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Enhancement of spsa algorithm performance using reservoir quality maps: Application to coupled well placement and control optimization problems

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JOURNAL OF PETROLEUM SCIENCE AND ENGINEERING 2020年第0期189卷 106984-000页

作者： Pouladi, Behzad Karkevandi-Talkhooncheh, Abdorreza Sharifi, Mohammad Gerami, Shahab Nourmohammad, Alireza Vahidi, Akram Amirkabir Univ Technol Dept Petr Engn Tehran Iran IOR EOR Res Inst Tehran Iran

Determination of optimal well location is a vital step in the design of an efficient field development plan which aims to maximize the hydrocarbon recovery and profits from the project. This step has become further complicated as the well control parameters are also introduced into the problem which is known as coupled well placement and control optimization problem. As the number of optimization variable increases, computational cost also increases and it becomes a serious challenge, especially in high resolution reservoir models since the optimization process becomes very time demanding. Simultaneous Perturbation Stochastic Approximation (spsa) has been introduced as an efficient algorithm in finding the optimum solution for problems with a large number of variables. In this work, spsa algorithm has been modified using reservoir quality maps to enhance and accelerate finding the good solutions with a minimum number of function evaluation which is desirable for high-resolution reservoir models and high dimensional optimization problems. In this modification, reservoir quality maps are employed to navigate production wells toward high potential areas instead of random movement in standard spsa. The modified algorithm is tested for joint well placement and control optimization problem using both simultaneous and sequential optimization approach in a synthetic and two benchmark models. The results show that modified spsa outperforms standard spsa both in terms of final result and convergence trend. Also, in most cases, simultaneous well placement and control optimization approach gives better results compared to sequential approaches for both algorithms.

关键词： spsa algorithm Joint well placement and control optimization Reservoir quality map Optimization

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Simulation-optimization for station capacities, fleet size, and trip pricing of one-way electric carsharing systems

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JOURNAL OF CLEANER PRODUCTION 2021年 321卷 129035-129035页

作者： Li, Yan Chen, Shuiwang Hu, Lu Liang, Zhimei Jiang, Yangsheng Tang, Youhua Southwest Jiaotong Univ Sch Transportat & Logist Chengdu 610031 Peoples R China Natl Engn Lab Integrated Transportat Big Data App Chengdu 610031 Peoples R China

This study presents an event-driven discrete-event simulation (EDDES) approach based on an (ODES)-D-2 framework for a one-way electric carsharing system (OECS). The developed model mainly consists of three modules: station, electric vehicle (EV), and link. The system carefully considers the impact of road congestion on travel speed and designs a detailed charging process for EVs to approximate the real world. Based on the high speed of EDDES, a simulation-optimization framework that jointly determines station capacities, fleet size, and trip pricing to maximize the net revenue of operators is proposed. A simultaneous perturbation stochastic approximation (spsa) algorithm is adopted to solve this problem. A case of EVCard in Chengdu is conducted to demonstrate the efficiency of the proposed framework. Several control experiments focusing on various pricing schemes are introduced to verify the advantage of optimization results further. Moreover, a one-way gasoline carsharing system (OGCS) is optimized to contrast with optimal OECS. These comparisons reveal some interesting findings: (1) from the perspective of operators, employing dynamic pricing achieves at least a 57.03% increase in net revenue compared to fixed pricing strategies;(2) from service, the optimal configurations and trip pricing of OECS effectively avoids vehicle overstock at stations;and (3) in terms of greener production, the optimal OECS could sustain a larger fleet size and a higher degree of cleaner production, and its profit generated by per CO2 emission is over six times higher than that of the optimal OGCS.

