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Summary The ever-growing demand for energy, relatively high price of hydrocarbons, and recent advances in production technologies have brought tight hydrocarbon-bearing reservoirs into attention as a potential source of energy. However, the displacement physics at nano and micro scales and their impact on fluid flow in these rocks is poorly understood. The unconventional rocks, such as shale rocks, are highly heterogeneous, fine-grained, and their representative elementary volume is uncertain. In order to identify flow pathways in the pore network of these rocks, it is essential to characterize nanopores and their connectivity. This can be achieved using high-resolution 3D imaging technique provided by Focused Ion Beam milling and Scanning Electron Microscopy (FIB-SEM). In this technique, a sequence of 2D cross sectional images, spaced evenly through a region of bulk specimen, is acquired. The stack of 2D images is then re-constructed into a 3D digital gray-scale representation of the sample volume. In this study, a reservoir rock sample from a major shale oil reservoir is selected for high-resolution imaging and statistical analysis. Rock specimens, 1 to 2 cm in dimensions, are cut from different locations of the reservoir core from which a high-resolution 2D map and multiple 3D FIB-SEM images are obtained. The digital images are then visualized, segmented, and analyzed to obtain porosity, pore size distribution, pore aspect ratios, spatial distribution of organic/total porosity, and total organic content. We find that the majority of the pores are below 100 nm in radius for this rock. In addition, the total visible porosity and total organic content are in the range of 1 to 2% and 8 to 14 vol.%, respectively. Chemical composition and mineralogy of the samples are also evaluated by Energy Dispersive X-Ray Spectroscopy (EDS) analysis. Furthermore, 3D pore networks are extracted from the FIB-SEM images; pore connectivities are examined; and permeabilies are calculated by solving the Stokes equation numerically using the finite volume method. It is observed that the pore connectivity for these rocks is poor, resulting in low permeabilities ranging from 1 to 6 μD. Finally, the impact of calculated parameters on fluid flow in unconventional rocks is discussed.
- Europe (0.94)
- North America > United States > Wyoming (0.28)
- Geology > Rock Type > Sedimentary Rock > Clastic Rock > Mudrock > Shale (1.00)
- Geology > Geological Subdiscipline (1.00)
- North America > United States > Texas > Fort Worth Basin > Barnett Shale Formation (0.99)
- Europe > United Kingdom > Kimmeridge Formation (0.99)
- North America > United States > Kentucky > Quality Field (0.93)
- Reservoir Description and Dynamics > Unconventional and Complex Reservoirs > Shale oil (1.00)
- Reservoir Description and Dynamics > Unconventional and Complex Reservoirs > Shale gas (1.00)
- Reservoir Description and Dynamics > Reservoir Fluid Dynamics > Flow in porous media (1.00)
- Reservoir Description and Dynamics > Reservoir Characterization > Exploration, development, structural geology (1.00)
ABSTRACT: Log models have been developed for the Bossier and Haynesville shales of East Texas and northwestern Louisiana to evaluate the hydrocarbon potential of these mudrock systems. This effort has targeted approximately 40 wells having conventional logging suites obtained during the past 35 years; sometimes sonic logs are not available. Comparisons of TOC computed using the Δ Log R method for the Haynesville Shale reveals substantial underestimation of TOC values measured from core samples. Geochemical and petrological analyses reveal that the Haynesville Shale contains important amounts of carbonate, in addition to kerogen, quartz and clay. As such it is not a ‘simple’ clay-rich shale that this term commonly implies. This paper addresses calculation of reliable TOC estimates from wire-line logs for a lithologically complex mudrock. Complex lithology, typical of the Haynesville and sometimes seen in the Bossier, consists of clay (illite with subordinate chlorite), quartz, calcite and kerogen with possible gas in limited pore space. This combination of variable mineral content and pore fluid affects responses of all logs and renders simple interpretative models ineffective. Three log models have been developed to calculate reservoir characteristics for these varied lithologies, named HAYNESVILLE, BOSSIER and SHALE. The first 2 of these models use an optimized multiple log solver; lithologic components of the HAYNESVILLE are silt-sized quartz/clay (55% quartz, 45% illite), calcite and kerogen, those of the BOSSIER are illite, quartz and kerogen. The chief interpretative model is HAYNESVILLE; when VOL_CALCITE < 0.075 the BOSSIER model is applied. A simple SHALE model is needed because some wells exhibit sub-caliper wellbore rugosity in the Bossier, which adversely affects the density log and renders its use inappropriate. Log model results indicate that substantially improved estimates of TOC can be computed for the Haynesville and that calculation of geologically reasonable lithology variations are possible.
- North America > United States > Louisiana (1.00)
- North America > United States > Texas > Travis County > Austin (0.28)
- Geology > Rock Type > Sedimentary Rock > Clastic Rock > Mudrock > Shale (1.00)
- Geology > Mineral > Silicate (1.00)
- North America > United States > Texas > Haynesville Shale Formation (0.99)
- North America > United States > Texas > Fort Worth Basin > Barnett Shale Formation (0.99)
- North America > United States > Texas > East Texas Salt Basin > Cotton Valley Group Formation > Cotton Valley Group Formation > Bossier Shale Formation (0.99)
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- Reservoir Description and Dynamics > Unconventional and Complex Reservoirs > Shale gas (1.00)
- Reservoir Description and Dynamics > Reservoir Characterization > Geologic modeling (1.00)
- Reservoir Description and Dynamics > Reservoir Characterization > Exploration, development, structural geology (1.00)
- Reservoir Description and Dynamics > Formation Evaluation & Management > Open hole/cased hole log analysis (1.00)