scholarly journals Production Optimization for Natural Flow and ESP Well A Case Study on Well NS-5 Mishrif Formation-Nasriya Oil Field

2020 ◽  
Vol 10 (2) ◽  
pp. 17-35
Author(s):  
Hamzah Amer Abdulameer ◽  
Dr. Sameera Hamd-Allah
Keyword(s):  
Production Rate ◽  
Production Optimization ◽  
Oil Field ◽  
Reservoir Pressure ◽  
Pump Frequency ◽  
Individual Parameter ◽  
Well Production ◽  
Well Design ◽  
Natural Flow ◽  
Reservoir Conditions

As the reservoir conditions are in continuous changing during its life, well production rateand its performance will change and it needs to re-model according to the current situationsand to keep the production rate as high as possible.Well productivity is affected by changing in reservoir pressure, water cut, tubing size andwellhead pressure. For electrical submersible pump (ESP), it will also affected by numberof stages and operating frequency.In general, the production rate increases when reservoir pressure increases and/or water cutdecreases. Also the flow rate increase when tubing size increases and/or wellhead pressuredecreases. For ESP well, production rate increases when number of stages is increasedand/or pump frequency is increased.In this study, a nodal analysis software was used to design one well with natural flow andother with ESP. Reservoir, fluid and well information are taken from actual data of Mishrifformation-Nasriya oil field/ NS-5 well. Well design steps and data required in the modelwill be displayed and the optimization sensitivity keys will be applied on the model todetermine the effect of each individual parameter or when it combined with another one.

scholarly journals Optimizing Production Schedule of Coalbed Methane Wells Using a Stochastic Evolution Algorithm

2020 ◽  
Vol 2020 ◽  
pp. 1-19
Author(s):  
Qiujia Hu ◽  
Xianmin Zhang ◽  
Xiang Wang ◽  
Bin Fan ◽  
Huimin Jia
Keyword(s):  
Production Rate ◽  
Coalbed Methane ◽  
Optimization Problem ◽  
Production Optimization ◽  
Production Performance ◽  
Production Schedule ◽  
Schedule Optimization ◽  
Well Production ◽  
Control Frequency ◽  
Optimized Schedule

Production optimization of coalbed methane (CBM) is a complex constrained nonlinear programming problem. Finding an optimal decision is challenging since the coal seams are generally heterogeneous with widespread cleats, fractures, and matrix pores, and the stress sensitivities are extremely strong; the production of CBM wells needs to be adjusted dynamically within a reasonable range to fit the complex physical dynamics of CBM reservoirs to maximize profits on a long-term horizon. To address these challenges, this paper focuses on the step-down production strategy, which reduces the bottom hole pressure (BHP) step by step to expand the pressure drop radius, mitigate the formation damage, and improve CBM recovery. The mathematical model of CBM well production schedule optimization problem is formulated. The objective of the optimization model is to maximize the cumulative gas production and the variables are chosen as BHP declines of every step. BHP and its decline rate constraints are also considered in the model. Since the optimization problem is high dimensional, nonlinear with many local minima and maxima, covariance matrix adaptation evolution strategy (CMA-ES), a stochastic, derivative-free intelligent algorithm, is selected. By integrating a reservoir simulator with CMA-ES, the optimization problem can be solved successfully. Experiments including both normal wells and real featured wells are studied. Results show that CMA-ES can converge to the optimal solution efficiently. With the increase of the number of variables, the converge rate decreases rapidly. CMA-ES needs 3 or even more times number of function evaluations to converge to 100% of the optimum value comparing to 99%. The optimized schedule can better fit the heterogeneity and complex dynamic changes of CBM reservoir, resulting a higher production rate peak and a higher stable period production rate. The cumulative production under the optimized schedule can increase by 20% or even more. Moreover, the effect of the control frequency on the production schedule optimization problem is investigated. With the increases of control frequency, the converge rate decreases rapidly and the production performance increases slightly, and the optimization algorithm has a higher risk of falling into local optima. The findings of this study can help to better understanding the relationship between control strategy and CBM well production performance and provide an effective tool to determine the optimal production schedule for CBM wells.

