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Article

Numerical Simulation Study on Optimization of Development Parameters of Condensate Gas Reservoirs

by
Kai Zhu
,
Lingjie Gao
and
Fengrui Sun
*
School of Energy Resources, China University of Geosciences, Beijing 100083, China
*
Author to whom correspondence should be addressed.
Processes 2024, 12(10), 2069; https://doi.org/10.3390/pr12102069
Submission received: 9 August 2024 / Revised: 19 September 2024 / Accepted: 23 September 2024 / Published: 24 September 2024
(This article belongs to the Section Energy Systems)
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Abstract

:
Due to the retrograde condensation phenomenon in the development process, the fluid phase change is complex, and it becomes particularly difficult to accurately describe the fluid flow characteristics and residual oil and gas distribution characteristics during the development of condensate gas reservoirs. It is difficult to select the development program and subsequent dynamic adjustment for the efficient, reasonable, and sustainable development of condensate gas reservoirs. In this paper, the phase characteristics of condensate gas reservoirs are clarified; the basic fluid model is created by using computer modeling, using Win-Prop; and in view of the characteristics of the target condensate gas reservoirs, the CMG (Computer Modeling Group) numerical simulation method is applied to study the effects of six factors, the thickness of the reservoir, permeability, porosity, rock compression coefficient, the ratio of the vertical permeability to the horizontal permeability, and the injection of different media, on the development effect through the study of different development parameters of gas condensate reservoirs. The purpose of this study is to provide guidance for the rational development of condensate gas reservoirs in practical production.

