Determination of minimum near miscible pressure region during CO2 and associated gas injection for tight oil reservoir in Ordos Basin, China

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Determination of minimum near miscible pressure region during CO2 and associated gas injection for tight oil reservoir in Ordos Basin, China ⁎

Haiyang Yua, , Xin Lua, Wenrui Fua, Yanqing Wangc, Hang Xua, Qichao Xieb, Xuefeng Qub, ⁎ Jun Luc, a

State Key Laboratory of Petroleum Resources and Prospecting, China University of Petroleum, Beijing, China Research Institute of Exploration and Development, PetroChina Changqing Oilfield Company, Xi’an, China c McDougall School of Petroleum Engineering, The University of Tulsa, Tulsa, OK, USA b

A R T I C LE I N FO

A B S T R A C T

Keywords: CO2 flooding Tight oil Minimum near-miscible pressure

CO2 flooding is believed as an effective and promising method to enhance oil recovery. However, for tight oil reservoirs of Long Dong (LD) region in Ordos Basin, CO2 flooding cannot achieve miscible condition since reservoir pressure is lower than minimum miscibility pressure (MMP). Meanwhile, this region has abundant associated gas production. Impure CO2 with associated gas re-injection at the near-miscible condition is a promising enhanced oil recovery (EOR) method which may solve the problem above. This study aims to investigate the oil recovery potential of this method by conducting experiments and simulations. Firstly, based on the reservoir condition (64 ℃), slim-tube experiments and simulations were performed to acquire correlations of pressure, interfacial tension (IFT) and oil recovery of pure CO2 flooding. Then the MMP, the minimum nearmiscible pressure (MNMP), and near-miscible region were determined. The pressure interval of the near-miscible region ranges from 17.82 MPa to 22.75 MPa. Secondly, the minimum CO2 concentration for conducting impure CO2 with associated gas re-injection at the near-miscible condition was investiaged, which is 73.3% for the target formation. Furthermore, by studying the composition of injected gas, it is found that the presence of methane and nitrogen impedes oil and gas to achieve the miscible or near-miscible phase. With the decrease of CO2 concentration of injected gas by 10% or the concentration of impurities in the injected gas increases by 7% each time, MMP and NMMP increase by 1.08 MPa and 0.89 MPa, respectively. This study explores the feasible application of using impure CO2 with associated gas re-injection to improve oil recovery for tight oil reservoirs.

1. Introduction Nowadays, with the increment of oil consumption and depletion of conventional oil resources, the development of tight oil reservoir is a matter of growing scientific and technological interest [1,2]. Tight oil resource has a broad prospect for exploration and development in China’s Ordos, Junggar, Songliao, Bohai and Sichuan basins [3–6]. However, the depletion recovery of tight oil reservoirs is unsatisfactory due to low natural formation energy [7–9]. It is hard to conduct conventional methods, such as water flooding, because of the extremely low permeability. Then CO2 flooding is regarded as an effective and promising method to enhance tight oil recovery [10–16], which not only can reach a satisfactory oil recovery but also is environmentally friendly as it can reduce CO2 emission by means of carbon capture and sequestration (CCS) [17,18], CCS has been testified as an effective way to combat the greenhouse effect by storing mass CO2 in geological

⁎

structures. Besides, the ratio of carbon storage and oil recovery increases with the decrease of permeability [19]. Injection pressure and oil composition mainly affect the EOR performance for CO2 flooding [20–24]. CO2 flooding can be divided into three types, namely immiscible flooding, near-miscible flooding, and miscible flooding. The mechanism of three flooding processes is not the same. Crude oil and gas can reach miscible state when the injection pressure is higher than the MMP. Decrease of oil viscosity, oil vaporization, and IFT reduction are the main reasons for the high oil recovery of miscible EOR method [25–27]. The phase of oil and gas is near-miscible and immiscible when the injection pressure is lower than MMP. Solution gas drive, oil swelling, and enhanced mobility control due to the reduction of oil viscosity are the main mechanisms of near-miscible and immiscible EOR methods [28–32]. Theoretically, miscible flooding has higher oil recovery compared with near-miscible and immiscible flooding. However, the prerequisite

Corresponding authors. E-mail addresses: [email protected] (H. Yu), [email protected] (J. Lu).

https://doi.org/10.1016/j.fuel.2019.116737 Received 26 August 2019; Received in revised form 24 October 2019; Accepted 23 November 2019 0016-2361/ © 2019 Elsevier Ltd. All rights reserved.

