SPE-171519-MS

Optimizing Recovery in Gas Condensate Reservoirs

Y. H. Seah, Schlumberger; A. C. Gringarten, Imperial College London; M. A. Giddins and K. Burton,Schlumberger

Copyright 2014, Society of Petroleum Engineers

This paper was prepared for presentation at the SPE Asia Pacific Oil & Gas Conference and Exhibition held in Adelaide, Australia, 14–16 October 2014.

This paper was selected for presentation by an SPE program committee following review of information contained in an abstract submitted by the author(s). Contentsof the paper have not been reviewed by the Society of Petroleum Engineers and are subject to correction by the author(s). The material does not necessarily reflectany position of the Society of Petroleum Engineers, its officers, or members. Electronic reproduction, distribution, or storage of any part of this paper without the writtenconsent of the Society of Petroleum Engineers is prohibited. Permission to reproduce in print is restricted to an abstract of not more than 300 words; illustrations maynot be copied. The abstract must contain conspicuous acknowledgment of SPE copyright.

Abstract

Gas condensate reservoirs exhibit complex flow behavior below the dewpoint pressure, caused bycompositional changes and the creation and growth of a condensate bank around the wellbore, whicheffectively reduces the relative permeability to gas flow. As a result, gas production decreases and liquidcondensate, a valuable resource, is left behind in the reservoir.

Well deliverability impairment resulting from liquid dropout has been a main focus of gas condensatestudies for over 60 years. We have used compositional reservoir simulation, with representative lean- andrich-condensate fluids and velocity-dependent relative permeability models, to predict condensate dropoutunder typical operating conditions. The effectiveness of different production methods and remediationsolutions in minimizing condensate buildup below the dewpoint pressure was quantified, using first asingle-well model and then full-field models of tight and low-permeability gas condensate reservoirs inwhich six vertical wells were compared with two horizontal wells.

We found that, although both horizontal wells and vertical well stimulation do improve well produc-tivity, productivity enhancement depends greatly on well and reservoir parameters such as horizontal welllengths, well placement, reservoir permeabilities, and gas condensate compositions. For gas condensateproduction below the dewpoint pressure, it is possible to achieve an optimum balance between gasproduction rate and pressure drawdown, thus minimizing condensate dropout effect while producing at areasonable rate. In a low-permeability gas condensate reservoir, the six vertical wells perform slightlybetter than the two horizontal wells for the same amount of gas production. In a tight gas condensatereservoir, on the contrary, gas recovery with two horizontal wells is significantly greater than with sixvertical wells. Although, in this model, well stimulation can increase the productivity of the vertical wellsin tight gas condensate reservoir, it is not as effective as using horizontal wells.

IntroductionContinuous developments in drilling and logging technologies have enabled deeper, higher pressure, andhigher temperature gas condensate reservoirs to be discovered and developed. In addition, most maturegas condensate fields worldwide are at the later stage of their field life, gradually approaching theirdewpoint pressure below which liquid condensate drops out. Globally, the increasing demand for naturalgas liquids on world markets has stimulated interest in optimizing gas condensate resources (BP 2014).

Gas condensate reservoirs exhibit complex flow behavior as a result of retrograde condensation whenthe bottomhole flowing pressure drops below the dewpoint pressure. Gas condensate dropout near thewellbore must be considered, as changes in fluid saturations affect relative permeabilities. As a result, itaffects the final decision made in the production planning of a gas condensate field.

This has been the subject of many studies for over 60 years (Muskat 1949). It was discovered that threeconcentric regions with different liquid saturations emerge around a gas condensate well producing belowthe dewpoint pressure (Kniazeff and Naville 1965). Away from the well, an outer region contains theinitial liquid saturation. Next, an intermediate region shows a rapid increase in liquid saturation and acorresponding reduction in gas relative permeability. Liquid in this region is still immobile because thecritical saturation has not been reached yet. Nearer to the well, an inner region forms where liquidsaturation exceeds the critical saturation and both the reservoir gas and liquid condensate flow into thewell with constant composition.

A fourth region in the immediate vicinity of the well with low interfacial tension resulting from highflow rate yields lower liquid saturation and higher gas relative permeability (Gringarten et al. 2000). Theexistence of this fourth region is important because it counters the productivity loss caused by liquiddropout. This region is where the capillary number effect is dominant over the inertial resistance effect,contributing to higher gas recovery.

