mechanistic pore scale modelling of eor processes

16th European Symposium on Improved Oil Recovery Cambridge, UK, 12-14 April 2011

A07Mechanistic Pore Scale Modelling of EORProcessesA. Skauge* (Centre for Integrated Petroleum Research) & S.F. Bolandtaba(CIPR)

SUMMARYA novel concept for modelling pore-scale phenomena included in several enhanced oil recovery (EOR)methods is presented. The approach combines quasi-static invasion percolation models with single-phasedynamic network modelling in order to integrate mechanistic chemical oil mobilization methods. Aframework is proposed that incorporates mobilization of capillary trapped oil.

The paper describes modelling tool for pore-scale study of several enhanced oil recovery (EOR) methods.The target is microscopic displacement that involves mobilization of capillary trapped oil by consideringboth viscous and capillary forces. The purpose is to model physical processes occurring on pore scale during injection of EOR processes,like, as an example, the linked polymer solutions (LPS) and investigate the effects of various polymermechanisms such as viscosity effect, adsorption and entrapment processes and consequently evaluate whywe see a mobilization of residual oil saturation. In addition, fluid flow function for a chemical process isgenerated and is used as input for simulation on the Darcy scale.

In this paper, we elaborate the implementation of the methodology to investigate the physics of waterfloodEOR processes with emphasis on the LPS process. Case studies comparing effect of wettability andpermeability to core flood results are also included.


Introduction

Chemical enhanced oil recovery (EOR) methods have received a renewed interest. Especially new possibilities with polymers Morel et al. (2010), Fenglan et al. (2010), polymer particles, Spildo et al., (2009 and 2010), and combined processes like low salinity waterflood combined with surfactants Alagic and Skauge, (2009 and 2010). A challenge for implementing these methods and also other EOR methods is the ability to estimate the process efficiency. An approach to move the process understanding forward has been with pore scale mechanistic modelling of chemical EOR methods, Bolandtaba and Skauge, (2009, 2011). Pore network models are in the authors view not predictive, but can help in explaining trends in measured data. The paper will give some examples of effect of wettability and rock permeability on the oil recovery by EOR processes explained by network modelling. One of many possible EOR methods is linked polymer solution (LPS). LPS consists of nano-scale polymer particles cross-linked with Aluminium Citrate at very low concentration, generally less than 1000 μg/g. Although polymer concentration of LPS systems is less than traditional polymer flooding, similar polymer mechanisms are valid for flow in porous media and fluid behaviour during LPS injection. In addition, slow aggregation and blocking of pores by LPS particles introduce a new mechanism for fluid displacement called log-jamming that increases the microscopic displacement efficiency. Linked polymer solution is therefore considered as a new EOR method. This study uses a network model that combines quasi static and dynamic modelling. The combination introduces a new tool for EOR studies with network modelling, e.g. sensitivity analysis on parameters affecting residual oil mobilization. This contributes to increase the understanding of the underlying physics and micro scale events of LPS flooding. Experimental studies on linked polymer solution have shown a significant potential for increasing the oil recovery, but simulation studies are limited. Since the network model is newly developed, a part of the study has focused on achieving a stable network model that produces reliable results with the necessary output data. While several experimental tests have investigated different parameters such as size of polymer particles, effect of brine salinity, temperature and ratio of polymer to cross-linker, none have addressed the effect of wettability on the performance of LPS injection. The first sensitivity study continues the simulation work by Bolandtaba and Skauge (2011) on the effect of wettability. The wettability of a system is an important parameter controlling the location, distribution and flow of fluids. Four different wettability systems have been analyzed, and the change in residual oil saturation is analyzed. The improved oil recovery with change in wettability for the different systems is attributed to the residual oil saturation and distribution after waterflooding, strength of contact angles and amount of blocking. Analyzing the change in oil saturation as function of pore sizes tell something about where the oil trapped is mobilized. Network Modeling Approach Coupled Quasi-static model In the network models, the pore volume of the rock where fluids could potentially flow can be expressed as a network of interconnected nodes and bonds where the nodes represent the pore bodies and the bonds represent the pore elements. In general, the micro-scale flow modelling can be studied using two types of network models; quasi-static and dynamic models. In the former,