关键词： One-way electric carsharing Station capacity Fleet size Trip pricing Event-driven mechanism spsa algorithm

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A stepwise simultaneous perturbation stochastic approximation algorithm for stability improvement of active noise control systems

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Mechanical Systems and Signal Processing 2025年 237卷

作者： Chao Liang Francesco Ripamonti Hamid Reza Karimi Stanisław Wrona Marek Pawełczyk Department of Mechanical Engineering Politecnico di Milano Via Privata Giuseppe La Masa 1 Milano 20156 Italy Silesian University of Technology Department of Measurements and Control Systems Akademicka 16 Gliwice 44-100 Poland

Simultaneous perturbation stochastic approximation (spsa) has been widely investigated in active noise control (ANC) due to its model-free nature, which eliminates the need for system model estimation. Despite extensive efforts to enhance its performance, spsa may suffer from instability and convergence issues, particularly in challenging environments. In this paper, we propose a stepwise spsa algorithm that applies perturbations separately rather than simultaneously, significantly improving stability while maintaining comparable performance to standard spsa. A Lyapunov-based theoretical analysis proves the algorithm’s robust stability. A parameter optimization framework further enhances performance by guiding the selection of perturbation coefficients and step sizes. Numerical simulations and real-time DSP board implementation validate the improved stability and practical effectiveness for ANC applications.

关键词： spsa algorithm Active noise control Stability

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Production optimization for alternated separate -layer water injection in complex fault reservoirs

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JOURNAL OF PETROLEUM SCIENCE AND ENGINEERING 2020年 193卷 107409-107409页

作者： Zhang, Liming Xu, Chao Zhang, Kai Yao, Chuanjin Yang, Yongfei Yao, Jun China Univ Petr 66 Changjiang West Rd Qingdao 266580 Shandong Peoples R China

Complex reservoirs possess some principal characteristics, such as strong geological heterogeneity, faults and multi-layers, etc. They can exert significant effects on the flow performance of water flooding vertically and horizontally. For most large-scale and well-connected reservoirs, water injection wells generally adopt manual adjustment method or intelligent well technology to control the water injection volume of a single well. However, these technologies are associated with high costs, and it is not a trivial task to obtain an optimal injection-production control for some complex reservoirs with small blocks or strong heterogeneity. More importantly, most complex fault block reservoirs have experienced multiple rounds of well pattern infilling adjustment in the development process, with large well pattern density, as well as because of complex structure, fault development and single injection production form of fault block reservoir. In view of the unbalanced vertical production of fault block reservoirs in high water cut stage, the alternative injection production mode is proposed to minimize the interlayer interference and achieve stable production under unstable injection production. However, the key parameters of the alternative injection production method are not clear and need to be optimized. Facing this situation, a new method for the injection-production optimization is proposed in this paper. This technology use underground regulator which can alternately open and close the different layers. Additionally, the heterogeneity of permeability is considered and a uniform displacement of water in each flooding unit is realized by adjusting the regulators of injectors and producers. By using this method, a series of measurements such as on-off time and injection volume can be chosen as decision variables. Hence, the commercial simulator and the optimization theory algorithm are used to optimize and adjust the alternative stratified water injection technolo

关键词： Alternate step method Well control Injection-production optimization spsa algorithm

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Parallel Implementation of Simultaneous Perturbation Stochastic Approximation with Adaptive Step Sizes 18

Parallel Implementation of Simultaneous Perturbation Stochas...

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2nd International Conference on algorithms, Computing and Systems (ICACS)

作者： Fan, Yue Liu, Tiegang Beihang Univ Sch Math & Syst Sci Beijing Peoples R China

ISBN: (纸本)9781450365093

The simultaneous perturbation stochastic approximation(spsa) is an iterative gradient-free optimization algorithm. This algorithm approximates the optimal solution by estimating the gradient of the loss function and uses only 2 values of the loss function to estimate the gradient which is independent of the dimension of the problem. But for the high dimensional problem with large-scale, the convergence of classical spsa algorithm is slow, even can not converge to the global minimum value. In order to accelerate the convergence of spsa algorithm and improve the precision of the optimum solution, this paper proposes an improvement of spsa algorithm based on the adaptive step sizes, which can adjust the step size of each iteration according to the gradient direction. The modified algorithm is implemented by Message Passing Interface (MPI) parallel in each iteration to widen the search scope for the better descending direction in order to accelerate the convergence. Numerical experiments of several classical nonlinear optimization problems shows that the modified spsa algorithm can accelerate the convergence of nonlinear optimization problems and find the global extremum point of high-dimension for some optimization problems which the spsa algorithm can not find. It proves that the modified algorithm with adaptive step sizes outperforms the classical spsa algorithm.