1. Introduction

With the continuous improvement of exploration technology, the exploitation of oil and gas resources has gradually shifted from conventional areas to unconventional areas, and coalbed methane and tight oil and gas have become important sources of oil and gas supply [1,2]. Unconventional hydrocarbons have two key markers: one is the continuous distribution of hydrocarbons over a large area, with insignificant trap boundaries; the other is the absence of natural industrially stabilized production and the lack of obvious Darcy seepage [2,3]. In the process of exploration and development, the proportion of condensate gas reservoir is increasing year by year. Therefore, gas condensate has great exploitation potential [4,5]. According to the data released by the Ministry of Natural Resources at the end of 2022, the proven geological reserves of condensate in China are about 7.1 × 108 t, and there are 163 condensate gas fields (reservoirs) in total [6]. Among them, the condensate gas fields with proven reserves greater than 1000 × 104 t are mainly distributed in the Tarim Basin and Bohai Bay Basin. By the end of 2022, the data of proved condensate reserves show that the Tarim Basin ranks first, and the Bohai Bay Basin ranks second, followed by the Sichuan Basin and the South China Sea [7,8].
Condensate gas reservoirs are a special type of hydrocarbon reservoir situated between conventional oil reservoirs and gas reservoirs [9]. They are characterized by original reservoir pressure higher than the critical pressure and a reservoir temperature between the critical temperature and the critical condensation temperature. Therefore, the hydrocarbon system in the original reservoir exists in a gaseous state [8,10]. When production begins, the reservoir pressure decreases to the dew point pressure, at which the liquid phase separates from the gas phase [11,12]. As gas is produced and pressure continues to decline, more liquid phase condenses, forming condensate in the reservoir. Phase changes increase the complexity of developing condensate gas reservoirs, highlighting the importance of phase behavior simulation studies for these reservoirs [13,14].
The main difficulties in exploiting condensate gas reservoirs are as follows: Firstly, the vertical distribution of gas caps and oil rings is complex, and they are in a unified hydrodynamic system [15]. Improper development will lead to fluid interface migration, resulting in oil and gas migration, water invasion and other problems, so that oil and gas resources are lost in the formation, and the development effect is poor; secondly, the law of formation fluid flow is extremely complex, and there are many flow patterns in the development process [16]. When the gas cap pressure is reduced to below the dew point pressure, the retrograde condensate phenomenon will also appear in the gas condensate, resulting in condensate precipitation [17]. Thirdly, the component contents of the gas cap and oil ring in the reservoir are different, the distribution of fluid components in different regions is quite different, and the state equations are also different. It is necessary to fit the fluid phase characteristics of gas cap and oil ring fluids [16,18].
In order to study the influence of various parameters on the exploitation of condensate gas reservoirs, this paper uses CMG software (version 2021) to study a condensate gas reservoir by establishing a numerical model. Li et al. [19] used the numerical simulation method to analyze the effect of the dry gas–nitrogen alternate injection method on the development of condensate gas reservoirs; the results show that the dry gas–nitrogen alternate injection method can improve the recovery rate of condensate in condensate gas reservoirs. The recovery rate of condensate is close to the recovery rate of condensate during dry gas injection development, but it can reduce the amount of dry gas reinjection by 50% and improve the economic benefits of condensate gas reservoir development. Dong et al. [20] took the Yaha-5 condensate gas reservoir as an example. Through numerical simulation, the three production methods of depletion mining, water injection mining, and gas injection mining are compared and analyzed. The results show that water injection and gas injection are better than depletion mining, and gas injection is better than water injection. In particular, the large well spacing gas injection development method can not only delay the gas channel and improve the gas injection efficiency, but also greatly improve the condensate oil recovery. Hu et al. [21] studied the impact of energy control (i.e., pressure control) on development efficiency during the extraction process of condensate gas reservoirs and used reservoir numerical simulation to demonstrate the influence of pressure on the distribution and production of gas condensate; the results indicate that pressure has a significant impact on the production of condensate in high/medium-permeability condensate gas reservoirs, while its impact on low-permeability or tight condensate gas reservoirs is not significant. Hou [22] conducted experiments and established a numerical model of CO2 flooding condensate mechanism and storage in near-critical condensate gas reservoirs; the results show that the injection–production well pattern, injection pressure, injection rate, and injection volume have a very important influence on the degree of condensate oil production. Under the same other conditions, only considering the influence of single-factor conditions, the higher the injection pressure, the higher the recovery degree of condensate and the greater the storage potential. Jiang and Younis [23] used a multi-component molecular simulation method to numerically analyze the enhanced oil recovery of carbon dioxide steam stimulation in complex fractured condensate gas reservoirs. On this basis, several design elements such as the number of cycles and the length of injection cycle in the process of steam stimulation were briefly studied. For experimental analysis and research methods, Yu [24] conducted a study on gas cap and bottom water reservoirs with a high concentration of condensate offshore. Firstly, the impact of gas injection on the phase change in gas condensate in the reservoir was analyzed. Then, numerical simulation of the reservoir