Please cite this article as: Haiyang Yu, et al., Fuel, https://doi.org/10.1016/j.fuel.2019.116737

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Nomenclature MMP MNMP IFT VIT PVT

GOR EOR PV PR CCS LD

Minimum miscibility pressure Minimum near-miscible pressure Interfacial tension Vanishing interfacial tension Pressure volume temperature

for conducting miscible flooding is to implement injected pressure to reach MMP [33]. There are three methods to predict the MMP, including empirical correlation method, experimental method, and numerical simulation method [34]. The empirical correlation method is convenient for field engineers to calculate as a quick tool [35]. However, most empirical correlations cannot be used to precisely calculate MMP because the correlations are obtained by matching a series of experimental data of some specific reservoirs [36]. For experimental methods, laboratory measurement of MMP is time-consuming and costly. The widely used methods for predicting MMP are Vanishing Interface Tension (VIT) method, Rising Bubble method, and Slim-tube experiment method [37,38]. The slim-tube experiment method is generally accepted as the preferred method [39]. However, the MMP determined by slim-tube experiment is affected not only by the relative permeability and other multi-phase flow parameters but also by experimental parameters of the slim tube. Therefore, experimental methods and numerical simulation methods are sometimes combined to determine the MMP of oil and gas. The reservoir pressures of most tight oilfields are lower than MMP in China. It means that the application of CO2 miscible flooding is hard to be performed [40]. Also, field research of some so-called miscible projects which has satisfactory EOR performance has revealed that most of them are actually immiscible or near-miscible projects [34]. This fact indicates that achieving miscibility should not be the only standard to evaluate the application of CO2 flooding. Meanwhile, reaching miscible state is difficult for tight oil reservoirs in the Ordos basin because of the technical challenges and poor reservoir conditions. More studies proposed that near-miscible displacement can achieve a recovery nearly equivalent to that of miscible displacement [41,42]. Lower injection pressure does affect the miscible phase of gas and oil, but to some extent, the gas breakthrough can be controlled and sweep efficiency is improved. Since the oil and gas cannot achieve the miscible phase in several tight oilfields, near-miscible displacement is an EOR option. So far, it is still a difficult problem to determine the pressure interval for conducting near-miscible flooding [10]. Unlike the miscible displacement of which a pressure (MMP) has to be determined, a pressure interval including an upper boundary and a lower boundary must be determined for near-miscible flooding. Chen et al. ascertained the near-miscible region of conventional offshore reservoirs [43,44]. In general, the formation pressure of tight onshore reservoirs are much lower than that of offshore reservoirs, which means that oil and gas can hardly achieve miscibility under reservoir conditions. Therefore, it is crucial to study the near-miscible CO2 flooding process for tight oil reservoirs. The LD region of Ordos Basin is a representative tight reservoir in China. Due to extremely low reservoir permeability and high threshold pressure gradient, conventional waterflooding cannot be performed. CO2 sources around LD region are scarce, but the associated gas production is massive. The cost of associated gas treatment is also expensive, which includes the costs of compression and separation, and dehydration. Therefore, this reservoir has promising feasibility to conduct CO2 and associated gas mixture injection at the near-miscible condition. If this method is performed by blending and injecting the mixture of associated gas and CO2 into the reservoir, it will solve cost and supply issues of CO2 sources as well as the associated gas treatment problem.

Gas oil ratio Enhanced oil recovery Pore volume Peng–Robinson Carbon capture and sequestration Long dong (a oil-producing region in Ordos Basin)

