Emulsions have emerged as advanced materials for wide industrial applications because of their unique properties. In the actual application in oilfields, emulsions can significantly enhance oil recovery. In the present study, the stability test shows that the concentrations of a surfactant and alkali and salinity have a great influence on the stability of the emulsion, but the addition of excessive chemical agents may adversely affect the emulsion stability. The addition of excessive alkali causes the phase inversion behavior of the emulsion to be discovered, which is also the main reason for the destabilization of the oil-in-water emulsion. Rheological experiments reveal that the emulsion produced by the chemical-flooding fluid is a pseudoplastic fluid, and the apparent viscosity decreases with the increase of the shear rate. Core-flooding experiments were conducted to study the effect of the emulsion stability on enhanced oil recovery, and the results indicate that the system with a better emulsion stability has higher oil recovery and displacement pressure.
Gas injection processes are among the effective methods for enhanced oil recovery. Miscible and/or near miscible gas injection processes are among the most widely used enhanced oil recovery techniques. The successful design and implementation of a miscible gas injection project are dependent upon the accurate determination of minimum miscibility pressure (MMP), the pressure above which the displacement process becomes multiple-contact miscible. This paper presents a method to get the characteristic curve of multiple-contact. The curve can illustrate the character in the miscible and/or near miscible gas injection processes. Based on the curve, we suggest a new model to make an accurate prediction for CO2-oil MMP. Unlike the method of characteristic (MOC) theory and the mixing-cell method, which have to find the key tie lines, our method removes the need to locate the key tie lines that in many cases is hard to find a unique set. Moreover, unlike the traditional correlation, our method considers the influence of multiple-contact. The new model combines the multiple-contact process with the main factors (reservoir temperature, oil composition) affecting CO2-oil MMP. This makes it is more practical than the MOC and mixing-cell method, and more accurate than traditional correlation. The method proposed in this paper is used to predict CO2-oil MMP of 5 samples of crude oil in China. The samples come from different oil fields, and the injected gas is pure CO2. The prediction results show that, compared with the slim-tube experiment method, the prediction error of this method for CO2-oil MMP is within 2%.
A series of experiments were conducted to investigate the flow pattern transitions and water holdup during oil–water–gas three-phase flow considering both a horizontal section and a vertical section of a transportation pipe simultaneously. The flowing media were white mineral oil, distilled water, and air. Dimensionless numbers controlling the multiphase flow were deduced to understand the scaling law of the flow process. The oil–water–gas three-phase flow was simplified as the two-phase flow of a gas and liquid mixture. Based on the experimental data, flow pattern maps were constructed in terms of the Reynolds number and the ratio of the superficial velocity of the gas to that of the liquid mixture for different Froude numbers. The original contributions of this work are that the relationship between the transient water holdup and the changes of the flow patterns in a transportation pipe with horizontal and vertical sections is established, providing a basis for judging the flow patterns in pipes in engineering practice. A dimensionless power-law correlation for the water holdup in the vertical section is presented based on the experimental data. The correlation can provide theoretical support for the design of oil and gas transport pipelines in industrial applications.
Water-cut detection of crude oil based on capacitive sensors and conductivity sensors are widely used in practice. However, the above two methods cannot achieve full-scale measurement of water-cut of crude oil. Besides, their measurement accuracy is sensitive to temperature, which greatly limits their application. A novel method of crude oil water-cut detection based on multi-sensor fusion is proposed in the paper. The proposed method uses a capacitive sensor and a conductivity sensor to measure the crude oil separately, and uses a temperature sensor to compensate the measurement result at the same time. Finally, the proposed method introduces a neural network for data fusion to predict the water content. The experiment results show that the proposed multi-sensor fusion technique performs better than capacitance and conductivity technique. The accuracy of this method is higher than single capacitance or conductivity method. When the water content is lower than 3%, the prediction error is less than 0.1%. When the water content is in a range from 3% to 10%, the prediction error is less than 0.5%. When the water content is in a range from 10% to 100%, the prediction error is less than 1.5%.
The CO2 huff-n-puff is an effective substitute technology to further improve oil recovery of natural fractured tight oil reservoirs after water flooding, for its high displacement efficiency and superior injectivity. The CO2 huff-n-puff process is influenced by many factors, such as miscible degree, complex fracture networks, and production schemes. What is worse, those influence facts affect each other making the process more complex. Many researchers concentrated on mechanisms and single sensitivity analysis of CO2 huff-n-puff process, whereas few optimized this process with the consideration of all influence factors and multiobjective to get favorable performance. We built multiobjective consisted of miscible degree, oil recovery, and gas replacing oil rate considering the aspects of CO2 flooding special characteristic, technical effectiveness, and economic feasibility, respectively. We have taken Yuan 284 tight oil block as a case, firstly investigated sensitivity analysis, and then optimized CO2 huff-n-puff process using orthogonal experiment design with multifactors and multiobjectives. The optimization results show CO2 huff-n-puff can significantly improve oil recovery by 8.87% original oil in place (OOIP) compared with water flooding, which offers guidelines for field operations.
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