2014 AIChE Annual Meeting

(39d) Simulation-Based Science and Engineering with Fossil Fuel Energy

Author

Chau-Chyun Chen - Presenter, Texas Tech University

In the pursuit of sustainable energy, chemical engineers harvest solar energy and wind energy, and develop energy storage devices. In addition, chemical engineers strive to make existing energy resources more sustainable. For example, we develop novel absorbents to capture CO2 generated from power plants. We develop processes to recycle or recover water we use or produce in hydraulic fracturing. We apply smart manufacturing to improve on vitrification processes for permanent and safe storage of nuclear wastes. We develop better molecular understanding on crude oils in order to make the most profitable use of valuable hydrocarbon resources.

This talk covers several simulation-based science and engineering research efforts with fossil fuel energy. First we showcase development of a comprehensive saline water thermodynamic model for hydraulic fracturing. The main problem with treating and reusing hydraulic fracturing flowback or produced water is precipitating followed by scaling. These fracturing products contain dissolved ions such as barium (Ba2+), strontium (Sr2+), calcium (Ca2+), carbonate (CO32-), or sulfate (SO42-) which can precipitate and produce scale. Thus, developing a comprehensive thermodynamic model which could be used to investigate the phase behavior of the saline water seems vital. The key thermodynamic and physical properties here include activity coefficient, salt solubility, density, and viscosity. Based on symmetric electrolyte NRTL model, the model is capable of accurately representing thermodynamic and physical properties of various saline water binary systems and higher order systems with temperatures from 273 to 473 K and salt concentrations up to saturation.

In addition, we present a revolutionary molecule-based characterization methodology developed for correlation and prediction of assays and properties for crude oil and petroleum fractions. From readily accessible crude oil assay data such as distillation curve, API gravity, and PNA contents, the method identifies an optimal set of chemical compositions of ~10,000 model hydrocarbon compounds designed to mimic measurable physical and chemical properties of crude oil. The model hydrocarbon compounds cover significant classes of hydrocarbon constituent molecules present in crude oil while each class is characterized by its molecular structural segments and segment distribution function parameters. The relative weights of the various classes of the hydrocarbon constituent molecules, the respective structural segment types, and the segment distribution function parameters together constitute a “molecular profile” of the crude oil. The chemical compositions of model hydrocarbon compounds as derived from the “molecule profile” are then used to interpolate, extrapolate, and predict crude oil assays and properties based on molecular thermodynamic models. The “molecule profile” further offers a highly prized molecular insight into crude oil for planning, scheduling, and process simulation of oil production and petroleum refining operations.