Chemical Engineering

Communication

Biosci. Biotech. Res. Comm. 10(1): 161-166 (2017)

A case study on simulation and optimization of

arti cial lift methods in one of the Iranian oil  elds

Amin Azdarpour*, Mohammad Afkhami Karaei and Abdolreza Dabiri

Department of Petroleum Engineering, Marvdasht Branch, Islamic Azad University, Marvdasht, Iran

ABSTRACT

Oil production from reservoirs usually occurs by natural  ow of the  uid out of the formation. This oil recovery is

called primary recovery, where the production is solely controlled by the natural energy of the formation. However,

after some times of production reservoir pressure declines, which causes a decline in oil production rate. Thus, regain-

ing the reservoir pressure to enhance oil production is of great importance. Gas lift as one of the best methods of oil

recovery when reservoir pressure declines has been implemented for decades. The reservoir pressure of one of the

oil  elds in Iran has been dropped to a level where no natural  uid  ow occurs form the reservoir. Gas lift has been

proposed to compensate the natural pressure of the reservoir and ease the petroleum production from the reservoir.

PIPESIM software was used to study the effectiveness of the gas lift system. Different parameters including tub-

ing diameter, injected gas rates, and injection depth and their effect on in ow performance relationship (IPR) were

investigated. The simulation results showed that natural energy of the reservoir is not suf cient for producing oil.

Thus, gas lift as of the best methods of increasing the production rate in this  eld could be implemented successfully.

KEY WORDS: OIL PRODUCTION, ARTIFICIAL LIFT, GAS LIFT, IMPROVED OIL RECOVERY, OPTIMIZATION

161

ARTICLE INFORMATION:

*Corresponding Author: amin.azhdarpour@miau.ac.ir;

aminazh22@gmail.com.

Received 15

Dec, 2016

Accepted after revision 19

March, 2017

BBRC Print ISSN: 0974-6455

Online ISSN: 2321-4007 CODEN: USA BBRCBA

Thomson Reuters ISI ESC and Crossref Indexed Journal

NAAS Journal Score 2017: 4.31 Cosmos IF : 4.006

reserved.

Online Contents Available at: http//www.bbrc.in/

INTRODUCTION

Gas lift is a method ofarti cial liftthat uses an exter-

nal source of high-pressure gas for supplementing for-

mation gas to lift the well  uids. The principle of gas

lift is that gas injected into the tubing reduces the den-

sity of the  uids in the tubing, and the bubbles have

a scrubbing action on the liquids. Both factors act to

lower the  owing bottom-hole pressure (BHP) at the

bottom of the tubing. There are two basic types of

gas lift in use today, continuous and intermittent  ow

(Denney, 1999, Al Abdin, 2000, Decker, 2008, Hearn,

2008, Akinnibosun et al. 2011, Allyeva and Novruzaliyev,

2015).

162 A CASE STUDY ON SIMULATION AND OPTIMIZATION OF ARTIFICIAL LIFT METHODS BIOSCIENCE BIOTECHNOLOGY RESEARCH COMMUNICATIONS

Azdarpour, Karaei and Dabiri

Bahadori et al. (2001) performed a simulation study

using PVD data along with  uid and multiphase  ow

correlations. They monitored the actual pressure and

temperature data to determine the point of gas injection

and construct the gas lift performance curve. They used

solution nodal method to determine the optimal gas lift

conditions including optimum injection depth, optimum

wellhead pressure, optimum production rate and mini-

mum injection gas volume. Their analysis showed that

the optimum production rate of 2200 bbl/day and opti-

mum injection gas volume of 1.1 MM SCF/day could

be gained using gas lift process. In addition, they also

concluded that the optimum gas liquid ratio is about

2100 SCF/bbl where increasing the gas liquid ratio from

its optimum value has no signi cant effect on produc-

tion rate.

de Souza et al. (2010) simulated the process of con-

tinuous gas lift using an optimization algorithm cou-

pled to a stationary two phase  ow network model. They

declared that the solution of the optimization system

could be used for the injected gas  ow rate to maxi-

mize the production rate and pro t as well as lowering

the capital cost of the process. Their study particularly

focused on two cases, an offshore single well case and

a complex subsea system. The analysis on offshore well

showed that the gas lift system could be optimized to

yield the maximum oil production for different well

pressure, while maximizing the pro t gained from the

process. At the second case study, a complex petroleum

production system with multiple wells is simulated and

optimized to obtain the optimal design considering

annualized costs of compressor, turbine driver, gas pipe-

lines and fuel gas consumption.

In another study by Mahmudi and Sadeghi (2013) the

gas lift system was optimized to maximize the pro t of

the well for a long period of time. They investigated the

effects of gas injection rate, tubing diameter and sepa-

rator pressure on overall performance of gas lift sys-

tem. They developed a mathematical model coupled

to a combination of Marquardt optimization method

and a genetic algorithm to simulate the gas lift system.

