scholarly journals An Investigation on Gas Lift Performance Curve in an Oil-Producing Well

2007 ◽  
Vol 2007 ◽  
pp. 1-15 ◽  
Author(s):  
Deni Saepudin ◽  
Edy Soewono ◽  
Kuntjoro Adji Sidarto ◽  
Agus Yodi Gunawan ◽  
Septoratno Siregar ◽  
...  

The main objective in oil production system using gas lift technique is to obtain the optimum gas injection rate which yields the maximum oil production rate. Relationship between gas injection rate and oil production rate is described by a continuous gas lift performance curve (GLPC). Obtaining the optimum gas injection rate is important because excessive gas injection will reduce production rate, and also increase the operation cost. In this paper, we discuss a mathematical model for gas lift technique and the characteristics of the GLPC for a production well, for which one phase (liquid) is flowing in the reservoir, and two phases (liquid and gas) in the tubing. It is shown that in certain physical condition the GLPC exists and is unique. Numerical computations indicate unimodal properties of the GLPC. It is also constructed here a numerical scheme based on genetic algorithm to compute the optimum oil production.

2019 ◽  
Vol 8 (4) ◽  
pp. 9737-9740

In petroleum industry, gas lift optimization is the most important for evaluating the reservoir. By improving the gas lift operation we can save money and time which we spend on the reservoir for effective production. The mainly accepted scenario of gas lift is to maximize production by using minimized cost infrastructure. If the production rate is increased, then the cost of oil production also increases due to the increase in surface facilities and increase in cost of gas compression to higher pressures. The production rate and production cost during gas lift are mutually conflicting in nature i.e., if anyone desires to increase the oil production rate, then at the same time it is difficult to minimize the cost of production. Therefore, this is an ideal candidate for multi-objective optimization study, where production rate needs to maximized while minimizing the cost of production. The oil production rate is calculated using nodal analysis of inflow performance and outflow performance curve while the production cost is calculated using the brake horsepower requirement of the compressor. Oil production rate during a gas lift operation can be defined as a function of various factors like (i) depth of gas injection, (ii) gas injection rate (iii) gas lift injection pressure, (iv) wellhead pressures, (v) bottom hole pressure, (vi) tubing size, (vii) surface choke size/wellhead pressure. Production cost mainly depends on the cost of gas compression which further depends on the pressure up to which gas has to be compressed in the annulus so that the gas lift valve at the bottom of the well opens. The opening of gas lift valve depends on the bottom hole pressure in the tubing i.e. the density of mixture present inside the tubing. The multi-objective gas lift optimization is carried out using multi-objective evolutionary algorithms (EAs) that use non-dominated sorting called elitist non-dominated sorting genetic algorithm (NSGA-II). In this project, we aim to find the optimum values of the decision parameters i.e. gas injection rate and wellhead pressure, for which oil production rate would be maximized while minimizing the cost of oil production.


Author(s):  
Gabriel A. Alarcón ◽  
Carlos F. Torres-Monzón ◽  
Nellyana Gonzalo ◽  
Luis E. Gómez

Abstract Continuous flow gas lift is one of the most common artificial lift method in the oil industry and is widely used in the world. A continuous volume of gas is injected at high pressure into the bottom of the tubing, to gasify the oil column and thus facilitate the extraction. If there is no restriction in the amount of injection gas available, sufficient gas can be injected into each oil well to reach maximum production. However, the injection gas available is generally insufficient. An inefficient gas allocation in a field with limited gas supply also reduces the revenues, since excessive gas injection is expensive due to the high gas prices and compressing costs. Therefore, it is necessary to assign the injection gas into each well in optimal form to obtain the field maximum oil production rate. The gas allocation optimization can be considered as a maximization of a nonlinear function, which models the total oil production rate for a group of wells. The variables or unknowns for this function are the gas injection rates for each well, which are subject to physical restrictions. In this work a MATLAB™ nonlinear optimization technique with constraints was implemented to find the optimal gas injection rates. A new mathematical fit to the “Gas-Lift Performance Curve” is presented and the numeric results of the optimization are given and compared with results of other methods published in the specialized literature. The optimization technique proved fast convergence and broad application.