Based on the gas and crude oil of the LD region, the MMP and nearmiscible region were studied by slim-tube experiments, slim-tube simulations, and empirical correlations. The MMP and the near-miscible region of pure CO2 for the LD region were determined from the results of oil recovery and IFT. It should be pointed out that the CO2 concentration of the reinjected gas is one of the main factors to evaluate the feasibility of near-miscible flooding for the target reservoir. Therefore, the relationship between CO2 concentration, MMP, and MNMP was studied by using slim-tube experiments and slim-tube simulations to determine the minimum CO2 concentration of injection mixture at nearmiscible conditions. This study shed light on the EOR by CO2 nearmiscible flooding strategy for the tight oil reservoir. 2. Methodology In this paper, experiments and simulation were conducted to investigate the MMP, MNMP, and mear-miscible region for the LD region. The experiments involve slim-tube experiments, Pressure volume temperature (PVT) analysis, and chromatographic analysis. The simulation work includes slim-tube simulation, reservoir fluids phase matching, and compositional modeling. Firstly, MMP, MNMP, and near-miscible region of pure CO2 were studied by slim-tube experiments and simulations. The research results combined with the aspects of IFT and oil recovery ascertain the MMP, MNMP, and near-miscible region. Then, more results with different CO2 concentrations (90%, 80%, 70%, 60%) were obtained by the above method. Moreover, several widely-applied empirical correlations were chosen to predict the MMP of gas mixtures with different CO2 concentrations. These predictions were compared with the experimental and simulation results in this paper. Finally, the influences of CO2 concentration on the miscibility were studied to determine the minimum CO2 concentration of gas mixture for re-injection at the near-miscible condition. Given that the enormous workload and cost of the slim-tube experiments, more MMP results were acquired through the slim-tube simulation after verifying the reliability of the simulation results. Table 1 summarizes slim-tube experiments and simulations conducted in this study. 2.1. Materials The gas and oil samples in this study were obtained from the tight oil reservoir of the LD region. Table 2 is a summary of the physical properties of reservoir fluids. The composition of the live oil sample is presented in Table 3. Table 4 shows the composition of the injected gas with different CO2 concentration in both slim-tube experiments and simulation. To study the effect of CO2 concentration in injected gas, pure CO2 and associated gas of LD region were mixed in different Table 1 Slim-tube experiment and simulation conducted in this study.

2

CO2 concentration (%)

Slim-tube experiment

Slim-tube simulation

100 90 80 70 60

√ √ – – √

√ √ √ √ √

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Table 2 Physical properties of reservoir fluids [7].

Reservoir condition Oil properties

Composition of associated gas

Table 4 Composition of injected gas.

Parameters

Value

Component

CO2

N2

C1

C2

C3

iC4

nC4

C5

Pressure (MPa) Temperature (℃) Saturation pressure (MPa) Gas/oil ratio (m3/m3) Oil formation volume factor (m3/m3) Oil viscosity (mPa·s) Oil density (g/cm3) C1 (mol%) C2 (mol%) C3 (mol%) nC4 (mol%) iC4 (mol%) C5+ (mol%) CO2 (mol%) N2 (mol%)

19.8 64 9.09 107.2 1.24 1.27 0.6468 66.21 14.04 14.37 1.86 1.15 0.44 0.31 1.62

Amount (mol%)

100 90 80 70 60

0 0.16 0.32 0.49 0.65

0 6.62 13.25 19.86 26.48

0 1.40 2.81 4.21 5.62

0 1.44 2.87 4.31 5.75

0 0.22 0.43 0.65 0.86

0 0.12 0.23 0.35 0.46

0 0.04 0.09 0.13 0.18

proportions to obtain the injected gas with different CO2 concentrations (100%, 90%, 80%, 70%, 60%).

2.2. Experimental apparatus The PVT analysis was performed by RUSKA-2730 high-temperature high-pressure visual PVT device, which is made by Ruska Ltd. The PVT device mainly consists of two stainless steel chambers, several storage vessels, and two displacement pumps. The primary chamber is equipped with a windowing system at the upper surface for visually examining the process. Slim-tube experiments were conducted using CFS-200 Reservoir Conditions Coreflooding System produced by Core Laboratories Inc. The sketch figure of the apparatus is presented in Fig. 1. All the experiments were accomplished at 64 ℃. Table 5 shows the slim tube parameters. The inside diameter of the stainless steel coiled tube is 4.1 mm. The length of the coiled tube is 18 m. The coil has a pore volume of 29.76 cm3 and a permeability of 4.241 mD. The effluents went across the back-pressure regulator and separated into a gas meter and liquid meter, respectively. Electronic pressure sensors measured the back, inlet, and outlet pressures.