was used to study the reasonable development method of the reservoir. The research results showed that injecting CH4 and CO2 can reduce the maximum reverse condensate pressure of the reservoir and reduce the amount of condensate; the use of cyclic gas injection can achieve the best development effect, followed by water injection development, and the depletion development effect is the worst. Zhou [25] studied the oil ring condensate gas reservoir in the East China Sea. Firstly, the phase change law of oil ring crude oil and gas cap gas fluid in the formation of the block was analyzed, and the influence of different influencing factors on the production and development effect of the reservoir was determined. The study found that a reasonable oil production rate and gas production rate should be adopted. By using natural energy, including gas cap expansion energy, the elastic energy of oil ring dissolved gas, and edge and bottom water displacement energy, better development results can be obtained. SU et al. [6] studied the effect of carbon dioxide injection in different periods during the development of condensate gas reservoirs by establishing a numerical model. The results show that compared with the water flooding model, carbon dioxide treatment can increase the gas condensate productivity by about 1.39 times. Alsanea [26] first established a condensate gas reservoir model with different permeability through PVT data and fluid composition and studied the influence of condensate gas reservoir permeability on gas condensate production efficiency; the results show that permeability has little effect on the exploitation of condensate gas reservoirs. Secondly, based on these different models, the models with the highest and lowest permeability values were selected to further study the influence of reservoir heterogeneity on production. The results show that the reservoir heterogeneity in high-permeability condensate gas reservoirs has little effect on liquid recovery, and the reservoir heterogeneity of low-permeability condensate reservoirs has a negative impact on liquid recovery. Zhou [16] established a numerical model of cyclic gas injection development for a condensate gas cap reservoir in G area, studied the development parameters of the condensate gas cap reservoir under cyclic gas injection mode, explored the development mode of cyclic gas injection to maintain pressure, and determined the reasonable injection and production parameters of G reservoir. Hassan [27] used the thermochemical treatment method to treat a near-wellbore area and used the reservoir numerical simulation method to simulate oil and gas recovery; the results show that this method can significantly improve oil and gas recovery, and the main reason for this phenomenon is that this method can reduce the capillary pressure and viscosity of condensate wells. Zhang et al. [28] studied the phase behavior and displacement mechanism of gas injection in a gas condensate reservoir. Based on the equation of state and phase equilibrium theory, the effects of pure gas types (N2, CO2, CH4 and C2H6) on displacement were analyzed; the results show that the injection of N2, CH4, and reinjection gas can increase the bubble point pressure of condensate, which is beneficial to the precipitation of condensate. However, the injection of C2H6 or CO2 has little effect on it. Feng et al. [29] took the Surig tight sandstone condensate gas reservoir in the Ordos Basin. Based on the experimental results of PVT phase behavior, the core gas injection displacement experiment was carried out; the variation characteristics of condensate recovery and the average condensate saturation of continuous gas injection, gas injection huff and puff, and pulse gas injection were studied in depth; and the best gas injection method to improve condensate oil recovery was selected. Under the premise that the key parameters meet the actual situation of the formation, Wu et al. [12] studied the injection mode, injection medium, injection–production ratio, and other parameters of the Yaha condensate gas reservoir by establishing a numerical model. The research shows that in the later stage of gas injection development of the condensate gas reservoir, it is recommended to select the development scheme of injecting CO2 from the top position and the injection–production ratio of 1:1. Gao et al. [30] studied the seepage mechanism of condensate gas reservoirs with different depletion levels under high-temperature and high-pressure conditions in the BZ19-6 condensate gas reservoir by studying the phase change and flow characterization of formation fluids under high-temperature and high-pressure conditions, and they carried out mathematical characterization studies based on the production dynamics. Using the results of the study as a guide, a production optimization strategy for the BZ19-6 condensate gas reservoir was proposed to adjust the gas production structure and achieve increased production. Pan et al. [31] investigated the recovery process of gas-driven condensate in a fracture-porosity system by building a model to simulate the injection of CO2 and CH4 into a condensate reservoir. It was shown that although the driving processes of CO2 and CH4 were roughly similar, the driving effect of CO2 was superior. During the permeation stage, CH4 is more capable of driving off the lighter condensate fractions, whereas CO2 excels in continuous extraction, especially for the heavier fractions. In contrast, CO2 induces the continuous dispersion and swelling of condensate components, resulting in more condensate replacement from the pore space. Many studies have shown that numerical simulation methods are widely used in the development of condensate gas reservoirs, but the use of CMG software component modules for numerical simulation research is relatively rare.
In this paper, data from a condensate field were used to establish a realistic numerical model of a condensate reservoir using the CMG software component module. The effects of parameters such as the oil layer thickness, permeability, porosity, rock compression coefficient, vertical permeability to horizontal permeability ratio, and injection medium on condensate and gas extraction were studied, providing rational guidance for condensate gas reservoir development in actual production.

