Acoustic and reservoir properties of microporous carbonate rocks: Implication of micrite particle size and morphology

International audience; This integrated study provides significant insight into parameters controlling the acoustic and reservoir properties of microporous limestones, improving the knowledge of the relationships among petrophysic and microstructural content. Petrophysical properties measured from laboratory and logging tools (porosity, permeability, electrical conductivity, and acoustic properties) have been coupled with thin section and scanning electron microscope observations on the EST205 borehole from the Oxfordian limestone aquifer of the eastern part of the Paris Basin. A major achievement is the establishment of the link between micrite microtexture types (particle morphology and nature of intercrystal contacts) and the physical response, introducing a new effective and interesting rock-typing approach for microporous reservoirs. Fluid-flow properties are enhanced by the progressive augmentation of intercrystalline microporosity and associated pore throat diameter, as the coalescence of micrite particles decreases. Concerning acoustic properties, the slow increase of P wave velocity can be seen as a reflection of crystal size and growing contact cementation leading to a more cohesive and stiffer micrite microtexture. By applying poroelasticity theory on our samples, we show that velocity dispersion can be a very useful tool for data discrimination in carbonates. This dispersion analysis highlights the presence of microcracks in the rocks, and their overall effect on acoustic and transport properties. The presence of microcracks is also confirmed with observations and permeability measurements under high confining pressure. Finally, a possible origin of high porous levels in neritic limestones is a mineralogical transformation of carbonates through freshwater-related diagenesis during subaerial exposure time. Finally, by applying poroelasticity theory on our samples, we show that velocity dispersion can be a very useful tool for data discrimination in carbonates.