关键词： spsa algorithm Adaptive step sizes MPI parallel Numerical experiments

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Inversion of fractures based on equivalent continuous medium model of fractured reservoirs

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JOURNAL OF PETROLEUM SCIENCE AND ENGINEERING 2017年 151卷 496-506页

作者： Zhang, Kai Zhang, Xiaoming Zhang, Liming Yao, Jun Yan, Xia China Univ Petr 66 Changjiang West Rd Qingdao 266555 Shandong Peoples R China

Because the fractures in fractured reservoirs have a significant effect on the flow behavior of fluid, the production performance of the fractured reservoirs contains important information of the distribution of fractures. That is the basic principle of applying the production information for the inversion of fractures. It is the first step to link the distribution information of fractures with the production information to establish inversion objective function on the basis of Bayesian theory. And the geometric parameters of fractures such as midpoint coordinate (x(o), y(o)), azimuth a and extension length L which directly determine the distribution of fractures and then affect the flow behavior are chosen as inversion parameters and some production data are chosen as inversion indexes. Secondly, in order to reconcile the demand of reflecting the flow effect of individual fractures and the use of mature simulators, equivalent continuous medium model whose equivalent permeability tensor is a crucial parameter reflecting the flow behavior of fractured porous media is applied for calculating the numerical simulation of the fractured reservoirs. Finally, spsa algorithm is adopted to minimize the inversion objective function and then update the distribution of fractures to obtain the optimal results. Theoretical cases verify that the inversion method is effective to identify fractures while the number of identified fractures is limited because of the multi-solution of the inverse problem.

关键词： Inversion of fractures Production performance Bayesian theory Equivalent continuous medium model spsa algorithm

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Inversion of fractures with combination of production performance and in-situ stress analysis data

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JOURNAL OF NATURAL GAS SCIENCE AND ENGINEERING 2017年 42卷 232-242页

作者： Zhang, Liming Zhang, Xiaoming Zhang, Kai Zhang, Hao Yao, Jun China Univ Petr 66 Changjiang West Rd Qingdao 266580 Shandong Peoples R China

Successful identification of the fractures in fractured reservoirs is important to guarantee an effective development. Considering that the production performance of fractured reservoirs contains important information of the distribution of fractures, the production performance can be applied for the inversion of fractures. However, the inversion of fractures is difficult to achieve because it is an inverse problem with an inherent defect of multiplicity of solutions. In order to alleviate the defect, we estimate the possible distribution ranges of fractures which can be obtained by analyzing the correlation of fractures and in-situ stress, and the ranges are used as constraint conditions when the production performance is applied for obtaining the accurate distribution of fractures. Firstly, we choose the geometric parameters of fractures such as midpoint coordinate, azimuth and extension length of fractures as inversion parameters and use production data as inversion indexes. Secondly, we simulate the flow behavior in fractured reservoirs based on the Discrete Fracture Matrix (DFM) module of Matlab Reservoir Simulation Toolbox (MRST) to explicitly describe the effect of fractures on the flow behavior of fluid. Thirdly, the possible distribution ranges of fractures which can be obtained by analyzing the correlation between fractures and in-situ stress based on Griffith failure criterion are used as the constraint conditions of inversion parameters. Finally, Simultaneous Perturbation Stochastic Approximation (spsa) algorithm is adopted to minimize the inversion objective function to obtain the accurate distribution of fractures. Theoretical cases verify that the method is effective for the accurate inversion of fractures while the inversion results of more fractures become worse because more fractures make the sensitivities of production performance to individual fractures decrease greatly. (C) 2017 Elsevier B.V. All rights reserved.

