5.1 Geological modelling results
Similar to other crystalline basement reservoirs, most of the pore volume exists within fractures, while the fracture distribution is entirely related to the existence of visible lineaments, as interpreted from seismic data.
Porosity distribution in this study was based on the Halo concept. The reservoir properties are known to decay with distance away from the fault and also with increasing depth. Therefore, high porosity values are observed in the upper zone of the basement and along fault planes. Also, in the vertical direction, porosity decreases as the distance from the top of the basement increases. This parameter is designated as vertical porosity. The vertical porosity versus depth represented by minimum, most likely, and maximum curves are presented in Table 3 and Figure 7. Based on this information, the final porosity of crystalline basement reservoirs was exhibited in Figure 8.
Table 3. The relationship between depth and porosity
Case
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The functions of porosity according to the Distance from top of basement
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Max
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Depth = 28141.40e-113.83Poro
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Most Likely
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Depth = 13441.19e-135.80Poro
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Min
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Depth = 4118.71e-166.47Poro
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Regarding the permeability models, based on relationship between the porosity and permeability on equation (5). From the DST data and porosity calculation, the porosity (Φmax ) and permeability (Kmax) maximum were estimated as follows: Kmax = 1000 mD and Φmax= 7%. Figures 9 illustrate the horizontal permeability distribution of the crystalline basement structure.
The porosity and permeability of this research has only 556,776 cells with 195,251 active cells, which is small enough to be used in the dynamic model, thus, no upscaling was required.
5.2 Hydrodynamic simulation models
5.2.1 DST matching
The initial model (before any modifications) shows quite optimistic results for both DSTs in TL-2X and TL-3X when performing DST matching. They should have resulted from very high permeability in the fracture system. Thus, a global permeability reduction was applied to get a better downhole pressure matching. While performing permeability reduction, the bottom-hole pressure behavior in TL-3X was much better than in TL-2X. It suggests that those two wells belong to different zones. Figure 10 present the visualization about permeability reduction for this study. A good match was acquired after multiply the TL-3X zone’s permeability by a factor of 0.2 and TL-2X zone’s permeability by a factor of 0.07. Figure 11 shows the bottom-hole pressure matching results for both TL-2X and TL-3X. It is indicated the excellent performance matching between simulated and measurement data. Thus, the history matched model could be used for investigating the oil production performance in this research.
5.2.2 Field Development Plan based simulation scenarios
The DST pressure matched reservoir simulation model was used to determine production and injection well locations, investigate the impact of an aquifer, and the effect of water injection and gas lift on field performance and its ultimate recovery for a fractured crystalline reservoir. All of the scenarios would be conducted in 30 years oil production life-cycle of the oil field.
5.2.2.1 Scenario 1: Well placement for injection and production considering aquifer support
Based on fractures distribution, 07 producer and 06 injector candidates were introduced. Several simulation runs were made to find the optimum locations and number of wells for development. The first step was to determine the optimum producer locations assuming 4 producers (P) (out of 7 candidates) and 3 injectors (which were 1I, 2I, and 3I). Next, sensitivity runs were made for both scenarios: with and without flank aquifer. Using aquifer size of 10 times, OIIP is prevalent practice for basement simulation models in other nearby fields, which was also used in this model. Additional assumptions for these runs were Tubing Head Pressure (THP) of 250 psia, gas-lift rate of 3MMSCFD/Well, and field production rate was capped at 12,000 STB/D.
Figure 12 illustrates the location of well producers and injectors for simulation scenario 1. This scenario will be investigated total 8 cases for well location of producers and injectors.