Background and TheoryMuskat (1949) first suggested that liquid condensate builds up around the wellbore when bottomholepressure drops below the dewpoint pressure and explained mathematically the condensate saturationprofile around a producing well in a gas condensate reservoir. Eilerts et al. and Kniazeff and Navillepublished papers in 1965, in which they modeled gas condensate well deliverability numerically withrespect to time and radial distance and studied the effects of non-Darcy flow. Two years later, Gondouinet al. (1967) extended the work by Kniazeff and Naville (1965) and demonstrated the significance ofnon-Darcy flow effects and condensate blockage by applying their formulations to the results data ofbackpressure tests from Hassi Er R’Mel field, Algeria. O’Dell and Miller (1967), on the other hand,applied Muskat’s solutions and presented a pseudopressure function to describe the gas condensateblockage.

Fetkovich (1973) developed a rate- and time-dependent skin based on Muskat’s results and incorpo-rated it into the standard gas flow equation. Subsequently, Fevang and Whitson (1996) applied themodified form of the Evinger-Muskat pseudopressure (Evinger and Muskat 1942) to calculate gas-condensate well deliverability and provided a simple method for calculating bottomhole flowing pressurein coarse-grid models. A more recent study by Gringarten et al. (2000) established the use of athree-region composite model to analyze gas condensate well test data.

Well productivity index (i.e., the relationship between pressure drop and flow rate) is complicated ingas condensate reservoirs below the dewpoint pressure due to the existence of the “fourth region” withlower interfacial tension and higher gas relative permeability. The two velocity-dependent relativepermeability effects contributing to the existence of the near-wellbore region are the capillary numbereffect, also referred to as “velocity stripping,” “viscous stripping,” or “positive coupling” effect, and thenon-Darcy flow or inertial resistance effect introduced by Forchheimer (Belhaj et al. 2003).

A compositional reservoir simulator has been used to model the complex flow behavior of gascondensates, with very fine grids near to the well, as pressure drawdown predominantly occurs within 10ft of the wellbore (Mott et al. 2000).

Velocity-Dependent Relative Permeability EffectsThe methods used in this study to model the two velocity-dependent relative permeability effects aredescribed below.

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Capillary number effect Previous studies have reported that gas deliverability increases as a result of anincrease in the gas relative permeability at high velocity when the capillary number is high (Danesh et al.1994; Henderson et al. 1995, 2000; Ali et al. 1997; Gringarten et al. 2000). Danesh et al. (1994) was thefirst to address the improvements of relative permeability to gas flow in condensate systems with increasesin velocity or decreases in interfacial tension, through laboratory experimental results. Miscibility betweenthe flowing phases due to reduced interfacial tension at high velocities, which increases mobility for oiland gas, can be modeled in compositional simulation using various different options for velocity-dependent relative permeability.

Capillary number is the ratio of viscous to capillary forces and can be represented by a singleparameter, Nc. Production data from several fields have revealed that deliverability is higher than theconventional simulated data because of the positive effect of capillary number (Mott 2002). It is essentialto incorporate the capillary number model into compositional simulations below the dewpoint pressure insystems that exhibit retrograde condensation. Otherwise, well productivity will be underestimatedwhereas pressure drops and condensate dropout will be overestimated.

The capillary number formulations applied in this study are after Henderson et al. (1995), as shownbelow. In their model, the capillary number for both phases depends only on the gas properties.

(1)

The “base capillary number” Ncbp is defined as the lower threshold value below which Ncp has no effecton phase relative permeabilities. This number is taken from input data and used to calculate a “normalizedcapillary number” Ncnp:

(2)

At higher capillary numbers, the residual saturation is reduced by multiplying the phase residualsaturation Srp by a factor Xp:

(3)

The capillary number is also used to define the interpolation between the “immiscible” relativepermeability curves defined by input tables and the “miscible” curves that are constructed internally asstraight lines.

