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Stochastic simplex approximation gradient for reservoir production optimization: algorithm testing and parameter analysis

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JOURNAL OF PETROLEUM SCIENCE AND ENGINEERING 2022年 209卷

作者： Xu, Jianchun Zhou, Wenxin Li, Hangyu Wang, Xiaopu Liu, Shuyang Fan, Ling China Univ Petr East China Minist Educ Key Lab Unconvent Oil & Gas Dev Qingdao 266580 Peoples R China China Univ Petr East China Sch Petr Engn Qingdao 266580 Peoples R China

Production optimization is an effective technique to maximize the oil recovery or the net present value in reservoir development. Recently, the stochastic simplex approximation gradient (StoSAG) optimization algorithm draws significant attention in the optimization algorithm family. It shows high searching quality in largescale engineering problems. However, its optimization performance and features are not fully understood. This study evaluated and analyzed the influence of some key parameters related to the optimization process of StoSAG including the ensemble size to estimate the approximation gradient, the step size, the cut number, the perturbation size, and the initial position by using 47 mathematical benchmark functions. Statistical analysis was employed to diminish the randomness of the algorithm. The quality of the optimization results, the convergence, and the computational time consuming were analyzed and compared. The parameter selection strategy was presented. The results showed that a larger ensemble size was not always favorable to obtain better optimization results. The increase of the search step size was favorable to escape from the local optimum. A large step size needed to match a large cut number. The increase of cut number was beneficial to increase the local searchability, but also made the algorithm more easily fall into the local optimum. The random initial position was beneficial to find the global optimal point. Moreover, the effectiveness of the parameter selection strategy was tested by a classical reservoir production optimization example. The final net present value (NPV) for water flooding reservoir production optimization substantially increased, which indicated the excellent performance of StoSAG by adjusting the key parameters.

关键词： Stochastic simplex approximation gradient Production optimization algorithm testing Computational cost Reservoir numerical simulation

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algorithm-709 - testing algorithm IMPLEMENTATIONS

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ACM TRANSACTIONS ON MATHEMATICAL SOFTWARE 1992年第4期18卷 375-391页

作者： BUCKLEY, AG ROYAL ROADS MIL COLL DEPT MATHVICTORIA V0S 1B0BCCANADA

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testing and optimization of a semiautomatic prostate boundary segmentation algorithm using virtual operators

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MEDICAL PHYSICS 2003年第7期30卷 1637-1647页

作者： Ladak, HM Wang, YQ Downey, DB Fenster, A Univ Western Ontario Dept Med Biophys London ON N6H 5C1 Canada Robarts Res Inst Imaging Res Labs London ON N6H 5C1 Canada London Hlth Sci Ctr Dept Radiol London ON N6H SC1 Canada Univ Western Ontario Dept Elect & Comp Engn London ON N6H 5C1 Canada

Image analysis tasks such as size measurement and landmark-based registration require the user to select control points in an image. The output of such algorithms depends on the choice of control points. Since the choice of points varies from one user to the next, the requirement for user input introduces variability into the output of the algorithm. In order to test and/or optimize such algorithms, it is necessary to assess the multiplicity of outputs generated by the algorithm in response to a large set of inputs;however, the input of data requires substantial time and effort from multiple users. In this paper we describe a method to automate the testing and optimization of algorithms using "virtual operators," which consist of a set of spatial distributions describing how actual users select control points in an image. In order to construct the virtual operator, multiple users must repeatedly select control points in the image on which testing is to be performed. Once virtual operators are generated, control points for initializing the algorithm can be generated from them using a random number generator. Although an initial investment of time is required from the users in order to construct the virtual operator, testing and optimization of the algorithm can be done without further user interaction. We illustrate the construction and use of virtual operators by testing and optimizing our prostate boundary segmentation algorithm. The algorithm requires the user to select four control points on the prostate as input. (C) 2003 American Association of Physicists in Medicine.

关键词： algorithm testing optimization segmentation prostate therapy ultrasound

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Deformation image generation for testing a strain measurement algorithm

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OPTICAL ENGINEERING 2008年第10期47卷

作者： Koljonen, Janne Alander, Jarmo T. Univ Vaasa Dept Elect Engn & Automat FIN-65101 Vaasa Finland

An optical extensometer was tested using artificially deformed images with a known strain field. A real image series from a tensile test was used to obtain realistic deformation parameters, including spatial and temporal strain characteristics, changes in tonal pixel properties due to deformation, and the effect of nonuniform illumination. These parameters are used to artificially deform a real image taken from an object with a random speckle pattern. The signal-to-noise ratio of the resulting artificially deformed images is varied by applying a blurring pillbox filter and additive Gaussian noise to them. The optical extensometer uses digital image correlation to track homologous points of the object, and further to measure strains. The strain measurement algorithm includes a heuristic to dynamically control the template size in image correlation. Furthermore, several other methods to improve the accuracy-complexity ratio of the algorithm exist. The effects of different parameters and heuristics on the accuracy of the algorithm as well as its robustness against blur and noise are studied. Results show that the proposed test method is practical, and the heuristics improve the accuracy and robustness of the algorithm. c 2008 Society of Photo-Optical Instrumentation Engineers. [DOI: 10.1117/1.2993319]