2. Establishment of Numerical Simulation Model of Condensate Gas Cap Reservoir

This numerical study takes a typical condensate gas reservoir as an example. The geological model of a condensate gas reservoir was established by using the Builder (GEM) module of CMG (Figure 1). Although this model cannot describe the characteristics of the entire reservoir, it can accurately describe the flow characteristics of the components in the process of formation and change. The proportion of the model was based on the actual reservoir, and the basic parameters of the model are shown in Table 1. The reservoir geological model contained a total of 2000 grid blocks. The initial pressure of the reservoir was 34473.8 Kpa and the initial temperature was 124.4 °C.
The first step in establishing a numerical model of condensate gas reservoirs is to create a basic fluid model through Win-Prop (version 2021) (Win-Prop is a CMG equation of the state multi-phase equilibrium characterization software package that includes fluid characterization, component lumping, regression fitting of laboratory data, phase diagram calculations, asphalt precipitation, and more). The fluid composition of condensate gas reservoirs is generally only measured to C7+. The first step in simulating gas condensate fluids is to split the component C7+ to complete the fine simulation of condensate gas components. In this paper, C7+ is divided into 5 quasi-components, and the existing 10 components constitute a 15-component gas condensate fluid model for fluid phase fitting. The EoS parameters and the Peng–Robinson state equation are adjusted to match the PVT data in the actual condensate gas reservoir. The input data include original fluid composition, reservoir temperature and pressure, and CVD test results. The mole fraction of each component is as follows (Table 2): CO2: 0.01%; N2: 0.11; C1: 68.93; C2: 8.63; C3: 5.34; IC4: 1.15; NC4: 2.33; IC5: 0.93; NC5: 0.85; FC6: 1.73; C07–C09: 4.68; C10–C12: 2.12; C13–C14: 1.37; C15–C17: 0.82; C18+: 1.00.
The relative permeability of the condensate and gas was tested, and the results are shown in Figure 2 and Figure 3.

3. Result and Discussion

During the development of condensate gas reservoirs, the characteristics of the reservoir itself and the production and construction parameters will have an impact on the development effect [32,33]. In order to study the influence of various factors on the development effect of a condensate gas reservoir in the development process of a condensate gas reservoir, this paper applies the numerical simulation method to consider the six factors of oil layer thickness, permeability, porosity, rock compression coefficient, vertical permeability to horizontal permeability ratio, and injection medium to provide guidance for the development of a condensate gas reservoir (Table 3), so as to maximize the development effect and improve the recovery rate of the condensate gas reservoir.

3.1. Geological Factor

3.1.1. Oil Layer Thickness

Under the condition that other parameters remain unchanged, the reservoir thickness of the theoretical model is changed, and the values are 2 m, 4 m, 6 m, and 8 m. The curves of cumulative oil production and cumulative gas production with time are obtained, as shown in Figure 4 and Figure 5.
It can be seen from Figure 4 that the cumulative oil production is obviously affected by the thickness of the oil layer. With the increase in oil layer thickness, the cumulative oil production increases continuously, and there is no obvious decreasing law in the range of 2 m, 4 m, 6 m, and 8 m. The thicker the reservoir, the higher the cumulative oil production.
It can be seen from Figure 5 that the thickness of the oil layer has a significant effect on the cumulative gas production. As the thickness of the oil layer increases, the cumulative gas production continues to increase, and the increase is obvious. This shows that the greater the thickness of the oil layer, the better the mining effect; in the later stage of production, the influence of oil layer thickness on cumulative gas production is still obvious.
Conclusion: The influence of oil layer thickness on cumulative oil production and cumulative gas production is obvious. With the increase in oil layer thickness, the cumulative oil production increases obviously, and the cumulative gas production also increases continuously, which can effectively improve the economic benefits of mining.

3.1.2. Permeability

The permeability of the reservoir affects the flow capacity of the fluid, and then the development effect of the reservoir. Therefore, it is necessary to analyze the influence of permeability on the development effect of condensate in the reservoir [34]. Under the condition of other parameters remaining unchanged, the horizontal permeability of the model is changed to 0.01, 10, 100, and 1000 mD, so as to study the influence of different levels of permeability on daily oil production and cumulative oil production. The curves of daily oil production and cumulative oil production under different penetration conditions are shown in Figure 6 and Figure 7.
It can be seen from Figure 6 that permeability has a great influence on the daily oil production of condensate. When the permeability is 0.01 mD, the daily oil production of condensate oil is very small, and the maximum is only 0.304 m3/d; with the increase in permeability, the daily output of condensate increases. When the permeability increases to 1000 mD, the maximum daily oil production can reach 3000.33 m3/d. The final daily oil production gradually tends to 0.
The greater the permeability of the condensate reservoir, the better the fluidity of the crude oil, and the higher the degree of recovery of the condensate. It can be seen from Figure 7 that the permeability has a significant effect on the cumulative oil production. With the increase in reservoir permeability, the cumulative oil production increases continuously, and when the permeability increases from 0.01 mD to 1000 mD, the cumulative oil production increases greatly. After the permeability is greater than 1000 mD, the permeability continues to increase, and the cumulative oil production increases to a certain extent, but the increase is not obvious. Under certain conditions of the production system, when the permeability is small, the permeability is the main factor restricting the cumulative oil production. As the permeability increases to a certain value, the production system becomes the main factor restricting the cumulative oil production.

