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In this paper, the DBR all-visible mercury-free high-temperature and high-pressure multifunctional formation fluid PVT analyzer developed and produced by Schlumberger company is used to conduct an experimental study on phase behavior characteristics of one offshore high CO2 condensate gas wells. The experiments include two-phase flash experiment, constant composition expansion experiment (CCE experiment), and constant volume depletion experiment (CVD experiment). Experimental results show that the higher the CO2 content in the condensate gas system, the higher the gas-oil ratio of condensate gas, the greater the density of condensate oil, the higher the dew point pressure of condensate gas, the greater the relative volume of condensate gas, the smaller the amount of retrograde condensate oil. And the higher the CO2 content in the condensate gas system, the phase diagram is shifted to the left and up, the critical point of the phase diagram is shifted to the lower left, the smaller the area of the two-phase envelope, the lighter the condensate gas system, the condensate oil recovery is higher. The above experimental results revealed that CO2 is well soluble with condensate gas, the expansion capacity of the condensate gas system was slightly enhanced, and because CO2 has a good extraction capacity, the light components of condensate gas were constantly extracted, the retrograde condensate rate of condensate oil decreases, and the maximum retrograde condensate volume also decreased. However, the condensate oil was produced along with the natural gas, and the higher the CO2 content, the stronger the extraction, the more condensate oil was produced. It is mainly because CO2 has the strong gasification and extraction capacity, on the one hand, the retrograde condensation of condensate gas was inhibited, and on the other hand, reverse evaporation of condensate oil was enhanced. The above experimental results indicate the law of the effect of CO2 on the phase behavior characteristics of condensate gas reservoirs, providing theoretical basis and guidance for the efficient development of condensate gas reservoirs at sea. [ABSTRACT FROM AUTHOR]

ABSTRACT With the ongoing development of rendering technology, computer graphics (CG) are sometimes so photorealistic that to distinguish them from photographic (PG) images by human eyes has become difficult. To this end, many methods have been developed for automatic CG and PG classification. In this paper, we present a simple, yet efficient, multiresolution approach to distinguish CG from PG based on uniform gray-scale invariant local binary patterns (LBPs) with the help of support vector machines (SVM). We select YCbCr as the color model. The original Joint Photographic Experts Group (JPEG) coefficients of Y, Cb, and Cr components and their prediction errors are used for two LBP operators. From each 2D array and each LBP operator, we obtain 59 uniform LBP features. In total, 12 groups of 59 features are obtained from each image. But after multiresolution analysis, we select six groups of 59 features for CG and PG classification. The proposed features have been tested with thousands of CG and PG. Classification accuracy reaches 95.1% with support vector machines and outperforms the state-of-the-art works. Copyright © 2013 John Wiley & Sons, Ltd. [ABSTRACT FROM AUTHOR]