(4)

The immiscible relative permeability is krp, and the miscible relative permeability is calculated asfollows, giving a straight line with endpoints defined by the adjusted phase residual saturation:

(5)

where Xp is defined in Eq. 3. The interpolation factor f is calculated as

(6)

(7)

Non-Darcy Flow Effect Darcy’s law does not explain gas flow accurately when the flow rate is high,especially near the wellbore. At high gas rate, pressure drop for flow into the well is no longer proportional

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to the rate. Turbulence, which causes increased pressure drop, can be modeled in the simulator using theForchheimer correction to account for inertial effects:

(8)

Non-Darcy flow effect is typically modeled as a rate-dependent skin in most numerical simulators. �can be determined from multirate pressure test analysis or from theoretical or empirical correlations (Liand Engler 2001). A typical empirical correlation for single-phase flow is:

(9)

Geertsma (1974) proposed an empirical correlation for two-phase flow, relating � to the fluid saturationand relative permeability:

(10)

In the case of two-phase gas condensate flow, inertial effects generate extra condensate dropoutbecause the inertial resistance in one phase is affected by the presence of the second phase.

Parameters Affecting Productivity of Horizontal WellsThe performance of horizontal wells in comparison with vertical wells has been investigated in previousstudies (Joshi 1988; Hashemi and Gringarten 2005). Results show that the relative productivity of ahorizontal well, compared to a vertical well in the same reservoir, depends on the producing horizontallength and the ratio of vertical to horizontal permeability, kv/kh.

Methodology

This study was carried out in three stages: first, gas condensate compositional analysis; second, basemodel study, and third, the full field model design. The following assumptions were made:

1. The near-well phase equilibrium and fluid flow interactions are accurately represented using a fineradial grid model and a fine tartan grid, with fluid properties calculated from an equation of state(EOS) model.

2. There is no limit on the tubing head flowing pressure, and only well bottomhole pressure limitsare considered.

3. The pressure drop due to condensate blockage is significant compared to the pressure drop in thetubing.

4. No aquifer support was considered in this study.

Gas Condensate Compositional AnalysisFour gas condensate mixtures with different compositions have been studied to distinguish between richand lean gas condensates (TABLE 1). A typical lean gas condensate generates a small volume of liquid(i.e., 30 to 50 stb/MMscf), whereas a rich gas condensate generates a relatively larger volume of liquid(i.e., 50 to 300 stb/MMscf) (Zheng et al. 2006).

Referring to Table 1, gas condensate B was selected for use in single-well sensitivity studies and forinvestigating production strategies in the full field model, because it represents a gas condensate with acondensate/gas ratio (CGR) that is not too rich and not too lean (Fig. 1). All four gas condensates wereused in the comparison of rich versus lean gas condensate for the full field model study.

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Base Model: Single WellCompositional gas condensate simulation cases have been constructed to simulate fluid flow behavior andto predict condensate dropout under typical operating conditions using single-well models.

Single-Well Model Gridding and Description The single-well models consisted of a five-layer homo-geneous reservoir of 100-ft thickness with a drainage area of 891 acres, 10% porosity, horizontalpermeability of 1 md, and vertical-to-horizontal-permeability ratio (kv/kh) of 0.1 (typical of sandstonereservoirs). Initially, the reservoir pressure is slightly above the dewpoint pressure.

Table 1—FLUID PROPERTIES FOR GAS CONDENSATE A, B, C, AND D

Gas condensate CGR (stb/MMscf) Dewpoint pressure (psia) Reservoir temperature (°F)

A 161 4767 340

B 87 4298 200

C 48 4028 251

D 27 3440 251

Figure 1—Phase diagrams of gas condensate A (left) and B (right). Gas condensate B is leaner than gas condensate A and therefore its phase diagramappears to be shifted to the left when compared to gas condensate A.

Figure 2—Single-well radial grid model.

Table 2—SINGLE-WELL RADIAL GRID MODEL GRID PROPER-TIES

Grid properties Value Unit

Number of active cells 20

Innermost grid radius 0.15 ft

Outermost grid radius 3515 ft

Cell spacing (ft) Cell sizes increase geometricallyin radial direction away from thecenter where the well is located.

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A finely gridded 1D radial, fully compositional model was used, with no wellbore storage ormechanical skin effect. A large outermost grid size of 1,335 ft was used to avoid boundary effects (Fig.2; TABLE 2).