The application of risk-based methods to multilateral well design

2016 ◽  
Vol 56 (1) ◽  
pp. 427
Author(s):  
Lucien Jason Nguyen ◽  
Paul F. Pickering ◽  
Zachary M. Aman
Keyword(s):  
Production Rate ◽  
Horizontal Well ◽  
Quantitative Methods ◽  
Oil And Gas ◽  
Fluid Viscosity ◽  
Discounted Cash Flow ◽  
Hydrocarbon Recovery ◽  
Incremental Change ◽  
Well Design ◽  
Reservoir Conditions

Horizontal and multilateral oil and gas wells are used to maximise hydrocarbon recovery while reducing the required well count and associated costs. Presently, lateral lengths are designed using semi-quantitative methods. Guided by a desire to minimise the risk of poor well deliverability, the tendency is to design producing lengths longer than required, with the rationale that the well connects with sufficient hydrocarbon bearing reservoir to provide good deliverability. Drilling long producing lengths, however, is expensive and generates a higher risk of drilling and lifecycle (intervention and workover) problems. Furthermore, attempting to increase deliverability by extending the producing length encounters the law of diminishing returns as the flow becomes constrained by tubing friction loss. This paper seeks to quantify the optimal length for a horizontal well for a given range of reservoir conditions through multiphase fluid modelling and stochastic analysis. A discretised horizontal well model was created, which shows how changing the well length transforms the probability density function of the production rate for the well. A parametric case study was conducted, which demonstrates the evolution of the optimal well length and production rate with parameters including well diameter, fluid viscosity and well flowing bottomhole pressure. A simplified economic analysis illustrates the incremental change in discounted cash flow and quantified risk from drilling a longer well. The model also considered the influence of inflow control devices (ICDs) to adjust the inflow to match permeability and even-out inflows along the producing length, thus reducing the risk of gas and water coning, and improving hydrocarbon recovery.

scholarly journals Injection-production optimization of carbonate reservoir based on an inter-well connectivity model

2021 ◽  
pp. 014459872199465
Author(s):  
Yuhui Zhou ◽  
Sheng Lei ◽  
Xuebiao Du ◽  
Shichang Ju ◽  
Wei Li
Keyword(s):  
History Matching ◽  
Water Injection ◽  
Field Application ◽  
Carbonate Reservoir ◽  
Production Optimization ◽  
Oil Field ◽  
Carbonate Reservoirs ◽  
Utilization Rate ◽  
Production Volume ◽  
Connectivity Model

Carbonate reservoirs are highly heterogeneous. During waterflooding stage, the channeling phenomenon of displacing fluid in high-permeability layers easily leads to early water breakthrough and high water-cut with low recovery rate. To quantitatively characterize the inter-well connectivity parameters (including conductivity and connected volume), we developed an inter-well connectivity model based on the principle of inter-well connectivity and the geological data and development performance of carbonate reservoirs. Thus, the planar water injection allocation factors and water injection utilization rate of different layers can be obtained. In addition, when the proposed model is integrated with automatic history matching method and production optimization algorithm, the real-time oil and water production can be optimized and predicted. Field application demonstrates that adjusting injection parameters based on the model outputs results in a 1.5% increase in annual oil production, which offers significant guidance for the efficient development of similar oil reservoirs. In this study, the connectivity method was applied to multi-layer real reservoirs for the first time, and the injection and production volume of injection-production wells were repeatedly updated based on multiple iterations of water injection efficiency. The correctness of the method was verified by conceptual calculations and then applied to real reservoirs. So that the oil field can increase production in a short time, and has good application value.

scholarly journals Evaluation of natural gas production optimization in Kailashtila gas field in Bangladesh using decline curve analysis method

2015 ◽  
Vol 50 (1) ◽  
pp. 29-38 ◽  
Author(s):  
MS Shah ◽  
HMZ Hossain
Keyword(s):  
Production System ◽  
Gas Production ◽  
Curve Analysis ◽  
Production Optimization ◽  
Reservoir Pressure ◽  
Gas Field ◽  
Wellhead Pressure ◽  
Decline Curve Analysis ◽  
Decline Curve ◽  
Overall Performance

Decline curve analysis of well no KTL-04 from the Kailashtila gas field in northeastern Bangladesh has been examined to identify their natural gas production optimization. KTL-04 is one of the major gas producing well of Kailashtila gas field which producing 16.00 mmscfd. Conventional gas production methods depend on enormous computational efforts since production systems from reservoir to a gathering point. The overall performance of a gas production system is determined by flow rate which is involved with system or wellbore components, reservoir pressure, separator pressure and wellhead pressure. Nodal analysis technique is used to performed gas production optimization of the overall performance of the production system. F.A.S.T. Virtu Well™ analysis suggested that declining reservoir pressure 3346.8, 3299.5, 3285.6 and 3269.3 psi(a) while signifying wellhead pressure with no changing of tubing diameter and skin factor thus daily gas production capacity is optimized to 19.637, 24.198, 25.469, and 26.922 mmscfd, respectively.Bangladesh J. Sci. Ind. Res. 50(1), 29-38, 2015

Diagnostic Plots for Production Decline During the Transition of Oil Field Development From Depletion to Water Injection

2021 ◽  
Author(s):  
Vil Syrtlanov ◽  
Yury Golovatskiy ◽  
Ivan Ishimov
Keyword(s):  
Water Injection ◽  
Simulation Models ◽  
Oil Field ◽  
Production Data ◽  
Oil Reservoir ◽  
Field Development ◽  
Well Production ◽  
Diagnostic Plots ◽  
Oil Field Development ◽  
Analytical Approaches

Abstract In this paper the simplified way is proposed for predicting the dynamics of liquid production and estimating the parameters of the oil reservoir using diagnostic curves, which are a generalization of analytical approaches, partially compared with the results of calculations on 3D simulation models and with actual well production data.

