The 8th International Chemical Engineering Congress & Exhibition (IChEC 2014) Kish, Iran, 24-27 February, 2014

Field Scale Analysis of Carbon dioxide, Nitrogen, and Lean gas

Injection Scenarios in Pazanan Gas Condensate Reservoirê

H.Rahmanifard, H. Amirzadeh, A. Rasouli, A. H. Amouri Corresponding Author’s Address: Drilling Fluids Engineering and Waste Management Department, Deputy

Managing Director of NIDC Projects, Ahwaz, Iran Corresponding Author’s E-mail: rahmanyfard@gmail.com

Abstract Upon depletion, falling the reservoir pressure below the dew-point of hydrocarbon mixture results in liquid condensation around the wellbore. This liquid barrier causes severe reductions in gas production rates, the permanent loss of a large portion of volatile and valuable condensates, and a wrong estimation of well deliverability. It is believed that applying the Generalized Pseudo Pressure (GPP) method leads to more accurate modeling of reservoir performance. Hence, using a compositional simulator, a sector of Pazanan reservoir (in the southwest of Iran) is modeled with two different permeabilities: with the average permeability of 42 md (original case) and 0.1 md (tight case). The results obtained from simulations demonstrate that the GPP method leads to acceptable results in permeable case while, in tight system, it underestimates the well deliverability. Furthermore, since gas injection/cycling is the main recovery process in gas condensate reservoir, using the GPP method, various gas injection scenarios in the reservoir (original case) at pressures below the dew point (maximum condensate appearance) are investigated which shows that gas cycling scenario is the optimum solution.

Keywords: Gas condensate; Generalized Pseudo Pressure, Gas injection/cycling

Introduction In order to calculate the well deliverability in a gas condensate reservoir, the conventional approach is to build a fine grid compositional model, using either a single-well model with a fine grid near to the wellbore, or a full-field model with the local grid refinement around the well. Despite the acceptable performance of these methods (fine grids and LGRs), their utilizations in a much more complex simulation model, can lead to a significant increase in run time; and may cause numerical and convergence problems [1]. So based on observations for many gas condensate systems, a simple method to accurately calculate the pseudopressure function was proposed by Fevang and Whitson [2]. In their method, the well inflow is calculated from a pseudopressure integral, which is analogous to the standard pseudopressure function used for dry gas reservoirs, but it also includes the gas relative permeability to take account of the reduced mobility due to liquid build-up near the well. Therefore, the methodological plan of this study is to assess the effect the Generalized Pseudo Pressure method on the performance of permeable and tight systems.

Analysis of different injection scenarios

Model preparation The grid model which is representative of a sector of Pazanan reservoir, contains 50 × 1 × 2 grid cells with inner grid cell size in the radial direction of 0.2 ft. The grid cell size in the radial direction varies geometrically with ri/ri-1 = constant. The external radius of the model is about 6330 ft. The reservoir with the initial pressure of 3400 psia contains rich gas condensate with the initial solution oil-gas ratio of 175 STB/MMscf and the initial saturation pressure of 3300 psia. To verify the multi-mechanistic flow and the pseudopressure option in a gas condensate reservoir, in addition to the permeable case which was representative of Pazanan reservoir with the average permeability of 42 md, a tight system with the permeability of 0.1 md was also considered. The permeable and tight cases were simulated with minimum well BHP constraint of about 1500 psia and maximum gas production rate constraint of 20 MMSCFD and 10 MMSCFD, respectively. Model porosity, connate water saturation, and the plateau gas production period are 0.198, 0.245, and a 30 year period for all cases, respectively. To model PVT behavior and fluid equilibrium, the modified Peng-Robinson equation of state is utilized [3]. This work uses an eleven component lumped of Pazanan retrograde gas reservoir. The reservoir relative permeability and capillary pressure values are also used [4]. Although, the effects of rock and water compressibilities on reservoir performance are negligible (4e-6 psi-1 and 2.216e-6 psi-1, respectively), they are considered. The Assessment of GPP Method for Calculation of Well Deliverability To further investigate the GPP method, the same radial grid model as the fine grid and an equivalent coarse grid one were used. The corresponding coarse grid model contained 20 × 1 × 1 grid cells with the first grid cell size in radial direction of 110 ft. simulations were performed for two cases: permeable and tight. The simulated performance with fine grid model and coarse grid models (with and without pseudopressure) for permeable and tight cases are shown in Figure 1a and b. Although, the gas production rate was over-predicted in the coarse grid model for both systems, the simulated performance of coarse grid with pseudopressure option and fine grid was quite similar in the permeable one while, for the tight system, utilizing the GPP method caused significant under-estimation of gas withdrawal rate.

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Figure 1. Comparison of gas production rate predictions for fine and coarse grid models (with and without the GPP option) for (a) permeable system and (b) tight system,

Results In this part a radial grid model contained 20 × 1 × 1 cells with the GPP method was utilized. Other model properties were the same as before. The investigated reservoir was allowed to produce under natural depletion mechanism until the time that maximum condensate appeared (3800 days). At this time, for condensate re-evaporation and partial pressure maintenance,

The 8th International Chemical Engineering Congress & Exhibition (IChEC 2014) Kish, Iran, 24-27 February, 2014

because of the better performance of gas injection among other solutions, different gas injection scenarios including Carbon dioxide, Nitrogen, and Gas cycling (the lean gas stream produced from NGL 900 factory) was started. It is essential to mention that for injection cases, an injection well was placed in the twentieth block with the maximum well BHP constraint of about 2000 psia and maximum gas injection rate constraint of 10 MMSCFD, 6.5 MMSCFD, and 9 MMSCFD for carbon dioxide, nitrogen, and gas cycling scenarios, respectively. Furthermore, in order to show the optimum recovery scheme (maximum hydrocarbon production and minimum liquid dropout), comparisons between injection scenarios and the case without any injection over some key parameters (condensate saturation around wellbore, reservoir condensate saturation, gas and condensate production rates, and cumulative condensate and gas production) are made (as shown in Figure 2a-e).

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Figure 2 various gas injection scenarios performance versus simulation time on (a) reservoir condensate saturation, (b) condensate saturation near wellbore (c) gas production rate, (d) condensate production rate (the time scale in the enlarged part is in days), and (e) Cumulative production of gas and condensate

Analysis of different injection scenarios

Conclusions • Despite the acceptable performance of pseudopressure method proposed by Fevang and Whitson for permeable cases, due to the severe effect of condensate blockage in tight cases (less than 0.1 md), this method gives pessimistic estimations of reservoir performance. Therefore, for tight cases the conventional approach (using fine grids or LGRs around wellbore) is suggested. • Although gas injection in gas condensate reservoirs causes higher condensate saturation around the wellbore, it leads to partial pressure maintenance, a sharp decrease in reservoir condensate saturation, and higher hydrocarbon (gas and condensate) production. • Because of more stable displacement front in gas cycling scenario, this case has got the highest gas and condensate recovery. • Finally, in order to choose the optimum scheme and evaluate its feasibility the detailed economic analyses are usually recommended. Moreover, capillary number and non-Darcy flow effects have been ignored in this study, which are areas open for research by future studies in the area.

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