A tartan grid model was then designed to match the radial grid model, to be used in the full field modelstudies at the later stage of the project (Fig. 3; TABLE 3).

Velocity-Dependent Relative Permeability Effect The same capillary number model and Forchheimer’snon-Darcy model were incorporated into all the simulation cases for the compositional simulation runs.The capillary number model introduced by Henderson et al. (1995) has been used to interpret thedifference between the base relative permeability and the miscible relative permeability models. Amultirate drawdown (200 Mscf/D for 1 day, 400 Mscf/D for 2 days, 800 Mscf/D for 3 days, and 1,600Mscf/D for another 4 days) followed by 10 days of buildup were simulated to observe the positive effectof the velocity-dependent relative permeability phenomenon.

The high capillary number and non-Darcy flow effects are both rate-dependent functions acting inopposite directions. Fig. 4 shows a stronger capillary number effect over the inertial effect, resulting ina positive velocity-dependent relative permeability effect. The pressure drawdown is lower than thatwithout velocity-dependent relative permeability models at the same designated flow rates.

Effect of Different Gas Production Rate The single-well radial grid model has been used to examinethe condensate dropout effect as production goes below the dewpoint pressure by operating at differentspecified rates. Various scenario cases were run for 10 days of drawdown followed by another 10 daysof buildup to achieve an optimum balance between gas production rate and well bottomhole pressure. Thisis important to minimize the condensate dropout effect in the reservoir.

The final operational decision was made after analyzing the results obtained from the scenario casesat high and low rates whilst also taking into account the initial reservoir conditions.

Fig. 5 shows two options for operating this gas condensate model, yielding different amounts ofcondensate dropout as the bottomhole pressure drops below the dewpoint pressure. For the well producingat 2 MMscf/D, oil saturation as high as 37% was observed around the wellbore at the end of the 10-daydrawdown. For a production rate of 1 MMscf/D, about 26% oil saturation was observed around the well.

There is a trade-off between high production rate and small liquid dropout effect. The two operatingscenarios shown in Fig. 5 are both producing at reasonable rates. An operational decision can be made,either aiming at reducing condensate dropout and therefore a lower production rate or aiming at producingat a higher rate and accepting a higher liquid dropout around the wellbore.

For the next stage of the study, it was decided that the pressure drawdown will be allowed to go belowthe dewpoint pressure, to allow the well to produce at a reasonable rate.

Figure 3—Single-well tartan grid model.

Table 3—SINGLE-WELL TARTAN GRID MODEL GRID PROPER-TIES

Grid properties Value Unit

Number of active cells 28125

Innermost grid size 2 ft

Areal cell spacing Number of cells Average cell size (ft)

Uniform 30 101.35

Logarithmic, Central 15 10

Uniform 30 101.35

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Full Field Model and Simulation ResultsThe full field simulation model consisted of a five-layer homogeneous reservoir of 300-ft thickness witha drainage area of 4,768 acres, 10% porosity, horizontal permeability of 1 md, and kv/kh ratio of 0.1(typical of sandstone reservoirs). A tartan grid was constructed with logarithmic cell spacing, with finegrid cells near the wells for enhanced grid definition to capture the fluid flow movement. All the modelshave the same initial gas in place. (Fig. 6)

Six vertical producing wells were placed equally apart from each other in the gas condensate field.Capillary number and non-Darcy flow effects were taken into account, but frictional losses in thewellbore, wellbore storage, and skin were neglected. The four main sensitivity studies conducted are gascondensate composition, reservoir permeability, well configuration, and well stimulation. A sensitivitystudy on rates was performed, and it was decided to produce at a field production daily contracted quantity(DCQ) of 12 MMscf/D from the field; with each well producing at 2 MMscf/D to minimize the condensatedropout effect around the wellbore. The condensate saturation profiles around well 1, well 2, and well 3were plotted against the radial distance from the wellbores (i.e., along distance A from well 1, distanceB from well 2, and distance C from well 3. (Fig. 7) Different radial directions from the wells gave distinctcondensate saturation plots, but their saturation profiles generally follow the same trend.

Figure 4—Effect of velocity-dependent relative permeability models on well bottomhole pressure.

Figure 5—Gas production rate (GRAT) control mode at 1 MMscf/D and 2 MMscf/D, respectively, with a limiting bottomhole pressure (BHP) targetor lower limit at 3000 psia.