Their results showed that production lifetime should be

divided into a number of consecutive operation intervals

with different tubing diameter, lift gas injection rates

and separator pressures and an optimum value for tub-

ing diameter.

Naderi et al. (2014) investigated the feasibility of arti-

 cial lift selection in the Khesht  eld. The Khesht  eld is

located in in south of Iran and was discovered in 1992.

Asmari reservoir, which is one the most important oil

reservoirs is located in this  eld. The authors performed

a comprehensive study to select the most suitable arti -

cial lift method, which can be applied in this  eld. They

investigated different production scenarios including

natural  ow, electrical submersible pump, and gas lift.

They concluded that, initially natural  ow should be

considered. However, by increasing the water cut gas lift

can be implemented and if the water cut is too high the

electrical submersible pump can be utilized.

Ebrahimi and Khamehchi (2016) have investigated

the feasibility and effectiveness of the natural gas lift

(NGL) using supportive vector machine (SVM). They

optimized the process using particle swarm optimiza-

tion (PSO) and genetic algorithm (GA). The optimum

SVM parameters were determined by the PSO algorithm.

Taguchi experiment design was used to determine opti-

mum GA and PSO parameters. The simulation results

showed that SVM could be used effectively to simulate

the gas lift process.

In this study, the feasibility of gas lift implementation

in one of the oil reservoirs in Iran was investigated. The

reservoir characteristics data including rock and  uid

properties were used as input data to be used in PIPESIM

software. In addition, different parameters including

tubing size, injection depth and  ow rates were varied

to determine the optimum production scenario.

MATERIALS AND METHODS

SIMULATION STUDY

In order to perform the optimization study, PIPESIM

software was used. This software is capable of deter-

ming optimum prodcution scenarios during arti cail

lift activities (Sedarat et al. 2014, Silva et al. 2015,

AlHarooni et al. 2015). The required data such as pro-

duction rate data, average reservoir pressure, bottom

hole  owing pressure, and well pro le data were used

as input data. The vertical multiphase  ow correlation

and  uid properties were utilized to determine produ-

ction rate as a function of gas injection rates. Injected

gas rate and production tubing size are the only main

parameters that affect well performance, however, since

production tubing is already  xed in the reservoir, thus

injection gas rate can be controlled to optimize the well

performance.

The methodology of perform the simulation study

was taken by the method presented by Bahadori et al.

(2001). The following steps were followed to perform the

simulation and optimization study of gas lift system. In

the  rst step of this study, appropriate  uid properties

correlations were selected. Then, pressure travers (P

)

inside the tubing string was calculated. Then, different

values of GLR and production rates were assumed and

gas injection pressure (P

) in the casing was calculated.

The values of P

and P

were compared and if P

-ΔP-

valve

, the depth of injection was determined. The well head

BIOSCIENCE BIOTECHNOLOGY RESEARCH COMMUNICATIONS A CASE STUDY ON SIMULATION AND OPTIMIZATION OF ARTIFICIAL LIFT METHODS 163

Azdarpour, Karaei and Dabiri

FIGURE 2. IPR of producing well with variable produc-

tivity index.

FIGURE 3. IPR-VLP plot of the production well.

pressure was calculated using the assumed GLR and pro-

duction rates. Then, well head pressure as a function of

 ow rates for horizontal and vertical tubing were plot-

ted and the intersection of these curves was determined.

Finally, the performance curve was plotted and optimum

production rates and injection rates were determined.

CHARACTERISTICS OF THE STUDIED OIL FIELD

The studied oil  led is located in south of Iran. Pres-

sure data analysis shows that reservoir pressure has been

declining to about 4368 psi, which is near the bubble

point pressure of the reservoir (4100 psi). The reservoir

temperature is 220 ºF. The reservoir permeability is 3

mD, connate water saturation is 0.24, and crude oil API

is 32. In addition, productivity index (PI) of the reser-

voir is 0.8 STB/Day/Psi and gas oil ratio is about 381

SCF/STB.

RESULTS

Figure 1 represents the IPR of this reservoir under dif-

ferent  ow rates, where PI is about 0.8 STB/Day/Psi and

reservoir pressure is 4368 psi. In this case the absolute

open  ow (AOF) of the well is determined to be around

2927.9 STB/Day. On the other hand, Figure 2 represents

the IPR of this reservoir under different PIs. As shown

in this  gure, increasing PI increases the AOF of the

well, which is considered positive from production per-

spective. It is worth mentioning that increasing the AOF

increases the prodcution from the reservoir, whcih is the

main target of this study.

FIGURE 1. In ow perfromance relationship (IPR) of the

production well.

