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Precipitation and removal of ionic compounds from produced water: observed versus modeling results

Date

2014

Authors

Yang, Xiaochen, author
Carlson, Kenneth, advisor
Catton, Kimberly, committee member
Bradley, Thomas, committee member

Journal Title

Journal ISSN

Volume Title

Abstract

Produced water is generated during the hydraulic fracturing and drilling process, and is regarded as the largest byproduct associated with oil and gas industrial development. Samples of produced water from wells near Greeley, Colorado, were collected from February - July 2013. Commercial produced water treatment at the laboratory scale was conducted and the results compared to computer-based software modeling predictions. Different parameters, such as pH and temperature, are adjusted in order to test how these parameters could affect the treatment for produced water softening. The study shows that removal treatment performance could be related to pH adjustment of coagulation process, temperature and to the size of the filtration membrane. Comparison between different membrane filtration size (2.5 micron and 0.2 micron) apparently shows finer membrane (0.2 micron) improves the removal treatment performance. The results indicate that precipitation is not the limiter to divalent cation removal. During the research, OLI Chemical Analyst, the computer based modeling program, analyzed the precipitation performance of water samples under different temperature (-15 °C - 25 °C) and pH (9.0 - 10.2) conditions. The OLI Chemical Analyst shows that lower temperature could precipitate out different species. Sodium ions get separated (as NaAl(OH)2CO3, aluminum di-hydroxide carbonate) from the inflow when temperature is lower than 10°C, while other metal ions, such as calcium ions, barium ions, cannot get removed efficiently. However, the modeling results of pH adjustments demonstrate that lower pH would not obviously affect the scaling tendency of the target salts. The results show magnesium ions can only get removed when pH is higher than 11.0, the pH adjustment for softening can be optimized.

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Subject

water treatment
equilibrium modeling
softening
modeling

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