Characterizing facies and porosity-permeability heterogeneity in a geothermal carbonate reservoir with the use of NMR-wireline logging data

If they are to be economically and technically sustainable, geothermal projects require the production of hot fluid at high flow rates over a 30-year thermal lifetime. The combined use of multiple logging tools in making pet-rophysical assessments of reservoir quality helps to optimize drilling in areas of high geothermal potential. The present paper focuses on four geothermal wells intercepting Middle Jurassic (Dogger) carbonate rocks of the Paris Basin where for the first time Nuclear Magnetic Resonance (NMR) log data have been successfully used to investigate reservoir porosity-permeability heterogeneities. A total of ten facies have been identified from recovered cuttings and cores and grouped into four facies associations along a schematic carbonate ramp profile. From the wells studied, four reservoir units exhibiting porosities exceeding 15% and permeabilities of up to 1 Darcy (D) were traced in the Calcaires de Comblanchien, the Oolithe Blanche and the Calcaires marneux a` Phola-domyes formations. The well's sub-horizontal trajectory and well-logs correlations between two wells, made it possible a priori to identify porous and permeable layers extending over at least 500 m and up to 2000 m within the Bathonian reservoir, providing useful pointers for further 3D reservoir geomodeling. Permeabilities derived from well testing proved to be overestimated when compared with NMR-derived permeabilities, illustrating the upscaling problem that is invariably a challenge in carbonate systems. NMR can be combined with production logging tool (PLT), that provides data on the distribution and thickness of productive layers, to give indications for example about continuous permeability record along the geothermal wells or about the proportion of micro and macroporosities in rocks. Based on the geological classification derived from examination of cores and cuttings, four rock-types (including mean T2 pore-size distributions) have been identified and attributed to a given sedimentary facies and depositional environment by extending a clustering method to NMR log distributions from wells.