关键词： Inversion of fractures DFM model MRST Griffith failure criterion spsa algorithm

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Assisted history matching for the inversion of fractures based on discrete fracture-matrix model with different combinations of inversion parameters

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COMPUTATIONAL GEOSCIENCES 2017年第5-6期21卷 1365-1383页

作者： Zhang, Kai Zhang, Xiaoming Zhang, Liming Li, Lixin Sun, Hai Huang, Zhaoqin Yao, Jun China Univ Petr 66 Changjiang West Rd Qingdao 266580 Shandong Peoples R China

Accurate prediction of fracture distribution in fractured reservoirs is important in the development process. Considering that assisted history matching technology is an effective method for the inversion of reservoir parameters, the technology can also be applied for the inversion of fractures. Because applying assisted history matching technology for the inversion of fractures has an inherent defect of multiplicity of solution, it is therefore necessary to alleviate the multiplicity for the success of inversion. Although there are many factors affecting the multiplicity, the paper focuses on the study of the inversion results of different combinations of inversion parameters which are all representative parameters of fractures and determine the distribution of fractures. Firstly, we simulate the flow behavior in fractured media based on the discrete fracture matrix (DFM) module of Matlab Reservoir Simulation Toolbox (MRST) to explicitly describe the effect of fractures on flow behavior. Secondly, history matching objective function is established based on Bayesian theory and different kinds of representative parameters of fractures are chosen as inversion parameters. Thirdly, simultaneous perturbation stochastic approximation (spsa) algorithm is adopted to minimize the objective function to achieve the inversion of fractures corresponding to different inversion parameters. Finally, theoretical cases verify that the inversion method is effective for the accurate prediction of fracture distribution and proper inversion parameters are crucial to the success of fracture inversion.

关键词： History matching Inversion of fractures DFM model MRST Inversion parameters spsa algorithm

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A Novel spsa Kernel Wavelet Neural Network for Model-free PID Controller 41

A Novel SPSA Kernel Wavelet Neural Network for Model-free PI...

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41st Annual Conference of the IEEE-Industrial-Electronics-Society (IECON)

作者： Zhao, Yuxin Du, Xue Xia, Genglei Jia, Renfeng Harbin Engn Univ Coll Automat Harbin Peoples R China Harbin Engn Univ Coll Nucl Sci & Technol Harbin Peoples R China

ISBN: (纸本)9781479917624

Model-free PID control tuning methods have been widely reported for the case with the time-varying uncertain systems. A model-free control system is introduced in this paper with PID controller. This control design could be considered as a contribution to kernel wavelet neural network PID controllers in model-free system with a straightforward tuning by the simultaneous perturbation stochastic approximation algorithm. It is particularly well suited to problems involving the measurement data without prior inner structure knowledge of the unknown system. On the other hand, neural network activation functions are bounded which cause the outputs of neural network to be limited. Therefore, the T-S Fuzzy control method on basis of kernel wavelet neural network (KWNN) is introduced to improve the control parameter tuning adaptivity in terms of boundedness of the KWNN excitation function. Finally, simulation results are presented to exhibit the effectiveness of the proposed IPWR control system.

关键词： KWNN algorithm PID control T-S fuzzy spsa algorithm

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A demonstration of distribution-based calibration

A demonstration of distribution-based calibration

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International Conference on Models and Technologies for Intelligent Transportation Systems (MT-ITS)

作者： Markou, Ioulia Papathanasopoulou, Vasileia Antoniou, Constantinos Natl Tech Univ Athens GR-15780 Zografos Greece

ISBN: (纸本)9789633131428

Calibration plays a fundamental role in successful applications of traffic simulation models and Intelligent Transportation Systems. In this research, the use of distributions in calibration process is motivated. The optimization of model parameters is fulfilled using the Simultaneous Perturbation Stochastic Approximation (spsa) algorithm. The output of the optimization is a distribution of parameter values, capturing a wide range of various traffic conditions. As a proof of concept, a case study is also presented where the proposed framework is implemented for the distribution-based calibration of the car-following model used in the TransModeler microscopic traffic simulation model. The use of parameter distributions is preferred to using point parameter values, as it is more realistic, capturing the heterogeneity of driver behavior, and allows the simultaneous study of various driving behavior patterns. Flexibility is thus introduced into the calibration process and restrictions generated by conventional calibration methods are relaxed.

关键词： distribution-based calibration spsa algorithm parameters optimization car-following models

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