R e p r o d u c e d with p e r m issio n o f th e co p y r ig h t o w n e r . F u rth er rep ro d u ctio n p roh ib ited w ith o u t p e r m issio n .

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This paper presents a new experimental method and its computational scheme for measuring gas diffusivity in heavy oil at high pressures and elevated temperatures by the dynamic pendant drop volume analysis (DPDVA). In the experiment, a see-through windowed high-pressure cell is first filled with a test gas at a prespecified pressure and temperature. Then, a heavy oil sample is introduced by using a syringe pump to form a pendant drop inside the pressure cell. Due to the oil swelling effect, the subsequent dissolution of the gas into the pendant oil drop causes its volume to increase until the saturation state is reached. The sequential digital images of the dynamic pendant oil drop are acquired and analyzed by applying computer-aided image acquisition and processing techniques to measure the oil drop volumes at different times. A mass-transfer model is developed theoretically to describe the diffusion process of the gas into the pendant heavy oil drop. This model is numerically solved by applying the semidiscrete Galerkin finite element method. The volume of the dynamic pendant oil drop is calculated from the numerically predicted transient gas concentration distribution inside the pendant oil drop. The gas diffusivity in heavy oil and the swelling factor of gas-saturated heavy oil are, thus, determined by finding the best fit of the theoretically calculated volumes of the dynamic pendant oil drop to the experimentally measured data. This novel experimental technique is applied to measure CO 2 diffusivities in a heavy oil sample and the swelling factors of a CO 2 -saturated heavy oil at P ) 2, 3, 4, 5, and 6 MPa and T ) 23.9 °C.

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Summary This paper presents a new experimental method and its computational scheme for measuring solvent diffusivity in heavy oil under practical reservoir conditions by DPDSA. In the experiment, a see-through windowed high-pressure cell is filled with a test solvent at desired pressure and temperature. Then, a heavy-oil sample is introduced through a syringe delivery system to form a pendant oil drop inside the pressure cell. The subsequent diffusion of the solvent into the pendant oil drop causes its shape and volume to change until an equilibrium state is reached. The sequential digital images of the dynamic pendant oil drop are acquired and digitized by applying computer-aided digital image-acquisition and -processing techniques. Physically, variations of the shape and volume of the dynamic pendant oil drop are attributed to the interfacial tension reduction and the well-known oil-swelling effect as the solvent gradually dissolves into heavy oil. Theoretically, the interfacial profile of the dynamic pendant oil drop is governed by the Laplace equation of capillarity, and the molecular diffusion process of the solvent into the pendant oil drop is described by the diffusion equation. An objective function is constructed to express the discrepancy between the numerically predicted and experimentally observed interfacial profiles of the dynamic pendant oil drop. The solvent diffusivity in heavy oil and the mass-transfer Biot number are used as adjustable parameters and thus are determined once the minimum objective function is achieved. This novel experimental technique is tested to measure diffusivities of carbon dioxide in a brine sample and a heavy-oil sample, respectively. It should be noted that, with the present technique, a single diffusivity measurement can be completed within an hour and only a small amount of oil sample is required. The interface mass-transfer coefficient at the solvent/heavy-oil interface can also be determined. In particular, this new technique allows the measurement of solvent diffusivity in an oil sample at constant prespecified high pressure and temperature. Therefore, it is especially suitable for studying the mass-transfer process of injected solvent into heavy oil during solvent-based post-cold heavy-oil production (post-CHOP). Introduction Western Canada has tremendous heavy oil and bitumen resources (Farouq Ali 2003, Miller et al. 2002). Approximately 80 to 95% of the original-oil-in-place is still left behind at the economic limit after cold heavy-oil production (Miller et al. 2002). This is a large oil-in-place target for follow-up enhanced oil recovery (EOR) processes. After primary production, most Canadian heavy-oil reservoirs cannot be further exploited economically by thermal recovery processes because reservoir formations are thin and/or there is active bottomwater. In the literature, some studies have been conducted to evaluate the other recovery methods for these heavy-oil reservoirs (Miller et al. 2002, Das 1995, Frauenfeld et al. 1998, Metwally 1998). Among these methods, vapor extraction (VAPEX) and other solvent-based post-CHOP processes are probably the most promising EOR techniques. In practice, the solvent can be carbon dioxide, flue gas, and light hydrocarbon gases, such as methane, ethane, propane, and butane.

Using singly connected rings with a collimating contact to the current leads, we have observed the spin quantum beating in the Aharonov-Bohm conductance oscillations. We demonstrate that the beating is the result of the superposition of two independent interference patterns associated with two orthogonal spin chiral states arising from intrinsic spin-orbit interactions. Our work provides the conclusive evidence of the spin Berry's phase in the conductance of quantum rings.

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Summary This paper describes the modeling of the main processes for CO2 trapping in saline aquifers, namely solubility trapping, residual gas trapping and mineral trapping. Several important aspects of CO2 storage are presented. It has been found that the total amount of CO2 trapped as a soluble component, and as residual gas, can be enhanced by injecting brine above the CO2 injector. An optimization technique is used to adjust the location and rate of the brine injector to maximize the total amount of CO2 trapping. The security of the trapping process is then evaluated by taking into account the leakage of mobile CO2 through the caprock. For long-term CO2 storage, the conversion of CO2 into minerals is found to depend on the pre-existing minerals in the aquifer that provide the necessary ions for the reactions to occur.