Comprehensive Evaluation of Gas-Liquid Cyclonic Separation Technologies

Abstract

PDVSA-Intevep has developed a portfolio of technologies for gas–liquid phase separation based on centrifugal forces effects on fluids of different densities. Research has been focused on both separation technologies cylindrical–conical cyclonic (CYCINT$^{{\circledR }}$) and multiple cylindrical cyclones ($\mathrm{{CIMCI}}^{{\circledR }}$), contemplating numerical modeling, construction, and extensive experimental tests conducted for a wide range of inflow rates and multiphase mixture properties (Brito et al. 2001, 2003, 2009; González et al. 2002; Martínez 2002; Carrasco 2008; Matson and Brito 2008; Cáliz et al. 2009; Valdez et al. 2009; Martínez 2010). Cyclonic separators are centrifugal technologies whose geometry construction promotes rotational flow within them. Centrifugal forces generated inside the separators conduct the fluid to follow a spiral trajectory with the heavier phase forced to flow nearby the separator walls, whilst the lighter phase is directed to the centre of the equipment ascending to the top of the device. This paper presents a comprehensive quantitative evaluation methodology based on a thorough parametric matrix developed to screen the most promising technologies based on experimental essays results. As a consequence, an optimal allocation of resources will allow further development of the top ranked technologies to conduct further field tests. The processing of experimental data from laboratory tests conducted on cyclonic technologies comprises parameters of great interest for the purpose of this evaluation. Gas carry under, liquid carry over, pressure loss, and generated G forces, in hand with liquid level control strategies, operational envelope width, operability, and compact design are some of the parameters used for the evaluation of technologies considered in this study. The evaluation of parameters was conducted through group categorization followed by variables grading on a 0–8 scale by means of a binary comparison methodology. The evaluation of technologies was conducted based on the results obtained during experimental tests and further analysis. As a result, an unbiased technology ranking was obtained, in which the multi-cylindrical technology ($\mathrm{{CIMCI}}^{{\circledR }}$) provides an overall best performance with emphasis in a superior gas separation efficiency and easier constructability, whilst the cylindrical-conic cyclonic technology (CYCINT$^{{\circledR }}$), on the other hand, presented the upmost liquid separation efficiency and wider operational envelope. Further efforts will focus on continuous development of these two technologies to provide more compact, efficient, and economical gas–liquid separation solutions.

Appendix A: Multiple Binary Decision Method

The binary comparison methodology employed for the technology evaluation is the Multiple Binary Decision Method (MBDM). The MBD method is used to assign weighting factors to different parameters comprised in an evaluation matrix and selecting, amongst different alternatives, the one that best qualifies according to the scores obtained. The procedure is detailed below and explained through a generic example:

• (1) Selection of the more relevant parameters to be considered. These parameters should be precisely defined in order to quantitatively assess the alternatives under evaluation.

• (2) Each selected parameter is assigned a weight resulting from a one-to-one comparison. This comparison determines which one of the evaluated parameters is the most important, by assigning it the value of ‘1’ and the least important resulting with a ‘0’ weight; following this procedure each parameter is compared to the remaining parameters. An illustration of the matrix obtained is shown in Table A.1.

• (3) Once the one-to-one comparison is completed and the indicative ‘ones’ and ‘zeros’ are obtained, the parameter weighting factors are computed by applying the following equation:

  $$\begin{aligned} {weight}=\frac{SW}{ST}\times 100, \end{aligned}$$

  (A.1)

  where SW represents the weight of each parameter and ST is the total sum of the parameters’ scores. Table A.2 is complemented to illustrate the weighting distribution.

• (4) Once the parameter weighting factors are obtained, the alternatives are evaluated. For the purpose of this illustration, three alternatives are proposed (I, II, and III). To obtain the most favourable alternative, all alternatives are compared to one another in reference to an alternate defined parameter. This way, alternatives I and II are compared to each other for parameter A, the alternative with the best performance gets a ‘1’; later alternatives II and III are compared and so on. Applying the weighting equation, the procedure is repeated, obtaining the alternatives’ scores by parameter. Tables A.3, A.4, A.5 and A.6 illustrate the procedure. Following the previously described steps the alternative’s partial score by parameter is obtained.

• (5) Scores obtained in Tables A.3, A.4, A.5 and A.6 are then weighted by the specific weight computed for each parameter within the Parameters’ Comparison Matrix (Table A.2). To exemplify this, take alternative II’s weight for parameter A (66.7 %), parameter A weights 33.3 % according to Table A.2, thereafter alternative II score within the general matrix is computed as follows:

  $$\begin{aligned} \frac{66.7\times 33.3}{100}=22.2\,\text {points}. \end{aligned}$$

  (A.2)

  Scores obtained from Eq. (A.2) are later tabulated and added together to obtain the general score for every alternative. The alternative with the highest score will be the preferred one. Table A.7 illustrates the general matrix of technology selection.

Table A.1 Parameters’ comparison matrix (MBDM)

Table A.2 Parameters’ comparison matrix with weights (MBDM)

Table A.3 Alternatives’ comparison matrix for parameter A (MBDM)

Table A.4 Alternatives’ comparison matrix for parameter B (MBDM)

Table A.5 Alternatives’ comparison matrix for parameter C (MBDM)

Table A.6 Alternatives’ comparison matrix for parameter D (MBDM)

Table A.7 Technology comparison general matrix (MBDM)