scholarly journals A Mathematical Model of Intermittent Gas Lift in Elevation-Production Operation with Line-Pack and Line-Drafting Phenomena in a Gas Line

2020 ◽  
Vol 9 (2) ◽  
pp. 88-101
Author(s):  
Silvya Dewi Rahmawati ◽  
Tasmi Tasmi ◽  
Pudjo Sukarno ◽  
Agus Yodi Gunawan ◽  
Edy Soewono ◽  
...  

This paper discusses a transient model of the intermittent gas lift technique in an oil well. The model is developed in the gas line, in the tubing-casing annulus, and the tubing. The line-pack and line-drafting phenomena in the gas line are considered in the model. A numerical approach will be used to solve the mathematical model that represents fluid flow during intermittent gas lift injection. The dynamics of important variables in the intermittent gas lift are investigated and analyzed to determine the best production strategy for intermittent gas lift. The variables are film thickness and velocity, slug height and velocity, and gas height and velocity. The relationships between surface injection control parameters (gas injection pressure and gas injection rate) and the velocity and height of film, gas, and liquid are shown in one cycle of the gas lift intermittent process. The higher the gas injection pressure, the faster the gas injection velocity, and the thinner the film thickness in the tubing. In order to obtain clean tubing from film thickness, the gas injection pressure needs to be optimized, which will lead to maintaining compressor discharge pressure availability. Detailed observation of the dynamic performance inside the tubing production well will give the optimum oil production rate for oil wells under a gas lift intermittent production strategy for field application.

Author(s):  
Dr. Mohamed A. GH. Abdalsadig

As worldwide energy demand continues to grow, oil and gas fields have spent hundreds of billions of dollars to build the substructures of smart fields. Management of smart fields requires integrating knowledge and methods in order to automatically and autonomously handle a great frequency of real-time information streams gathered from those wells. Furthermore, oil businesses movement towards enhancing everyday production skills to meet global energy demands signifies the importance of adapting to the latest smart tools that assist them in running their daily work. A laboratory experiment was carried out to evaluate gas lift wells performance under realistic operations in determining reservoir pressure, production operation point, injection gas pressure, port size, and the influence of injection pressure on well performance. Lab VIEW software was used to determine gas passage through the Smart Gas Lift valve (SGL) for the real-time data gathering. The results showed that the wellhead pressure has a large influence on the gas lift performance and showed that the utilized smart gas lift valve can be used to enhanced gas Lift performance by regulating gas injection from down hole.


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.


2021 ◽  
Vol 73 (05) ◽  
pp. 21-27
Author(s):  
Stephen Rassenfoss

Gas lift is one of the most popular ways to increase oil-well production, and it is no secret that it is an underperformer. Back in 2014, ExxonMobil reported that by creating a team of roving gas-lift experts it was able to add an average of 22% more output on several hundred wells where the gas injection had been optimized. Gains were expected because “wells do not remain the same over time; they change,” said Rodney Bane, global artificial-lift manager at ExxonMobil, in this JPT story covering the 2014 SPE Artificial Lift Conference and Exhibition (https://jpt.spe.org/paying-close-attention-gas-lift-system-can-be-rewarding). The problem with gas injection is that change is hard. Injection adjustment or repairs require either pulling the tubing to reach the injection mandrels or a wireline run. Those with good- producing wells, particularly offshore, need to weigh the possible gain against the cost and lost production during the job. Those managing more and more wells live with iffy data, injection systems prone to malfunction, horizontal wells prone to irregular flows, and a time-consuming process for calculating the proper injection rates. New approaches addressing those negatives have led a few big operators to try new systems designed to allow constant adjustments based on downhole data with electric control systems designed to be more reliable. Programmable digital controls raise an obvious question: How do you take advantage of that capability? Constantly updated injection data based on traditional evaluation methods is the first step. And new capabilities are inspiring new thinking about how injected gas lifts production and how to make it work more efficiently. Optimizing the process has not been a priority in gas lift. “It was a fairly imprecise thing. But the beauty of gas lift is it works even where it’s broken. It’s not a pump; it’s flow assurance,” said Brent Vangolen, surface and base management technology manager with Occidental. Occidental is among the early adopters of new gas-lift methods along with companies including Chevron, Shell, ExxonMobil, Petronas, and ADNOC. Vangolen expects the industry will follow. “Gas lift is going through the same transformation as rod pumps went through in the 60s and 70s,” he said. Back then, rod pump engineers began tracking changes in the load on the rod through each pump stroke by using dynamometer cards. That data was used to better program pump controls. “You went from egg timers on pumping units to full-blown optimization pumpoff controllers, variable speed drives … this huge infant technology that changed the rod pump space,” he said. Papers at last year’s SPE artificial lift conference covered the continuing digitization in rod lift and that gas lift was finally moving in that direction.


2011 ◽  
Vol 402 ◽  
pp. 654-659
Author(s):  
Yan Qiang Wu ◽  
Xiao Dong Wu ◽  
Teng Fei Sun ◽  
Jing Fei Tang

This paper has created a rapid optimum method to design the gas lift parameters. Optimal Containment Genetic Algorithm (OMSGA) is applied in this method to optimize the parameters such as mass flow rate(Q), volume of gas injection(Qin), injection pressure(Pin), tubing header pressure(Pt), tubing inside diameter(Dt). According to practical situation of gas lift production, the gas lift efficiency (η) is selected as the objective function, the suitable fitness function and value of operators of OMSGA are given, and reasonable convergence delay-independent conditions is set. Based on the intelligence and global quick search of GA and the convergence of OMSGA, the design parameters of gas lift can be globally optimized quickly and accurately. An example is taken to prove that the application of GA in the field of gas lift production is successful. This new optimization method based on GA can provide guide for field design.


