale fracture network characterisation on carbonate platforms. Journal of Structural Geology 140 , 104160. 10.1016/j.jsg.2020.104160

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Abstract

Characterisation of fracture networks at different scales is challenging and important to many fields of geoscience, especially when access to multiple resolution datasets is limited. Here, we develop an integrated analysis of fracture networks on carbonate platforms using three scales of observation: small (outcrop), intermediate (airborne LiDAR) and large (3D seismic). Statistical analyses and ternary diagrams of geometrical and topological data from Cariatiz (South East Spain) and Pernambuco (East Brazil) are used to understand the relationships and distribution of fracture networks between multi-scale datasets. A variety of fracture types at each scale of observation reveal how complex fracture networks are on carbonate platforms. Our results demonstrate that fracture network properties behave differently depending on the fracture size, and that transitional scale gaps between datasets constrain fracture characterisation. Airborne LiDAR maps show that intermediate-sized fractures appear to have a better controlled orientation and a lower connectivity than smaller fractures from the same area in Cariatiz. Fracture branch length distributions fit a negative exponential or log-normal distribution for massive non-stratabound units. This work is important as it demonstrates that the use of outcrop data is a good approach to understand fracture complexity of carbonate platforms. Understanding sub-seismic fracture networks is therefore critical in quantifying fluid flow and permeability in carbonate reservoirs.

Item Type:	Article
Date Type:	Publication
Status:	Published
Schools:	Earth and Environmental Sciences
Publisher:	Elsevier
ISSN:	0191-8141
Funders:	Conacyt-SENER
Date of First Compliant Deposit:	3 September 2020
Date of Acceptance:	8 August 2020
Last Modified:	10 Nov 2024 15:00
URI:	https://orca.cardiff.ac.uk/id/eprint/134655

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