We report a novel partial dissolution strategy to liberate uniform cellulose nanofibers with diameter of 5-10 nm from macroscopic cellulose fibers and promote separation of nanofibers in an aqueous environment by forming water-soluble sodium carboxymethylcellulose (CMC) through heterogeneous sodium acetoxylation of cellulose. With the obtained cellulose nanofibers, we fabricated nanopapers which exhibit high optical transparency of 90.5% (@550 nm) with promising mechanical properties and high thermal stability. By directly depositing Ag nanowires on a wet nanofiber sheet, we fabricated a flexible transparent electrode with 86.5% (@550 nm) transparency and 26.2 Ω/sq sheet resistance (R). Meanwhile, we studied the magnetic properties of sputter deposited thin film of permalloy on nanopaper which exhibited a similar magnetic coercivity and a close saturation magnetization to conventional silicon dioxide-based permalloy.
In trying to speed up reservoir simulators, we have given significant attention to improving runtime performance and efficiency on various components of the simulator, i.e. linear solvers, flash calculations, time-step controls, with further performance gain from parallelization. This paper describes an enhanced version of Newton's method, the adaptive Newton's method, that reduces time spent in nonlinear loops of a reservoir simulator. It is commonly observed that clusters of reservoir simulation cells are responsible for the convergence behavior within a Newton loop at a given timestep. In our investigations on field cases, the number of cells that had not converged, as defined by the magnitude of the residual and solution changes, would decease very rapidly as the Newton iteration progresses. In most cases, the number of unconverged cells was significantly less than 2% after just one or two Newton iterations. An adaptive nonlinear method was developed to use the residual of the previous Newton iteration as a guide to select a subset of cells for subsequent Newton iterations. The subset of cells includes all the unconverged cells plus a collection of bordering cells. Using this adaptation, the matrix solved at Newton iterations after the first one is very much reduced, resulting in significant speedup. Several variations in the adaption were investigated, varying the size of the border, varying the timing of the application of adaption and including a residual smoothing step. This adaptive Newton's method was applied to multiple field cases, with the numbers of simulation cells ranging from 14,000 to 900,000 cells. The use of the residual smoothing operator prevented material balance errors with minimal impact on the Newton convergence behavior and timestep sizes. Run times were reduced by 30~70 % in these field test cases with no negative effects on results.
ExxonMobil and its Canadian affiliate Imperial Oil Resources are pursuing an integrated research program targeted at developing the next generation of heavy oil recovery processes which utilize light hydrocarbon solvents in conjunction with steam or as an alternative to steam-only processes to mobilize the in-situ heavy oil. The key benefits of employing solvent are improved economics and increased recovery from resource that is impractical with steam-only processes, improved environmental performance, particularly reduced greenhouse gas emissions and reduced water use.A suite of field trials, pilots and commercial applications have been operating over the past several years at Imperial Oil's Cold Lake field in Alberta, Canada. These have included both solvent-assisted and solvent-only field trials. Collectively, the results of these trials show that solvent recovery processes for heavy oil are technically viable and have considerable commercial potential. This paper summarizes the dimensions of the integrated research program that have been key to delivering the successful results to date. Simulation, laboratory testing and physical modelling with a focus on scaling to the field have been employed extensively prior to field testing. Short-term, relatively low cost field trials have been utilized to calibrate models prior to more costly, longer term pilots with dedicated facilities. Extensive field characterization has been conducted prior to final site selection and pilot operation. Integrated operational and surveillance plans have been employed to ensure measurable and reliable field performance data is acquired that can be used to calibrate and validate simulation performance. Finally, learnings from this integrated research program can be more broadly applied to the commercialization of other EOR processes and the research and development processes leading up to the decision to execute a major pilot.
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