The pore sizes of shale and other unconventional plays are of the order of tens of nanometers. Based on the fundamental theory of thermodynamics, several studies have indicated that, in such small pores, phase behavior is affected by the capillary pressure and surface forces and is different from that characterized in PVT cells. No experimental evidence of this phenomenon, however, has been presented in the literature. In this study, we apply nanofluidic devices to visualize phase changes of pure alkane and an alkane mixture under nanoconfinement as a means to approach oil/gas phase behaviors in nanoporous rocks. Pure alkane starts vaporizing in the micro-channels first, and then the meniscus flashes into the nanochannels immediately after the complete vaporization of the liquid in the micro-channels. The vaporization of the ternary hydrocarbon mixture, however, is very different from pure alkane. Although the liquid starts to vaporize in the microchannels first, as expected, the meniscus cannot propagate into the nano-channels in a comparable time scale as the pure alkane. The reason is that the liberation of lighter components from the liquid phase to the gas phase in the micro-channels increases the apparent molecular weight of the liquid in the nano-channels, suppressing the bubble point of the remaining fluid. A modified flash calculation procedure that uses the sizes of micro-channels and nano-channels as the characteristic lengths and assumed contact angle can reproduce the vaporization propagation sequence in the experimental observations. Experiments and modeling presented in this paper provide the proof of the concept and promote the understanding of phase behavior in nanoporous unconventional reservoirs.
Condensation of petroleum retrograde gas and especially that around a wellbore can decrease the deliverability of the well significantly. Better estimation of the point of phase transition is the key for reservoir engineers to devise management strategies to reduce condensate dropout and improve production and ultimate recovery. It has been established theoretically that the point of phase transition obtained from bulk PVT experiments does not represent the phase behavior of hydrocarbon fluids confined in nano-pores. However, very few experimental data are available. In this study, we measured the impact of nano-confinement on the phase behavior of propane using nano-fluidic devices. Direct observations of phase changes show that nano-confinement led to reductions in the vapor pressure that are consistent with the theory of capillary condensation. The shifts in the vapor pressure, however, were not always in good agreement with the Kelvin equation.
Liquid loading is an important determinant for the performance of tight, unconventional gas wells. Although plunger lift is one of the best solutions when applicable, marginal economics of unconventional gas production does not tolerate un-optimized plunger lift performance. In this paper a reservoir-performance based algorithm proposed by Ozkan et al. (2003) is applied to optimize the gas production and shut-in periods of plunger lift operation. The objective of the optimization is to maximize gas production with the condition that the liquid loaded during production can be lifted to the surface by the pressure that builds up during the following shut-in period. Unlike the current plunger lifts that work in time mode (like timer clock), this algorithm is based on pressure (pressure mode). The optimization algorithm combines the conventional plunger-lift theory with an analytical description of the reservoir performance. The conventional plunger lift theory provides the pressure required for lifting the plunger with a liquid column on top of it, and the analytical reservoir model is used to optimize the sequence of production and shut-in times. The optimization algorithm presented in this paper improves the economics of unconventional gas production not only by increasing gas production but also automating the process by which optimization is achieved. Another advantage of the proposed method is the ability to automatically adjust to changes in the line pressure. A case study is presented to demonstrate that the proposed automated model can achieve the same optimization performance as that implemented by expert technicians.
scite is a Brooklyn-based organization that helps researchers better discover and understand research articles through Smart Citations–citations that display the context of the citation and describe whether the article provides supporting or contrasting evidence. scite is used by students and researchers from around the world and is funded in part by the National Science Foundation and the National Institute on Drug Abuse of the National Institutes of Health.
hi@scite.ai
10624 S. Eastern Ave., Ste. A-614
Henderson, NV 89052, USA
Copyright © 2024 scite LLC. All rights reserved.
Made with 💙 for researchers
Part of the Research Solutions Family.