New mapping, mineralogical, and geochemical studies help characterize late Tertiary primitive, alkaline, sodic basanite, alkali olivine basalt, transitional basalt, and diabase in the Nechako River, Whitesail Lake, and McLeod Lake map areas of central British Columbia and distinguish the Miocene Cheslatta Lake suite. The suite encompasses scattered erosional remnants of topographically distinct, columnar-jointed, olivine-phyric basalt and diabase volcanic necks, dykes, and associated lava flows north of the Anahim volcanic belt and west of the Pinchi Fault. Volcanic centres at Alasla Mountain and at Cutoff Creek, near Cheslatta Lake, are proposed as type areas. Olivine, plagioclase, and pyroxene phenocrysts, megacrysts, and (or) xenocrysts; common ultramafic xenoliths; and rare but significant plutonic and metamorphic xenoliths are characteristic. Basanite, transitional basalt, and alkali olivine basalt groundmass contain plagioclase, clinopyroxene, Fe-Ti oxides, feldspathoid, olivine, and apatite. The Cheslatta Lake suite is characterized by its alkaline character, olivine-rich (>10 wt.%) normative mineralogy, and silica-undersaturated nature (>1 wt.% normative nepheline; hypersthene-normative rocks are uncommon). Mg numbers vary between 72–42. Some samples encompass near-primitive mantle melt compositions. Cheslatta Lake suite rocks in the Nechako River area are distinguished from the underlying Eocene Endako and stratigraphically higher Neogene Chilcotin groups basaltic andesite lavas within the study area, and from the Chilcotin Group basalt in the type area south of the Anahim volcanic belt, by form, preserved thickness, phenocryst–xenocryst mineralogy, amygdule abundance, included xenoliths, isotopic age, and major and incompatible, high field strength, and rare-earth trace element contents.

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Summary Particle-size distribution (PSD) is a list of values that defines the relative amount of particles present according to the size in a sample. The PSD of the McMurray Formation sediments characterizes rock granulometry and is a fundamental indicator of the nature of the sediment. The size distribution of the component solid particles in the McMurray Formation sediments relates to their porosity; volume of water and bitumen contained within the pore space; and the depositional environment, including lithological association, stratigraphy, areal distribution, and associated physical processes. PSD is known to be a significant factor for evaluating bitumen recovery from an oil-sand mine. This is because presence of fines (evaluated by PSD analysis) affects the hot-water-separation process and processing-plant recovery prediction and provides grade control. Presence of more fines translates into lower recovery from commercial oil-sand processing. In this study, we investigate whether the PSD should be also considered a critical parameter for evaluation and estimation of permeability of an oil-sand reservoir. We show, by use of the data from Cenovus Energy's Telephone Lake lease, that there is a strong relationship between permeability and PSD data. We also show that the information provided by the PSDs for permeability prediction is more significant than that inferred from a simple porosity/permeability relationship. Subsequently, we comment on permeability modeling by use of PSD data and list the techniques available for cleaning and modeling of multivariate PSDs. We document a methodology for modeling of PSDs and provide a work flow for incorporating these data in improved understanding and modeling of permeability and its distribution.

The McMurray Formation is the most volumetrically important source of bitumen in the Canadian oil sands. While there are many parameters that affect prediction of bitumen recovery in commercial in situ oil sand projects, absolute permeability is the most important geological parameter. In this paper, we describe a customized near-wellbore modelling workflow for the estimation of vertical and horizontal permeability in the McMurray Formation using high-resolution microresistivity images. All steps required to calculate permeability logs calibrated to core plug measurements are documented and detailed. To show a general applicability of the method, a case study of several wells from the Cenovus Energy Inc. (Cenovus) Foster Creek project is presented. The wells are specifically selected to be different in terms of facies, their characteristics and interval lengths.

Particle-size distribution (PSD) is a list of values that defines the relative amount of particles present according to the size in a sample. The PSD of the McMurray Formation sediments characterizes rock granulometry and is a fundamental indicator of sediment's nature. The size distribution of the component solid particles in the McMurray Formation sediments relates to their porosity, volume of water and bitumen contained within the pore space, and to depositional environment, including lithological association, stratigraphy, aerial distribution, and associated physical processes.Particle size distribution is known to be a significant factor for evaluating bitumen recovery from an oil sands mine. This is because presence of fines (evaluated by PSD analysis) affects the hot water separation process, processing plant recovery prediction and provides grade control. Presence of more fines translates into lower recovery from commercial oil sands processing. In this paper we investigate whether the particle size distribution should be also considered a critical parameter for evaluation and estimation of permeability of an oil sands reservoir.We show using the data from the Cenovus Energy's Telephone Lake lease that there is a strong relationship between permeability and particle size distribution data. We also show that the information provided by the PSDs for permeability prediction is more significant than the one inferred from a simple porosity-permeability relationship. Subsequently, we comment on permeability modeling using particle size distribution data and list the techniques available for cleaning and modeling of multivariate PSDs.We document a methodology for accurate modeling of PSDs and provide a workflow for incorporating these data in improved understanding and modeling of permeability and its distribution.• Grain size: sands with smaller grains have smaller pore throats and therefore smaller permeability, reverse holds for sands with coarse grains. Permeability may vary several orders of magnitude between very fine and coarse sand (Hogg et al. 1996).