https://www.researchgate.net/publication/254532374_First_Polymer_Injection_In_Deep_Offshore_Field_Angola_Recent_Advances_on_DaliaCamelia_Field_Case?el=1_x_8&enrichId=rgreq-28311b99-5e0d-43a8-abf3-24f1ccb9e240&enrichSource=Y292ZXJQYWdlOzI2MjUyMzY2NTtBUzoxMzg1OTAzOTQ3ODU3OTJAMTQxMDA1MzkzMzIwNQ==


which is the most used network model type, the effect of viscous forces on fluid displacement is neglected in both bulk fluid (fluid that fills the centre of the pore-throats) and wetting layers (fluid resides in the corners of the pore-throats). In the dynamic network models, fluid displacement is controlled by both viscous and capillary forces. Thus, the dynamic model provides a rate-dependent displacement approach for simulating multiphase flow in porous media. The LPS simulation in the network model begins with a quasi-static primary drainage and continues by ageing or altering wettability in the oil-filled pores and thereafter water imbibition until the oil phase is fully trapped at all positions in the network. Fig. 1 shows the flow chart of the whole simulation. In order to mobilise the capillary trapped oil either the capillary effects must be reduced or the viscous force should be increased, either of the methods would give larger capillary number. The algorithm suggests double displacement of fluids consisting of displacement of oil by water and water by oil for each trapped bond which contains oil. The volume of oil displaced is determined by volume conservation. Backbone attachment All the calculations up to this point are performed in the quasi-static network. The process continues by extracting the water-filled elements from the two-phase network. We have named this single-phase network the “Water Backbone”, and we use it to perform time-dependent (dynamic) calculations and model displacements that happen during the LPS injection. These dynamic calculations specify how fluid and rock properties in water backbone change due to the several mechanisms imposed by linked polymer solution. To evaluate the effect of LPS on reducing residual oil saturation, we need to reattach the modified water backbone to the network of disconnected oil phase at the end of imbibition process. The new two-phase network, made by attaching the modified water backbone to the network of disconnected oil clusters gives dissimilar pressure distribution. This pressure difference is used to develop criteria for trapped oil mobilisation. It should be noted that once the quasi-static network is used, no further LPS injection is carried out. The different pressure distribution in the modified quasi static network changes the local viscous force in each pore throat. Such pressure difference, when it is combined with capillary forces, could contribute to the oil movement.

Figure 1. The flow chart showing LPS simulation steps. The processes in each network type (quasi-static, dynamic and coupled quasi-static) is shown by different patterns (pattern map in bottom left)


The basic criterion for oil displacement for a given pore-throat that is connected to the outlet is found by Eq. 1 that compares the imposed capillary pressure on the network with the entry pressure of the pore-throat. Po – Pw < PEntry (1) To displace the oil that has been trapped due to capillary forces, a new criterion is introduced that includes the effect of viscous forces on fluid movement. Figure 2 shows a trapped pore channel that has been surrounded by two water bonds. P1 and P2 are the water pressures in pore bodies (nodes) and Pentry1 and Pentry2 are the capillary pressure required for oil being displaced by water and water being displaced by oil respectively. By modifying the condition of oil displacement and considering the viscous forces, we can show that oil can be displaced if following condition is satisfied: P1 – P2 + PEntry1 – PEntry2 > 0 (2) This criterion represents a double displacement scheme in which water displaces oil and oil displaces water. We assume the water cluster is always in pressure communication with the outlet of the network. Therefore, water can easily escape from the outlet boundary.

Figure 2. The schematic of a capillary-trapped oil bond, having different nodal pressures and showing oil mobilization. PEntry1 and PEntry2 are capillary entry pressures for oil bond and water bond respectively The double displacement approach combines the drainage and imbibition process. For displacement of oil by water, the entry pressure of pore-throats is calculated based on the advancing contact angels. However, for the second part of the displacement, the entry pressure of pore channels should be updated. This is due to the fact fluids displacement depends on the direction of flow. Therefore, the entry pressure of pore channels for the displacement of water by oil is recalculated using receding contact angels instead of advancing. Once the modified water backbone is attached to disconnected oil network, we can examine fluid-fluid interface stability to determine the possibility of trapped oil mobilization. No oil displacement takes place if the same principles of quasi static networks are applied. However, during the dynamic modelling, the mechanisms of EOR method affect properties of model and influence the conductance of fluids. These dynamics effect may change pressure distribution in pore bodies. Such pressure difference when it is combined with capillary forces, could contribute to the oil movement according to the condition in Eq. 2. Different configuration of trapped oil in the model can be considered. The trapped oil may exist in single pore-throat or may occupy cluster(s) of bonds (See Fig 3).


