Date of Award
Doctor of Philosophy (PhD)
Ignacio E. Grossmann
This thesis focuses on the optimization of an important natural resource, water, in chemical processes and shale gas production. In the chemical industry, many unit operations require intensive use of water for processes such as synthesis, cleaning, cooling cycle, and steam production. The wastewater stream contains pollutants such as total dissolved solids (TDS) and organics that need to be removed prior to discharge into natural water bodies. With the increasingly stringent environmental regulations, freshwater and wastewater reuse allocation has become a major topic in process synthesis. Chapter 2 presents an approach to perform simultaneous optimization of heat and water integration for a process flowsheet. As opposed to the sequential integration approach where heat and water integration are performed for flowsheets with fixed operating conditions, the simultaneous optimization method allows for variable stream qualities to account for potential trade-offs among raw material, investment cost, and utility and water consumption. Since detailed heat-exchange network and water network designs are generally formulated as nonconvex mixed-integer nonlinear programming and nonconvex nonlinear programming models, respectively, reducing complexities for these two networks is of utmost priority. We have developed a novel linear programming targeting model for minimizing freshwater consumption of multi-contaminants systems. This water targeting model, which is either exact or else predicts upper bounds, is incorporated along with the available heat targeting model into flowsheet optimization process to achieve the best operating conditions through the proposed simultaneous framework. The conventional water network synthesis approach greatly simplifies wastewater treatment units by using fixed recoveries, creating a gap for their applicability to industrial processes. Chapter 3 describes a unifying approach combining various technologies capable of removing contaminants through the use of more realistic models. Unit-specific short-cut models are developed in place of the fixed contaminant removal model to describe contaminant mass transfer in reverse osmosis, ion exchange, sedimentation, ultrafiltration, activated sludge, and trickling filter. In addition, uncertainty in mass load of contaminant is considered to account for the range of operating conditions. Furthermore, the superstructure is modified to accommodate realistic potential structures. We also present a modified Lagrangean-based decomposition algorithm in order to effectively solve the resulting nonconvex mixed-integer nonlinear programming problem. Management of water use in the rapidly developing shale gas industry has become a major challenge in recent years. Unlike most chemical processes that operate at steady-state conditions, hydraulic fracturing requires a large volume of water in a short period of time. In addition, there is a cost associated with each of the four key aspects, source water acquisition, wastewater production, reuse and recycle, and subsequent transportation, storage, and disposal. In chapter 4, water use life cycle is optimized for wellpads through a discrete-time two-stage stochastic mixed-integer linear programming model under uncertain availability of water. The objective is to minimize expected operating cost while accounting for the revenue from gas production. As the number of producing wells increase, desalination options are evaluated since produced water management becomes an important economic driver. In chapter 5, we expand the operational model in chapter 4 to optimize capital investment decisions in water use for shale gas production. The goal is to determine the location and capacity of impoundment, the type of piping, treatment facility locations and removal capability, freshwater sources, as well as the frac schedule. In addition, we examine in several scenarios the impact of limiting truck hauling and increasing flowback volume on the solution. Case studies in both Marcellus and Utica shale are presented to illustrate the application of the proposed formulations.
Yang, Linlin, "Optimization Models for Water Management in Chemical Processes and Shale Gas Production" (2014). Dissertations. 433.