Integrated Reservoir Characterization for Enhanced Oil Recovery, Tar Springs Formation, Illinois Basin, USA
The Illinois basin contains many mature Mississippian-aged reservoirs that are potential targets for enhanced oil recovery (EOR). In this study we integrate sedimentology, petrography, quantitative mineralogy (XRD), Fourier transform infrared analysis (FTIR), thermogravimetric analysis/evolved gas analysis (TGA/EGA), and scanning electron microscopy (SEM) to characterize the physical and chemical properties of the Tar Springs Formation in a producing field. Reservoir cores were described, sampled, and analyzed on a foot-by-foot scale using sedimentology and petrography. Five distinct lithofacies serve to categorize the studied reservoir: F1 – fine- to medium-grained, horizontally-stratified sandstone with consistent porosity but large variations in permeability; F2 – very fine- to fine-grained flaser bedded sandstone with consistent porosity and permeability; F3 – very fine-grained wavy bedded sandstone with reduced porosity and permeability; F4 – fine-grained sandstone and mudstone with little porosity and permeability; and F5 – medium-grained sandstone with calcite cement that occludes all porosity and permeability. Lithofacies F1 represents the highest quality reservoir interval but thin-section observations show millimeter-scale heterogeneity as a function of calcite cement and clay-rich horizons. XRD analyses confirm the presence of quartz and calcite but also identify illite, kaolinite, and chlorite as primary constituents in F1. SEM work has revealed pore mineralogy variations that can significantly influence flow distribution as it relates to porosity, permeability, and possible polymer degradation. TGA/EGA and FTIR confirm mineralogy but quantitatively assess residual oil saturations of pre- and post-coreflood studies. Exposures of the Tar Springs Formation along the basin margin as well as available core data from the Indiana Geological Survey and Pioneer Oil Company have also been integrated to provide a geologic framework to better understand the expected variability within producing reservoir core suites. Collectively, all of our data sets are internally consistent with identifying framework grains, cement types, and clay minerals that help define flow parameters such as compartmentalization by permeability barriers and pore space constituents. We will also discuss how these integrated data sets are being used by other members of our research team to determine the optimal surfactant-polymer pairs and reservoir simulation modeling needed for EOR.
AAPG Datapages/Search and Discovery Article #90291 ©2017 AAPG Annual Convention and Exhibition, Houston, Texas, April 2-5, 2017