Figure 3 The configuration of trapped oil bond(s) which could exist in network model a) the trapped oil bond is not connected to other trapped oil bonds. b) A number of oil bonds connected to each other forming a trapped oil cluster. water tries to displace oil from node marked with the pressure of P1. The displacement criterion determines node (P2) from which oil displaces water Depending on the coordination number, each node in the network has number of connecting bonds. Therefore, there are number of possible double displacement events that can be imagined. For example in Figure 3a, water displaces the trapped oil from node marked with the pressure P1. The displaced oil can potentially push water that has filled either of bonds connected to node P2. However, only the double displacement event which has the highest driving force occurs. Figure 3b shows a simple representation of trapped oil as a cluster of pore channels. In such condition, finding the double displacement event with highest driving force is more time consuming and complicated. The complexity the algorithm in a 3D model increases with the size of the model. The left hand side of Eq. 2 represents the flow potential or driving forces necessary to make the double displacement event. For all the possible double displacements in the 3D model, this driving force is calculated and is ranked. The combination of oil-water bonds with the highest driving force is identified and the trapped oil is mobilized accordingly. Since the fluid configurations are changed in the network, the pressure distribution should also receive an update. If after the double displacement the mobilized oil reaches the outlet of the network and the driving force is sufficient, oil is produced. The search for double displacement events ends when there is no further potential displacement with positive driving force. The calculation of oil saturation at this point determines how efficient the EOR method can contribute to recovery of residual oil. Modeling of successive EOR slugs and possible oil mobilization follows the same way as it was described for the first slug (See Fig. 1). It means that extraction of water backbone from two phase model, running the dynamic model and the examining of oil mobilization are performed for the next step. The whole simulation reaches to the end when injection of EOR material does not generate considerable effect on oil mobilization.


LPS Mechanisms Adsorption of polymer onto the rock reduces the conductance of the pore elements due to a decreased area open to flow (See Fig 4). The adsorption of LPS particles on the pore-throats wall has been modeled using the Langmuir isotherm equation:

pol

polAds BC

ACC

+=

1 (3)

where Cpol is the polymer concentration and “A” and “B” are constant terms which vary for different brine salinity.

Figure 4. Adsorption of polymer on pore-throat wall a) pore throat before adsorption with the effective radius of R b) Pore throat after adsorption the effective radius is reduced by dr. dr is the thickness of the adsorbed layer The viscosity effect is included in the network model by adopting the Flory equation for the polymer solution and a mechanism for blocking of bonds by straining is controlled by the pore and particle size. In order to model the log-jamming mechanism, an extra controlling parameter is added. The new parameter is called steep of log-jamming curve and is implemented to control the critical concentration for pore blocking. See Bolandtaba et al. (2009) for more details. The post-LPS injection simulation involves examining all the disconnected oil bonds for the stability condition given in the model. Finally, the oil is mobilised from the bond combination which has the largest driving force. Since fluid configurations are changed due to the oil displacement, the nodal pressures are updated accordingly. The same procedure is repeated in order to obtain the next event having the highest flow potential. The process continues until none of the possible bond combinations gives positive driving force. The oil saturation at this point determines how efficient the LPS slug is to mobilise the residual oil. After LPS simulation, oil always occupies the bulk section of the pore throats while water could exist at both bulk and film areas. The bond volume which is not filled by oil is considered as water film. Injection of following LPS slugs are carried out when no displacement with positive driving force exists. The same procedure for trapped oil mobilisation is repeated after each LPS injection step. The whole simulation can reach to the end if the LPS effluent reaches stable condition and no further blocking occurs. LPS flooding on the water backbone result in blocking of bonds and a new pressure distribution. The water backbone is reconnected to the original network and the new pressure distribution mobilises oil.


Consider a MWS system with strongly wetted bonds. The pore size and residual oil distribution is illustrated in Figure 5. As a comment we would like to note that the total volume of the bonds with oil in bulk section has been used when the residual oil distribution is visualised.