Table 3 Composition of live oil sample [7]. Component

Concentration (mol%)

CO2 N2 C1 C2 C3 iC4 nC4 iC5 nC5 iC6 nC6 BENZENE iC7 nC7 TOLUENE iC8 nC8 C9 C10 C11 C12 C13 C14 C15 C16 C17 C18 C19 C20 C21 C22 C23 C24 C25 C26 C27 C28 C29 C30 C31 C32 C33 C34 C35

0 2.21 22.44 7.54 10.02 3.72 1.89 0.63 2.62 1.17 2.13 0.11 3.91 1.45 0.48 1.63 3.62 2.92 2.78 2.67 2.45 2.58 2.54 2.39 1.94 1.87 1.65 1.66 1.39 1.24 1.09 0.97 0.82 0.78 0.69 0.59 0.45 0.38 0.23 0.16 0.09 0.05 0.03 0.02

2.3. Experiment procedure Firstly, chromatographic analyses (based on China National standard GB/T 29172-2012) were conducted to ascertain the composition of oil sample and associated gas. The PVT analysis was then performed to study fluid behaviors and properties of oil and gas samples [54]. Commonly, the PVT experiment results cover density, viscosity, volume factor, gas oil ratio (GOR), saturation pressure. Slim-tube experiments (based on China petroleum industry standard SY/T 6573-2016) were designed to investigate the MMP, MNMP, and the near-miscible region at the conditions of various pressures and three CO2 concentrations (100%, 80%, and 60%). The packing material of the slim tube is quartz sand and crude oil. The packing material of the slim tube is quartz sand and oil sample. First, the slim tube was cleaned and kerosene was injected at the experimental temperature and pressure. Then the oil sample was used to displace the kerosene in the slim tube at a rate of 60 cm3/h. After displacement of double pore volume, the properties of the fluids at the outlet are measured every 0.1 times pore volume. When the properties of the produced fluids are the same as those of the oil sample, the slim tube is ready. To improve the accuracy of slim-tube experiment results, for each experiment, 9 points of the pressure points were selected, instead of 6 points as usual. The injected gas stored in the transfer vessel at the experimental temperature. At the experimental pressure, the gas was injected by the pump at a rate of 6 cm3/h into the slim tube to displace the oil sample. The total volume of the injected gas is 1.2 pore volume (PV). The output fluids went across the back-pressure regulator and seperated into a gas meter and a liquid meter, respectively. The metering system recorded the experiment data, including density, viscosity, and volume of the output gas and oil. Based on the experiment results, the correlation curve of displacement pressure, GOR, and oil recovery can be drawn out. 3

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Fig. 1. The sketch of the apparatus used in the slim-tube experiment.

Based on the PVT experiments data, simulation research was conducted to match the composition and phase behavior of reservoir fluids. After that, the compositional model was constructed to simulate slimtube experiments. More specifically, the compositional model was built up through the Peng–Robinson (PR) state equation in the WinProp module of CMG simulator. To ensure the accuracy of slim-tube simulation, the physical properties of the simulated fluid were matched with those of the crude oil by adjusting the relevant parameters correctly. Binary interaction coefficients, coefficients of Pedersen viscosity compositions, and molecular weight were coordinated to match saturation pressure, oil viscosity and oil density, respectively. Then, all the slimtube simulations were implemented on this compositional model. The slim-tube simulation results includes GOR, IFT, and oil recovery. Eventually, the MMP and near-miscible region of different CO2 concentrations were finally determined by comparing and analyzing the simulation results and slim-tube experiments results.

demonstrates the MMP diversity caused by selecting different pressure points in slim-tube experiments. More specifically, choosing different experiment pressure points will result in different values of MMP. To determine the MMP, three miscible and three immiscible data are required to fit two trend lines. The relationship between oil recovery and pressure is not a rigorous linear function. The different selection of pressure points lends to different MMP values, as shown in Table 7. Therefore, if the pressure points of the immiscible phase are selected improperly, the MMP value will be unreliable. Based on results of the slim-tube simulation, vanishing interfacial tension (VIT) method is another method to determine MMP value. The zero IFT is considered as the standard of the miscibility. Fig. 3 demonstrates the VIT method. The red line (IFT versus pressure) was extrapolated to zero value of IFT to determine MMP, which is the typical VIT method. However, as the pressure continues to ascend, the IFT goes down very slowly. When extrapolated to the point where IFT equals zero, the actual value of IFT is not zero. Therefore, there are some defects in the determination of MMP by VIT method.

