# A New CO\({}_{2}\)-EOR Methods Screening Model Based on Interdependency Parameters
## 2 Materials and Methods  
Based on the collected data set, this research developed a screening model for miscible and immiscible CO\({}_{2}\)-EOR. The database was collected and documented according to references of actual fields worldwide to develop an improved and more realistic screening model. Data reference sources were taken from the Worldwide EOR Surveys reported by Oil and Gas Journal (OGJ) from 1986 to 2014, SPE publications, Elsevier publications, technical field reports, and AAPG bulletin. The workflow of the screening model is shown in Figure 1, which is divided into three stages. Stage 1: Data preparation. The quality of the data greatly affects the final result. Therefore, this stage plays an essential role in controlling data quality. This stage was carried out by collecting, sorting, and filling in missing data. For the sorting phase, only the successful and profitable CO\({}_{2}\)-EOR project data were chosen for miscible CO\({}_{2}\)-EOR. However, this was not the case for immiscible CO\({}_{2}\)-EOR due to limited published data. \begin{table}
\begin{tabular}{c} Sandstone or carbonate \\ \end{tabular} & \\ \hline \hline \end{tabular}
\end{table} 
Table 2: Existing screening criteria for immiscible CO\({}_{2}\)-EOR. The collected data also had to be reorganized because of duplications and typos in unit measurements reported in the data source. For the incomplete data due to missing values, mean imputation based on the same type of formation was applied for screening parameters other than MMP. A fully expert domain approach of Yellig-Metcalfe empirical correlation as a function of temperature (T), as shown in the following, was used for determining MMP [13; 14]. \[MMP\ (MPa)=12.6472+(0.01553\times T)+\left(1.24192\times 10^{-4}\times T^{2} \right)-\frac{716.9427}{T} \tag{1}\]  
Stage 2: Processing and analysis. These are the main steps in developing the screening model in this research. The data required for the process was collected in Stage 1. Then, a correlation analysis was carried out to determine the relationship between screening parameters with the Pearson linear correlation method. The results of the correlation analysis were synchronized with the expert domain rules to match the fundamental physical phenomena. Furthermore, the PCA method reduced the data dimension into several principal components (PCs). The PCs were the input for the MQC method in determining the screening limit simultaneously. For uncorrelated screening parameters, the screening limit was determined by simple descriptive statistics to obtain the individual screening limit for each parameter. Stage 2 results in a simultaneous and individual combination screening model as a new screening model for CO\({}_{2}\)-EOR. Linear assumptions were adopted in the statistical calculation methods, including Pearson correlation, PCA, and MQC. Figure 2 describes the relationship among the statisti  
Figure 1: CO\({}_{2}\)-EOR screening model workflow. cal methods used to create a simultaneous screening model. The first calculations on the covariance matrix measured changes in the two related variables linearly. The normalized covariance produced a correlation matrix that showed the strength and direction of the relationship among the screening parameters in a linear manner. The t-statistic test was used to check the significance of the correlation coefficients [15]. MQC is a method for simultaneously monitoring the variability of a multivariate case of two or more related quality characteristics. MQC method is suitable for a small number of process variables since the covariance matrix of MQC method will become singular when implemented in large and intercorrelated process variables [16]. A popular approach for reducing the dimensions of this variable is PCA [17]. The PCA method expresses information by constructing new variables in linear combinations called principal components (PC) without eliminating the original variables to minimize the excessive loss of information [18].