Gas Lift Wells Research Articles

Machine-Learning Techniques Assist Data-Driven Well-Performance Optimization

This article, written by JPT Technology Editor Chris Carpenter, contains highlights of paper SPE 201696, “Robust Data-Driven Well-Performance Optimization Assisted by Machine-Learning Techniques for Natural-Flowing and Gas-Lift Wells in Abu Dhabi,” by Iman Al Selaiti, Carlos Mata, SPE, and Luigi Saputelli, SPE, ADNOC, et al., prepared for the 2020 SPE Annual Technical Conference and Exhibition, originally scheduled to be held in Denver, Colorado, 5–7 October. The paper has not been peer reviewed. Despite being proven to be a cost-effective surveillance initiative, remote monitoring is still not adopted in more than 60% of oil and gas fields around the world. Understanding the value of data through machine-learning (ML) techniques is the basis for establishing a robust surveillance strategy. In the complete paper, the authors develop a data-driven approach, enabled by artificial-intelligence methodologies including ML, to find an optimal operating envelope for gas-lift wells. Real-Time Well-Performance Optimization Wellsite Measurement and Control. - Flow Tests. - Past tests include sporadic measurement of multiphase rates and the associated flowing pressure and temperature, collected at various points of the production system, from bottomhole to separator conditions. Flow tests are also known as well tests; however, the authors use the term “flow test” in this paper to avoid confusion with well testing as used in pressure transient tests, including temporary shut-in pressure buildups (for producers) and pressure falloff tests (for injectors). Normally, a well would have limited data points from the past well tests (i.e., less than 50 valid flow tests in a period of 5–10 years). This data is the basis of creating ML models. Continuous Monitoring. - Every well should have adequate instrumentation, and its supporting infrastructure should include reliable power supply, minimum latency telemetry, and desktop access to production parameters. Alignment among real-time data and relational databases is required. Remote Control and Automated Actuation. - In addition to controllable valves, every well should be enabled with actuators to control the process variables. Remote control allows the operator to make changes to the current well-site configuration. Regulatory and Supervisory Control. - The value of automated closed-loop regulatory and supervisory control is to sustain optimal production while providing high well availability. Real-Time Production Optimization. - Continuous production optimization means that expected performance is challenged frequently by updating an optimal forecast with upper-level targets and current asset status. This is achieved by applying actions that close the gap between actual and expected performance. Faster surveillance loops compare actual vs. expected performance to determine minute, hourly, and daily gaps. A slower surveillance loop updates the asset’s expected performance. Well-Management Guidelines. - These are established, known limits to address and honor restrictions such as concession-contract obligations and legal limits, optimal reservoir management, flow assurance, economics, safety, and integrity.

Application of machine learning algorithms to predict tubing pressure in intermittent gas lift wells

Tubing pressure at gas injection depth in intermittent wells is one of the most critical parameters for production engineers to evaluate the performance of the system. However, monitoring of the tubing pressure is not usually carried out in real time. It has been realized that the generally used correlations are not effective enough due to complexity of the intermittent process which involve many parameters and assumptions to develop such equations. The focus of this study is to utilize machine learning (ML) algorithms to develop a model that can accurately predict tubing pressure in artificial intermittent gas lift wells. intelligent algorithms built on the field data provide a solution that is easy to use and universally applicable to the complex problems. Various non-linear regression ML methods are employed in this study, namely, Decision Tree-regression (DT), Random Forest-regression (RF) and K Nearest Neighbors-regression (KNN). All the tubing pressures obtained from ML models were compared with the actual values to ensure the effectiveness of the work. The developed models show that it can predict the pressure with more than 99.9% accuracy. This is an interesting result, as such outcome accuracy has not been reported usually in the open literature.

