Real-Time Gas Lift Well Optimization Using Surface Read Out (SRO) System in Bunyu Field

2021 ◽  
Author(s):  
C. F. Amiin
Keyword(s):  
Real Time ◽  
Gas Injection ◽  
Injection Rate ◽  
Performance Model ◽  
Rate Variation ◽  
Production Test ◽  
Total Production ◽  
Well Performance ◽  
Production Forecast ◽  
Gas Lift

Gas lift optimization is required to sustain production in Bunyu Field. There are 35 gas lifted wells from total of 61 production wells, which contribute to2916 BOPD from the total production of 6000 BOPD or around 49% of the total production. The performance of these wells are pivotal to ensure production target is achieved. An optimum gas injection rate in each well is essential to maximize the oil production by reducing the Flowing Bottom Hole Pressure (FBHP). Previously, a conventional downhole Pressure – Temperature (P-T) gauge was used to record well response to gas lift injection rate variation to determine the optimum point. However, this method is considered time consuming since the adjustment to determine the optimum gas injection rate can only be done after the data has been downloaded and being analyzed . Thus, the measurement program should be repeated several times until the optimum gas injection rate is determined. This paper presents an approach to optimize the production of gas lifted well by selecting the optimum gas injection rate using a real-time downhole data monitoring system, called Surface Read Out (SRO). This system is used to evaluate the changes in the downhole pressure and temperature in a real-time. When the downhole P-T gauge reaches the perforation depth, a Multi-Rate Test (MRT) is carried out with variation in gas injection rate to find the optimum rate. Optimum gas injection rate is then determined based on the lowest FBHP observed and the highest production test result during the MRT. This optimization method has been proven effective to quickly increasing well production because gas injection rate adjustment can be done during the measurement program based on the real-time analysis. In addition, calibration of well performance model based on the actual Gas Lift Performance Curve (GLPC) of the MRT result can provide more accurate production forecast.

Lessons Learnt from Integrated Production Modelling and Performance Analysis of Gas Lift Wells of One of the Biggest Offshore Complexes in India

2021 ◽  
Author(s):  
Sagun Devshali ◽  
Ravi Raman ◽  
Sanjay Kumar Malhotra ◽  
Mahendra Prasad Yadav ◽  
Rishabh Uniyal
Keyword(s):  
Performance Analysis ◽  
Flow Line ◽  
Gas Injection ◽  
Injection Rate ◽  
Oil Wells ◽  
Nodal Analysis ◽  
Integrated Production ◽  
And Performance ◽  
Gas Lift ◽  
Production Modelling

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.

scholarly journals IMPACT OF GAS LIFT INJECTION RATE ON OIL PRODUCTION RATE

2021 ◽  
pp. 76-94
Author(s):  
Dr. Mohamed A. GH. Abdalsadig
Keyword(s):  
Real Time ◽  
Energy Demand ◽  
Oil And Gas ◽  
Injection Pressure ◽  
Production Operation ◽  
Well Performance ◽  
Time Data ◽  
Daily Work ◽  
Wellhead Pressure ◽  
Gas Lift

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.

scholarly journals Gas Injection Optimization to Increase Oil Production at MRA PT. PHE ONWJ

2021 ◽  
Vol 2 (2) ◽  
pp. 75
Author(s):  
Harry Budiharjo Sulistyarso ◽  
KRT Nur Suhascaryo ◽  
Mochamad Jalal Abdul Goni
Keyword(s):  
Gas Injection ◽  
Economic Feasibility ◽  
Feasibility Analysis ◽  
Offshore Platforms ◽  
Total Production ◽  
The North ◽  
Artificial Lift ◽  
Production Wells ◽  
Java Sea ◽  
Gas Lift

The MRA platform is one of the offshore platforms located in the north of the Java Sea. The MRA platform has 4 production wells, namely MRA-2ST, MRA-4ST, MRA-5, and MRA-6 wells. The 4 production wells are produced using an artificial lift in the form of a gas lift. The limited gas lift at the MRA Platform at 3.1 MMSCFD makes the production of wells at the MRA Platform not optimal because the wells in the MRA Platform are experiencing insufficient gas lift. Optimization of gas lift injection is obtained by redistribution of gas lift injection for each. The results of the analysis in this study indicate that the optimum gas lift injection for the MRA-2ST well is 0.5552 MMSCFD, the MRA-6 well is 1.0445 MMSCFD, the MRA-5 well is 0.7657 MMSCFD, finally the MRA-4ST well with gas injection. lift is 0.7346 MMSCFD. The manual gas lift in the MRA-4ST is also replaced based on an economic feasibility analysis to ensure that the gas lift injection for each well can be kept constant. The redistribution of gas lift carried out by the author has increased the total production rate of the MRA Platform by 11,160 BO/year or approximately USD 781,200/year. Keywords: Gas lift; Insufficient; Optimization