Figure 5. Pore size and trapped oil volume distribution after waterflooding for a MWS system. The oil is located in the smallest and largest bonds after waterflooding. Mobilisation of oil in the largest bonds will contribute significantly in reducing the residual oil saturation. LPS is injected in slugs and simulations have shown that the reduction in residual oil saturation decreases with increasing slug number (Bolandtaba et. al 2009). The reduction in Sor for the MWS system with slug number is illustrated in Figure 6.

Figure 6. Reduction in residual oil saturation as function of LPS slug number for a MWS system.


The first three slugs result in a high reduction in Sor, while the following slugs give little reduction in residual oil saturation. Even though the purpose of each slug injection is to block bonds, the reduction is Sor is not a measure of blocked bonds. During LPS injection the water relative permeability fluctuates. The blocking of pore channels caused by log-jamming mechanism decreases the absolute permeability of network and in particular reduces the water relative permeability (Bolandtaba and Skauge 2011). Moreover, the increase in water relative permeability is contributed to the additional extra room available for water after some oil is produced. Therefore, the water relative permeability is a balance between the amount of blocking and the amount of oil produced. Effect of rock wettability. By altering the wettability of the system after primary drainage, different wettability scenarios will occur prior to water imbibition and LPS flooding. The sensitivity study on wettability is performed on uniformly water-wet, mixed-wet and fractional-wet systems, for more details about different wettability classes, see Dixit et al. (1999), and Skauge et al., 2007. Each system was treated separately looking at blocking, oil distribution and mobilisation. This is possible since the distribution of oil and blocked bonds can be extracted from the network model after injection of each LPS slug. Visualisation of blocking and micro scale oil mobilisation represents a new tool for analysing LPS flooding. Further discussion will show some examples. Each case is characterised by different distribution of contact angle after ageing process. Bolandtaba and Skauge (2010) performed a wettability study on a uniformly-wet system and found that the LPS efficiency on mobilising trapped oil increases as the medium becomes weakly water-wet. They attributed the observation to the fact that the entry pressure required for displacement of oil by water decreases as the medium becomes weakly water-wet. Therefore, in the double displacement criteria less driving force is needed to mobilise the disconnected oil. Variation of wettability from pore to pore has a major effect on phase continuity along pores through films and layers in two-phase flow. Morrow and McCaffery (1978) found that in weakly wetted pores continuous wetting films are absent. For an interconnected pore network model, this means that a large number of phase clusters are disconnected from inlet or outlet. Mobilisation of these clusters can only happen through multiple displacements (van Dijke et al., 2002). For mixed- and fractional-wet systems not only the wettability, but also the relative amount of oil and water-wet pores is decisive. For mixed-wet systems the amount is controlled by the separating wettability radius (rwet), while for fractional-wet systems it is the oil-wet fraction. Observations from the simulations show that the most water wet case is having significant snap-off displacements, as expected. Snap-off traps oil in globules in the bulk section of the pores by swelling of water films, while the less water-wet cases trapping is more due to bypass on the oil. The trend in trapping for snap-off and bypass with contact angle distribution is illustrated in Figure 7.


Figure 7 Effect on trapping from distribution of contact angles in the uniformly water-wet system. Bypass increases as the contact angles are reduced, while trapping due to snap-off increases as the contact angles are increased. As a result, the residual oil in intermediate cases is not trapped due to bypass or snap-off alone, rather a combination. The diversity in trapping and wettability close to weakly water-wet could be optimal for LPS flooding and following oil mobilisation. Blocking of water bonds may reduce the water conductivity and potentially yield a new pressure distribution. If sufficient to fulfil the double displacement criteria, water displaces oil to find a new path through the network. Therefore, the amount of blocking is important for the effect of LPS flooding. The distribution of blocking for the water wet case is visualised in Figure 8.

Figure 8 Distribution of blocked bonds for a water wet case. 17.3 % of the bonds were blocked and as expected it is the smallest bonds that are blocked by LPS particles. Another more unexpected observation is that the majority of the smallest bonds are blocked. For these bonds to be blocked they must be accessible and water filled. The distribution of oil bonds after imbibition and mobilisation of these after LPS flooding is visualised in Figure 9.