Technology for Preventing the Wax Deposit Formation in Gas-Lift Wells at Offshore Oil and Gas Fields in Vietnam

Within the past few decades, the production of high-wax oils at offshore fields in Vietnam has been fraught with severe problems due to the intense formation of asphalt-resin-paraffin deposits (ARPD) in the downhole oil and gas equipment. The formation of organic wax deposits in the tubing string led to a significant decrease in gas-lift wells production, efficiency of compressor units, transport capacity of the piping systems, along with an increase in equipment failure. Subsequently, the efficiency of gas-lift wells dramatically decreased to less than 40% as a whole. The existing methods and technologies for combating organic wax deposit formation in downhole equipment have many advantages. However, their use in producing high-wax anomalous oil does not entirely prevent the wax formation in the tubing string and leads to a significant reduction in oil production, transport capacity, and treatment intervals. The results of theoretical and experimental studies presented in this article demonstrate that a promising approach to improve the efficiency of gas-lift wells during the production of high-wax oil is to use the technology of periodic injection of hot associated petroleum gas (APG) into the annulus of an oil-producing well. The effectiveness of the proposed method of combating wax formation in gas-lift wells highly depends on the combination of a few factors: the determination of wax deposit formation intensity in the well and the implementation of a set of preparatory measures to determine the optimal injection mode of hot APG (flow rate and injection depth) into the annulus between tubing strings and technological pipes. The injection depth of the hot APG should not be less than the depth of wax formation in the tubing string. The optimal injection rate of hot APG is determined by analyzing and mathematically modeling the APG injection system based on well-known thermodynamic laws.

Comparative study of the operational properties of deviated and straight gas-lift wells and sensitivity analysis of pressure gradient

The article presents a benchmarking analysis of the complex well body structure effect on the hydraulic parameters of the liquid-gas flow pattern in deviated wells. The difference between the consumption of the working agent (gas) required to lift the same amount of liquid from the same depth in vertical and inclined gas-lift wells is shown. Considering the complexity of the hydrodynamic flow properties in deviated wells, the impossibility of analytical flow simulation, the article provides the problem study using statistical methods and gives its practical solution. The article presents a mathematical expression to determine the dynamic pressure gradient using this method, that is, by group calculation of indicators of gas-lift wells with an deviated body, and its numerical value was found. Keywords: vertical and deviated gas-lift wells; pressure drop; special gas flow rate; gas-liquid mixture.

Performance of a gas-lifted oil production well at steady state

Although gas-lift is an established technology for improving the performances of oil production wells, the simplicity, robustness and accuracy of gas-lift models remain to be fully resolved. As an improvement on the traditional practice, this paper proposes a new approach for modelling the performance of gas-lifted wells at steady-state conditions. The conceptual framework splits the wellbore into two segments. The segments are of unique characteristics, yet they are hydraulically connected. While one segment is controlled primarily by the upstream reservoir-sandface conditions, the dynamics of the second segment are dominated by the lift-gas. This work results in a new four-phase model and an accompanying workflow for analysing the steady-state performance of a gas-lifted well. Using examples from fields operating under diverse conditions in the Niger Delta and North Sea, the new model is validated against a commercial wellbore performance simulator and actual field results. The new model yields average absolute deviation (AAD) of 2.7 and 5.4% against the commercial simulator and field results, respectively. Notwithstanding its relative simplicity, the range of AAD recorded for the new model and workflow attests to its robustness and applicability in practice. In addition to its simple mathematical form, a competitive feature of the proposed model relative to the commercial simulator and most other models is that it accounts for the four phases (gas, oil, water and solid particulates) typically encountered in mature oil production wells and brown fields.

Research on Downhole Plunger Position and Pressure Temperature Detection of Plunger Gas Lift System

Plunger gas lift utilizes the energy of gas production in the formation. By periodically switching on and off the gas well, the plunger moves up and down in the tubing to discharge the bottom hole fluid. The purpose is to reduce the back pressure on the production layer and increase the gas production of the formation. Power, prolong the production life of the gas well. The plunger gas lift detection is the core part of the plunger gas lift system. Adjusting the working status of the downhole plunger through the detection of downhole plunger position, temperature and pressure has important engineering value for improving the oil recovery efficiency of the gas lift process. In order to promote the development of downhole detection systems for gas lift wells in my country and overcome the difficulties of late start and lack of experience, this article focuses on the development status of the detection of plunger gas lift systems.the paper briefly introduce the composition of the plunger gas lift system, analyze the problems of the plunger arrival position detection and temperature and pressure detection in the gas lift detection system, and then analyze the current status of the plunger position monitoring of the plunger gas lift downhole. A review is made, followed by a review of the current status of domestic temperature and pressure monitoring systems for plunger gas lift wells. The review found that the detection of plunger position in my country is still at a relatively weak stage, and direct measurement cannot be achieved; however, there have been breakthroughs in the detection of temperature and pressure, especially in the fields of pressure and temperature detection, storage and wireless transmission. breakthrough. The analysis believes that the detection of downhole parameters of plunger gas lift should be developed in the direction of the integration of well digital control and data acquisition system and digital measure adjustment.