3.1.3. Porosity

Under the condition that other parameters remain unchanged, different porosity changes in the model are made: 0.1, 0.2, 0.3, and 0.5. Curves of daily oil production and cumulative oil production with dates are shown in Figure 8 and Figure 9.
It can be seen from Figure 8 that setting different porosities has a great influence on the development of condensate reservoirs. The smaller the porosity is, the faster the daily oil production of condensate decreases.
It can be seen from Figure 9 that when the porosity is 0.1, the cumulative oil production in the early stage of production is larger than that when the porosity is 0.2 and 0.3. As the simulation progresses, the cumulative oil production with porosity of 0.2 increases rapidly. In the middle of the simulation, the cumulative oil production with porosity of 0.3 increases rapidly, indicating that porosity is also one of the important factors affecting the development of condensate gas reservoirs.

3.1.4. Rock Compression Coefficient

The mining dynamics of condensate gas reservoirs in the high-pressure mining stage mainly depend on the release characteristics of rock elastic energy. The rock compressibility is greatly affected by the clay content in the reservoir. The measured rock compressibility is usually used to predict the productivity performance [35,36,37]. The rock compressibility coefficient is the main parameter used to adjust reservoir energy. Under the condition of other parameters remaining unchanged, different rock compression coefficient changes are made: 4.05 × 10−6, 3.61 × 10−5, 1.57 × 10−5, and 2.24 × 10−7. Daily oil production and cumulative oil production curves with dates are shown in Figure 10 and Figure 11.
It can be seen from Figure 10 that different rock compression coefficients have a great influence on the development of condensate reservoirs. The smaller the rock compression coefficient, the greater the daily oil production of condensate gas in the early stage; with the development of mining, the daily oil production decreases rapidly. The larger the rock compression coefficient is, the slower the daily oil production decreases in the later stage.
It can be seen from Figure 11 that when the rock compression coefficient is the smallest, the cumulative oil production in the first 4 years is larger than that when the rock compression coefficient is 1.57 × 10−5 and 2.24 × 10−7. Among the geological factors, the rock compression coefficient has a certain influence on the development of condensate gas reservoirs.

3.2. Engineering

3.2.1. The Ratio of Vertical Permeability to Horizontal Permeability

The vertical permeability of condensate reservoirs affects the flow capacity of crude oil and gas caps. Under the condition that other parameters remain unchanged, the ratio of vertical permeability to horizontal permeability of the model is set to 0.2, 0.4, and 0.6. The curves of the daily output and cumulative oil production of condensate with different vertical permeability levels are studied, as shown in Figure 12 and Figure 13.
From Figure 12 and Figure 13., it can be seen that under certain other conditions, with the increase in the vertical permeability to horizontal permeability ratio, the daily production of condensate changes little, and the increase in cumulative oil production is also small.

