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Title: | Optimising the Treatment of Flowback and Produced Wastewater (FPW) from Hydraulic Fracturing in the Marcellus Shale |
Authors: | Rogers, Gabrielle Mercedes |
Advisors: | Fitts, Jeffrey P. |
Department: | Chemical and Biological Engineering |
Class Year: | 2016 |
Abstract: | Natural gas production is growing steadily, with the energy generated in the United States by natural gas increasing from 24% to 27% between 2011 and 2013. This is mainly due to new improvement in hydraulic fracturing - horizontal drilling. While, natural gas is considered to be a transitional fuel by many, bridging the way between coal and renewable energy, it can still have other detrimental effects on the environment. One of the many concerns surrounds the effect of its extraction on the water supply. Not only does it take roughly 2-8 million gallons of water to fracture one well, but the water that returns to the surface is usually severely contaminated. The most common method of treatment of this water is metal removal followed by dilution. In the treatment process, sodium sulphate is used to remove barium by means of a precipitation reaction. The main goal of this thesis was to investigate the effectiveness of this precipitation reaction as the primary method of treatment, by determining the impact of total dissolved solids and arsenate on the precipitation of barium sulphate. From this study, it is clear that higher concentrations of total dissolved solids inhibit the precipitation reaction, resulting in longer reaction times. It is also clear that arsenate has some effect on the precipitation reaction, but it is unclear from this study what exactly that is. |
Extent: | 48 pages |
URI: | http://arks.princeton.edu/ark:/88435/dsp019c67wq28n |
Type of Material: | Princeton University Senior Theses |
Language: | en_US |
Appears in Collections: | Chemical and Biological Engineering, 1931-2019 |
Files in This Item:
File | Size | Format | |
---|---|---|---|
Factor-Adjusted Regularized Model Selection for Logistic Regression in the Presence of Missing Data | 1.55 MB | Adobe PDF | Request a copy |
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