2002 ◽  
Vol 124 (4) ◽  
pp. 262-268 ◽  
Author(s):  
Gabriel A. Alarco´n ◽  
Carlos F. Torres ◽  
Luis E. Go´mez

Continuous flow gas lift is one of the most common artificial lift methods widely used in the oil industry. A continuous volume of high-pressure gas is injected as deep as possible into the tubing, to gasify the oil column, and thus facilitate the production. If there is no restriction in the amount of injection gas available, sufficient gas can be injected into each oil well to reach maximum production. However, the injection gas available is generally insufficient. An inefficient gas allocation in a field with limited gas supply reduces the revenues, since excessive gas injection is expensive due to the high gas prices and compressing costs. Therefore, it is necessary to assign the injection gas into each well in optimal form to obtain the field maximum oil production rate. The gas allocation optimization can be considered as a maximization of a nonlinear function, which models the total oil production rate for a group of wells. The variables or unknowns for this function are the gas injection rates for each well, which are subject to physical restrictions. In this work a nonlinear optimization technique, based on an objective function with constraints, was implemented to find the optimal gas injection rates. A new mathematical fit to the gas-lift performance curve (GLPC) is presented and the numeric results of the optimization are given and compared with those of other methods published in the specialized literature. The GLPC can be either measured in the field, or alternatively generated by computer simulations, by mean of nodal analysis. The optimization technique proved fast convergence and broad application.


2021 ◽  
Author(s):  
Sagun Devshali ◽  
Ravi Raman ◽  
Sanjay Kumar Malhotra ◽  
Mahendra Prasad Yadav ◽  
Rishabh Uniyal

Abstract The paper aims to discuss various issues pertaining to gas lift system and instabilities in low producer wells along with the necessary measures for addressing those issues. The effect of various parameters such as tubing size, gas injection rate, multi-porting and gas lift valve port diameter on the performance analysis of integrated gas lift system along with the flow stability have been discussed in the paper. Field X is one of the matured offshore fields in India which has been producing for over 40 years. It is a multi-pay, heterogeneous and complex reservoir. The field is producing through six Process Complexes and more than 90% of the wells are operating on gas lift. As most of the producing wells in the field are operating on gas lift, continuous performance analysis of gas lift to optimize production is imperative to enhance or sustain production. 121 Oil wells and 7 Gas wells are producing through 18 Wellhead platforms to complex X1 of the field X. Out of these 121 oil wells, 5 are producing on self and remaining 116 with gas lift. In this paper, performance analysis of these 116 flowing gas lift wells, carried out to identify various problems which leads to sub-optimal production such as inadequate gas injection, multi-porting, CV choking, faulty GLVs etc. has been discussed. On the basis of simulation studies and analysis of findings, requisite optimization/ intervention measures proposed to improve performance of the wells have been brought out in the paper. The recommended measures predicted the liquid gain of about 1570 barrels per day (518 barrels of oil per day) and an injection gas savings in the region of about 28 million SCFD. Further, the nodal analysis carried out indicates that the aforementioned gas injection saving of 28 million SCFD would facilitate in minimizing the back pressure in the flow line network and is likely to result in an additional production gain of 350 barrels of liquid per day (65 barrels of oil per day) which adds up to a total gain of 1920 barrels of liquid per day (583 barrels of oil per day). Additionally, system/ nodal analysis has also been carried out for optimal gas allocation in the field through Integrated Production Modelling. The analysis brings out a reduction in gas injection by 46 million SCFD with likely incremental oil gain of ~100 barrels of oil per day.


2018 ◽  
Vol 2 (1) ◽  
pp. 32
Author(s):  
Mia Ferian Helmy

Gas lift is one of the artificial lift method that has mechanism to decrease the flowing pressure gradient in the pipe or relieving the fluid column inside the tubing by injecting amount of gas into the annulus between casing and tubing. The volume of  injected gas was inversely proportional to decreasing of  flowing  pressure gradient, the more volume of gas injected the smaller the pressure gradient. Increasing flowrate is expected by decreasing pressure gradient, but it does not always obtained when the well is in optimum condition. The increasing of flow rate will not occured even though the volume of injected gas is abundant. Therefore, the precisely design of gas lift included amount of cycle, gas injection volume and oil recovery estimation is needed. At the begining well AB-1 using artificial lift method that was continuos gas lift with PI value assumption about 0.5 STB/D/psi. Along with decreasing of production flow rate dan availability of the gas injection in brownfield, so this well must be analyze to determined the appropriate production method under current well condition. There are two types of gas lift method, continuous and intermittent gas lift. Each type of gas lift has different optimal condition to increase the production rate. The optimum conditions of continuous gaslift are high productivity 0.5 STB/D/psi and minimum production rate 100 BFPD. Otherwise, the intermittent gas lift has limitations PI and production rate which is lower than continuous gas lift.The results of the analysis are Well AB-1 has production rate gain amount 20.75 BFPD from 23 BFPD became 43.75 BFPD with injected gas volume 200 MSCFPD and total cycle 13 cycle/day. This intermittent gas lift design affected gas injection volume efficiency amount 32%.