2.5. Empirical correlation

3.2. Determination of the MMP and near-miscible region

In addition to experimental and simulative approaches, empirical correlations methods were used as an auxiliary way to verify the MMP obtained by other means. For the above objective, based on the compositional data of injected gas, associated gas, and oil, the MMP results were calculated and compared with those of slim tube simulation and slim tube experiment. Table 6 summarizes more widely-applied empirical correlations for calculating the MMP of oil and gas at different CO2 concentration conditions.

In practice, the miscible flooding in the oilfield was not actually achieved miscible phase using the MMP obtained from the Lab [40]. It means that many “successful miscible” implement were not the real miscible flooding in dozens of projects that had been implemented, which should be called near-miscible flooding. Although the implemented pressure neither reaches MMP or leads to zero IFT, the oil companies were still delighted for the satisfactory oil recovery performance using near-miscible flooding. Besides, the gas channeling and breakthrough were controlled easily under lower pressure. Therefore, it is not necessary to take great pains to ensure zero IFT of oil and gas during gas flooding, especially for the tight oil reservoirs of the LD region, where the IFT of oil and gas is too high to ensure the oil and gas can achieve the miscible phase. For these reasons, near-miscible flooding is a promising method to enhance tight oil recovery. However, there is still no specific conclusion to ascertain MMP. The determination of marking out the near-miscible region is not clear. To solve this problem, we precisely calculated the value of MMP and ascertained the near-miscible region in this study. Experimental and simulation results jointly determined the MMP and near-miscible region. Different from the typical method using six experiment points, the slim-tube experiments and simulations were conducted with nine experiment points to determine MMP accurately in this study. For the results of slim-tube experiments, MMP of pure CO2 was determined to be 21.78 MPa by the typical method, as Fig. 4 illustrates. However, as

2.4. Slim-tube simulation

3. Results and discussion 3.1. Defect of the typical MMP determination method The slim-tube experiment is a typical method to evaluate the occurrence of the miscible phase of oil and gas, which is the commonly accepted option. The miscible criterion is that the oil recovery at miscible pressure is not lower than 90% after 1.2PV gas injection. Through a series of experiments, the oil recovery at different pressures can be obtained. Then, all experiment points were divided into the miscible group and immiscible group. Two trend lines appear on a plot of recovery versus pressure for these two groups. The intersecting point of those trend lines is the estimated MMP for the given oil-gas system. For this criterion, it is the most typical method to calculate MMP but not accurate enough because of the uncertainty of the trend lines. Fig. 2 Table 5 Slim tube parameters. Parameter

Diameter (mm)

Length (m)

Permeability (mD)

Porosity (%)

Pore Volume (cm3)

4.1

18

4.241

12.53

29.76

4

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Table 6 Widely-applied empirical correlations. Researcher

Widely-applied empirical formula

Cronquist [45]

MMP = 0.11027 × (1.8T + 32)Y Y = 0.744206 + (0.0011038MWc5 +) + (0.0015279Vol)

Lee [46]

MMP = 7.3942 × 10b b = 2.772 −

Yellig and Metcalfe [47]

1519 492 + 1.8T

MMP = 12.6472 + 0.015531 × (1.8T + 3.2) + 0.000124192 × (1.8T + 32)2 −

Alston et al. [48]

716.9427 1.8T + 32

Vol 0.136 Intern −1.058 786.8MC 7+ ) T 810.0 − 3.404MC7 + + (1.700 × 10−9MC3.730 7+ e − − 2 4 1 − 2.13 × 10 (TcM − 304.2) + 2.51 × 10 × (TcM − 304.2)2 − 2.35 × 10−7 × (TcM − 304.2)3

MMP = 6.056 × 10−6 × (1.8T + 32)1.06 × MWc1.78 5+ ×

Glaso [49]

MMP =

Sebastian et al. [50]

MMP =

(

)

TcM = ∑ xi Tci Emera and Sarma [51]

MMP = 0.474265308 − 0.0187974 × MWC7 + + (278.6388 × 10−11 × MWC3.023 7+ × e

Shokir [52]

−1.189 809.9 × MWC 7+ )

× (1.8TR + 32)

MMP = −0.068616 × z 3 + 0.31733 × z 2 + 4.9804 × z + 13.432 8

z = ∑ zn n−1

z n = A3n x n3 + A2n x n2 + A1n xn + A0n Li et al. [53]

