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Foams have been used as hydraulic fracturing fluids to reduce water usage and minimize the potentially deleterious impact on water-sensitive formations. Traditionally, carbon dioxide (CO2) and nitrogen (N2) have been used as the internal phase in these foamed fluids. Hydraulic fracturing with natural gas (NG) is a relatively inexpensive option, particularly if NG produced from the wellhead can be used without significant processing. In an ongoing program sponsored by the US Department of Energy (DOE), an alternative fracturing process is being developed that uses NG-based foam. Previously, the optimal thermodynamic pathway was identified to transform wellhead NG into pressurized NG suitable for use as the internal phase in a foamed fracturing fluid. Recent work has focused on preparing a NG-based foam at surface conditions typically encountered in hydraulic fracturing and measuring the stability and rheological properties of the foam. In addition, the transient response of the foam during fracture initiation was simulated using a fast-acting solenoid valve. A single base-fluid mixture was prepared by combining a commercially available viscosifier and foaming surfactant with water. The base fluid was then injected into a tee using a water pump. Simultaneously, liquefied natural gas (LNG) was pressurized using a cryogenic pump, vaporized using a heat exchanger, and injected into the tee to mix with the base fluid and generate foam. The foam then flowed through approximately 300 ft of 0.312-in. inside diameter (ID) tubing equipped with pressure transducers at several locations. The test fixture included a sight glass to visually inspect the quality of the foam. This paper reports on findings related to foam stability and rheology and compares these results to previous studies on foamed fracturing fluids.

Wet Gas Compression (WGC) continues to be an important topic as oil and gas production is driven further out into the ocean and moves critical equipment to the ocean floor. In the last year, significant milestones have been reached for WGC by the installation of the first wet gas compressor off the coast of Norway. Even with this achievement, there is a lack of understanding of the physics behind WGC and there are deficiencies in the ability to predict the compressor performance. Understanding the two phase flow structure inside the compressor is important for validating WGC simulations and being able to predict compressor performance. This paper reviews the results from a test program focused on characterizing the flow inside the compressor by using flow visualization. An open impeller centrifugal compressor was outfitted with windows to view the flow inside the compressor at the inlet, inside the impeller and in the diffuser section. Testing was conducted with an ambient suction pressure at various compressor speeds, flow rates, and liquid volume fractions. Images and videos were captured at the different conditions in order to observe the two phase flow structure. The general patterns and trends that characterize wet gas flow are discussed in this paper.

In the current economic and political environment, there is a push for gas turbine operators to achieve higher operating efficiencies, which in turn, reduces emissions and fuel consumption. As these owners and operators seek to increase the efficiency of their machines, they are increasingly turning to physics-based performance modeling. This allows the end user to analyze machine performance, plan for performance upgrades, and evaluate use cases and operating conditions not originally envisioned by the original equipment manufacturers (OEMs). For owners/operators who do not have access to physics-based models provided by the hardware OEM or would like to evaluate modifications to legacy hardware, physics-based models may be developed using measured turbine performance data and high-level knowledge of the turbine architecture. In previous work, a physics-based performance model of an industrial gas turbine engine was created using measured plant operating data and an inverse solution method to allow off-design exploration of its performance. However, this model’s uncertainty was unknown, and knowledge of uncertainty is crucial to understanding a model’s reliability. In the present work, the model’s uncertainty in predicted performance at a particular operating point is investigated using statistical methods. Polynomial regressions of standard deviation are used alongside the performance regressions to describe the uncertainty at various operating points. These regressions are also used to visualize the variation of uncertainty across the performance map. Such knowledge of uncertainty can aid gas turbine operators in decision making with regard to the risks of off-design operation or equipment modifications.

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