2019 ◽  
Vol 38 (4) ◽  
pp. 801-818
Author(s):  
Ren-Shi Nie ◽  
Yi-Min Wang ◽  
Yi-Li Kang ◽  
Yong-Lu Jia

The steam chamber rising process is an essential feature of steam-assisted gravity drainage. The development of a steam chamber and its production capabilities have been the focus of various studies. In this paper, a new analytical model is proposed that mimics the steam chamber development and predicts the oil production rate during the steam chamber rising stage. The steam chamber was assumed to have a circular geometry relative to a plane. The model includes determining the relation between the steam chamber development and the production capability. The daily oil production, steam oil ratio, and rising height of the steam chamber curves influenced by different model parameters were drawn. In addition, the curve sensitivities to different model parameters were thoroughly considered. The findings are as follows: The daily oil production increases with the steam injection rate, the steam quality, and the degree of utilization of a horizontal well. In addition, the steam oil ratio decreases with the steam quality and the degree of utilization of a horizontal well. Finally, the rising height of the steam chamber increases with the steam injection rate and steam quality, but decreases with the horizontal well length. The steam chamber rising rate, the location of the steam chamber interface, the rising time, and the daily oil production at a certain steam injection rate were also predicted. An example application showed that the proposed model is able to predict the oil production rate and describe the steam chamber development during the steam chamber rising stage.


2021 ◽  
Author(s):  
Farasdaq Sajjad ◽  
Steven Chandra ◽  
Alvin Wirawan ◽  
Silvya Dewi Rahmawati ◽  
Michelle Santoso ◽  
...  

Abstract In the implementation of gas lift, understanding flow behavior in highly-deviated well is critical in avoiding production loss due to liquid fallback and blockage, even in highly-productive reservoir. In this work, we utilize Computational Fluid Dynamics (CFD) to optimize gas lift design under various flow behavior in highly-deviated well. The analysis is directly implemented into Arjuna offshore field case. Arjuna offshore field has gas-lifted wells, producing from a high-permeability reservoir. However, several wells suffer from huge production loss due to the effect of well's deviation. In deviated well, there exists frequent liquid fallback causes blockage, therefore, reducing the production. Motivated by this issue, we use CFD framework to perform gas lift optimization. We firstly adopt the geometry of gas-lifted wells as the computational domains for our simulation. An image-based meshing technique is deployed to capture the well's trajectory and internal geometry. We secondly utilize compressible Navier-Stokes equation and Finite Volume Method to evaluate the flow behavior. We capture the location of liquid fallback and liquid accumulation at elbows to estimate production loss. We consider the variation of viscosity, density, gas lift valve placement, injected gas rate, and reservoir pressure. We finally perform gradient-based optimization utilizing production loss as the objective function to obtain optimum design. The final result is then used to optimize the current design. The simulation results show that productivity index, pipe diameter, and deviation heavily influence the amount of production loss. At big pipe diameter and high deviation, the gravitational force governs the fluid flow. Therefore, slugs are developed and accumulated at elbows. This accumulation blocks gas flow and reduces production. Changing the gas injection rate affects the lifted density. High injection rate triggers segregation between the liquid and gas, while low injection rate does not reduce the liquid density. Shifting the gas lift valve placement influence the mixing between the liquid and gas. It also determines the cost of gas injection. Hence, we need to optimize both parameters at once. Six of thirty wells in Arjuna field experience severe liquid fallback, therefore, the production significantly decreases. The simulation shows up to 40% coverage of the pipe internal diameter, which blocks the gas flow. We perform the optimization by shifting the gas lift valve placement and adjusting the gas injection rate. By implementing the study result into the field case, we manage to improve the production by 20%. We provide an effective way to connect high-resolution simulation to the field design and revise the current concept in designing gas lift well completion. The simulation allows engineers to provide more insight on flow assurance in highly deviated wells.


Energies ◽  
2019 ◽  
Vol 12 (20) ◽  
pp. 3961
Author(s):  
Haiyang Yu ◽  
Songchao Qi ◽  
Zhewei Chen ◽  
Shiqing Cheng ◽  
Qichao Xie ◽  
...  

