Enhanced gas recovery by nitrogen injection: The effects of injection velocity during natural gas displacement in consolidated rocks
Introduction
Primary oil and gas recovery methods unlock only about 10% of the oil and gas initially in place, while secondary recovery efforts obtain an additional 20–40%. Therefore, a substantial quantity of oil and gas remains in the formation until more advanced recovery methods are employed. These methods are known as enhanced oil or gas recovery techniques (Anonymous, 2020). Enhanced gas recovery (EGR) and storage by CO2 injection are gaining recognition within the research environment as its combined natural gas (CH4) recovery and CO2 storage benefits. Even though, both nitrogen (N2) and CO2 can be used to increase hydrocarbons (HCs) yield from oil and gas reservoirs. However, CO2 drawbacks are mainly excessive mixing and high compression ratio, thus hindering the overall process less economical. In contrast, N2 could be easily obtained through cryogenic air separation. It requires less compression ratio than CO2, which is why a lower amount of it was required to initiate much pressure in the CH4 reservoir. Also, the sweetening process cost of natural gas contaminated with N2 is less than that with CO2. This was why the fraction of produced N2 tolerance is higher than the CO2 limit during the natural gas exploration.
The promotion of EGR is still at its infant stage due, to the excessive mixing between the injected (displacing fluid) CO2 and the nascent displaced fluid (natural gas) during the flooding process (Oldenburg and Benson, 2002; Shtepani, 2006; Turta et al., 2007; Sim et al., 2008; Al-abri et al., 2009; Sim et al., 2009; Sidiq et al., 2011; Hughes et al., 2012; Honari et al., 2013; Khan et al., 2013; Zhang et al., 2014; Honari et al., 2015; Patel et al., 2016; Honari et al., 2016). This adulterates the recovered natural gas and thus, reduces its heating and market value, which results in the high cost of the sweetening process to maintain its purity standard for consumption (Oldenburg and Benson, 2002; Sim et al., 2009). Such an overall problem has not only limited the EGR project to a few pilot trials (Pooladi- Darvish et al., 2008) but also made the process apparently uneconomical because of unprecedented mixing with the displaced gas. This makes the whole phenomenon to be poorly understood (Patel et al., 2016). Thus, finding an alternative gas with good displacement properties and minimal miscibility could be a nice development for the oil and gas industry.
Several authors (Gu et al., 2019; Hughes et al., 2012; Janssen et al., 2018; Abba et al., 2018) have carried out an extensive study on how to delay CO2 breakthrough time during EGR process. Among them, Abba et al. (2018) and Gu et al. (2019) were able to achieve reasonable improvement. Abba et al. (2018) use varying connate water concentration and was able to delay CO2 breakthrough by 20 min at a concentration of 10% wt. sodium chloride (NaCl). On the other hand, Gu et al. (2019) use different mole ratios of CO2/N2 mixture gases in coalbed core samples. They reveal that injection of N2-rich mixtures contributes to preventing the nascent early breakthrough of injected CO2 and safely stored large volumes of CO2 into the shale sediment over the long term (Gu et al., 2019). The injection of CO2 into the reservoir generally results in premature breakthrough due to nascent mixing with methane, eventually limiting it application for efficient natural gas recovery. This was the reason why many researches on carbon dioxide injections were tailored toward storage rather than recovery. Furthermore, most of the works on the effect of CO2 injection on gas production are simulation-based. Till date, no established efficient alternative gas and injection rate capable of unlocking the residual gas beneath the ground has been highlighted. This necessitated the need for an in-depth study to use N2 as an alternative to minimize such complex phenomenon of gas-gas miscibility since both CO2 and CH4 are miscible in all outcomes (Abba et al., 2018; Honari et al., 2016). The choice of the flow velocity in EGR thus becomes important since higher injection rates could lead to premature mixing of the fluids while lower injection rates generally provide longer resident times for the fluids in contact and indirectly increases the mixing of the gases yet again. In this research, the experimental study of the effect of N2 injection rates during the EGR process using consolidated rocks was conducted. Determining the best and optimum injection rate is vital for better recovery and less miscibility. This could provide reservoir engineers, geologist, and production engineers with the desired tools to successfully characterize the transport of injected N2 as it plumes transverse within the porous media during the displacement process. The mechanism behind the concept of the enhanced gas recovery process is well demonstrated using a dispersion theory as will be explained in the next two sections.
Newberg and Foh (1988) used a single parameter diffusion-like model based on the 1D Advection-Dispersion equation (Perkins and Johnston, 1963; Coats et al., 2009). The model is mostly used to describe the flow of gas transport through a porous medium along the x-direction as shown in Eq. (2.1):
The effluent composition (C) from the GC at distance (x) under time (t), longitudinal dispersion coefficient (KL), and interstitial velocity (u) are key parameters in the above equation. The displacement of methane by N2 in consolidated rocks is governed by Eq. (2.1). This model is widely accepted to simulate fluids movement in porous medium. However, simulation studies have proved that using the equation in its current form resulted in some abnormal behaviour named upstream migration. It occurs especially when the concentration gradient (dC/dx) along the length scale becomes positive, which is invariable like the case of supercritical N2 flowing through a contaminant after breakthrough in the porous medium generating a large magnitude of both dC/dx and dispersion coefficient. Invariably Eq. (2.1) can be re-written in a dimensionless form (Mamora and Seo, 2002) as follows;Where;
Since the injection of N2 is at x = 0, then
Initial condition: C = 0 at tD = 0,
Boundary conditions: C = 1 at xD = 0, C → 0 as xD → ∞
Therefore, the solution to Eq. (2.2) maybe presented as follows:
The effluent core flooding composition could be fitted into the analytical solution of the 1D differential Advection Dispersion (AD) equation (Eq. (2.3)) in terms of the Péclet number to evaluate the corresponding dispersion coefficient. The real dispersion coefficient for the experiment is the value which provides the optimum synergy between the experimental result compared to the numerical solution.