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.


2020 ◽  
Vol 1 (2) ◽  
pp. 61
Author(s):  
Ikenna Tobechukwu Okorocha ◽  
Chuka Emmanuel Chinwuko ◽  
Chika Edith Mgbemena ◽  
Chinedum Ogonna Mgbemena

Gas Lift operation involves the injection of compressed gas into a low producing or non-performing well to maximize oil production. The oil produced from a gas lift well is a function of the gas injection rate. The optimal gas injection rate is achieved by optimization. However, the gas lift, which is an artificial lift process, has some drawbacks such as the deterioration of the oil well, incorrect production metering, instability of the gas compressor, and over injection of gas. This paper discusses the various optimization techniques for the gas lift in the Oil and Gas production process. A systematic literature search was conducted on four databases, namely Google Scholar, Scopus, IEE Explore and DOAJ, to identify papers that focused on Gas lift optimizations. The materials for this review were collected primarily via database searches. The major challenges associated with gas lift were identified, and the different optimization strategies available in the literature reviewed. The strategies reviewed were found to be based on artificial intelligence (AI) and machine learning (ML). The implementation of any of the optimization strategies for the gas lift will enhance profitability, reduce operational cost, and extend the life of the wells.


1983 ◽  
Vol 23 (06) ◽  
pp. 885-891
Author(s):  
J.M. Mach ◽  
E.A. Proano ◽  
H. Mukherjee ◽  
K.E. Brown

Abstract The importance of the differential pressure at the point of injection in continuous-flow gas-lift design is discussed. The role played by differential pressure in the selection of optimal flow in gas lift is also explained. It is shown that good wells with high productivity have continued increase in production as the differential pressure decreases. Weaker wells with low productivity, however, are less sensitive to the change in differential pressure. Also, a concept of error envelope surrounding the point of gas injection is presented. Suitable valve spacing in this error envelope is shown to offset any errors in locating the depth of injection caused by errors in the multiphase flow correlations or in the well productivity. The maximum valve spacing within the error envelope is shown to be directly proportional to the differential pressure. The smaller this differential pressure, the smaller the valve spacing. Introduction The theory behind continuous-flow gas-lift design is quite simple. It allows injection of gas in the production string to aerate the producing fluids which in turn lowers the bottomhole flowing pressure (BHFP). Any reduction in BHFP causes the reservoir to respond with increased flow rate. Consequently, once the piping system is fixed, the extent of reduction in the BHFP depends on two parameters-the amount of gas injected and the depth of injection. Although the increased volume of gas injected should yield higher production, there is an upper limit to the volume of gas injected. This upper limit can be an economic limit of gas injection beyond which the cost of gas injection supersedes the price of extra oil produced as discussed by Kanu et al. The economic limit is beyond the scope of this discussion. There is a physical limit of gas injection too, which results in the reversal of the tubing gradients caused by the increased irreversible pressure losses in the tubing. Consequently, a sensitivity analysis on the volume of gas injected should always be carried out before any decision is made regarding this parameter. The second parameter that significantly affects the efficiency of continuous-flow gas-lift design is the depth of injection. The maximum depth of injection achievable in a gas-lift design is function of surface injection pressure and rate, if all other variables remain constant. Once the surface injection pressure is fixed, the depth of injection can be controlled by altering the differential pressure at the point of infection. The lower this differential pressure, the lower the point of injection will be before bottomhole injection starts (see Fig. 6). However, the computed depths of injection may be inaccurate because of errors associated with the use of pressure gradient correlations. As a result, an error envelope surrounding the point of injection is created to define the upper and lower limit of the point of injection caused by calculation errors resulting from pressure loss correlations or well productivity. Considerations such as declining productivity with depletion can also be accounted for in the selection of error envelopes. Judgments based on the closeness of valve spacings, valve interference, and costs must be exercised in making the final selection of the differential pressure at the point of gas injection. SPEJ P. 885^


2020 ◽  
Author(s):  
Mohammed Bashir Abdullahi ◽  
Usman Abdulkadir ◽  
Ahmad Musa Aliyu ◽  
Bashir Umar Shehu

2014 ◽  
Vol 496-500 ◽  
pp. 497-502
Author(s):  
Luo Wei ◽  
Rui Quan Liao ◽  
Yong Li ◽  
Ren Dong Feng

As to three kinds of continuous gas lift design methods commonly used using surface casing pressure control all have several disadvantages when the pressure drop between the valves is small, and they have some deficiency when gas injection pressure is relatively inadequate on ground or want to play the affection of the gas injection pressure on ground as much as possible, therefore, the applied study is made in this regard. First, the precise calculation method of the top valve depth under different conditions was achieved based on the principle of U type tube, then an improved variable pressure drop design method was derived based on the basic principle of gas lift unloading and by using another set of gas injection pressure system on ground independently for designing the valve depth. The obvious advantages of the improved method were found by comparing the available maximum of the gas injection depth and the production rate of the existing methods and the improved method in the same condition of gas injection on ground and on the basis of ensuring the safety design principle.


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