4. RESULTS AND DISCUSSION
4.12 Optimization analysis of the field model on the CMG CMOST
75 Before the waterflooding
process
After 39 hours of water injection
After 21 days of water injection
Figure 24. The water saturation profile for 3 different times of simulation
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rate and the layout of production injection wells, as specified in Table 9. Notably, all changes in injection rates are amalgamated and assigned a singular value denoted as "injection rate."
Table 9. Adjusting parameters before and after optimization
Injector J direction
Producer J direction
Injector I direction
Producer I
direction Injection rate
Base case 3 3 1 50 104.8
Optimal case 5 1 1 50 19.8
Table 10. The objective functions before and after optimization using an oil trading price of “37 $/bbl”
RF Water cut Field NPV, $ Oil Revenue, $
Water injection cost, $
Base case 73,7 99,99 -44934 75755.5 -120684.5
Optimal case 51.9 76 48218.5 73182.9 -24964.4
Table 11. The objective functions before and after optimization using an oil trading price of “66.3 $/bbl”
RF Water cut Field NPV, $ Oil Revenue, $
Water injection cost, $
Base case 73,7 99,99 15052 135736.7 -120684
Optimal case 52 76 106171.5 131135.9 -24964.4
Table 12. The objective functions before and after optimization using an oil trading price of “106 $/bbl”
RF Water cut Field NPV, $ Oil Revenue, $
Water injection cost, $
Base case 73,7 99,99 96330.5 217015 -120684.5
Optimal case 51.97 76 184833.7 209798 -24964.4
The aforementioned Table 10, 11 and 12 illustrates that the implementation of new values obtained from the optimization analysis has yielded favorable outcomes. A study focused on the optimization of three distinct oil prices for the purpose of estimating revenue has been conducted. The results indicate that optimal parameter values for all three optimization studies are the same and are presented in Table 9. The optimal injection rate is determined to be 19.8
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m3/d based on the findings of the three optimization studies. A comparison of the base case and optimal case for all oil prices indicates that the difference in oil revenue is negligible.
However, a significant decrease in the expenses associated with water injection has been observed in the optimal case due to the reduction in the water injection rate. Consequently, even with a fivefold reduction in the cash outflows for water injection, the optimal values have yielded equivalent revenues to those of the base case. In the base case, which had the lowest oil price of “37 $/bbl,” expenditures associated with water injection exceeded the cash inflows resulting from oil trading, causing the net present value (NPV) of the field to become negative.
On the other hand, the optimal case has turned the NPV from negative to positive, making the field profitable. The average and high oil trading prices have resulted in promising outcomes with the NPV increasing seven times and two times, respectively. Another vital objective function, the water cut, showed the same decreasing trend for all optimal cases, decreasing from 99.99% to 76%. This indicates a decrease in the expenditures associated with the production of water from the reservoir, which will contribute to the NPV. Following the substitution of the base case design values with the new values obtained from the study, new plots pertaining to water cut, cumulative oil production, recovery factor, and the pore volume of injected fluid have been generated (see Figure 25).
Water cut profile Cumulative oil production
Oil production vs PV injected Recovery Factor vs Time
Figure 25. Field model outcomes after using optimal values of adjusted parameters
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The reduction of water cut is a critical aspect of this process. Afi (2017) reported that well intervention led to an increase in water cut in one of their wells in 2014, resulting in a rise in the average water cut from 84% to 91.5%. Consequently, oil production from the well decreased by approximately 125 barrels of oil per day (bopd). This example highlights the significance of maintaining a low water cut in the oil and gas industry. The water cut profile demonstrates that the substitution of optimal values leads to a more stable front of displacing fluid with a delayed water breakthrough time. The water cut percentage gradually increases, with the highest point being fixed at 95% at the end of the waterflooding process. After polymer injection, the water cut percentage experiences fluctuations, dropping tremendously to 43%
and then restoring back to 65%. The latter value remains constant until the end of the polymer flooding. In the base case, a high injection rate of 105 m3/day creates a highly permeable channel through which injected water flows, reaching the production well within 14 days, considered as early water breakthrough. All subsequent injected fluids flow through the same channel, bypassing more mobile oil volumes in the pore spacing. In the 44-day simulation period of the base case, the injected fluid pore volume consists of 36 PV. In contrast, the optimal case involves injecting a minimal pore volume of fluid of around 1.7 PV during the same period, which effectively displaces a large volume of oil compared to the base case.
Nevertheless, in the optimal field model case the Flaxseed gum natural polymer injection shows an increase in RF to 13% over the waterflooding. The oil saturation profile, as shown in Figure 26, validates the earlier observations.
At the end of floodings for optimal case At the end of floodings for the base case
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Figure 26. Oil saturation propagation for the base case and optimized case
The figure above illustrates that in the base case, the distribution of oil saturation within the pore spaces becomes disorderly at the end of the flooding process. After the 44-day simulation period, the oil saturation distribution in all grid blocks is close to the residual oil saturation value. The simulation outcomes suggest that after 39 days of simulation, the water displacement front reached all the grid blocks, and residual oil saturation was achieved in almost every grid block. In contrast, in the optimal case, the oil saturation profile after the 44- day simulation period shows an initial oil saturation value near the producing well, indicating favorable displacement where the mobility difference between the displacing and displaced phases is not significant. The distribution front of water and polymer flooding is stable and piston-like, displacing all recoverable oil and leaving only residual oil saturation behind the displacement front. As the injected fluids did not reach the zones around the producing well, the oil saturation in those zones retains the initial value. According to Wang's (1998) findings, in the staggered line drive pattern, when the mobility ratio is favorable, the displacement pattern is characterized by radial flow around the injector before the front reaches the nearest corner. Subsequently, the front reaches the closest corner first. Our study has observed the same flow pattern for the water saturation distribution profile under optimal conditions. It is noteworthy to mention that the reservoir still holds potential for oil extraction as the residual oil saturation has not yet been reached. Consequently, this analysis suggests that the optimized case is more profitable in the long run since it can sustain oil production at that high level.
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