PRECIPITATION AND FOULING IN HEAVY OIL–DILUENT BLENDS

Heavy oil fractions rich in asphaltenes were mixed with diluents containing from 0.6-25% aromatics, and the resulting blends subjected to batch precipitation experiments at 85°C, and thermal fouling tests at surface temperatures in the range 230-310ºC. Deposit compositions were determined, and are compared with suspended asphaltene composition. When the heavy oils were blended with the most aromatic diluents, precipitation and fouling were negligible. As the aromaticity of the diluents was decreased, the extent of asphaltene precipitation and the fouling rates increased. The solubility parameter of the blends, δmix, and the flocculation solubility parameter for asphaltenes, δf , were determined from measurements of the asphaltene flocculation onset by titration with heptane at temperatures from 25 to 50°C. Literature models predict no asphaltene precipitation (and presumably little fouling) will occur when [δmix- δf ] \u3e0 . Both the amount of asphaltene precipitated in the batch experiments, and the rate of thermal fouling decreased as the solubility parameter difference [δmix - δf] increased from negative to positive values. However some precipitation and fouling was observed at the expected condition for mixture stability δmix ≥ δf . As the temperature of the flocculation titration was raised towards the bulk temperatures of the experiments, values of [δmix-δf] decreased, and the agreement of the data with prediction of the point for zero precipitation and fouling improved. For unstable oil blends, the solubility parameter provides a good predictive measure of the tendency for asphaltene precipitation, and for heat exchanger fouling

Mathematical Modeling of Deposition of Carbonaceous Material from Heavy Hydrocarbon Vapors

https://digitalrepository.unm.edu/abq_mj_news/4576/thumbnail.jp

Investigation of Initial Fouling Rates of Calcium Sulfate Solutions under Non-Boiling Conditions (Work-in-Progress)

This study initiates an experimental investigation of how process variables such as temperature and velocity affect the initial precipitation fouling rate of the inverse solubility salt, calcium sulfate, under sensible heating conditions. The effect of fluid velocity and temperature on the delay time is also being measured

Determining the probability of cyanobacterial blooms: the application of Bayesian networks in multiple lake systems

A Bayesian network model was developed to assess the combined influence of nutrient conditions and climate on the occurrence of cyanobacterial blooms within lakes of diverse hydrology and nutrient supply. Physicochemical, biological, and meteorological observations were collated from 20 lakes located at different latitudes and characterized by a range of sizes and trophic states. Using these data, we built a Bayesian network to (1) analyze the sensitivity of cyanobacterial bloom development to different environmental factors and (2) determine the probability that cyanobacterial blooms would occur. Blooms were classified in three categories of hazard (low, moderate, and high) based on cell abundances. The most important factors determining cyanobacterial bloom occurrence were water temperature, nutrient availability, and the ratio of mixing depth to euphotic depth. The probability of cyanobacterial blooms was evaluated under different combinations of total phosphorus and water temperature. The Bayesian network was then applied to quantify the probability of blooms under a future climate warming scenario. The probability of the "high hazardous" category of cyanobacterial blooms increased 5% in response to either an increase in water temperature of 0.8°C (initial water temperature above 24°C) or an increase in total phosphorus from 0.01 mg/L to 0.02 mg/L. Mesotrophic lakes were particularly vulnerable to warming. Reducing nutrient concentrations counteracts the increased cyanobacterial risk associated with higher temperatures