Smectite-bitumen interactions in non-aqueous bitumen extraction process
Source abstract
Abstract
The non-aqueous extraction (NAE) is an alternative to the commercial water-based extraction technology used to liberate bitumen from oil sands. Although the impact of kaolinite, illite, chlorite, illite-smectite and montmorillonite on NAE process has been previously studied, the effect of different types of smectites has not been fully understood yet. In this work, mixtures of bitumen with bentonites dominated by saponite, hectorite, nontronite, beidellite and montmorillonite were reacted for several days and then washed with solvent (cyclohexane) to remove bitumen from the bentonites. The main goal was to better understand the impact of different smectites properties (specific surface area, pore structure characteristics, particle size, crystallite thickness, swelling ability, cation exchange capacity, layer charge and crystal-chemistry of smectites) on NAE process. The results showed that the porosity, particle size and swelling ability were the key parameters affecting the solvent-based bitumen recovery under the studied conditions. Samples with larger initial total pore volume and smaller particle size displayed reduced solvent bitumen extractability. The particle size of studied samples was affected primarily by swelling of smectites during the solvent bitumen extraction experiments. Smectites were swelling in water but not in cyclohexane. Swelling of smectite caused splitting of larger clay particles into many smaller particles. As a consequence, the efficiency of solvent bitumen extraction was significantly lower for fine grained samples, consisting of thin delaminated smectite particles, in which the bitumen was distributed among small-sized clay particles.
Source: expertdata · Quality: candidate unverified · Source record ↗
Research context
OpenAlex topics: Hydrocarbon exploration and reservoir analysis · Enhanced Oil Recovery Techniques · Petroleum Processing and Analysis
SciVX discovery tags are terminology-based. OpenAlex topics are source-provided classifications.
References (44)
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