Diagenesis, Petrophysics and Reservoir Quality Modeling in the Montney Formation – A Major Siltstone Reservoir in Western Canada
Models for reservoir quality are key in evaluating the economic viability of field development. Unlike sandstone and shale reservoirs, the controls for siltstone reservoir quality are not yet well understood. We have advanced the existing knowledge of siltstones by developing a reservoir quality model for the Lower Triassic Montney Formation, a westward-thickening accumulation of fine, well-sorted silisiclastics and carbonates in the West Canada Sedimentary Basin, containing up to 400 TCF of recoverable gas, based on geochemistry, rock fabric, paragenesis and petrophysical properties for the 6-17-083-25W6M well in British Columbia, Canada. Rock mineralogy was determined by XRD and whole rock chemical analyses, using the LPNorm software to calculate the quantitative composition, supplemented by QEMSCAN analysis. SEM imaging and thin section petrography were used to unravel the diagenetic sequence. Core analyses, including mercury injection porosimetry, pulse decay and continuous flow permeability tests, were compared with estimates made by standard well logs analysis. Our results indicate that original mineralogy exerts a strong control on rock composition. Minerals include quartz, feldspar, plagioclase, carbonate minerals, pyrite and marcasite, apatite, muscovite and clay minerals (illite, chlorite and other unidentified detrital clays). Halite and to a lesser extent gypsum were also found in many samples. Diagenetic processes, as cementation and authigenic clay minerals growth clearly reduced primary porosity. Cementation and dissolution patterns have been recognized for carbonate minerals, feldspars and quartz. Quartz dissolution suggests periodic basic conditions in the formation water. Analyses to date indicate that the porosity of the Montney formation is between 0.5 and 5%. Air permeability also ranges widely, between 10-3 and 5 md, and shows no obvious relationship to rock composition. All results were combined into GAMLS (Geologic Analysis via Maximum Likelihood System) software to calculate a predictive model for reservoir quality and characterization along the well bore. With the model calibrated to the multiple analysis results and with future information gathered from different Montney wells, a predictive model for the entire siltstone reservoir are computed.
AAPG Datapages/Search and Discovery Article #90189 © 2014 AAPG Annual Convention and Exhibition, Houston, Texas, USA, April 6–9, 2014