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Minimum miscibility pressure (MMP) is a key parameter in the design of gas flooding. There are experimental and computational methods to determine MMP. Computational methods are fast and convenient alternatives to otherwise slow and expensive experimental procedures. This research focuses on the computational aspects of MMP estimation. It investigates the shortcomings of the current computational models and offers ways to improve the robustness of MMP estimation. First, we develop a new mixing cell method of estimating MMP that, unlike previous "mixing cell" methods, uses a variable number of cells and is independent of gas-oil ratio, volume of the cells, excess oil volumes, and the amount of gas injected. The new method relies entirely on robust P-T flash calculations using any cubic equation-of-state (EOS). We show that mixing cell MMPs are comparable with those of other analytical and experimental methods, and that our mixing cell method finds all the key tie lines predicted by MOC; however, the method proved to be more robust and reliable than current analytical methods. Second, we identify a number of problems with analytical methods of MMP estimation, and demonstrate them using real oil characterization examples. We show that the current MOC results, which assume that shocks exist from one key tie line to the next may not be reliable and may lead to large errors in MMP estimation. In such cases, the key tie lines determined using the MOC method do not control miscibility, likely as a result of the onset of L₁-L₂-V behavior. We explain the problem with a simplified pseudo-ternary model and offer a procedure for determining when an error exists and for improving the results. Finally, we present a simple mathematical model for predicting the MMP of contaminated gas. Injection-gas compositions often vary during the life of a gasflood because of reinjection and mixing of fluids in situ. Determining the MMP by slim-tube or other methods for each possible variation in the gas-mixture composition is impractical. Our method gives an easy and accurate way to determine impure CO₂ MMPs for variable field solvent compositions on the basis of just a few MMPs. Alternatively, the approach could be used to estimate the enrichment level required to lower the MMP to a desired pressure. / text

The disposal of waste from agricultural activities has been recognised as a source of environmental contamination by endocrine disrupting chemicals (EDCs). The New Zealand dairy industry produces a large volume of dairy farm effluent, which contains EDCs in the form of estrogens. Most of this dairy farm effluent is applied onto the land for disposal. Groundwater and soil contamination by estrogens following waste application on the land have been reported overseas, but our understanding of the processes and factors governing the fate of estrogens in the soil is poor. Therefore the main goal of the present study was to better understand the fate and transport of estrogens, in particular 17β-estradiol (E2) and estrone (E1) in soil. In order to quantify E1 and E2 in drainage water and soil samples, chemical analysis by gas-chromatography mass-spectrometry (GC-MS) was carried out. This included sample extraction, sample clean-up through silica gel and gel permeation chromatography, and sample extract derivatisation prior to analysis. In order to develop a reliable method to extract estrogens from soil, research was conducted to optimise E1 and E2 extraction conditions by adjusting the number of sonication and shaking events, as well as the volume and type of solvent. Among five solvents and solvent mixtures tested, the best recovery on spiked and aged soil was obtained using an isopropanol/water (1:1) mix. A microcosm experiment was carried out to determine the dissipation rates of E2 and E1, at 8°C and at field capacity, in the Templeton soil sampled at two different depths (5-10 cm and 30-35 cm). The dissipation rates decreased with time and half-life values of 0.6-0.8 d for E1 and 0.3-0.4 d for E2 were found for the two depths studied. A field transport experiment was also carried out in winter, over three months, by applying dairy farm effluent spiked with estrogens onto undisturbed Templeton soil lysimeters (50 cm in diameter and 70 cm deep). The hormones were applied in dairy farm effluent at 120 mg m⁻² for E2 and 137 mg m⁻² for E1. The results of the transport experiment showed that in the presence of preferential/macropore flow pathways 0.3-0.7% of E2 and 8-13% of E1 was recovered in the leachate at the bottom of the lysimeters after 3 months, and 1-7% of the recovered E2 and 3-54% of the recovered E1 was leached within 2 days of application. These results suggest that leaching of estrogens via preferential/macropore flow pathways is the greatest concern for groundwater contamination. In the absence of preferential/macropore flow pathways, a significant amount (> 99.94%) of both hormones dissipated in the top 70 cm of soil, due to sorption and rapid biodegradation. Surprisingly, in all cases, estrogen breakthrough occurred before that of an inert tracer (bromide). This could not be explained by the advection-dispersion transport of estrogens, nor by their presence as antecedent concentrations in the soil. It was therefore suggested that colloidal enhanced transport of estrogens was responsible for the earlier breakthrough of estrogens and caused the leaching of a fraction of the applied estrogens to a soil depth of 70 cm. A two-phase model, adapted from a state-space mixing cell model, was built to describe the observed estrogen transport processes under transient flow. The model takes into account 3 transport processes namely, advection-dispersion, preferential/macropore flow and colloidal enhanced transport. This model was able to successfully describe the estrogen transport observed from the lysimeters.