Less than a decade has passed since altered and fractured basement rocks were found to be commercial hydrocarbon reservoirs, and also to be possible providers of migration pathways in some of the fields, which are situated on the Norwegian North Sea. These fractured basement reservoirs are underlying thick clastic successions from Triassic to Quaternary.
Recently, a modern oil-based mud resistivity imaging log with ultra-high-resolution was run in two appraisal wells with the aim to understand the complex fracture network in these basement rocks (in off-set wells: biotite-muscovite schist, garnet schist, albite-microcline gneiss, microcline gneiss to sericite-bearing quartzite and cataclasite) which will help in understanding the migration paths, which are deemed vital for further development of this area.
This latest generation of oil-based mud imagers required us to question the traditional assumptions that open fractures would have a "Bright" response due to being filled with resistive mud and thus the role drilling mud has in the electro-magnetic response. To gain an image in oil-based mud, high frequencies and short current paths allow capacitive coupling of the formation to the buttons. The signal received is measured by two components, the phase and amplitude. These are affected by resistivity, permittivity, and stand-off. By dealing with the phase and amplitude as complex numbers, we can generate a resistivity dominated impedivity image and a permittivity dominated "imaginary" image.
These impedivity and permittivity dominated images plus an understanding of the mud behaviour help to differentiate between the types of fractures to create a more robust localized fracture model. It also proves that the assumption that a fracture has to be "bright" to be open is now invalid (Fig. 1).
This paper provides several examples of fractures and how traditional thinking falls down when the effects of solids in the mud and the behaviour of the water phase are considered. The use of permittivity dominated images is to help identify and classify fractures, which may be missed by just looking at resistivity-based images is also demonstrated.