Figure 9 Distribution and mobilisation of oil bonds for water wet case. For a uniformly water-wet media, the smallest pores have the largest driving force for spontaneous water imbibition. Although this is not a fully accessible network, oil is primarily trapped in the larger bonds (Figure 9). The figure also shows that LPS flooding mobilises oil from all bond radii. Larger pores contain more oil, so mobilising oil from a large bond and to the outlet contributes more than oil from a small bond (Figure 10).

Figure 10 Distribution and mobilisation of oil volumes for the water wet case. All mixed-wet large cases are primarily oil-wet with water index less than 0.2. Results turn towards that the more water-wet the case is, the better the effect from LPS flooding become. This is indicated by increased increase in oil recovery with water index. About 20 % of the bonds are blocked, primarily the water-wet bonds in mixed wet large (MWL) cases. The amount and distribution of blocking is actually quite similar to the one observed in the uniformly water-wet system. As mentioned earlier, the amount of blocking must be seen in perspective to the residual oil saturation and oil distribution after waterflooding. The oil filled bond distribution is similar to the one found by Nyre et al. (2008) for a MWL system with the residual oil located in the pores above rwet. There is practically no oil left in the water-wet pores after waterflooding. These pores are filled first, but the effect could be reinforced by the strongly water-wet value for these pores (0.8 ≤ cos θow ≤ 1) which present a strong driving force for spontaneous water imbibition. Another possibility is that little or no


oil invaded into the smallest pores during oil drainage, and that this oil was displaced early in the imbibition process. Although it can be discussed which wettability option that gives the highest increase in oil recovery, it must be noted that all cases improve the oil recovery by 16 - 25 %. This is 0.05 – 0.12 reduction in residual oil saturation. Case 1 gives the highest increase in oil recovery, but all cases give substantial increase. The MWL system is therefore only to some degree sensitive towards wettability. However, the effect from LPS could have been significantly higher if not much of the mobilized oil had become retrapped in the larger pores. Results from different wettability systems have shown that residual oil saturations prior to LPS flooding needs to be taken into account when discussing wettability sensitivity. Figure 11 illustrates the relationship between residual oil saturation and increase in oil recovery for the different cases in each wettability system.

Figure 11 Increase in oil recovery as function of residual oil saturation after waterflooding for different wetting systems. The mixed-wet small system (yellow) shows a strong dependency between residual oil saturation and increase in oil recovery. This is in contrary to the fractional-wet system (turquoise) where no dependency is observed. The uniformly water-wet (dark blue) and mixed-wet large (pink) systems show some relationship between Sorw and increase in oil recovery, but significantly less than the mixed-wet small system. The fractional-wet system is too complicated to be explained by one parameter only (Sorw). The wettability sensitivity for the systems is illustrated by plotting the increase in oil recovery for each case as function of the water index (Figure 11). As illustrated in Figure 11, the MWS system is also the most sensitive system towards wettability. In the MWS system the increase in oil recovery ranges from 5 – 50 %, with a reduction in Sor between 0.01 and 0.16. The result for the MWS system is in great contrary to the MWL system where all cases give significant increase in oil recovery. Since the water index is relatively low for the MWL system due to the smallest pores being water-wet, it must be noted that also this system is sensitive towards wettability. Skauge et al (2010) found log-jamming to be most efficient at mixed-wet conditions where locally increased differential pressure can mobilize capillary trapped oil. This observation is observed for the mixed-wet small system where an increase in oil recovery of 50 % is observed, twice the best increase found for the uniformly water-wet and mixed-wet large systems. Even though the mixed-wet small system is classified as most sensitive towards