Figure 13 illustrate the field production performance by varying the well placement for producers and injectors for aquifer and no aquifer support. It can easily be observed that the case Case 1 & Case 1A achieving the best recovery factor for either with or without aquifer support (Figure 13a and Figure 13b). The 4 producers (1P, 2P, 3P, and 4P) were then used in the sensitivity runs to find the optimum locations for injectors. 3 out of 6 injector candidates were picked to run in both with and without aquifer scenarios. The injected volume was set as such the voidage equals to one. All other control points are the same as the above cases. The well location injector sensitivity indicated that the case (1I, 2I, and 3I) has excellent performance in field production total and oil recovery (Figure 13c and Figure 13d). Overall, the well producers (1P, 2P, 3P, and 4P) and injector (1I, 2I, and 3I) with aquifer support will give the highest oil production for the target crystalline fractured basement reservoirs
5.2.2.2 Scenario 2: considering gas lift application for improving oil production performance
Several simulations run with different GasLift rates to investigate the impact of gas lift on field performance for the case while no aquifer support existed. Case 4 used an injection rate with 4 MMSCFD that shows the highest result. However, the improvement is not significant for an additional 1MMSCFD to the base case (Case 1). Thus, a base case is still recommended for our simulation study. This work was investigated the gas lift rate for simulation study purposes. However, the gas lift operation is strongly dependent on well process. Also, the well model would be a better illustration of gas lift. The simulation study provides the possible option for a field development plan in fractured crystalline reservoirs. The simulation study for gas lift application is illustrated in Figure
5.2.2.3 Scenario 3: water injection effect
In order to make sure that water injection plays a vital role in-field performance, the two base cases were set to run without water injection. The simulation results clearly show that the recovery factor is reduced drastically when no water injection is applied. The simulation results are exhibited in Figure 15. This result is indicated the critical water flooding on oil field development in fractured crystalline reservoirs. The water injection will support maintaining reservoir pressure to accelerate oil production. Also, the water injection provides the waterfront sweeps the oil towards the production well.
Besides that, the water injection time and water volume injection were investigated in this work. The simulation results advise that the beginning water injection application is the best solution for oil production crystalline basement reservoirs. The later water injection would decrease the oil recovery efficiency. It is clear indicated in Figure 16a. In addition, the voidage injection was also the critical factor in the water-flooding operation. In this work, the voidage injection volume increased to lead to improving the oil recovery factor. Figure 16b is the evidence for our finding. However, the voidage injection volume is dependent on the reservoir connectivity and characterization of the specific field. Thus, this parameter should be carefully considered for the field development plan in a case by case.
5.2.2.3 Scenario 4: production rates
The next study is to look at the effect of changing plateau rate. Production constraints were set at 10,000 and 14,000 STBD then compared to Case 1. The plateau is more extended when the rate is reduced and shorter as the rate increases, as expected. Not much different in EUR is observed for production rates constraints. This scenario found that the field production rate does not affect field production development plans in crystalline basement reservoirs. The simulation results are clear illustration in Figure 17. However, the field production rate is not a strong influence in the simulation investigation for this work. However, the field production rate might be carefully for specific well operation in each field, especially the field with complex reservoirs such as crystalline basement reservoirs.
5.2.2.3 Scenario 4: Tubing head pressure
Sensitivity runs were made to see the impact of tubing head pressure (THP) on production. Same assumptions as in Case 1 were used, except the variation of THP. A little change in the recovery factor is observed when the THP increased to 430 psia as less drawdown in the well. Thus, THP should be carefully considered for field development in crystalline fractured basement reservoir. The simulation results was a highlight in figure 18. Tubing head pressure is considered for simulation study because it can monitor for field operation. The well operator could be followed the guideline from the field development plan. On the other hand, the practical operation might be changed to the specific situation. However, the simulation study supports smoothing the well process that is our objective to conduct investigation tubing head pressure.
Comparative analysis
To verify the crucial and feasibility of the workflow proposed in this research, a comparative analysis of the simulation results was also conducted and highlighted in Table 4. The simulation results of this research are compared by crystalline basement reservoir in Cuu Long basin, namely i) X field which have been successfully explored and optimization oil production, recently in Viet Nam (Ba et al. 2019). In our work, the simulation scenarios consider less wells than previous study. The main contribution of this study is novel approach of Halo model for geological modellng to get sucessul DST matching for future development plan. Also, this study did not use the long production history but our effort is better than previous work by proposing the comprehensive plan for oil production in granite basement reservoir. In the other hand, the detail of comparison is exhibited in Table 4.
Table 4. Comparison this work and previous study
Oil Field
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Field development method
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Oil Recovery improvement
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X field
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10 producers 4 injector
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10-13%
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This study
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4 producers 4 injectors
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10-24%
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This comparison indicates that our method has an improvement than previous study. The Halo method is one of the key factor for our research. The geological models consider the fracture length for distribution porosity and permeability in granite basement reservoir in this study.