In (1963) Perkins & Johnston proposed a widely accepted model that can predict the dominant displacement mechanism during the EGR process in a porous medium. This model equation can be present as:Where;
Pexp is the experimental medium Péclet number, which can be evaluated using the average interstitial velocity (u) in m/s, D is the molecular diffusion coefficient in m2/s, and d is the characteristic length scale in meters. The characteristic length scale is defined as the average medium-grain diameter of the core sample or sand pack. Generally, at Pem <0.1, diffusion dominates the dispersion process, and at Pem>10 advective mixing dominates the dispersion process. The analytical solution to Eq. (2.3) is used to fit the concentration profiles obtained from the experimental data to evaluate the dispersion coefficient.
Coats et al. (2009) correlated the dispersion coefficient with the molecular diffusion coefficient as shown in Eq. (2.5).
Here, is in meter (m) and is called the dispersivity of the porous medium, and n represent an exponent. The tortuosity () can range from 1 to as high as 13 or more for consolidated rocks as reported by Honari et al. (2013). The tortuosity , can be obtained empirically through various methods, whereas n is mostly determined using a core flooding system (Hughes et al., 2012).
The diffusion coefficient (D) signifies the extent or magnitude at which a substance or fluid disperses through a unit area (m2) per unit time (s) at a given unit of a concentration gradient. The proposed empirical model which relates the molecular diffusion, temperature, and pressure for empirical diffusion coefficient determination as indicated by (Hughes et al., 2012; Liu et al., 2015) was developed by Takahashi and Iwasaki in (1970). Similarly, empirical equation has been tested by various researches in determining the real and accurate diffusivity using Eq. (2.6) at conditions applicable to EGR by CO2 injection. The diffusion coefficient of CO2 in CH4 was dignified at 298–348 K and pressures of 5–15 MPa in a porous bronze plug (Takahashi and Iwasaki, 1970). The results were well within the range of conditions applicable to the EGR process (Abba et al., 2017).where DCO2, CH4 is the molecular diffusion coefficient of CO2 in pure CH4 calculated in m2 s−1 with P in MPa and T in K. The absolute average deviation (AAD) of this correlation from the experimental data was 1.5% over the range of 298–348 K and 5–15 MPa (Abba et al., 2017, 2018). In this study, a different model was used to cater for the inclusion of Nitrogen (N2) gas during the natural gas displacement. This model equation was presented in Eq. (2.7). It is a correlation formula obtained by Fuller et al. (1966) by means of computer-aided correlation of 340 experimental points, expressed as:Where (∑ ) and (∑ ) are the values derived from the summation of atomic diffusion volumes of N2 and CH4 molecules respectively. These values and other simple molecules are presented in Table 1.
The equation was further simplified after inserting the values of atomic diffusion volumes and the molecular weight of nitrogen and methane. The same was applied for carbon dioxide and methane displacement mechanism. These simplified equations were presented in equations (2.8), (2.9) respectively.where T and P are temperatures and pressure in kelvin (K) and megapascal (MPa) respectively. For example, at the same temperature and pressure, Eq. (2.9) was validated using the experimental work of Abba et al. (2018). The molecular diffusion coefficient () was found to be 22.52 × 10−8 m2/s, which was 0.18% absolute average deviation (AAD) when compared with Abba et al. (2018) results.
Section snippets
Materials and method
In this research, an experimental study using a core flooding system to investigate the effect of injecting velocity during EGR process. The experiment was conducted by saturating the core plug with CH4 and injecting of N2 at different injection rates. The core plugs used were Berea and Bandera Gray sandstones whose properties as presented in Table 2.
Original gas in place (OGIP) determination
In order to evaluate the CH4 recovery efficiency of each injection rate, the Original Gas in Place (OGIP) must be determined.
Vb is the bulk volume of the reservoir ft3, φ is reservoir porosity, Sw is formation water saturation, and Bg is gas formation volume factor, ft3/scf.Where z is gas compressibility factor, Psc and Tsc are pressure and temperature at standard conditions; P and T are pressure and temperatures at desired conditions. Taking Psc and Tsc to be
Conclusion
Identifying displacement phenomenon in fluid transport in porous media is quite important especially when investigating solute transport in sandstone rocks. The choice of the flow velocity in EGR thus becomes important since higher injection rates could lead to premature mixing of the fluids and lower injection rates generally provide longer resident times for the fluids in contact and indirectly increases the mixing of the gases again. The medium peclet numbers mostly indicate the best
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
The authors wish to acknowledge the Petroleum Technology Development Fund (PTDF) for the studentship and Petroleum and Gas Research Group of the University of Salford, Manchester, UK, for their support.
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