Figure 3 represents the in ow (IPR) and out ow

(VLP) curve of the investigated well where AOF was

calculated to be 2927.9 STB/day. The optimum produc-

tion rate of 184.4 bbl/day was yield based on the tubing

size and present condition of well. This  ow rate yields

a well head pressure of 350 psi. In order to optimize

the production rate form this well, different tubing size

were utilized and the production pro le (IPR-VLP) curve

was plotted as shown in Figure 4. Different tubing size

including 2.44, 2.99, 3.92, and 8.60 inches were utilized

Azdarpour, Karaei and Dabiri

164 A CASE STUDY ON SIMULATION AND OPTIMIZATION OF ARTIFICIAL LIFT METHODS BIOSCIENCE BIOTECHNOLOGY RESEARCH COMMUNICATIONS

with the bottom measured depth of 3593.3 m and bot-

tom true vertical depth of 3299.9 m.

In another production scenario, well performance

was investigated where the liquid and gas rates were

344.1 STB/day and 0.13109 MMSCF/day, respectively

and total depth was 1500 m. Figure 5 represents the

IPR-VLP curve under this production scenario. On the

other hand, the effect of different tubing size on produc-

tion rate at total depth of 1500 m was investigated and

the results are shown in Figure 6. Table 1 represents the

calculated production rates under different tubing size.

As shown in this table, the maximum production rate

is achieved under 2.875 inch tubing size. The minimum

pro table production rate of 1000 bbl/day is expected

under natural  ow from the well, which in this case has

not been achieved. Thus, gas lift could be implemented

to maximize the production rate from this  eld.

Gas lift approach can be implemented in this  eld

since intersection of IPR and VLP curves happens in low

 ow rates. Gas was injected to the  eld with the gas

to liquid ratio (GLR) of 850 SCF/STB. The optimum oil

production rate of 1139 STB/day was achieved under gas

lift implementation in this  eld. Figure 7 represents the

IPR-VLP plot of this  eld after gas lift implementation.

DISCUSSION

Ga s injection is one of the most important paramters for

prodcution optimization during arti cial lift activities.

The pressure drop due to  uid level drop is reduced by

gas injection to the wellbore, thus, the density of the

 uid is reduced and it moves more easily to the sur-

face (Hana zadeh et al., 2014; Ebrahimi and Khamechi,

2016; Elldakli and Soliman, 2017). Increasing the tubing

FIGURE 4. System analysis plot of production well with

different tubing size.

FIGURE 5. IPR-VLP plot of production well at 1500 m.

Table 1. Oil production rate under different tubing size

Tubing size (inch) Oil rate (STB/day)

350.6 2.875

188.8 3.5

182.8 4.5

179 9.875

FIGURE 6. System analysis plot with differnet

tubing size at 1500 m

Azdarpour, Karaei and Dabiri

BIOSCIENCE BIOTECHNOLOGY RESEARCH COMMUNICATIONS A CASE STUDY ON SIMULATION AND OPTIMIZATION OF ARTIFICIAL LIFT METHODS 165

size decreases the pressure drop due to friction in the

wellbore, thus increasing the prodcution rate. However,

the pressure drop due to  uid level drop would be domi-

ninat over the pressure drop due to friction when the

tubing size is more than the optimum tubing size. This

would result in production rate to decrease (Campono-

gara et al., 2010; Mahmudi and Sadeghi, 2013; Allyeva

and Novruzaliyev, 2015; Elldakli and Soliman, 2017).

Therfore, there always must be an optimum value for

the tubing size as it was shown in Figures 4-6 in this

study. The value of GLR is increased with increasing gas

injection rate. Hence, the pressure drop is reduced and

prodcution rate is increased, which creates a favorable

condition in terms of oil recovery. On the other hand,

when the value of the GLR is more than its critical value

(GLR>GLR

limit

), the results is inverse, which causes the

production rate to decline. The reason is that the pres-

sure drop due to friction would be dominant over the

pressure drop due to  uid level drop (Ray and Sarker,

2007; Guerrero-Sarabia and Fairuzov, 2013; Elldakli

and Soliman, 2017). The same thing happened in this

study, where the value of GLR

limit

was found to be 850

SCF/STB, which resulted in the maximum prodcution

rate as shown in Figure 7.

CONCLUSIONS

In this study, different tubing size and total depth were

simulated to determined the effectiveness of natural

 ow from the reservoir. The simulation results showed

that the natural  ow from the well is not capable of

producing suf cient hydrocarbon to the surface. Gas lift

process can be implemented in wide range of depth and

 ow rate, which is one of the advantages of this method

over other arti cial methods. The simulation results

showed that the optimum tubing size during gas lift

process is 2.875 inch, which resulted in the maximum

 ow rate. In addition, the simulation results showed that

gas lift can be implemented in wells with low produc-

tivity index and low gas to liquid ratio. Moreover, the

simualtion results showed that gas lift is one of the best

arti cial methods to be considered in Iran since large

gas resources are available. This is one of the most

important advantages of using gas lift for improving oil

recovery in Iran.

ACKNOWLEDGMENT

The authors would like to appreciate the Department of

Petroleum Engineering, Marvdasht Branch, Islamic Azad

University, Marvdasht, Iran for the provision of the

laboratory facilities necessary for completing this work.

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