关键词： algorithm testing computer vision pattern recognition strain analysis test image generation

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Iterative algorithm for Time Series Decomposition into Trend and Seasonality: testing Using the Example of CO2 Concentrations in the Atmosphere

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IZVESTIYA ATMOSPHERIC AND OCEANIC PHYSICS 2021年第8期57卷 813-836页

作者： Deshcherevskii, A. V. Sidorin, A. Ya. Russian Acad Sci Schmidt Inst Phys Earth Moscow Russia

An iterative algorithm for the decomposition of data series into trend and residual (including the seasonal effect) components is proposed. This algorithm is based on the approaches proposed by the authors in several previous studies and allows unbiased estimates for the trend and seasonal components for data with a strong trend containing different periodic (including seasonal) variations, as well as observational gaps and omissions. The main idea of the algorithm is that both the trend and the seasonal components should be estimated using a signal that is maximally cleaned of any other variations, which are considered a noise. In estimating the trend component, seasonal variation is a noise, and vice versa. The iterative approach allows a priori information to be more completely used in the optimization of models of both trend and seasonal components. The approximation procedure provides maximum flexibility and is fully controllable at all stages of the process. In addition, it allows one to naturally solve the problems in the case of missing observations and defective measurements without filling these dates with artificially simulated values. The algorithm was tested using data on changes in the concentration of CO2 in the atmosphere at four stations belonging to different latitudinal zones. The choice of these data is explained by the features that complicate the use of other methods, namely, high interannual variability, high-amplitude seasonal variations, and gaps in the series of observed data. This algorithm made it possible to obtain trend estimates (which are of particular importance for studying the characteristics and searching for the causes of global warming) for any time interval, including those that are not multiples of an integer number of years. The rate of increase in the CO2 content in the atmosphere has also been analyzed. It has been reliably established that in around 2016, the rate of CO2 accumulation in the atmosphere became stabilized and

关键词： time series time series analysis time series decomposition iterative algorithm trend periodic components seasonal periodicity algorithm testing CO2 concentration in the atmosphere

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An algorithm for Adaptive Assessment in Time Series Seasonal Oscillations and Its testing Based on the Example of Variations in the CO2 Concentration in the Atmosphere

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IZVESTIYA ATMOSPHERIC AND OCEANIC PHYSICS 2022年第7期58卷 681-707页

作者： Deshcherevskii, A. V. Sidorin, A. Ya. Russian Acad Sci Schmidt Inst Phys Earth Moscow 123242 Russia

An adaptive model is proposed to describe time-varying seasonal effects. The seasonal average function is constructed using an iterative algorithm that provides a neat decomposition of the signal into a generalized trend, seasonal and residual components. By a trend, we mean long-term evolutionary changes in the average signal level, both unidirectional and chaotic, in the form of a slow random drift. This algorithm allows one to obtain unbiased estimates for each of the signal components, even in the presence of a significant number of missing observations. The series length is not required to be a multiple of an integer number of years. In contrast to the usual "Climate Normals" (CN) model, the considered adaptive model of seasonal effects assumes a continuous slow change in the properties of the seasonal component over time. The degree of allowable variability in seasonal effects from year to year is entered as a tunable parameter of the model. In particular, this allows one to show the dynamics of the growth of the amplitude of seasonal fluctuations in time in the form of a continuous (smooth) function without necessarily linking these changes to predetermined calendar epochs. The algorithm was tested on the atmospheric CO2 concentration monitoring series at Barrow, Mauna Loa, Tutuila, and South Pole stations located at different latitudes. The form of the seasonal variation was estimated, and the average amplitude of the seasonal variation and the rate of its change at each station were calculated. Noticeable differences in the dynamics of the studied parameters between stations are demonstrated. Mean amplitude of seasonal variation in CO2 concentration at Barrow, Mauna Loa, Tutuila, and South Pole stations in the epoch 2010-2019 was estimated as 18.15, 7.08, 1.30, and 1.26 ppm, respectively, and the average rate of increase in the amplitude of the seasonal variation in the increase in CO2 concentration in the interval 1976-2019 is 0.085, 0.0100, 0.0165, and 0.

关键词： time series time series analysis time series decomposition iterative algorithm trend periodic components seasonal periodicity algorithm testing carbon dioxide CO2 concentration in the atmosphere

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A Novel testing Method for Narrowband Synthetic Aperture Radar (SAR) Imaging algorithm 4

A Novel Testing Method for Narrowband Synthetic Aperture Rad...