IMPACT OF GAS LIFT INJECTION RATE ON OIL PRODUCTION RATE

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.

New approach for two-phase flow calcuation of artifical lift

The article develops a method for adjusting design pressure of bellows gas lift valves in deviated gas lift wells based on research and calculations and provides a method for the arrangement of gas lift valves along tubing. As a result of the calculations, the valve opening pressure of the first gas lift valve was taken equal to the initial gas pressure, the valve opening pressure of the following valves was 0.05-0.175 MPa lower than that of the previous gas lift valve, and the pressure difference between the last valve and the second from the last valve was 0.28-0.35 MPa.

Comparative study of the operational properties of deviated and straight gas-lift wells and sensitivity analysis of pressure gradient

The article presents a benchmarking analysis of the complex well body structure effect on the hydraulic parameters of the liquid-gas flow pattern in deviated wells. The difference between the consumption of the working agent (gas) required to lift the same amount of liquid from the same depth in vertical and inclined gas-lift wells is shown. Considering the complexity of the hydrodynamic flow properties in deviated wells, the impossibility of analytical flow simulation, the article provides the problem study using statistical methods and gives its practical solution. The article presents a mathematical expression to determine the dynamic pressure gradient using this method, that is, by group calculation of indicators of gas-lift wells with an deviated body, and its numerical value was found.

Research on the Technology of Integral Water Searching and Plugging for Two-Stage Casing Gas-Lift Wells in Sudan Oilfield

The combination structure of and casing is used in some gas-lift wells in Sudan Oilfield. The existing mechanical water searching and plugging technology cannot meet the technical requirements of this type of well, so a integral water searching and plugging string for two-stage casing gas-lift well is developed. The string is composed of two kinds of packers and one kind of regulator. The two kinds of packers are set by hydraulic pressure synchronously to seal the layers of two kinds of casing. After the packers are set, the steel wire is used to fish and drop the blanking plug and search the water layer by layer to realize the adjustment of production layers. This process string has the characteristics of accurate water layer searching, reliable sealing, dynamic adjustment, etc. The string can realize water searching and plugging for two-stage casing wells by one trip. The string has been applied in well JS-2 in Sudan. After adjustment and plugging, the water cut is 25.6% lower than before. The effect of water control and oil production increase is significant, and the production life of the well is prolonged.

A new approach to improving efficiency of gas-lift wells in the conditions of the formation of organic wax deposits in the Dragon field

Gas-lift is one of the artificial methods in which gas is injected down the production casing–tubing annulus and enters the production tubing through a number of gas-lift valves. During the production of a gas-lift well, the injected compressed gas might cause changes in pressure, temperature as well as fluid composition. When the temperature of the oil falls below the wax appearance temperature, it leads to the formation of organic wax deposits. Wax precipitation in well tubing and processing equipment might lead to dramatic reduction in production, equipment failures, loss of storage and transport capacity, and loss of efficiency. This paper presents a detailed study of wax formation in a gas-lift well. Taking into account changes in the oil component composition during gas injection, the depth of wax formation has been determined by applying a highly accurate developed algorithm. The optimal operating regime of the gas-lift well has been determined using a compositional multiphase model.