An Integrated IR4.0 Software Enables Autonomous Casing Crossflow Rate Calculation

2021 ◽  
Author(s):  
Nasser M. Al-Hajri ◽  
Akram R. Barghouti ◽  
Sulaiman T. Ureiga
Keyword(s):  
Industrial Revolution ◽  
Water Injection ◽  
Flow Characteristics ◽  
Injection Rate ◽  
Performance Model ◽  
Injection Well ◽  
Production Model ◽  
Well Performance ◽  
Secondary Formation ◽  
Well Model

Abstract This paper will present an alternative calculation technique to predict wellbore crossflow rate in a water injection well resulting from a casing leak. The method provides a self-governing process for wellbore related calculations inspired by the fourth industrial revolution technologies. In an earlier work, calculations techniques were presented which do not require the conventional use of downhole flowmeter (spinner) to obtain the flow rate. Rather, continuous surface injection data prior to crossflow development and shut-in well are used to estimate the rate. In this alternative methodology, surface injection data post crossflow development are factored in to calculate the rate with the same accuracy. To illustrate the process an example water injector well is used. To quantify the casing leak crossflow rate, the following calculation methodology was applied:Generate a well performance model using pre-crossflow injection data. Normal modeling techniques are applied in this step to obtain an accurate model for the injection well as a baseline case.Generate an imaginary injection well model: An injection well mimicking the flow characteristics and properties of the water injector is envisioned to simulate crossflow at flowing (injecting) conditions. In this step, we simulate an injector that has total depth up to the crossflow location only and not the total depth of the example water well.Generate the performance model for the secondary formation using post crossflow data: The total injection rate measured at surface has two portions: one portion goes into the shallower secondary formation and another goes into the deeper (primary) formation. The modeling inputs from the first two steps will be used here to obtain the rate for the downhole formation at crossflow conditions.Generate an imaginary production well model: The normal model for the water injector will be inversed to obtain a production model instead. The inputs from previous steps will be incorporated in the inverse modeling.Obtaining the crossflow rate at shut-in conditions: Performance curves generated from step 3 & 4 will be plotted together to obtain an intersection that corresponds to the crossflow rate at shut-in conditions. This numerical methodology was analytically derived and the prediction results were verified on syntactic field data with very high accuracy. The application of this model will benefit oil operators by avoiding wireline logging costs and associated safety risks with mechanical intervention.

Computational Fluid Dynamics for Gas Lift Optimization in Highly Deviated Wells

2021 ◽  
Author(s):  
Farasdaq Sajjad ◽  
Steven Chandra ◽  
Alvin Wirawan ◽  
Silvya Dewi Rahmawati ◽  
Michelle Santoso ◽  
...  
Keyword(s):  
Fluid Dynamics ◽  
Computational Fluid Dynamics ◽  
Gas Flow ◽  
Flow Behavior ◽  
Gas Injection ◽  
Injection Rate ◽  
Production Loss ◽  
Valve Placement ◽  
Offshore Field ◽  
Gas Lift

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.

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 ◽  
...  
Keyword(s):  
Production Rate ◽  
Gas Injection ◽  
Oil Production ◽  
Injection Rate ◽  
Performance Curve ◽  
Production Well ◽  
Phase Liquid ◽  
Two Phases ◽  
Gas Lift ◽  
Operation Cost

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.

Data Driven Gas Well Performance Model Hands Back Control to Engineers

2021 ◽  
Author(s):  
Cornelis Veeken
Keyword(s):  
Real Time ◽  
Performance Model ◽  
Data Driven ◽  
Production Data ◽  
Performance Parameters ◽  
Well Performance ◽  
Gas Well ◽  
Reservoir Performance ◽  
Fit For Purpose ◽  
Over Time

Abstract This paper presents a fit-for-purpose gas well performance model that utilizes a minimum set of inflow and outflow performance parameters, and demonstrates the use of this model to describe real-time well performance, to compare well performance over time and between wells, and to generate production forecasts in support of well interventions. The inflow and outflow parameters are directly related to well-known reservoir and well properties, and can be calibrated against common well surveillance and production data. By adopting this approach, engineers develop a better appreciation of the magnitude and uncertainty of gas well and reservoir performance parameters.

