Determination of gas dispersion in vapor extraction of heavy oil and bitumen

In this work, a mathematical model is developed and simulated to determine gas dispersion along with solubility during the vapor extraction (Vapex) of live oil from a laboratory scale physical model. The physical model is a rectangular block of homogenous porous medium saturated with heavy oil and bitumen. At a given temperature and pressure, the block is initially exposed on its side to a solvent gas, which diffuses into the medium and gets absorbed. The absorption of gas reduces the viscosity of heavy oil and bitumen causing it to drain under gravity. The low-viscosity “live oil” is produced at the bottom of the porous block. The production of live oil with time is accompanied by the shrinkage of oil in the block as well as its increased exposure to gas from top. These phenomena of Vapex are described by the mathematical model, which is used to calculate live oil production with various values of gas solubility and dispersion. Their optimal values are determined for the vapor extraction of Cold Lake bitumen with butane by matching calculated live oil production with its experimental values published earlier.     

塞浦路斯考古博物馆

正建筑师Theoni Xanthi获得新塞浦路斯国际建筑竞赛一等奖。此次竞赛分为两个阶段,第一阶段共收到129份参赛作品,第二阶段入围7份作品。项目耗资7 500万欧元,新的考古博物馆将容纳塞浦路斯考古机构所有的重要收藏;同时,博物馆作为"文化之岛"——尼科西亚市的多功能文化设施,功能包括文物部办公室、会议室、图书馆、咖啡馆及餐厅、文化活动平台及一个达42 000平方米的开放的底层景观平台。考古博物馆坐落在离尼科西亚中世纪城墙不远的地方,处于城市绿地与城市中心区的中间地带。因此,作为应对,     

NETWORK SIMULATION OF RELATIVE PERMEABILITY CURVES USING A BOND CORRELATED-SITE PERCOLATION MODEL OF PORE STRUCTURE

This paper deals with the conductivity and relative conductivity properties of irregular 3-D networks of pores that represent the continua of the oil phase and the aqueous phase respectively, during steady slate two phase flow in porous media. The relative conductivity properties presented, correspond to the saturation history defined by the drainage, imbibition and secondary drainage capillary pressure curves respectively. Use has been made of the pore accessibility history of a 20 × 20 × 20 network and a 10 × 10 × 10 nodes core portion of the network is used to write the flow equations. A set of 1001 linear equations is solved using the Preconditioned Conjugate Gradients Method for the conductivities of the wetting phase and the non-wetting phase respectively, as a function of network saturation and saturation history. The effects of pore throat size distribution and pore body size distribution on relative permeability behaviour has been investigated. Furthermore, the effect of conductivity function q(D) proportional to Dⁿ (n = 0, 1, 2, 3, 4) on relative permeability behaviour was investigated, where D stands for pore throat diameter and n is an exponent depending on pore geometry.

The results of this work are very significant in elucidating the following points that are not clearly stated in the literature: 1) using the bypassing as the only trapping mechanism, the primary drainage and secondary drainage relative permeability curves are in agreement with experimental findings; 2) more realistic displacement mechanisms in secondary imbibition are required to have better agreement with experimental findings; 3) the correlated network models after the site type problem of percolation theory are realistic models of pore structure; 4) the conductivity function q(D) proportional to D³ is the most appropriate pore throat conductivity function because of lamelar like pore geometries; and 5) accurate prediction of the effective permeability requires knowledge of the porosity and the detailed pore geometry in the pore network, in addition to pore size distributions used in the network simulation.     

Nonsurgical infarctectomy in acute experimental myocardial infarction

This study examines whether a catheter mounted left intraventricular balloon may prevent left ventricular (LV) dysfunction following acute experimental myocardial infarction. In 10 anesthetized pigs, multiple coronary arterial ligations were applied around the apex of the heart. LV end-diastolic pressure (LVEDP), aortic flow (AF), and LV long and short axis fractional shortening (FS) were measured before and at 15 min intervals after ligations. At the 60th min after ligation, the LV long axis FS and AF decreased by 7.2 +/- 2.6% (p < 0.05) and 13.25 +/- 2.68% (p < 0.01), respectively, and the LVEDP increased by 4.3 +/- 1.1 mm Hg (p < 0.01) while no change was noted in the LV short axis FS. An intraventricular catheter mounted nonpulsating balloon was positioned over the endocardium of the infarcted area at the LV apex. Inflation of the nonpulsating balloon to an optimal volume, which was found to be equal to 8-10% of the LV end-diastolic volume, resulted in a reduction (by 3.8 +/- 1.2 mm Hg, p < 0.01) of the already increased LVEDP and in an increase (by 6.6 +/- 2.1%, p < 0.05) in the LV short axis FS while no statistically significant change was noted in the AF and LV long axis FS. It is concluded that an intraventricular catheter mounted balloon patch positioned over the endocardium of the infarcted area may ameliorate early LV dysfunction, possibly by interfering with the functional geometry of the LV contraction.     