3.2.2. Injection of Different Media

During the development of condensate gas reservoirs, with the gradual decrease in formation pressure, condensate may precipitate and remain in the formation, resulting in the loss of condensate, which will affect the reservoir, especially the reservoir around the wellbore, and further affect the productivity of gas wells [38]. Therefore, the formation pressure can be supplemented by injecting medium to slow down the rate of pressure reduction, thereby reducing the precipitation and accumulation of condensate. In addition, the injection medium can also contact and be miscible with the gas in the reservoir to change the properties of gas condensate, such as condensate content, viscosity, and density, which will further affect the development effect of condensate gas reservoirs [29,39]. In this paper, the influence of different injection media on the development of condensate gas reservoirs is studied. By setting up a gas injection well and a recovery well at the simulated injection site, the injection volume is controlled to 200 m3/d, and the influence of different injection media is analyzed. The results are shown in Figure 14.
It can be seen from Figure 14 that because CO2 does not produce gravity overlap, the development effect is the best when the CO2 injection scheme is adopted, and the cumulative production of condensate is about 21.8743 × 104 m3. The effect of the N2 injection scheme is second best, and the cumulative condensate oil production is about 20.1693 × 104 m3, which has a certain gap with the CO2 injection scheme. The development scheme of injected water has the worst effect, and the difference with the other two media is obvious. The cumulative production of condensate is about 13.0498 × 104 m3. Compared to the yield of the depleted development mode (19.3321 × 104 m3), the cumulative oil production of CO2 and N2 injection increases by 13.15% and 4.33%, respectively. However, when the water injection development scheme is adopted, the cumulative condensate oil production decreases instead. A possible reason for this is that in the low-permeability water injection development reservoir, the solid suspended matter and oil content in the water injection water quality exceed the standard. When the suspended solid content of ferrous sulfide, iron oxide, precipitated carbonate and sulfate, fine sand, and clay particles in the injected water is too high, the solid particles will be filtered out in the wellbore or into the reservoir, forming a low-permeability filter cake or low-permeability pollution area, blocking the flow channel of the reservoir, so that the water absorption of the reservoir is greatly reduced, which seriously affects the water injection development effect. And when the injection water and formation water matching is poor, the injection of water containing scaling ions of Ca2+, Mg2+, SO42−, CO32−, etc., which can easily form precipitation, results in serious scaling in the reservoir, blocks pore channels, results in increased injection pressure, and decreases the reservoir’s water absorption capacity.

4. Conclusions

By selecting the typical parameters of an actual reservoir, a theoretical numerical model is established to study the influence of different parameters on the development effect of condensate oil and gas. The main conclusions are as follows:
(1)
In the process of the depletion development of a condensate gas reservoir, the influence of geological factors such as oil layer thickness, permeability, porosity, rock compressibility, and the vertical permeability and horizontal permeability ratio on the development of a condensate gas reservoir is analyzed. By comparing the effects of these parameters on cumulative oil production, it is found that changing permeability has the greatest effect on the change in cumulative oil production, followed by porosity.
(2)
By changing the formation energy, the influence of different media injection on the development of condensate gas reservoir is analyzed. CO2 has unique physical properties in the supercritical state. After injection into the formation, it will produce an obvious gravity differentiation effect and can inhibit the edge and bottom water and promote the production of low-position reservoirs. Therefore, the injection of CO2 has the best mining effect. N2 has good expansibility and a high compression coefficient, which can effectively supplement formation energy and maintain reservoir pressure. However, due to its low density and the fact that it is prone to gravity differentiation, the viscosity after injection into the formation is relatively small, so the effect is worse than that of CO2. In addition, the cumulative oil production is reduced when water is injected. Therefore, it is not recommended to use water as an injection medium in development.
Based on these results, it is demonstrated that CMG numerical simulation has applicability in studying condensate gas reservoirs, which may help provide reasonable guidance for the development of condensate gas reservoirs.

Author Contributions

Methodology, F.S.; software, K.Z. and L.G.; formal analysis, K.Z. and L.G.; writing—original draft, K.Z.; writing—review and editing, F.S.; funding acquisition, F.S. All authors have read and agreed to the published version of the manuscript.

Funding

This study was supported by the National Natural Science Foundation of China (42202203, 42372195) and the Basic Research Ability Enhancement Project for New Teachers (2-9-2023-050).

Data Availability Statement

The original contributions presented in the study are included in the article, further inquiries can be directed to the corresponding author.