Successful Pilot of DIAL Digital & Interventionless Gas Lift Production Optimization System Offshore Malaysia

2021 ◽  
Author(s):  
Zaidi Awang@Mohamed ◽  
Jagaan Selladurai ◽  
Siti Nur Mahirah Mohd Zain ◽  
Juhari Yang ◽  
Badroel Rizwan Bahar ◽  
...  
Keyword(s):  
Real Time ◽  
Continuous Production ◽  
Gas Injection ◽  
Value Added ◽  
Lessons Learned ◽  
Production Optimization ◽  
Design Stage ◽  
Optimization System ◽  
The Impact ◽  
Gas Lift

Abstract Objectives/Scope This paper describes a pilot installation of a digital intelligent artificial lift (DIAL) gas lift production optimization system. The work was inspired by PETRONAS' upstream digitalization strategy with five single and dual-string gas lift completions planned from 2018 to 2020, offshore Malaysia. The authors evaluate the impact of the DIAL system in terms of increasing production, optimizing lift-gas injection, reducing well intervention frequency, as well as OPEX and risk reduction. Methods, Procedure, Process DIAL is a unique technology that enhances the efficiency of gas lift production. Downhole monitoring of production parameters informs remote surface-controlled adjustment of gas lift valves. This enables automation of production optimization removing the need for well intervention. The paper focuses on a well installed in June 2020, the first in a five well campaign. The authors will provide details of the technology, and pilot program phases: system design; pre-job preparations; run in hole and surface hook-up; commissioning and unloading; and subsequent production operations. For each phase, challenges encountered, and lessons learned will be listed together with observed benefits. Results, Observations, Conclusions DIAL introduces a paradigm shift in the design, installation, and operation of gas lifted wells. This paper will compare the differences between this digital technology and conventional gas lift techniques. It will consider the value added from the design stage through installation operations to production optimization. The DIAL system's ability to operate at greater than 80-degree deviation enabled deeper injection while avoiding tractor interventions for GLV maintenance in the highly deviated section of the well. Built-in downhole sensors provided real-time pressure monitoring that enabled a better understanding of reservoir behaviour and triggered data-driven reservoir stimulation decisions. The technology also proved very beneficial for production optimization, with the intervention-less adjustment of gas injection rate and depth downhole, based on the observed reservoir response in real time. The variable port sizes can be manipulated by means of surface switch/control. Overcoming the completion challenges due to COVID-19 restrictions, the well was unloaded and brought online with the assistance of personnel located in Houston and Dubai using Silverwell's visualization software. The well continues to be remotely monitored and controlled ensuring continuous production optimization, part of PETRONAS' upstream digitization strategic vision. Novel/Additive Information First deployment worldwide of new and unique gas lift production optimization technology in offshore highly deviated well. The technology deployment was the result of collaborative work between a multi-discipline engineering team in PETRONAS, Silverwell, and Neural Oilfield Service.

scholarly journals Gas lift optimization in the oil and gas production process: a review of production challenges and optimization strategies

2020 ◽  
Vol 1 (2) ◽  
pp. 61
Author(s):  
Ikenna Tobechukwu Okorocha ◽  
Chuka Emmanuel Chinwuko ◽  
Chika Edith Mgbemena ◽  
Chinedum Ogonna Mgbemena
Keyword(s):  
Production Process ◽  
Oil And Gas ◽  
Gas Injection ◽  
Injection Rate ◽  
Gas Production ◽  
Optimization Techniques ◽  
Oil Well ◽  
Oil And Gas Production ◽  
Artificial Lift ◽  
Gas Lift

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.

scholarly journals Multi-Objective Gas Lift Optimization using Elitist Non-Dominated Sorting Genetic Algorithm (NSGA-II)

2019 ◽  
Vol 8 (4) ◽  
pp. 9737-9740
Keyword(s):  
Production Rate ◽  
Production Cost ◽  
Gas Injection ◽  
Oil Production ◽  
Injection Rate ◽  
Nsga Ii ◽  
Wellhead Pressure ◽  
Multi Objective ◽  
The Cost ◽  
Gas Lift

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.

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