Numerical Simulation of Gas Lift Optimization Using Artificial Intelligence for a Middle Eastern Oil Field

2021 ◽  
Author(s):  
Mohammed Ahmed Al-Janabi ◽  
Omar F. Al-Fatlawi ◽  
Dhifaf J. Sadiq ◽  
Haider Abdulmuhsin Mahmood ◽  
Mustafa Alaulddin Al-Juboori
Keyword(s):  
Genetic Algorithm ◽  
Sensitivity Analysis ◽  
Middle Eastern ◽  
Optimization Technique ◽  
Injection Rate ◽  
Oil Field ◽  
Oil Fields ◽  
Reservoir Pressure ◽  
Artificial Lift ◽  
Gas Lift

Abstract Artificial lift techniques are a highly effective solution to aid the deterioration of the production especially for mature oil fields, gas lift is one of the oldest and most applied artificial lift methods especially for large oil fields, the gas that is required for injection is quite scarce and expensive resource, optimally allocating the injection rate in each well is a high importance task and not easily applicable. Conventional methods faced some major problems in solving this problem in a network with large number of wells, multi-constrains, multi-objectives, and limited amount of gas. This paper focuses on utilizing the Genetic Algorithm (GA) as a gas lift optimization algorithm to tackle the challenging task of optimally allocating the gas lift injection rate through numerical modeling and simulation studies to maximize the oil production of a Middle Eastern oil field with 20 production wells with limited amount of gas to be injected. The key objective of this study is to assess the performance of the wells of the field after applying gas lift as an artificial lift method and applying the genetic algorithm as an optimization algorithm while comparing the results of the network to the case of artificially lifted wells by utilizing ESP pumps to the network and to have a more accurate view on the practicability of applying the gas lift optimization technique. The comparison is based on different measures and sensitivity studies, reservoir pressure, and water cut sensitivity analysis are applied to allow the assessment of the performance of the wells in the network throughout the life of the field. To have a full and insight view an economic study and comparison was applied in this study to estimate the benefits of applying the gas lift method and the GA optimization technique while comparing the results to the case of the ESP pumps and the case of naturally flowing wells. The gas lift technique proved to have the ability to enhance the production of the oil field and the optimization process showed quite an enhancement in the task of maximizing the oil production rate while using the same amount of gas to be injected in the each well, the sensitivity analysis showed that the gas lift method is comparable to the other artificial lift method and it have an upper hand in handling the reservoir pressure reduction, and economically CAPEX of the gas lift were calculated to be able to assess the time to reach a profitable income by comparing the results of OPEX of gas lift the technique showed a profitable income higher than the cases of naturally flowing wells and the ESP pumps lifted wells. Additionally, the paper illustrated the genetic algorithm (GA) optimization model in a way that allowed it to be followed as a guide for the task of optimizing the gas injection rate for a network with a large number of wells and limited amount of gas to be injected.

Multidisciplinary Approach in The Permian Basin - A Geological, Statistical and Engineering Case Study to Production Results on the Wichita-Albany Formation

2015 ◽  
Author(s):  
Fabián Vera ◽  
Casee Lemons ◽  
Ming Zhong ◽  
William D. Holcomb ◽  
Randy F. LaFollette
Keyword(s):  
Design Patterns ◽  
Point Of View ◽  
Production Optimization ◽  
Multivariate Statistical ◽  
Data Set ◽  
Modern Approach ◽  
Well Production ◽  
Fracture Fluid ◽  
Major Factors ◽  
The Impact

Abstract This study compares reservoir characteristics, completion methods and production for 431 wells in 6 counties producing from the Wichita-Albany reservoir to assess major factors in production optimization and derive ultimate recovery estimates. The purpose of the study is to analyze completion design patterns across the study area by combining public and proprietary data for mining. Integrating several analyses of different nature and their respective methods like statistics, geology and engineering create a modern approach as well as a more holistic point of view when certain measurements are missing from the data set. Furthermore, multivariate statistical analysis allows modeling the impact of particular completion and stimulation parameters on the production outcome by averaging out the impact of all other variables in the system. In addition to completion type, more than 18 predictor variables were examined, including treatment parameters such as fracture fluid volume, year of completion, cumulative perforated length, proppant type, proppant amount, and county location, among others. In this sense, this contribution seems unique in unifying statistical, engineering, and geological perspectives into a singular point of view. This work also provides complementary views for well production consideration.

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