SPE-171519-MS 7

Phase DiagramAs the well bottomhole flowing pressure falls below the dewpoint pressure, lighter components of gascondensate B are produced as gas phase whereas the heavier components drop out as immobile liquid. Theproduced gas becomes leaner as the near-wellbore region becomes richer in liquid condensate. As can beseen in Fig. 8, the phase diagram of the gas condensate near the wellbore has shifted to the right at theend of the drawdown, indicating that condensate dropout has occurred around the well.

Fig. 9 further confirms that the produced reservoir gas has become leaner at the end of the drawdownperiod as condensate has dropped out in the reservoir. The CGR decreases rapidly from 87 stb/MMscf toapproximately 72.5 stb/MMscf during the first year of production; it then remains relatively constant ata plateau CGR until the end of the production.

Rich versus Lean Gas CondensateA first objective of the simulation runs was to compare the condensate saturation profile around thewellbore for different gas condensate compositions, with all other parameters kept constant. The four gascondensates shown in Table 1 were used in this study. Compositional simulation runs were made withcapillary number and inertial effects, at a constant gas flow rate of 2 MMscf/D per well.

A plot of condensate saturation profile against distance from well 1 at the end of the 5-year drawdownis shown in Fig. 10. Gas condensate A (the richest gas condensate) exhibits the highest amount of liquid

Figure 6—Full field model with six vertical wells producing from the gas condensate reservoir. Tartan grid (right) was used for enhanced griddefinition.

Figure 7—Comparison of condensate B saturation profile around the wellbores at different production rates (i.e., 2MMscf/D, 5 MMscf/D, and 10MMscf/D).

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dropout near the wellbore whereas gas condensate D (the leanest gas condensate) exhibits the least amountof liquid dropout around the wellbore.

Gas condensate B, which has been used for all the simulation models, has about 31% of liquidsaturation within 2 ft of the wellbore; this increases gradually up to approximately 35% 10 ft away fromthe wellbore and then eventually tails off farther away from the wellbore. Examination of the condensatesaturations and fluid properties near the wellbore indicates the existence of the “fourth saturation region”due to capillary number effect (Gringarten et al. 2006). This was not observed in the simulation resultsof the other three gas condensate types in this study.

Tight versus High-Permeability Gas Condensate ReservoirA series of simulation runs was performed to compare the condensate saturation profile and gas and liquidproduction rates for different reservoir permeabilities. Four different reservoir permeabilities werestudied, with each representing different types of gas condensate reservoir (i.e., ultratight reservoir (0.001md), tight reservoir (0.1 md), low-permeability reservoir (1 md), and high-permeability reservoir (1,200md). All four reservoirs have a kv/kh ratio of 0.1 and a porosity of 10%. Gas condensate B was used inthis study.

Figure 8—Comparison of phase diagrams at the start and the end of the 5-year production from the full field model using six vertical wells.

Figure 9—Changes of CGR in the gas condensate field with respect to producing time.

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The condensate dropout effect is most significant in the tight reservoir, even more than in the ultratightreservoir. Gas condensate production is lowest in the ultratight reservoir because the nature of thereservoir inhibits the flow of the gas and condensates. There is no liquid dropout in the high-permeabilityreservoir due to the very good formation connectivity, which enables both the gas and liquid phases toflow easily into the producing wells and eventually up to the surface. (Fig. 11 and Fig. 12)

Well ConfigurationHorizontal wells can enhance reservoir contact and improve well deliverability. The simulation modelused in this study is exactly the same as the full field model with six vertical wells discussed earlier, exceptthat two horizontal wells are used instead of the six vertical wells (Fig. 13). The two horizontal producingwells were placed equally apart from each other in the gas condensate reservoir to minimize boundaryeffects. Both of the horizontal wells are fully cased and perforated over their entire horizontal length.Frictional losses in the wellbore, wellbore storage, and skin were neglected.

In this section, sensitivity studies were performed in the low-permeability gas condensate field (1 md)and the tight gas condensate field (0.1 md). A series of simulation runs were performed to compare thepressure drawdown and the condensate saturation profile when the flowing bottomhole pressure dropsbelow the dewpoint pressure. To match the field production DCQ at a rate of 12 MMscf/D, each of thetwo horizontal wells was produced at 6 MMscf/D. The full field model was operated for 5-year drawdownfollowed by 500 days of buildup period.