Application of Artificial Intelligence to Estimate Oil Flow Rate in Gas-Lift Wells

Optimization and monitoring schemes for oil well and reservoir system require accurate estimation of production rate. Real-time monitoring is conducted typically using flow transmitters that contain their own inherent uncertainties due to flow of multiple fluids. Because of these limitations, industrial practices involve the usage of wellhead conditions and intermittent well test data to estimate well flow rates through certain established correlations such as Gilbert’s empirical model. These correlations, however, have become ineffective due to inadequate well test data and associated operational and cost-intensive commitments. The main objective of this work was to utilize artificial intelligence (AI) techniques to develop robust correlation to predict oil rates in gas-lift wells. The AI techniques implemented in this study are artificial neural network (ANN), artificial neuro-fuzzy inference systems, support vector machines, and functional networks. In addition, ANN was used to develop physical equation to predict oil flow rate. Separator test dataset from multiple wells of an oil field operating on continuous gas lift was collected. Extensive data analytics were performed before feeding it in the algorithms. The inputs consisted of only the easily available surface parameters. All the developed AI models were compared among themselves as well as with conventionally used empirical models. The comparison was conducted based on average absolute error percentage and coefficient of determination. The newly developed AI model can predict oil rates with accuracy exceeding 98% that is extremely efficient, and examples of such results have not been reported previously.

Optimisation of gas lift performance using artificial neural network

Gas lift is one of the most widespread methods of artificial lift technologies used when wells' production rate declines. Gas is employed to maintain the production by injecting gas into the tubing through a gas lift orifice. Lifting costs are generally low. However, capital costs of compression are very high, so it is necessary to optimise gas lift wells. In this paper, conventional nodal analysis models were used to predict the optimisation parameters based on wells system parameters. Artificial neural network (ANN) models were also used based on gas lift databases. ANN models were trained then tested against nodal analysis models. Also, this paper presents a new theory about the relative importance of gas lift system inputs on output parameters of gas lift system. [Received: June 9, 2020; Accepted: August 7, 2020]

Dither signals optimization in constrained multi-agent extremum seeking control

Abstract In this paper we consider the problem of optimization of a multi-agent system with constraints through perturbations-based extremum seeking control. We demonstrate that for such systems, effects of dither signals applied to individual agents can sum up to significant perturbations in the outputs at the overall system level despite the fact that individual dither signals can be small. These perturbations are especially detrimental in constrained outputs. To resolve this challenge, we propose a method of dither signals optimization: while maintaining persistent perturbations of individual agents, dither signals are coordinated between the agents to minimize their summed effect in constrained outputs. This problem is formulated as a computationally feasible mathematical programming problem that can be solved numerically at each time step. Combined with a constrained steady-state optimizer and a least squares-based gradient estimator, this method provides better performance than a similar perturbation-based extremum seeking scheme without dither optimization. This is demonstrated with an example on oil production optimization from a system of multiple gas-lifted wells with a total water processing constraint.

Intermittent Gas Lift Used in Hydrate Mitigation and Flare Reduction in Algeria

This article, written by JPT Technology Editor Chris Carpenter, contains highlights of paper SPE 191542, “Hydrate Mitigation and Flare Reduction Using Intermittent Gas Lift in Hassi Messaoud, Algeria,” by Ala Eddine Aoun, SPE, Faouzi Maougal, and Lahcene Kabour, Sonatrach, and Tony Liao, SPE, Brahim AbdallahElhadj, and Sabrina Behaz, Halliburton, prepared for the 2018 SPE Annual Technical Conference and Exhibition, Dallas, 24–26 September. The paper has not been peer reviewed. Hassi Messaoud is a mature oil field with more than 1,100 production wells. Approximately half of the wells are natural flow and the other half use continuous gas lift (CGL) with concentric (CCE) strings. To reduce the usage of the high volume of lift gas, intermittent gas lift (IGL) was selected in a pilot project to evaluate its applicability in the field for wells characterized by high gas/oil ratio (GOR) and without continuous concurrent water injection (with lift gas) to dissolve salt•deposited•downhole. Production Overview Field production began in 1957. During the first 20 years, all production wells were naturally flowing; in 1980, gas lift was introduced into the field development and has remained the only artificial-lift method. Electrical submersible pumping systems have been introduced into the field recently. Of the production wells, 795 are flowing while 376 are shut in for a variety of reasons. Among the flowing production wells, 409 are naturally flowing and 386 are artificial-lift wells. Production fluids are processed by 25 separator stations throughout the field. Gas usually is compressed first at the satellite level; then, at the central processing facilities, the gas is further compressed to the pressure required for injection into the reservoir. Water is treated by the addition of surfactants. The treated water is pumped into the water-injection network to be used in both reservoir-pressure maintenance and salt wash in wells. In the field’s first years, the oil-production rate increased quickly as the number of wells grew. Since 2007, oil production has declined quickly in naturally flowing wells. The steady increase in oil production from gas-lift wells offset the fast production decline in the full field. However, the oil production from gas-lift wells has leveled off during the past 2 years, while the production from naturally flowing wells recovered slightly. The gas lift wells contribute approximately 40% of the field production. Combined Gas Network for•Reservoir Gas Injection and Gas Lift A specific challenge of the Hassi Messaoud field operation is the highly complex gas network, in which the gas-lift network is attached to the gas- injection network for reservoir-pressure maintenance. The gas lift was grown organically out of the reservoir gas-injection network. Initially, when only a small number of wells needed gas lift, this approach might have been cost- effective, but the increasing number of gas-lift wells meant that different methods had to be•considered.

