Quantitative characterisation of fracture connectivity from high-resolution borehole image logs

Abstract

Fractures are fundamental structural elements in brittle rocks. They have a primary role in transporting geofluids, particularly in basement and carbonate rocks, where they have been the focus of reservoir characterisation and modelling for decades. Fracture networks are often described by statistical analysis of their geometrical attributes such as orientation, length and aperture. However, the spatial arrangement (topology) of fractures/fracture sets and its temporal evolution is equally important to better understand physical attributes of rocks. How much is a fracture network connected? Can this be quantified? Does connectivity change in different locations, if yes what is the reason for it? What is the brittle strain distribution in a fracture network? How much are fracture density and connectivity influenced by mechanical stratigraphy?This paper attempts to address these relevant questions and test quantitative fracture connectivity analysis on high resolution electrical and ultra-sonic borehole image logs in an appraisal well (Total depth, TD: 2195.36 mMD), drilled into the Utsira High basement, in the extensional Norwegian North Sea rift basin. Fracture connectivity and fracture size attributes were investigated in Permian Zechstein carbonates and Ordovician-Silurian granitic basement and separately for defined fracture zones at the interval of 2050–2195 mMD. The average degree of fracture/fault connection is good (D = 2.6) for the sediments and excellent (D = 3.5) for the basement. Accordingly, the block intensity (R22) is 0.4 for sediments and 0.2 for basement, which imply a moderately and strongly disintegrated host rock, respectively. There is a large fracture connectivity variation in different fracture zones, i.e. completely isolated fractures (Zone 1) vs highly interconnected and strongly disintegrated basement (Zones 9–10). The connectivity variation is governed by lithology, mechanical properties (stiffness), strain distribution and presence of weakness zones (faults). The study also highlights some possible applications of fracture connectivity results to reservoir modelling and future follow-up trends in quantitative spatial characterisation of fracture networks.