In the Ethereum network, miners are incentivized to include transactions in a block depending on the gas price specified by the sender. The sender of a transaction therefore faces a trade-off between timely inclusion and cost of his transaction. Existing recommendation mechanisms aggregate recent gas price data on a per-block basis to suggest a gas price. We perform an empirical analysis of historic block data to motivate the use of a predictive model for gas price recommendation. Subsequently, we propose a novel mechanism that combines a deep-learning based price forecasting model as well as an algorithm parameterized by a user-specific urgency value to recommend gas prices. In a comprehensive evaluation on real-world data, we show that our approach results on average in costs savings of more than 50% while only incurring an inclusion delay of 1.3 blocks, when compared to the gas price recommendation mechanism of the most widely used Ethereum client.
Subhash Ayirala, Ali AlâYousef, Zuoli Li, Zhenghe Xu
Summary Smart waterflooding (SWF) through tailoring of injection-water salinity and ionic composition is receiving favorable attention in the industry for both improved and enhanced oil recovery (EOR) in carbonate reservoirs. Surface/intermolecular forces, thin-film dynamics, and capillary/adhesion forces at rock/fluid interfaces govern crude-oil liberation from pores. On the other hand, stability and rigidity of oil/water interfaces control the destabilization of interfacial film to promote coalescence between released oil droplets and to improve the oil-phase connectivity. As a result, the dynamics of oil recovery in smart waterflood is caused by the combined effect of favorable interactions occurring at both oil/brine and oil/brine/rock interfaces across the thin film. Most of the laboratory studies reported so far have been focused on only studying the interactions at rock/fluid interfaces. However, the other important aspect of characterizing water ion interactions at the crude oil/water interface and their impact on film stability and oil-droplet coalescence remains largely unexplored. A detailed experimental investigation was conducted to understand the effects of different water ions at the crude-oil/water interface by using several instruments such as Langmuir trough, interfacial shear rheometer, Attension tensiometer, and coalescence time-measurement apparatus. The reservoir crude oil and four different water recipes with varying salinities and individual ion concentrations were used. Interfacial tension (IFT), interface pressures, compression energy, interfacial viscous and elastic moduli, oil-droplet crumpling ratio, and coalescence time between crude-oil droplets are the major experimental data measured. The IFTs are found to be the largest for deionized (DI) water, followed by the 10-times-reduced-salinity seawater and 10-times-reduced-salinity seawater enriched with sulfates. Interfacial pressures gradually increased with compressing surface area for all the brines and DI water. The compression energy (integration of interfacial pressure over the surface-area change) is the highest for DI water, followed by the lower-salinity brine containing sulfate ions, indicating rigid interfaces. The transition times of interfacial layer to become elastic-dominant from viscous-dominant structures are found to be much shorter for brines enriched with sulfates, once again confirming the rigidity of interface. The crumpling ratios (oil drop wrinkles when contracted) are also higher with the two recipes of DI water and sulfates-only brine to indicate the same trend and to confirm elastic rigid skin at the interface. The coalescence time between oil droplets was the least in brines containing sufficient amounts of magnesium and calcium ions, while the highest in DI water and sulfate-rich brine, respectively. These results, therefore, showed a good correlation of coalescence times with the rigidity of oil/water interface, as interpreted from different measurement techniques. This study, thereby, integrates consistent results obtained from different measurement techniques at the crude-oil/water interface to demonstrate the importance of both salinity and certain ions, such as magnesium and calcium, on crude-oil-droplets coalescence, and to improve oil-phase connectivity in smart waterflood.
An industrial scheme, to simulate the compressible two-phase flow in porous media, consists of a finite volume method together with a phase-by-phase upstream scheme. The implicit finite volume scheme satisfies industrial constraints of robustness since the proposed scheme discretizes the equations with gravity and capillary terms. We show that the proposed scheme satisfies the maximum principle for the saturation, a discrete-energy estimate on the pressures, and a function of the saturation that denotes capillary terms. These stability results allow us to derive the convergence of a subsequence to a weak solution of the continuous equations as the size of the discretization tends to zero. To our knowledge, this is the first convergence result of a finite volume scheme in the case of two-phase compressible flow in several space dimensions. The proof is given for the complete system when the density of each phase depends on its own pressure.
Advanced Numerical Methods in Computational Mathematics