Application of Mechanistic Modeling for Gas Lift Optimization: A General Scaling Curve for Variations of Tubing Size to Optimum Gas Injection

Gas Lift is currently held as one of the most prominent method in artificial lift, proudly operated flawlessly in hundreds of oil wells in Indonesia. However, gas lift optimization is still governed by the exhaustive Gas Lift Performance Curves (GLPC). This practice, albeit as established as it should be, does require repetitive calculations to be able to perform in life of well operations. Therefore, a new approach is introduced based on the mechanistic modeling. This research highlights the application of fundamental mechanistic modeling and its derivative, the Flow Pattern Map (FPM) for quick estimation of optimum injection gas rate, accompanied by a novel correction factor to account changing tubing sizes. It is hoped that this approach can be beneficial in developing a multitude of gas lift wells with changing tubing sizes.

Optimization of Continuous Gas Lift wells based on Well Modeling, Surveillance, Diagnostics and Lift Gas Re-allocation in a Mature Offshore Oil Field

In an oil field, the optimization study of Continuous Gas Lift (CGL) wells require to encompass the single or multiphase inflow performance within the reservoir and the outflow performance from perforations up to the first separator; along with evaluation of the effect of lift gas injection through the operating Gas Lift Valve (GLV). Mature oil fields that inherit problems of increasing trend of water cut, decreasing trend of Formation Gas Oil Ratio, both leads to further increase in demand for lift gas. To optimize a group of CGL wells sharing common manifold and pipeline, it is required to first optimize every individual well. Well problem and Instability in one well can adversely affect the well performance of other wells of the same gathering system. Literature survey shows that the CGL optimization issues were studied either focused on part of the problem or based on secondary data, and not specific to the challenges of Mature Oil Field. Hence, a study has been carried out to address the well optimization problems with CGL, specifically based on field parameters monitored in a mature offshore oil field. In this present study, development of well models of 12 CGL wells of the study area Heera Field of western Indian offshore basin were carried out, in three different simulators with same set of input data. The best fit well models were selected based on comparative error analysis for approximation of operating points by plotting inflow and outflow performance curves using Nodal Analysis approach. Production History of each well, Flowing Gradient Survey data were correlated with the real-time monitored surface measured field parameters. Deviations were analyzed based on empirical data and screening criteria were used to preliminary diagnose well problems. Simulation experiments were performed on the best fit well models for the detail diagnostic analysis. Recommendations were drawn well wise for optimization, by applying engineering judgments, correlating the simulation results with the surface parameters. Gas Lift Performance Curves (GLPC) were generated for each well by simulation experiment on well models. Non-linear functions of Production rate as a function of Gas Lift Injection Rates (GLIR) were approximated by curve fitting of GLPCs using non-linear regression. GLPC based Lift gas re-allocation problem was formulated and solved with limited lift gas quantity as constraints by Equal Slope Graphical Method and by FMINCON solver of MATLAB. Comparative results of envisaged production gain from both approach is being discussed. The integrated approach for real time monitoring of surface parameters, well model based diagnostic analysis and then further allocation of optimum GLIR to each well shows better results than addressing part of the problem for optimization of CGL wells. Lessons learnt from this ‘integrated optimization approach’ were presented, which will be useful in optimization of CGL wells as standalone well or as a part of a group of wells, especially with similar constraints of mature oil field.