The global greenhouse effect makes carbon dioxide (CO2) emission reduction an important task for the world, however, CO2 can be used as injected fluid to develop shale oil reservoirs. Conventional water injection and gas injection methods cannot achieve desired development results for shale oil reservoirs. Poor injection capacity exists in water injection development, while the time of gas breakthrough is early and gas channeling is serious for gas injection development. These problems will lead to insufficient formation energy supplement, rapid energy depletion, and low ultimate recovery. Gas injection huff and puff (huff-n-puff), as another improved method, is applied to develop shale oil reservoirs. However, the shortcomings of huff-n-puff are the low sweep efficiency and poor performance for the late development of oilfields. Therefore, this paper adopts firstly the method of Allied In-Situ Injection and Production (AIIP) combined with CO2 huff-n-puff to develop shale oil reservoirs. Based on the data of Shengli Oilfield, a dual-porosity and dual-permeability model in reservoir-scale is established. Compared with traditional CO2 huff-n-puff and depletion method, the cumulative oil production of AIIP combined with CO2 huff-n-puff increases by 13,077 and 17,450 m3 respectively, indicating that this method has a good application prospect. Sensitivity analyses are further conducted, including injection volume, injection rate, soaking time, fracture half-length, and fracture spacing. The results indicate that injection volume, not injection rate, is the important factor affecting the performance. With the increment of fracture half-length and the decrement of fracture spacing, the cumulative oil production of the single well increases, but the incremental rate slows down gradually. With the increment of soaking time, cumulative oil production increases first and then decreases. These parameters have a relatively suitable value, which makes the performance better. This new method can not only enhance shale oil recovery, but also can be used for CO2 emission control.


SPE Journal ◽  
2017 ◽  
Vol 23 (01) ◽  
pp. 117-127 ◽  
Author(s):  
Zeinab Zargar ◽  
S. M. Farouq Ali

Summary Steam-assisted gravity drainage (SAGD) is a widely tested method for producing bitumen from oil sands (tar sands). Several analytical treatments of the basic process have been reported. In a typical model, the focus is on bitumen drainage ahead of an advancing heat front. In a few cases, a steady expression for bitumen-drainage rate is obtained. This has been modified by several investigators to include other effects. In all cases, the bitumen rate is obtained with no recourse to the steam-injection rate, which is worked out after the fact. The treatment of time dependence, in a few models, is tenuous, building it in partly by use of experimental data. In this work, the SAGD process is considered to develop during two stages: steam-chamber rise (or unsteady stage) and sideways-expansion (or steady stage). The sideways-expansion phase is modeled by two different approaches: constant volumetric displacement (CVD) and constant heat injection (CHI). In the transient-steam-chamber-rise stage of SAGD, initially there is no heat ahead of the rising front, but as the front rises with time, heat accumulates ahead of the front. In the sideways-spreading stage, there is a dynamic equilibrium situation. The accumulated heat ahead of the front plays a crucial role in this phase of SAGD modeling to find the advancing-front velocity. There is a reciprocal relation between the advancing-front velocity and the amount of stored heat ahead of the front. Higher front velocity leads to lower heat accumulation ahead of the front for mobilizing oil ahead and making it drain. By considering the equilibrium situation for thermal-recovery methods with a dominant-gravity-drainage driving force, the advancing-front velocity is responsible for heat accumulation ahead of the front, and, in turn, this heated oil drains away and is responsible for advancing the front. Therefore, the key point in the modeling is to determine the advancing-front movement that satisfies heat and mass balances over the system under equilibrium. In the CVD model, we postulate that the front movement is such that the steam-chamber growth is constant; that is, the oil-production rate is constant over time. In this work, it is shown that to obtain a constant oil-production rate from a mass balance, the injected heat has to be increased to compensate for the heat loss to the overburden and the growing accumulated heat ahead of the front caused by interface extension and decreasing front velocity. In the CHI model, heat is injected at a constant rate into the system, which provides heat for the growing steam-chamber size, increasing heat loss to the overburden, and heat flow by conduction ahead of the front. In this model, we are computing the front velocity that satisfies heat balance and mass balance for a constant heat-injection rate. Decreasing steam-chamber velocity with time from this model leads to decreasing oil-production rate. The modeling of the SAGD process in this work is different from that in previous works because it is believed that the steam-chamber velocity is the key point in SAGD modeling. In the CVD model, a constant maximum steam-chamber velocity is derived that gives a constant oil-production rate with a better agreement with field data. In the CHI approach, steam-chamber velocity, and hence the oil-production rate, is decreasing with time (strongly affected by increasing heat loss to the overburden).


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