INTRODUCTION ONS 24 4 2S EN EI The methodology used here is the Computer Modeling Group (CMG) IMEX and Saphir. CMG IMEX will produce well test / isochronal data to determine stabilized flow coefficients. In contrast, Saphir will be used to determine when stabilization time can be achieved by looking at the performance of pressure changes in the pressure derivative graph. Finally, the model deliverability results will be seen, which will get a stabilized flow coefficient value. Figure | shows the work steps summarized in the form of a flowchart in this study. From the Figure 1, here are some explanations of the methodology in this study. Reservoir Modeling Evaluation In evaluating reservoir modelling, one of the methods above is used, which is CMG IMEX. We use a 10% value of porosity which is the maximum considering on tight gas reservoir. We associate Dashtgard et al. (2008) results for the permeability, which shows the relationship between porosity and permeability of several types of existing reservoirs. Dashtgard et al. (2008), in their study, inject the COz into certain formations and reservoirs to get a relationship between permeability and porosity, shown in Figure 2. From Figure 2, we decided to use K /@ = 3, where we decided to take that comparison to facilitate the results obtained. Vol. 10 No. 1, March 2021, pp 18-31 Figure 2. Permeability vs porosity showing flow units for conventional, tight gas and shale gas reservoirs based 01 process (or delivery) speed (K/@) (Dashtgard et al., 2008) Figure 3. The Shape of Reservoir Model Figure 5. Well Test at High Drainage Rad, Mid Drainage Rad, Low Drainage Rad Table 1. Comparison Time Stabilization Model with John Lee Equation Figure 10. Well Test at Number of Relative Permeabilities Figure 11. Example of Pressure Derivative Plot Figure 12. (change of lop AP on Pressure Derivative plo In determining the stabilized C value, isochronal data is needed, which will be used as initial input data in finding these values. Isochronal data is obtained from the reservoir model results in well test by performing some flow rate sensitivity in the gas well. Figure 13 shows that by determining some time duration on the well test curve, bottom hole pressure data can be obtained at that time duration. Table 2 shows the results of the isochronal data conclusions obtained from the results of the well test so that the isochronal data will be used as input data in determining the stabilized flow coefficient. Figure 13. Isochronal Data from Well Test Results Table 2. Isochronal Data from Well Test Model. A Deliverability Method for Estimating Stabilized Gas Well Performance during Transient Flow in Unconventional Reservoir (A Yasutra. C Orliando) Table 3. Deliverability Exponent value of each isochronal data A deliverability plot can be obtained from isochronal data by plotted log pressured squared vs log Q as shown in Figure 14. Furthermore, the results of isochronal data can be determined by the value of the deliverability exponent on any existing data using Eq. 12. Table 3 shows the deliverability exponent results, where usually the range in the value is between 0.5 - 1.0. The value of the range depends on the Figure 14. Deliverability Plot flow characteristics that exist. If the value of n approaches 0.5, then the flow is turbulent, whereas if it is close to 1.0, the flow is more likely to be laminar. To prove the results of true exponent deliverability can be likened to the Power equation of Rawlins and Schellhardt, we can see in Figure 15 that the value of n in each plot's power equation is the same with a result the deliverability exponent derived in Eq. 12. Then, the average result of deliverability exponent data in Eq. 13 is used to determine the stabilized flow 1 ci/n results will be averaged based on the number of flow rate sensitivity in the previous. The results can be 1 c1/n a graph is obtained in Figure 16. When a linear trendline is made on the line, we can get the equation's results to determine the stabilized C value. coefficient from which isochronal data will be inputted into Eq. 2 and then from each of the existing seen in Table 4. In the end, when plotted results with log t based on time duration in isochronal data, Figure 15. Rate vs Pressure Squared with Trendline Power Figure 17. Comparison IPR Model with Validation Table 5. Results Comparison of model flow coefficient values with the results of validation Figure 18. Comparison Model IPR Flow Coefficient Stabilized with IPR Flow Coefficient when in Transient Period In determining the time stabilization value in the tight gas reservoir model, it ta only in a matter of hours but even for days. Because of the flow situation wit many technologies are developed to increase the permeability and porosity va kes quite a long time, not h the reservoir condition, ue. Figure 13 shows that there is a significant pressure change on day 571. The John Lee equation model can also be obtained in days and can even be calculated in years. Also, the development of the Hashem and Kazemi equations can be applied to the tight gas reservoir model (Hashem & Kazemi, 1996). From a prediction in the transient period, a stabilized C value can be determined for the future. The derived exponent equation can help complete the determination of the flow coefficient. Figure 18. Comparison Model IPR Flow Coefficient Stabilized with IPR Flow Coefficient when in Transient Period