Optimal operation of oil and gas production using simple feedback control structures

The purpose of this paper is to describe the control challenges related to optimal operation of oil and gas production wells, and show that optimal operation can be achieved using simple feedback control structures. In particular, we find that conventional feedback control structures can efficiently handle changes in active constraint regions using simple logics such as split-range and selectors. This eliminates the need for complex models to be used in the optimization problem, and in addition eliminates the need to solve numerical optimization problems online. Thus, by using only simple feedback controllers that have been used widely in the oil and gas industry, it has a higher chance of implementation. We demonstrate the use of simple feedback controllers on two application examples; 1) a gas-lift optimization simulation study with a network of six gas-lifted wells, 2) an experimental study of optimal control of electrical submersible pump (ESP) lifted oil wells tested on a large-scale experimental test facility with a full scale ESP and live viscous crude oil.

Geometry Modified Square Edge Orifice Valve Study for Efficiency Gas Lift with Computational Fluid Dynamic (CFD) Method

The gas lift lifting system is widely used as an artificial lift on the X Field, with an average depth of gas lift production wells of 3,000-3,500 ft. Design of 3 to 5 Gas lift Valves (GLV) designwith size of 1 inch is ussualy applied. While at the point of gas injection, the GLV square edge orifice is applied. The problem in the optimization of gas lift wells is the flow instability due to gas flow rate fluctuations, the limited volumetric gas injection and limited gas compressor pressure. With the limited compressor pressure, the lift flow and gas design speed is very dependent on the amount of pressure on the compressor, the production wells with limited injection pressure will result in a limited amount of gas injection, the square edge orifice requires a pressure difference of 40% to achieve the maximum gas flow rate. This study aims to find the modification of the GLV orifice geometry to improve the efficiency of the gas lift system so that it can get optimal production. This GLV design modification includes changing the GLV orifice geometry. Design studies using Computational Fluid Dynamic (CFD) simulations aim to analyze any changes in GLV geometry design to the performance of the gas flow rate in the orifice valve described in the valve performance curve. The design modification approach is in accordance with the GLV venturi orifice geometry and the availability of equipment for GLV modification. The CFD simulation results of the first modification geometry by increasing the orifice diameter from 0.25 to 0.5 inch with the condition of upstream 650 psig and downstream 625 psig pressure increasing the injection gas flow rate capacity by 355% and modifying the second geometry with the venturi orifice form by 280%. In modifying the shape of the orifice venture to reach critical flow requires a pressure difference of 10%. Based on simulation results, the modified orifice application is able to increae production up to 44%.

Optimized production profile using a coupled reservoir-network model

This paper presents an integrated approach for scheduling and forecasting oil and gas production by integrating models of the entire value chain, from the reservoirs to the sales points. The methodology ensures maximum oil production at each time step of the reservoir simulator while honoring all operational constraints of the system. The proposed method is applied to a small North Sea offshore field consisting of two oil reservoirs with API gravities of 37 and 39. 3 gas-lifted wells are producing in each reservoir. They are arranged in a production network connected to a surface process. Control variables include individual well choke opening (early stage) and gas lift injection rate (later stage). The system is subject to numerous operational constraints (e.g., maximum field liquid production, maximum gas lift injection rate). The proposed solution is built in a commercial IAM platform that connects the models and orchestrates the software execution and optimization. The optimization problem is formulated as a Mixed Integer Linear Program. The well and flowline performance curves are approximated with piecewise linear functions. Results show that such an integrated approach can significantly affect the production profile (up to 15% difference against traditional “silo” approach). The proposed integrated solution is two-to-three times faster than traditional non-linear optimization methods, guarantees convergence towards the global maximum and it represents with an appropriate level of accuracy the original black-box model. This allows to run a lot of different scenarios making it a suitable tool for field development and planning optimization. The proposed method is used to optimize the field design and schedule. Optimal surface capacities are determined by brute force exploration of net present value function.