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Transient signals were registered in a modified fluidized bed and statistically analyzed. Particle agglomerates in the emulsion were identified from signals and the agglomerate properties were investigated. The volume fraction of the bubble phase varied from 0.16 to 0.52 with operation pattern and spatial positions. Mean solid holdup and its standard deviation inside bubbles significantly increased when operation pattern transitioned from bubbling fluidization to turbulent fluidization, while the increasing tendency leveled off in the turbulent regime. The volume fraction of particle agglomerates in the emulsion decreased with increasing superficial gas velocity, varying over the range of 0.2–0.65 with flow regimes. Agglomerate solid holdup slightly fluctuated in the range of 0.608–0.63, barely influenced by switch of operation pattern. Agglomerate frequency varied over the range of 1.5–3.7 Hz and the duration time was <0.3 s for most cases. The correlations of agglomerate volume fraction and frequency were proposed. The terminal velocity and the size of the effective agglomerates in the emulsion phase were calculated via a modified Richardson–Zaki equation and found to be 4.16 m/s and 1.19 mm, respectively.

Test results from mixtures of anionic-cationic surfactants significantly broaden the application scope for conventional chemical Enhanced Oil Recovery methods; these mixtures produced ultra low Critical Micelle Concentrations (CMC) as well as ultra-low interfacial tension (IFT) and high oil solubilization that promote high oil recovery.Mixtures of anionic and cationic surfactants with molar excess of anionic surfactant for EOR applications are described herein. Physical chemistry properties, such as surface tension, CMC, surface excess and area per molecule of individual surfactants and their mixtures were measured by Wilhelmy Plate Method. Morphologies of surfactant solutions, both surfactant-polymer (SP) and alkaline-surfactant-polymer (ASP), were studied by Cryo TEM. Phase behaviors were recorded by visual inspection including with crossed polarizers at different surfactant concentrations and different temperatures. Interfacial tensions between normal octane, crude oil and surfactant solution were measured by spinning drop tensiometer method. Properties of interfacial tension, viscosity and thermal stability of surfactant, surfactant-polymer, and alkalinesurfactant-polymer solutions, were also tested. Static adsorption on sandstone was measured at reservoir temperature. IFT was measured before and after multiple contact adsorptions to recognize the influence of adsorption on interfacial properties. Forced displacements were conducted by flooding with water, polymer, SP and ASP. The core flooding experiments were conducted with water made of a simulated formation brine having approximately 5000 ppm TDS, and with a crude oil from a Sinopec reservoir.

Ensemble empirical mode decomposition (EEMD) is a noise-assisted adaptive data analysis method to solve the mode mixing problem caused by empirical mode decomposition (EMD), which is a significant step of Hilbert-Huang Transform (HHT). In this paper, a novel fast EEMD preferences algorithm called Quasi-Gradient Search (QGS) is proposed. For a given ensemble number, we first apply Nonlinear Correlation Coefficient (NCC) to estimate the lower bound of decomposition error, which leads to the best amplitude of added noise. According to the accuracy requirement, we can obtain the minimum ensemble number to solve mode mixing by increasing the ensemble number exponentially. Furthermore, the QGS is applied to extract the accents of the emotion speeches in different scales to solve the mode mixing problem. Compared with the result of traditional EEMD, the proposed QGS can greatly enhance the calculation speed with the same decomposition accuracy.

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