wettability, it also has the potential to be the most efficient system. One explanation to this could be that the residual oil after waterflooding is trapped in the largest bonds. This is contrary to the mixed-wet large system where oil is trapped in the medium sized bonds above the separating wettability radius (rwet). Following this argumentation, the water-wet case should have potential for reducing the oil saturation substantially. For core flooding at water-wet conditions, oil mobilization by microscopic diversion can occur by log-jamming in water films or in pore throats during bulk flow. In the case of film flow, water will find a new path by swelling of the films, whereas blocking of pore throats may divert water from water filled pores to oil filled pores. Another factor specific for core flooding at water-wet conditions is that log-jamming can occur at lower concentrations and by smaller particle size when water film flow is predominant. This mechanism may be different than for intermediate-wet porous media (Skauge et al., 2010). An assumption made in the network model is that LPS particles travel in bulk section of pore throats (bonds) and not in the water films (Bolandtaba et. al. 2009). Therefore, even better results are expected for the water-wet system if we included particle flow also in the films. Blocking is an important factor for the LPS effect. However, the amount of blocked bonds has not turned out to be decisive for increase in oil recovery, even though it often gives a good indication. Sometimes blocking will give locally increased differential pressures sufficient to mobilize the trapped oil. Other times, blocking has not given sufficient pressure redistribution to mobilize any oil. Within the same wettability system there has been observed higher increase in oil recovery for cases with less blocking. This must be seen in perspective to the residual oil saturation, distribution and contact angles for the system. Generally, the wettability of a system is important when determining the effect from LPS flooding. From the results presented here, it turns out that the distribution of oil after waterflooding, leading to blocking and mobilization from certain pore sizes, as a result of wettability, is more important than the reduction in entry pressures in the double displacement criteria. However, it is most likely a combined effect from the two contributions. The effect from the mixed- and fractional-wet systems could also be substantially improved if the capillary forces re-trapping the oil after mobilization were reduced, e.g. by combined LPS and surfactant flooding. Effect of permeability on LPS flooding The variation of rock permeability and the influence of the LPS process also involve analysis of oil distribution, oil mobilization and bond blocking. As the PSD is shifted within the same range from a majority of small pores to a majority of large pores, both permeability and porosity increases. While the porosity varies only slightly with the coordination number (z), the permeability decreases significantly as z is reduced. With less connected pathways through the network, the ease with which fluid moves through the network is reduced. The effect on permeability is investigated by changing rmax. The increased porosity with rmax has been balanced by increasing the bond length. Increasing the bond length does not have any effect on permeability or LPS flooding. The effect from permeability on LPS flooding with regards to permeability is thereby controlled by the maximum pore radii.


Figure 12. Increase in oil recovery at waterflood residual oil saturation as function of permeability for uniformly water-wet systems. Figure 12 illustrates almost a linear increase in increase in oil recovery with permeability. This is in line with what Spildo et al. (2009) found in an experimental study of LPS flooding on uniformly water-wet cores with different permeability. From the pore size distribution there is a trend for increased heterogeneity with increasing permeability. If microscopic diversion by blocking of pores is responsible for increased recovery, an increase in recovery with increasing heterogeneity is expected (Spildo et. al. 2009). The simulated data for the uniformly water-wet system is thus consistent with the proposed mechanism for increased recovery. As observed in the wettability sensitivity study, LPS particles block the primarily the smallest bonds. A reason for the improved recovery with increased permeability is that there is more oil available for mobilization in the largest pores of the high permeable network. This can be confirmed by visualization of the oil bonds before and after LPS flooding. The distribution and mobilization for one network is visualized below.

Figure 13 Distribution and mobilisation of oil bonds for a water wet network.


Figure 14. Distribution and mobilisation of oil volume for a water wet network According to Chatzis (1983) and pore filling sequence in uniformly water-wet systems, residual oil is trapped in the largest pores (Figure 13 and 14). The largest pores in the low permeable network are significantly smaller than in the high permeable network since and the pore size distribution has been kept constant, mobilization of the oil from the largest bonds will contribute more to the LPS effect than mobilizing the largest bonds for low permeability network. The capillary entry pressures decrease with increasing pore size this will contribute to reduce the entry pressures in the double displacement criteria. This fact will be valid for all networks with increasing pore radii. On the other hand, the decreasing capillary entry pressures can also reduce the contribution to the double displacement criteria if the capillary driving force is positive. The pore size is therefore a parameter that can improve or reduce the increase in oil recovery. It must also be seen in perspective with other parameters. The increase in oil recovery with permeability for the uniformly water-wet networks ranges from 16 to 34 % over a range of 1400 mD. This is a reduction between 0.05 – 0.09 saturation points of the residual oil saturation. Increase in oil recovery increases with permeability, and all cases studied have given substantial change in oil recovery. The mixed-wet large networks do not show the same linear trend in increase in oil recovery as the uniformly water-wet networks.

Figure 15 Distribution and mobilization of oil volume for a network with fixed separating wettability radius rwet (MWL).