MMP = 7.30991 × 10−5 [ln(1.8TR + 32)]5.33647

(

[ln(MWC7 + )]2.08836 1 +

xvol xint

2.01658 × 10−1

)

Fig. 3. The IFT result of slim-tube simulation at the temperature of 64 °C. Fig. 2. The diversity of MMP caused by different selection points in slim-tube experiments at the temperature of 64 °C.

immiscible region and the miscible region. The blue points in this middle region are fitted to determine a region called near-miscible region which ranges from 17.25 MPa to 22.92 MPa. The near-miscible region is below the miscible boundary and above the immiscible boundary. The pressure at the lower boundary and that at the upper

the pressure increases, the curve of pressure versus recovery is not always linear. The slope of the curve starts getting smaller when pressure is higher than 17.25 MPa, and there is an obvious region between the

Table 7 MMP and MNMP of different CO2 concentrations at the temperature of 64 °C. CO2 concentration, %

100% 90% 80% 70% 60%

MNMP, MPa

MMP, MPa

MNMP/MMP

Experiment

SimulationOR

SimulationIFT

MNMP Ave.

Experiment

SimulationOR

SimulationIFT

MMP Ave.

17.25 ± 0.42 18.53 ± 0.58 – – 22.29 ± 0.73

18.07 18.21 19.10 20.07 21.15

18.13 19.29 20.04 21.01 21.42

17.82 18.68 19.57 20.54 21.62

22.92 ± 0.29 23.76 ± 0.46 – – 26.24 ± 0.61

22.49 23.60 24.68 25.54 26.66

22.83 23.28 24.56 25.42 26.91

22.75 23.54 24.62 25.48 26.60

SimulationOR: Simulation results acquired by oil recovery method. SimulationIFT: Simulation results acquired by IFT method. 5

0.783 0.791 0.793 0.804 0.811

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injected gas would lead to an increase in MMP and MNMP. Therefore, the presence of CH4 and N2 is not conducive to attain the miscible phase of oil and gas. 3.4. Limitations of the empirical correlation The empirical correlation method is a way to obtain the MMP formula matched with experimental data, and this method represents MMP as a function of reservoir temperature and the composition of injected gas and crude oil. Cronquist proposed a formula for calculating the MMP, which considers that the molar fraction of C5+ is the critical factor affecting MMP [45]. The formula proposed by Lee considers the effects of reservoir temperature and C5+ concentration in crude oil, but ignores the influence of light components (C2–C4) [46]. Yellig and Metcalfe agreed that temperature is the most critical factor affecting MMP, but they weaken the influence of oil composition, which accords with Glaso’s view [47,49]. These empirical correlations only apply to calculation of MMP for pure CO2 condition. Alston provided an MMP formula for impure CO2 conditions, but this formula has strict limits on the impurity concentration in the injected gas, so the actual calculation results are not satisfactory [48]. Sarma and Emera used the genetic algorithm to fit and optimize Glaso's MMP formula on pure CO2 and mixed gas injection conditions [51]. Shokir proposed an equation for the MMP of mixed gas flooding using an alternating conditional expectation algorithm [52]. Li et al. declared the molar fraction of the light component (C2–C6) is also a key parameter and proposed a new MMP formula which can be used for pure and impure CO2 conditions [53]. Table 8 shows the MMP predictions of the LD region calculated by these typical empirical correlations. In the case of pure CO2 injection, MMP was underrated by five of the eight formulas and was overrated by the other three correlation. The relative error of MMP results obtained by the method of Li et al. and Lee does not exceed 10%. Yellig and Metcalf’s method produces the most unsatisfied results because only the influence of temperature is considered, while the influence of crude oil composition is not included. Empirical formulas proposed by Alston et al., Sebastian et al., Emera and Sarma, Shokir, and Li et al. can be employed to calculate MMP of impure CO2 injection. However, the calculated results are still not accurate enough. The formulas of Alston et al. and Sebastian et al. have limits on the interval of the critical temperature of the injected gas. Therefore, these two formulas can merely calculate the MMP of CO2 with the concentration above 90%.