Figure 10—Comparison of condensate saturation profiles for different gas condensate compositions (A, B, C, and D).

Figure 11—Comparison of condensate B saturation profiles in ultratight, tight, low-permeability, and high-permeability gas condensate reservoirs.

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Low-Permeability Gas Condensate Field The liquid dropout effect in the low-permeability gas con-densate field (1 md) is shown in Fig. 14. A plot of pressure against time is shown in Fig. 15 (left) for thetwo horizontal wells with different completion lengths (1,000 ft, 2,000 ft, and 3,000 ft) and for the sixvertical wells (from the previous full field simulation) with 300 ft of completion length. Compositionalruns were made with capillary number and inertial effects at a constant gas flow rate of 6 MMscf/D.

Figure 12—Comparison of pressure drawdown, well gas cumulative production volume, well gas, and liquid production rates in ultratight, tight,low-permeability, and high-permeability gas condensate reservoirs.

Figure 13—Full field model with two horizontal wells producing from the gas condensate field. Tartan grid (right) was used for better runtimeperformance and enhanced grid definition.

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As can be seen in Fig. 15 (left), the pressure drop in horizontal wells decreases as the horizontal welllength increases, although six vertical wells yield a smaller pressure drop than the two horizontal wells(producing the same total amount). The horizontal well length of 3,000 ft was selected because it yieldsa lower pressure drawdown, thus reducing the condensate dropout around the wellbore. Nonetheless, thismust be justified against the cost of using a longer horizontal well length. Fig. 15 (right) shows that forthe same field gas cumulative production, the six vertical wells produce approximately 10% more liquidcondensate compared with the two horizontal wells at the end of the drawdown.

Figure 16—Comparison of condensate saturation profile for vertical and horizontal wells in the low-permeability reservoir.

Figure 14—Liquid condensate dropout effect from the first year to the fifth year of production.

Figure 15—Comparison of pressure drawdowns (left) and of field gas and liquid cumulative production volume (right) for vertical and horizontalwells in the low-permeability gas condensate field.

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The condensate saturation profile around the vertical and horizontal wells in the field at the end of the5-year drawdown is illustrated in Fig. 16. For the two horizontal wells, the condensate saturation is plottedagainst the distance from the heel in the x-direction (perpendicular to the well). In this particular reservoir,condensate saturation is fairly uniform because of the isotropic horizontal permeability throughout thefield. Fig. 16 also indicates that, as the horizontal well length increases from 1,000 ft to 3,000 ft, thecondensate saturation decreases.

Tight Gas Condensate Field To compare well productivities between vertical and horizontal wells andto quantify the effectiveness of horizontal wells in tight gas condensate field (0.1 md), compositionalsimulation runs of 5-year duration were made for different horizontal well lengths (1,000 ft, 2,000 ft and3,000 ft). As for the low-permeability case, the runs were made with capillary number and inertial effectsat constant gas flow rate of 6 MMscf/D per well.

A plot of pressure against time for a 5-year drawdown followed by a 500-day buildup is shown in Fig.17 (left) for the two horizontal wells with different completion lengths (1,000 ft, 2,000 ft, and 3,000 ft)and for the six vertical wells with 300 ft of completion length. Due to the very low permeability of thereservoir, it is difficult for the gas condensate to flow from the field into the wells. As can be seen in Fig.17 (left), the bottomhole pressure limit of 400 psia for the vertical and horizontal wells has been reachedonce the production was started.

Fig. 17 (right) shows that cumulative gas production from the two horizontal wells is approximately4.7 Bscf more than production from the six vertical wells. In addition, it was found that the two horizontalwells produce approximately 85 Mstb more liquid condensate than the six vertical wells.

The difference in well productivity between horizontal wells and vertical wells is very significant in atight gas condensate field. The cumulative gas production increases with the horizontal well length andexceeds the production from the vertical wells for lengths over 2,000 ft (Fig. 18). Fig. 19 compares thecumulative field liquid production for each horizontal well length and the vertical wells.