As observed in Figure 15, oil is only displaced from the water-wet pores during the waterflood. This should be suitable for blocking by LPS particles. The residual oil saturation is trapped in the largest bonds and mostly oil from the smaller bonds is mobilized by LPS injection. The mobilized oil comes primarily from the largest water-wet bonds. This is probably because these bonds are targeted next according to pore filling sequence. Note also that the oil saturation is increasing in the largest pores. The re-trapping in large pores is more pronounced for other wetting classes.

Figure 16 LPS effect for different permeabilities and wettability systems. Increasing the permeability increases the oil recovery from LPS flooding for all wettability systems (Figure 16). Another distinct feature is the jump in increase in oil recovery between 300 – 500 mD. There may be a threshold permeability to be overcome before the effect from LPS injection becomes substantial. Above this threshold permeability there is a linear increase in increase in oil recovery with permeability for all systems. The mixed-wet small system is the most sensitive system to permeability with increase in oil recovery ranging from 4 to 49 % with a fixed rwet. This sensitivity is reduced significantly if a variable rwet is used, where the increase in oil recovery from all permeabilities become substantial. Above a certain permeability the effect from using a fixed or variable rwet become less significant. This is also observed for the mixed-wet large system. The MWL and uniformly water-wet systems show similar increase in oil recovery with permeability except for the lowest permeable network. The fractional wet system shows the same trend as the mixed-wet systems, except for a significant lower increase in oil recovery. The smallest pores often remain water filled after oil drainage which is suitable for blocking since LPS particles target the smallest pores. Even though blocking is an important parameter it is not decisive for the increased oil recovery, this is especially illustrated by the mixed-wet small system. The mixed-wet small system turns out to be the most sensitive system towards both wettability and permeability. On the other hand, it is also the system with the highest increase in oil recovery. This is primarily attributed to the fact that oil is trapped and mobilized from the largest bonds. The fractional-wet system is also sensitive to both wettability and permeability changes, but gives little increase in oil recovery. The mixed wet large and uniformly water-wet systems have similar sensitivity to wettability and permeability and give an increase in oil recovery in between the two other wettability systems.


For the systems with mixed wettability some of the mobilized oil becomes retrapped in the larger pores due to capillary forces. This reduces the effect from LPS injection significantly as oil in the largest pores make the largest contribution to reduction in oil saturation. In order to have less retrapping of oil the capillary forces needs to be reduced. This is possible by reducing the interfacial tension by surfactant flooding. Therefore, this study has found potential for a new EOR method combining surfactant and LPS injection. By comparing the results from each network it is observed that at low permeabilities the wettability has a major effect on the increase in oil recovery, while it becomes less important at higher permeabilities. This implies that at high permeabilities the wettability effect is overruled by the permeability. However, the wettability is still influential, but to a less extent than for the low permeable networks where it is decisive in determining the increase in oil recovery. Results indicate that the permeability have a significant impact on the effect from LPS flooding for all wettability systems. For a uniformly water-wet system there is almost a linear increase in increase in oil recovery with permeability. For the mixed-wet systems a theory about threshold permeability is introduced. Below the threshold permeability the increased oil recovery is significantly less than above and highly dependent on the permeability. The same trend is observed for the fractional-wet system, but the increased oil recovery with permeability is less than for the mixed-wet and uniformly water-wet systems. Results also indicate that there is an effect of the coupling of wettability and permeability. At low permeabilities the increased in oil recovery is very sensitive to wettability changes, while wettability changes turn out to be less influential at higher permeabilities. For the systems with mixed wettability, much of the mobilized oil becomes retrapped in the largest pores. This indicates that the capillary forces have a significant impact on the mobilization and that a reduction in these forces could enhance the effect from LPS injection significantly. A combination of LPS and surfactant flooding is proposed to reduce the amount of retrapping after oil mobilization.

Conclusions

The developed network model has been tested and found to give results in line with earlier published experimental results. The network modelling results have been used to interpret trends in data and give more in-depth understanding of the mechanisms and parameters that govern the EOR processes. The network model characterizes an idealised micro scale representation of the porous media. Therefore, the results should not be over interpreted, and the assumptions made must be considered. The effect of LPS performance was been studied as a function of rock wettability. The results show a strong dependency of oil recovery on wettability. Simulation results imply that the wettability effect is more than just reduced capillary entry pressures. Residual oil saturation, oil distribution after waterflooding and potential for blocking are important parameters that need to be addressed prior to LPS flooding.