Fig. 4. MMP, MNMP and mear-miscible region of pure CO2 determined by slimtube experiments at the temperature of 64 °C.

boundary of the near-miscible region are regarded as MNMP and MMP, respectively. The MMP determined by this new method is more accurate and slightly higher than that determined by the typical method. For slim-tube simulation, the oil recovery results and the IFT results are used to determine the near-miscible region. The oil recovery data of slim-tube simulation are processed in the same way as those of the slimtube experiment. Table 7 shows the MMP results of pure CO2 by simulation, the near-miscible region ranges from 18.07 MPa to 22.49 MPa. For IFT results, as Fig. 3 shows, the IFT of gas and oil goes down rapidly at first, and then it reduces tardily as the pressure increases. In this study, the IFT data is processed with the semi-logarithmic coordinate transformation. The two distinct trend lines appear on the plot. The pressure at the intersection point of two trend lines is the NMMP, which is the lower boundary of the near-miscible region. The near-miscible region obtained by the IFT method ranges from 18.13 MPa to 22.83 MPa, which is approximately equal to slim-tube experiment results. In conclusion, for the first time, the determination method is established to ascertain the injection pressure to conduct CO2 near-miscible flooding for the tight oil reservoir of the LD region. The final pressure interval of the near-miscible region ranges from 17.82 MPa to 22.75 MPa, which is determined by calculating the average results of the IFT method and oil recovery method. It is beneficial for the field to determine the state of oil and gas through injection pressure during pure CO2 flooding.

Table 8 MMP predictions calculated by empirical correlations. CO2 concentration, %

Empirical correlation

MMPF, MPa

MMPS, MPa

Relative error, %

100

Cronquist Lee Yellig and Metcalfe Alston et al. Glaso Emera and Sarma Shokir Li et al. Alston et al. Sebastian et al. Emera and Sarma Shokir Li et al. Emera and Sarma Shokir Li et al.

26.59 20.84 16.55

22.75

16.96 8.32 27.18

3.3. MMP and MNMP at different CO2 concentrations After determination of near-miscible region for pure CO2 injection, the MMP and MNMP of gas mixture of CO2 and associated gas were measured by the same method under different CO2 concentrations (60%, 90%, 100%), as shown in Table 7. MMP of 100%, 90% and 60% CO2 concentration determined by slim-tube simulation are 22.66 MPa, 23.44 MPa and 29.79 MPa, respectively. Compared with the results of slim-tube experiments, the relative errors are 1.13%, 1.35%, and 2.08%, respectively. The results of the slim-tube simulation are in good agreement with those of slim-tube experiments. After validating the reliability of simulative results, the slim-tube simulations were carried out at another two CO2 concentration conditions (70%, 80%) to get the near-miscible region for impure CO2 injection. As shown in Table 7, MMP and MNMP ascend as the descendant of CO2 concentration in injected gas. The ratio of MNMP to MMP ranges from 0.783 to 0.811. The results showed that the increase of CH4 and N2 concentration in

90

60

19.72 27.60 30.11

13.22 21.41 32.44

20.03 21.79 25.33 29.26 19.47

11.89 4.17 7.65 24.31 17.28

26.69 20.52 22.09 29.70 22.66

MMPF: MMP (Formula); MMPS: MMP (Simulation). 6

23.54

26.60

13.40 12.82 16.97 11.65 14.77

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boundary of the near-miscible region. The MMP determined by this method is more accurate and slightly higher than that determined by the typical method. The plot of oil recovery versus pressure is divided into three parts: miscible region, near-miscible region, and immiscible region. Based on tight reservoir conditions (19.8 MPa and 64 ℃), it means that the feasible option of CO2 flooding for LD region is near-miscible flooding. (2) The minimum CO2 concentration of injected gas is 73.3% for conducting associated gas re-injection at near-miscible conditions. The presence of CH4 and N2 components impede oil and gas to achieve the miscible phase. The CO2 concentration of injected gas decreases by 10% or the concentration of impurities in the injected gas increases by 7% each time, MMP and NMMP increase by 1.08 MPa and 0.89 MPa, respectively. In the case that the target reservoir pressure cannot reach MMP, the CO2 concentration of injected gas between 73.3% and 100% can realize near-miscible flooding, which can achieve satisfactory oil recovery performance. Impure CO2 with associated gas re-injection at near-miscible condition is a promising method for the LD region to improve tight oil recovery. (3) According to the MMP predictions of the LD region calculated by typical empirical correlations, MMP for pure or impure CO2 flooding are not accurate enough. There are two main reasons for these unsatisfied predictions. Firstly, the majority of correlations built by given oilfield data cannot accurately predict the MMP for other oilfields. Also, Other important factors are not comprehensively considered in these formulas, such as thermodynamic or physical principles of fluid miscibility. Therefore, slight deviations in reservoir conditions, fluid properties and oil composition may cause the predicted MMP to be inconsistent with the real MMP.