The condensate saturation profile around the vertical and horizontal wells in the tight gas condensatereservoir at the end of the 5-year drawdown is illustrated in Fig. 20. The different horizontal well lengthsyield similar condensate saturation profiles around the wellbore. The vertical and horizontal wells showeda maximum saturation of about 48%, which eventually tails off as it gets further away from the wellbore.

In the tight gas condensate field, horizontal wells yield higher total gas recovery than vertical wells.This was not the case in the low-permeability gas condensate field, as discussed above.

Figure 17—Comparison of pressure buildups (left) and of field gas and liquid cumulative production volume (right) for vertical and horizontal wellsin the tight gas condensate reservoir.

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Well Spacing between Horizontal WellsWell spacing is generally defined as the maximum area of a reservoir that can be efficiently andeconomically drained by one well (Keuengoua and Amorin 2011). Sensitivity studies were performed tostudy the effects of well spacing between the horizontal wells. In this study, the low-permeability gascondensate field was used to examine the boundary effects caused by the neighboring well when the twohorizontal wells were placed closer to each other. Fig. 21 shows another full field model having exactlythe same size and fluid properties as the original full field model, but with different well location and

Figure 18—Comparison of field gas cumulative production for vertical and horizontal wells in the tight gas condensate reservoir.

Figure 19—Comparison of field liquid cumulative production for vertical and horizontal wells in the tight gas condensate reservoir.

Figure 20—Comparison of condensate saturation profile for vertical and horizontal wells in the tight gas condensate reservoir.

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smaller well spacing. As a result, the two horizontal wells acted as no-flow boundaries against each other,leading to an increase in the pressure drawdown at a constant flow rate (Fig. 22).

Stimulation of Vertical WellsSensitivity analysis of well stimulation was performed to investigate the well productivity/deliverabilityenhancement upon stimulating the six vertical wells in the tight gas condensate reservoir. The possibleeffect of well stimulation was modeled by a productivity index (PI) multiplier in the simulation. Theresulting cumulative gas production is shown in Fig. 23.

Well (acid) stimulation enhances the productivity index and reduces the pressure drawdown at constantflow rate, thus reducing the condensate dropout effect in the tight reservoir. However, in this study, asshown in Fig. 23, localized well stimulation does not have a major impact on the productivity of thevertical wells, compared to the use of two horizontal wells. Well stimulation yields an incremental fieldgas recovery of 600 MMscf compared to the unstimulated vertical wells. However, the two horizontalwells produce 4.1 Bscf more gas than the six stimulated vertical wells.

Neither hydraulic fracturing nor well stimulation on horizontal wells was investigated in this projectdue to time constraints. Further study would be recommended to evaluate these options.

DiscussionIn this study, well deliverability impairment due to liquid dropout in gas condensate fields was success-fully represented in compositional simulation models. A sensitivity study on gas condensate compositions

Figure 21—Horizontal wells placed closer to each other to observe boundary effects, where each well acts as a no-flow boundary against the other.

Figure 22—Comparison of pressure drawdowns for the two horizontal wells being placed closer to each other and the two horizontal wells in theoriginal full field model.

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(rich versus lean) has been conducted to understand production behavior for different fluid characteristics.A richer gas condensate yields higher liquid dropout in the field than a leaner gas condensate. A sensitivitystudy on reservoir permeability was also performed to investigate the effects of formation permeabilityaround the wellbore on gas recovery and liquid dropout. This study assumes a homogeneous reservoir. Inreal life, gas condensate reservoirs are complex and highly heterogeneous, resulting in more complicatednear-well flow behavior. Sensitivity studies on gas condensate reservoir properties are essential to confirmthe best production method for individual cases.

Good operational decisions in managing the gas condensate field yield higher recovery efficiency. Theproduction options considered in this study were production rates, well configuration, and well stimula-tion. In this study, for a low-permeability gas condensate reservoir, six vertical wells have a slightly betterperformance than two horizontal wells (well length � 3,000 ft), with both producing at the same DCQ.On the other hand, the performance of two horizontal wells in a tight gas condensate reservoir is superiorto that of the six vertical wells, obtaining 47% more gas recovery.