In cases with mixed wettability much of the mobilised oil may become re-trapped in the largest pores due to capillary forces. The mixed-wet small system seems to have the highest potential for LPS injection, but is also the most sensitive system to wettability changes. Results from the permeability study show that it has a significant impact on the increase in oil recovery by LPS flooding. For a uniformly water-wet system there is almost a linear increase in increase in oil recovery with permeability, while for the other wettability systems the influence is greatest at low permeabilities and a threshold permeability is observed. Results also indicate that there is a effect from the combination between wettability and permeability. At low permeabilities, the wettability has a major influence on the increase in oil recovery, while it becomes less important at higher permeabilities.

Acknowledgments

We gratefully acknowledge financial support from the PETROMAKS program at the Norwegian Research Council.

References

Alagic, E., and Skauge, A., “Combined Low Salinity Brine Injection and Surfactant Flooding in Mixed−Wet Sandstone Cores,” Energy and Fuels, 2010, DOI: 10.1021/ef1000908 Alagic, E., and Skauge, A., “Change to Low Salinity Brine Injection in Combination with Surfactant Flooding,” 2009, paper B31, proceedings from Improved Oil Recovery Symposium, Paris, France, April 27-29. Bolandtaba, S. F., Skauge, A. , Mackay, E.: Pore-Scale Modeling of Linked Polymer Solution (LPS) – A New EOR Process. EAGE IOR Conference, Paris, 27-29 April (2009) Bolandtaba, S.F., Skauge, A.: Network Modeling of EOR Processes; A Combined Invasion Percolation and Dynamic Model for Mobilization of Trapped Oil, accepted for publication in Transport in Porous Media, (2011) Chatzis, I., Morrow, N. R. and Lim, H. T., “Magnitude and Detailed Structure of Residual Oil Saturation”, SPE Journal, 23 (2), 311-326, 1983. Dixit, A. B., McDougall, S. R., Sorbie, K. S., Buckley, J. S.: Pore-Scale Modeling of Wettability Effects and Their Influence On Oil Recovery, SPE Reservoir Evaluation & Engineering, 2, 25-36 (1999)

Fenglan, W., Xia, L., Siyuan, L., Peihui, H., Wenting, G., and Yonghui, Y., Performance Analysis and Field Application Result of Polymer Flooding in Low-Permeability Reservoirs in Daqing Oilfield, SPE 136904-MS, 2010


Morel, D., Vert, M., Jouenne, S.,and Gauchet R., and Bouger, Y., First Polymer Injection In Deep Offshore Field Angola: Recent Advances on Dalia/Camelia Field Case, SPE 135735-MS, SPE Annual Technical Conference and Exhibition held in Florence, Italy, 19–22 September 2010.

Morrow, N. R. and McCaffery, F., “Displacement Studies in Uniformly Wetted Porous Media”, Wetting, Spreading and Adhesion, Academic Press, New York, 289-319., 1978

Nyre, A., Spildo, K., and Skauge, A.: “Functional Relations of Intermediate Wettability by Network Modelling,” 10th International Symposium on Evaluation of Wettability and Its Effect on Oil Recovery, Abu Dhabi, 2008 Skauge, A., Spildo, K., Høiland, L., and Vik B., “Theoretical and experimental evidence of different wettability classes,” Journal of Petroleum Science and Engineering 57 (2007) 321–333 Spildo, K, Skauge, A., Aarra, M.G., and Tweheyo, M.T., “A New Polymer Application for North Sea Reservoirs,” SPERE&E, June 2009, 427 – 432 Spildo, K., Skauge, A., and Skauge, T., “Propagation of colloidal dispersion gels (CDG) in laboratory core floods,” SPE-129927-PP, paper prepared for presentation at the 2010 SPE Improved Oil Recovery Symposium held in Tulsa, Oklahoma, U.S.A., April 2010.

Van Dijke, M. I. J. and Sorbie, K. S., “Three-phase flow in WAG processes in mixed- wet porous media: pore scale network simulations and comparison with micromodel experiments”. Paper SPE 75192-MS presented at the SPE Improved Oil Recovery Symposium in Tulsa, Oklahoma, 13-17 April, 2002

mechanistic pore scale modelling of eor processes

Documents