Although the empirical formulas of Emera and Sarma, Shokir and Li et al. are widely used, the relative errors are higher than 10%. There are two main reasons for these unsatisfied predictions calculated by empirical correlations. Firstly, the majority of correlations are built by given oilfield data and cannot accurately predict the MMP for other oilfields. Besides, most of the factors considered in these empirical formulas are crude oil composition, injected gas composition and reservoir temperature. Other important factors are not comprehensively considered in these formulas, such as thermodynamic or physical principles of fluid miscibility. Therefore, slight deviations in reservoir conditions, fluid properties and oil composition may cause the predicted MMP to be inconsistent with the real MMP. 3.5. The minimum CO2 concentration of associated gas re-injection for miscible and near-miscible flooding Achieving miscibility is the main challenge to conduct CO2 flooding for the LD region. Meanwhile, a large number of associated gas resources are wasted. The critical issue is to improve tight oil recovery for the LD region while saving injection costs and handling the associated gas treatment. Therefore, impure CO2 with associated gas re-injection is a win-win method to enhance oil recovery. For impure CO2 flooding, the first thing to study is whether oil and gas can achieve miscible phase or near-miscible phase at reservoir condition with different CO2 concentrations. The second is to determine the minimum CO2 concentration of gas mixture for re-injection, which guides the LD region to conduct near-miscible displacement for tight oil reservoirs. Based on the method proposed in this study, the CO2 concentrations of re-injection gas were designed as 100%, 90%, 80%, 70%, 60%. Slimtube simulations of these five CO2 concentrations were conducted to investigate the effect of CO2 concentration on MMP, MNMP, and nearmiscible region, as shown in Fig. 5. Based on the reservoir pressure (19.8 MPa), it can be concluded that miscible flooding cannot be realized even when CO2 concentration is 100%. However, the CO2 concentration ranging from 73.3% to 100% can result in near-miscible flooding. MMP and NMMP increase by 1.08 MPa and 0.89 MPa, respectively, with the decrease of CO2 concentration of injected gas by 10%. The presence of CH4 and N2 impedes oil and gas to achieve the miscible phase.When the concentration of impurities in the injected gas increases by 7%, MMP and MNMP increases by 1.08 MPa and 0.89 MPa, respectively. The presence of CH4 and N2 impedes oil and gas to achieve the miscible phase. This result is consistent with the fact that more CH4 or N2 in the injected gas, the harder it is to be miscible with the oil. So the presence of CH4 and N2 is not conducive to conduct miscible or near-miscible flooding for the tight oil reservoir in the LD region. Although the oil recovery of near-miscible flooding is not as high as that of miscible flooding, the injected pressure and gas consumption of near-miscible flooding are less. The reservoir pressure of the LD region is lower than the MMP, so the near-miscible flooding is believed as a feasible method to enhance the tight oil recovery.

Declaration of Competing Interest The authors declare that they have no known competing financial interests or personal relationships that could have appeared to influence the work reported in this paper. Acknowledgements This study was supported by National Natural Science Foundation of China (51874317) and National Science and Technology Major Projects (2017ZX05069-003). Special thanks for Changqing Oilfield in the Ordos basin providing essential reservoir data. Computer Modeling Group for

4. Conclusions In this study, the MMP for the tight oil reservoir in the LD region was determined more accurately by slim-tube experiments and simulation. After that, the existence of near-miscible region was verified and studied. Moreover, the influences of CO2 concentration on the miscibility were studied to determine the minimum CO2 concentration of re-injection gas at the near-miscible condition. This study shed light on the EOR by CO2 near-miscible flooding strategy for the tight oil reservoir. (1) Based on the relationship of pressure, oil recovery, and IFT, a method is established to determine MMP and MNMP for the LD region in this paper. The MMP and MNMP are 22.75 MPa and 17.82 MPa, respectively, which are the upper boundary and lower

Fig. 5. The minimum CO2 concentration of associated gas re-injection at the temperature of 64 °C and the pressure of 19.8 MPa. 7

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offering CMG software are also acknowledged.

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