Well stimulation (e.g., acid treatment) enhances the productivity of the vertical wells and yields 6%more gas recovery than the unstimulated vertical wells in the tight gas condensate reservoir. Hydraulicfracturing was not investigated in this particular work and is recommended for further study. Hashemi andGringarten (2005) compared horizontal wells and hydraulically fractured wells in single-well models andshowed that these well configurations are comparable and can improve productivity and reduce pressuredrop. The final choice between a horizontal well and an equivalent vertical well with a fracture can onlybe determined from economic evaluation.

In practice, particularly in a gas condensate reservoir where reservoir pressure is close to dewpointpressure, there are two extreme options for operating the field. The first is to allow for very quickdepletion to produce most of the gas and condensates out of the field within the next few years ofproduction, without considering the effect of liquid dropout. Then, shut in the well for pressure buildupfor some time and produce from the field again, assuming the resulting pressure buildup plateau is abovethe dewpoint pressure and the condensate bank will revaporize. The second option is to produce the fieldat a lower rate by limiting the pressure drawdown above the dewpoint pressure. The optimum operatingdecision for a specific field is likely to be between these two extremes, and it will require more simulationstudies to determine the best operating rates.

Figure 23—Productivity index enhancement after well stimulation (left) and the comparison of field gas cumulative production volume in vertical andhorizontal wells (right).

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ConclusionsThe results of this study demonstrate the critical importance of liquid dropout effects in a gas condensatefield. The main conclusions are as follows:

1. Well productivity index impairment due to liquid dropout in a gas condensate field will beoverestimated if the compositional simulation model ignores the velocity-dependent relativepermeability effects in the immediate vicinity of the wellbore.

2. For gas condensate production below the dewpoint pressure, simulation studies can be used toachieve a balance between the gas production rate and the pressure drawdown, to minimizecondensate dropout effect while at the same time producing at a reasonable rate from the field.

3. The optimum well configuration and selection of vertical or horizontal wells for a gas condensatefield depend on the type of reservoir (low permeability versus tight reservoirs).

4. Horizontal well length affects gas production in gas condensate fields. A longer horizontal wellcan increase reservoir contact and enable operation at a higher bottomhole pressure, thus reducingcondensate dropout in fields operated below the dewpoint pressure.

5. Well stimulation enhances the productivity of the vertical wells in the tight gas condensatereservoir; however, in this study it is not as effective when compared to the use of horizontal wells.

Recommendations for Further StudyFor this study, reservoir models with fine grids near the wellbore were successful, and the simulationmodels ran in reasonable timescale. For a bigger field, it may be necessary to use coarser gridsincorporating methods of upscaling such as the generalized pseudopressure model proposed by Fevangand Whitson (1996).

This work focuses on operational decisions and reservoir management of gas condensate fields. For amore comprehensive understanding of the options available for field development, the following addi-tional studies should be considered:

1. More detailed analysis of the costs and economic benefits of using horizontal wells compared tovertical wells.

2. A study of hydraulic fracturing effects, before and after the formation of condensate bank.3. Investigation of the effects of acid stimulation and hydraulic fracturing for horizontal wells.4. Investigation of gas cycling, which can be used to maintain reservoir pressure above the dewpoint

pressure while producing at a reasonably high rate, thus avoiding condensate dropout in thereservoir.

5. Research into solvent injection treatment to mitigate condensate banking.6. Studies on the impact of aquifer drive and water encroachment for a gas condensate field with

aquifer support.

Nomenclature

a, b, c, d Non-Darcy coefficients (experimental)dp/dL Pressure drop along distance Lf Interpolation factorSubscript g Phase (gas)k Absolute permeability (md)kh Horizontal permeability (md)krmp Miscible relative permeability of phase pkrp Immiscible relative permeability of phase pkrvp Interpolated (velocity-dependent) relative permeability of phase p

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kv Vertical permeability (md)LH Horizontal well length (ft)mp, n1p, n2p Dimensionless user-defined input parametersNcbp Base capillary number for phase pNcnp Normalized capillary number for phase pNcp Capillary number for phase pp Pressure (psia)Subscript p Phase (oil, gas)Sp Saturation of phase pSrp Residual saturation of phase pXp Residual saturation multiplying factor for phase p� Forchheimer’s non-Darcy coefficient� Viscosity (cp)� Interstitial velocity in the reservoir (ft/d)� Density� Interfacial tension� Porosity

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