Conflicts of Interest

The authors declare no conflict of interest.

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Figure 1. Three-dimensional shape of the model.
Figure 1. Three-dimensional shape of the model.
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Figure 2. Oil–gas permeability curve.
Figure 2. Oil–gas permeability curve.
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Figure 3. Oil–water permeability curve.
Figure 3. Oil–water permeability curve.
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Figure 4. Effect of oil layer thickness on cumulative oil production.
Figure 4. Effect of oil layer thickness on cumulative oil production.
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Figure 5. Effect of oil layer thickness on cumulative gas production.
Figure 5. Effect of oil layer thickness on cumulative gas production.
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Figure 6. Effect of permeability on daily oil production.
Figure 6. Effect of permeability on daily oil production.
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Figure 7. Effect of permeability on cumulative oil production.
Figure 7. Effect of permeability on cumulative oil production.
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Figure 8. Effect of porosity on daily oil production.
Figure 8. Effect of porosity on daily oil production.
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Figure 9. Effect of porosity on cumulative oil production.
Figure 9. Effect of porosity on cumulative oil production.
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Figure 10. Effect of rock compressibility on daily oil production.
Figure 10. Effect of rock compressibility on daily oil production.
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Figure 11. Effect of rock compressibility on cumulative oil production.
Figure 11. Effect of rock compressibility on cumulative oil production.
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Figure 12. Effect of vertical horizontal ratio permeability on daily oil production.
Figure 12. Effect of vertical horizontal ratio permeability on daily oil production.
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Figure 13. The effect of vertical horizontal permeability ratio on cumulative oil production.
Figure 13. The effect of vertical horizontal permeability ratio on cumulative oil production.
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Figure 14. Effect of injection of different media on cumulative oil production.
Figure 14. Effect of injection of different media on cumulative oil production.
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Table 1. Basic parameters used in the numerical model developed in this paper.
Table 1. Basic parameters used in the numerical model developed in this paper.
Depth of Burial (m)3300
Grid size (m)20 × 20 × 5
Porosity (%)0.3
Oil layer thickness (m)2
Permeability (mD)10
Rock compression coefficient (KPa−1)4.05 × 10−6
Initial temperature (°C)124.4
Reservoir pressure (KPa)34473.8
Table 2. Condensate composition.
Table 2. Condensate composition.
ComponentComponent Content (%)
CO20.01
N20.11
C168.93
C28.63
C35.34
IC41.15
NC42.33
IC50.93
NC50.85
FC61.73
C07-C094.68
C10-C122.12
C13-C141.37
C15-C170.82
C18+1.00
Total100
Table 3. Classification and value of influencing factors.
Table 3. Classification and value of influencing factors.
Stratigraphic ConditionsFactor TypesValue
Homogeneous stratigraphyOil layer thickness2 m, 4 m, 6 m, 8 m
Permeability (mD)0.01, 10, 100, 1000
Porosity (%)0.1, 0.2, 0.3, 0.5
Rock compression coefficient1.57 × 10−5, 3.61× 1 0−5, 4.05 × 10−6, 2.24 × 10−7
Vertical horizontal permeability ratio0.2, 0.4, 0.6
Inject mediumCO2, N2, H2O
Evaluation indicatorsCumulative oil production; cumulative gas production; daily oil production
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Zhu, K.; Gao, L.; Sun, F. Numerical Simulation Study on Optimization of Development Parameters of Condensate Gas Reservoirs. Processes 2024, 12, 2069. https://doi.org/10.3390/pr12102069

AMA Style

Zhu K, Gao L, Sun F. Numerical Simulation Study on Optimization of Development Parameters of Condensate Gas Reservoirs. Processes. 2024; 12(10):2069. https://doi.org/10.3390/pr12102069

Chicago/Turabian Style

Zhu, Kai, Lingjie Gao, and Fengrui Sun. 2024. "Numerical Simulation Study on Optimization of Development Parameters of Condensate Gas Reservoirs" Processes 12, no. 10: 2069. https://doi.org/10.3390/pr12102069

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