Statistical analysis of the porous microstructure as a method for estimating reservoir permeability

Back-scatter scanning electron microscope images of cross-sections of several porous rocks were analyzed to determine the statistical properties of the porous microstructure. For statistically homogeneous media these properties are the porosity and autocorrelation function. A length scale (integral correlation scale), characteristic of the spatial distribution of porosity, was obtained as the integral of the autocorrelation function. The permeability of a wide variety of rock samples, including those investigated by Coskun and Wardlaw (1993), was adequately described by an empirical equation of the form k α φ^aI_S^b, where φ is the porosity and I_S is the integral correlation scale. The results obtained have useful application in the estimation of reservoir permeability from samples not amenable to experimental testing (e.g., drill cuttings) and provide support for the use of statistical methods for the generation of 3-D model porous media.     

Fuzzy cell Hough transform for curve detection

In this paper a new variation of Hough Transform is proposed. It can be used to detect shapes or contours in an image, with better accuracy, especially in noisy images. The parameter space of Hough Transform is split into fuzzy cells which are defined as fuzzy numbers. This fuzzy split provides the advantage to use the uncertainty of the contour point location which is increased when noisy images are used. By using fuzzy cells, each contour point in the spatial domain contributes in more than one fuzzy cell in the parameter space. The array that is created after the fuzzy voting process is smoother than in the crisp case and the effect of noise is reduced. The curves can now be detected with better accuracy. The computation time that is slightly increased by this method, can be minimized in comparison with classical Hough Transform, by using recursively the fuzzy voting process in a roughly split parameter space, to create a multiresolution fuzzily split parameter space.     

A fuzzy c-means-type algorithm for clustering of data with mixed numeric and categorical attributes employing a probabilistic dissimilarity functional

Gath–Geva (GG) algorithm is one of the most popular methodologies for fuzzy c-means (FCM)-type clustering of data comprising numeric attributes; it is based on the assumption of data deriving from clusters of Gaussian form, a much more flexible construction compared to the spherical clusters assumption of the original FCM. In this paper, we introduce an extension of the GG algorithm to allow for the effective handling of data with mixed numeric and categorical attributes. Traditionally, fuzzy clustering of such data is conducted by means of the fuzzy k-prototypes algorithm, which merely consists in the execution of the original FCM algorithm using a different dissimilarity functional, suitable for attributes with mixed numeric and categorical attributes. On the contrary, in this work we provide a novel FCM-type algorithm employing a fully probabilistic dissimilarity functional for handling data with mixed-type attributes. Our approach utilizes a fuzzy objective function regularized by Kullback–Leibler (KL) divergence information, and is formulated on the basis of a set of probabilistic assumptions regarding the form of the derived clusters. We evaluate the efficacy of the proposed approach using benchmark data, and we compare it with competing fuzzy and non-fuzzy clustering algorithms.     

Estimation of breakthrough time for water coning in fractured systems: Experimental study and connectionist modeling

Water coning in petroleum reservoirs leads to lower well productivity and higher operational costs. Adequate knowledge of coning phenomena and breakthrough time is essential to overcome this issue. A series of experiments using fractured porous media models were conducted to investigate the effects of production process and pore structure characteristics on water coning. In addition, a hybrid artificial neural network (ANN) with particle swarm optimization (PSO) algorithm was applied to predict breakthrough time of water coning as a function of production rate and physical model properties. Data from the literature combined with experimental data generated in this study were used to develop and verify the ANN‐PSO model. A good correlation was found between the predicted and real data sets having an absolute maximum error percentage less than 9%. The developed ANN‐PSO model is able to estimate breakthrough time and critical production rate with higher accuracy compared to the conventional or back propagation (BP) ANN (ANN‐BP) and common correlations. The presence of vertical fractures was found to accelerate considerably the water coning phenomena during oil production. Results of this study using combined data suggest the potential application of ANN‐PSO in predicting the water breakthrough time and critical production rate that are critical in designing and evaluating production strategies for naturally fractured reservoirs. © 2014 American Institute of Chemical Engineers AIChE J, 60: 1905–1919, 2014     

Multimodal decision-level fusion for person authentication

The use of clustering algorithms for decision-level data fusion is proposed. Person authentication results coming from several modalities (e.g., still image, speech), are combined by using fuzzy k-means (FKM) and fuzzy vector quantization (FVQ) algorithms, and a median radial basis function (MRBF) network. The quality measure of the modalities data is used for fuzzification. Two modifications of the FKM and FVQ algorithms, based on a fuzzy vector distance definition, are proposed to handle the fuzzy data and utilize the quality measure. Simulations show that fuzzy clustering algorithms have better performance compared to the classical clustering algorithms and other known fusion algorithms. MRBF has better performance especially when two modalities are combined. Moreover, the use of the quality via the proposed modified algorithms increases the performance of the fusion system