By means of electrospray ionization Fourier transform ion cyclotron resonance mass spectrometry (ESI FT−ICR MS), we identify nonvolatile polar acidic and basic emulsion stabilizers in nine geographically distinct light, medium, and heavy oils. Although oil class distributions are unique, oils of similar API specific gravity exhibit similar relative abundances for the O2 and O4S classes. Heavy oils are high in O2 and low in low in O4S. The light oils follow the opposite trend. However, independent of parent oil O2 and O4S class abundances, O2 and O4S species preferentially adsorb and are the two most abundant classes in the emulsion interfacial material. Negative-ion nitrogen-containing classes do not have a high affinity for emulsion interface adsorption. However all positive-ion nitrogen-containing species adsorb to the oil/water interface.

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1. Most forecasts for the future state of ecological systems are conducted once and never updated or assessed. As a result, many available ecological forecasts are not based on the most up-to-date data, and the scientific progress of ecological forecasting models is slowed by a lack of feedback on how well the forecasts perform. Iterative near-term ecological forecasting involves repeated daily to annual scaleforecasts of an ecological system as new data becomes available and regular assessment of the resulting forecasts. We demonstrate how automated iterative near-term forecasting systems for ecology can be constructed by building one to conduct monthly forecasts of rodent abundances at the Portal Project, a longterm study with over 40 years of monthly data. This system automates most aspects of the six stages of converting raw data into new forecasts: data collection, data sharing, data manipulation, modelling and forecasting, archiving, and presentation of the forecasts.3. The forecasting system uses R code for working with data, fitting models, making forecasts, and archiving and presenting these forecasts. The resulting pipeline is automated using continuous integration (a software development tool) to run the entire pipeline once a week. The cyberinfrastructure is designed for long-term maintainability and to allow the easy addition of new models. Constructing this forecasting system required a team with expertise ranging from field site experience to software development.4. Automated near-term iterative forecasting systems will allow the science of ecological forecasting to advance more rapidly and provide the most up-to-date forecasts possible for conservation and management. These forecasting systems will also accelerate basic science by allowing new models of natural systems to be quickly implemented and compared to existing models. Using existing technology, and teams with diverse skill sets, it is possible for ecologists to build automated forecasting systems and use them to advance our understanding of natural systems. K E Y W O R D Sforecasting, iterative forecasting, mammals, Portal Project, predictionThis is an open access article under the terms of the Creative Commons Attribution License, which permits use, distribution and reproduction in any medium, provided the original work is properly cited.

The primary objective of this work was to determine the effect of emulsified water on the onset and the amount of asphaltene precipitation from diluted crude oils. Asphaltene precipitation yields were measured from an Athabasca bitumen and a Gulf of Mexico crude oil diluted with n-heptane. The experiments were performed with and without emulsified water added to the oils. Yields were compared to determine the effect of the emulsified water. At dilution ratios above the onset of precipitation for dewatered oils, yields were observed to be same for both dewatered oils and oils emulsified with water. Hence, the presence of water had no detectable effect on the solubility of asphaltenes in a crude oil. However, asphaltenes adsorbed on the surface of emulsified water droplets were removed with the water droplets and reported as yield below the onset. The secondary objective of this work was to analyze the compositional differences between the asphaltenes precipitated at the onset condition, asphaltenes adsorbed onto the interface, and bulk asphaltenes. On the basis of CHNSO analysis, it was found that there is no compositional difference between these three different asphaltenes. ■ INTRODUCTIONOne of the flow assurance issues in the oil industry is asphaltene precipitation from crude oils. Asphaltenes can be precipitated when the oil experiences changes in pressure, temperature, and composition. Usually, crude oil samples with no or very little water (typically around 0.5 wt %) are used for asphaltene phase behavior modeling or assessing the risk of asphaltene precipitation in the laboratory. However, crude oils are almost always co-produced with formation water and also with injected water during secondary or enhanced oil recovery processes. In the case of bitumen extraction processes, a large amount of water is used for froth treatment, and therefore, water-in-oil emulsion formation is unavoidable. When present, water is usually emulsified in the oil but can also have an appreciable solubility at sufficiently high temperatures (generally above 250°C). The effect of the presence of water on the measured onset and yield of precipitated asphaltenes is not understood. The focus of this study is to investigate only the effect of emulsified water on asphaltene precipitation from diluted crude oils.Most of the investigations on the effect of water on asphaltene precipitation have focused on solubilized water. Solubilized water may affect asphaltene self-association, which, in turn, can affect asphaltene precipitation. Andersen et al. 1 tested this idea with calorimetric measurements of asphaltene association. A sample of dewatered toluene was placed in a calorimeter, and an asphaltene−toluene solution was added. The amount of heat absorbed because of the addition of the solution was measured and related to the aggregation behavior. The experiment was then repeated with an asphaltene−toluene solution containing trace amounts of water (∼0.047 wt %). The data indicated a change in the amount of heat absorbed with a change in ...

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