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4th International Conference on Dependable Systems and Their Applications (DSA)

作者： Zeng, Letian Yang, Chunhui Zhao, Yuelong Chen, Pin Wang, Qiang CEPREI Software Qual Engn Res Ctr Guangzhou Guangdong Peoples R China South China Univ Technol Sch Comp & Engn Guangzhou Guangdong Peoples R China

ISBN: (纸本)9781538636909

Imaging algorithms are the key factors of the performances of the synthetic aperture radar (SAR) imaging. Most existing methods usually need to utilize field environment and data, which dramatically reduces the effectiveness of the software testing. This paper presents a novel testing method for narrow-band SAR imaging algorithms, which is consisted of four parts: system parameter verification, echo data simulation, algorithm simulation and real data verification, evaluations of imaging results. This scheme has fully validated the correctness and feasibility of imaging algorithms. Also, this approach greatly improves the validity of the testing work. Finally, the correctness and effectiveness of the proposed method are verified by simulation experiments and real data results.

关键词： Synthetic aperture radar (SAR) imaging algorithm testing echo data simulation algorithm simulation and real data verification evaluations of imaging results

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Regularization of the Solution of the Inverse VES Problem by the Contrast Stabilization Method: testing the algorithm on Model Data

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SEISMIC INSTRUMENTS 2022年第5期58卷 581-600页

作者： Bobachev, A. A. Deshcherevskii, A. V. Sidorin, A. Ya. Lomonosov Moscow State Univ Moscow 119991 Russia Russian Acad Sci Schmidt Inst Phys Earth Moscow 123242 Russia

Earlier, it was shown that conventional algorithms for solving the inverse VES problem cannot achieve the accuracy required for precision monitoring of a geoelectric section, and regularized algorithms were proposed to improve the accuracy and stability of solving the inverse VES problem. In this paper, we test the resistivity contrast stabilization algorithm on synthetic data. For modeling, a geoelectric section is used, similar to the section of the Garm test site both in the set of layers and their resistivities, and in the characteristics of seasonal variations, as well as noise. It is shown that regularization of the inverse problem greatly reduces errors. The most significant effect is achieved by suppressing the buildup of resistivity. Estimates are obtained for the accuracy in solving the inverse problem, which can be achieved when working with experimental data.

关键词： VES data inversion solution regularization contrast stabilization algorithm testing model series

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testing a measure of image quality for acquisition control

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IMAGE AND VISION COMPUTING 2002年第7期20卷 449-458页

作者： Marchant, JA Silsoe Res Inst Image Anal & Control Grp Bedford MK45 4HS England

Previous work by the author has shown that the entropy of an image's histogram can be used to control the acquisition variables (brightness, contrast, shutter speed) of a camera/digitiser combination in situations where the imaging conditions are changing. Although the control leads to histograms that satisfy pragmatic expectations of what a 'good' histogram should look like (i.e. filling the dynamic range of the digitiser without too much saturation), it avoids the problem of what we mean by a good histogram in the machine vision context and whether the control produces images that have these histograms. In this work a good image is defined to be one where the subsequent analysis algorithms work well. Three different algorithms, each containing many diverse components, are tested on sets of images with different acquisition parameters. As well as acquiring at different parameters, a simulation of the image acquisition process is derived and validated to assist evaluation. Test results show that near-optimal performance is obtained with maximum entropy and it is concluded that this measure is a suitable one for control of image acquisition. (C) 2002 Elsevier Science B.V. All rights reserved.

关键词： image quality acquisition control information theory entropy algorithm testing simulation active vision

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Simulator for testing algorithms for Estimation of Parameters of Power System 41

Simulator for Testing Algorithms for Estimation of Parameter...

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41st International Convention on Information and Communication Technology, Electronics and Microelectronics (MIPRO)

作者： Alispahic, Mirza Vila, Muhamed Aksamovic, Abdulah Univ Sarajevo Fac Elect Engn Sarajevo Bosnia & Herceg

ISBN: (纸本)9789532330953

In the paper, realized simulator for testing parameters estimation of the power system was described. Simulator allows definition of the test conditions like amplitude and phase, activity of decreasing direct component, variation of number of samples, variation of harmonic components, and change of frequency of the basic harmonic. The test criterion takes the error of the estimated value in relation to the default value and then time of convergence of the estimated value. As an illustration of algorithm functioning, the time format of the input signal and the timing response of the estimated amplitude and phase of signals are shown. In the simulator, algorithms for amplitude and phase estimation are implemented. For amplitude estimation, algorithms that were implemented: algorithm based on the Fourier bandwidth filter and algorithm based on the least squares method. For phase estimation, algorithms that were implemented: zero crossing algorithm and algorithm based on the Fourier bandwidth filter. All of the implemented algorithms are described and given with their mathematical models. Simulator was made in Matlab and can be expanded with addition of the noise, implementation of other algorithms, development and testing of new algorithms. For the demonstration of the usability of the simulator, results that were obtained by testing are shown.

关键词： simulator amplitude phase parameters estimation of power system algorithm testing

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