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Integrated well placement and fracture design optimization for multi-well pad development in tight oil reservoirs

COMPUTATIONAL GEOSCIENCES 2019年第3期23卷 471-493页

作者： Wang, Shuhua Chen, Shengnan Univ Calgary Schulich Sch Engn Dept Chem & Petr Engn Calgary AB T2N 1N4 Canada

Multi-well pad has been considered the most efficient horizontal well development technique in unconventional reservoirs since it does not only maximize oil production but also significantly reduces operation costs and environmental footprints by drilling a group of wells on a single pad. To optimize both well placement and hydraulic fracture parameters simultaneously in a multi-well pad is still largely unexplored and remains to be a challenging task. In this study, we develop a global optimization framework based on generalized differential evolution (GDE) algorithm to maximize the expected net present value (NPV) in a constrained well-pad production optimization. More specifically, differential evolution (DE) algorithm is extended for constrained optimization problem through a generalized selection operation. Unlike the penalty functions, the GDE is capable of handling the constraints without introducing any extra parameters. Subsequently, a new well completion economic model is firstly proposed based on a 200 well completion dataset. This enables us to integrate the available field information into the optimization framework and obtain a practical optimum scenario for the multi-well pad development. Furthermore, a geological model is generated and matched to the field production data and operation costs of a four-well pad in Cardium tight oil formation. Based on the newly developed economic model and well-tuned simulation model, the well spacing, well length, fracture spacing, fracture half-length, and fracture conductivity of each well in a multi-well pad are optimized and a highest NPV is achieved. The oil recovery and NPV of the optimum scenario derived through the GDE are increased by 37.2 and 63.7% respectively in comparison with the field reference case.

关键词： Multi-well pad optimization Fracture design constrained optimization problem Generalized differential evolution Practical knowledge integration

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GENERALIZATION OF LEAST-SQUARE ISOTONIC REGRESSION

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JOURNAL OF STATISTICAL PLANNING AND INFERENCE 1994年第3期38卷 389-397页

作者： QIAN, SX UNIV PITTSBURGH DEPT MATH & STATPITTSBURGHPA 15260

In this paper, we give simple general conditions for optimization problems with order constraints to be solved by least-square isotonic regressions.

关键词： ORDER RESTRICTED STATISTICAL INFERENCE constrained optimization problem MAXIMUM LIKELIHOOD ESTIMATION

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Designing matching waveform pair with sparse frequency and low autocorrelation sidelobes

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ELECTRONICS LETTERS 2021年第1期57卷 34-36页

作者： Chen, Xiaoying Chen, Baixiao Wu, Chuanzhang Xidian Univ Natl Lab Radar Signal Proc Xian Peoples R China

Sparse frequency waveform is widely used to suppress the narrow-band interferences. The performance that can be achieved with a single waveform is limited. The authors study the approach to design a pair of matching waveforms with low autocorrelation sidelobes and arbitrary frequency stopbands. Two algorithms based on the minimum mean square error (MMSE) between the actual waveform characteristics and the desired waveform characteristics are proposed to deal with this problem. The constrained optimization problem is solved by an alternating iteration method. Numerical experiments show that the proposed algorithms can provide better performance than the existing methods.

关键词： Signal processing theory Optimisation techniques least mean squares methods MMSE alternating iteration method Signal processing and detection interference suppression arbitrary frequency stopbands low autocorrelation sidelobes narrowband interferences actual waveform characteristics minimum mean square error Interpolation and function approximation (numerical analysis) correlation methods iterative methods constrained optimization problem sparse frequency waveform Electromagnetic compatibility and interference matching waveform pair desired waveform characteristics single waveform optimisation

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Control of Autonomous Underwater Vehicle using Reduced Order Model Predictive Control in Three Dimensional Space

Control of Autonomous Underwater Vehicle using Reduced Order...

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4th IFAC Conference on Advances in Control and optimization of Dynamical Systems (ACODS 2016)

作者： Jagtap, Pushpak Raut, Pranoti Kumar, Pawan Gupta, Ankit Singh, N. M. Kazi, Faruk Veermata Jijabai Technol Inst Ctr Excellence Complex & Nonlinear Dynam Syst Bombay 19 Maharashtra India Veermata Jijababai Technol Inst Dept Elect Engn Bombay 19 Maharashtra India

The paper investigates the motion control problem of Autonomous Underwater Vehicle (AUV) in three-dimensional space. Here, we consider a rim linear, nonholoncanic and highly under-actuated dynamical model of AUV with six degrees of freedom. Because of its higher-dimensional complex model, the traclitioual model predictive control technique leads to computational complexity and loss of controllability. The paper proposes a novel MPC Scheme using reduced dynamical model. In which, the MPC problem to control AUV in vertical and horizontal planes is formulated as independent, optimization problems. The proposed scheme reduces higher-dimensional model to two independent time-varying linearized models for controlling motion in vertical and horizontal planes by neglecting weakly coupled dynamics. Further the reduced optimization problem is solved using quadratic programming to achieve trade-off between computational complexity and control effort optimization. The simulation results show the effectiveness of the proposed control scheme which is employed On non-linear model. (C) 2016, IFAC (International Rderation or Automatic Control) Hosting by Elsevier Ltd. All rights reserved.

关键词： Autonomous underwater Vehicle model predictive control non-linear dynamical system constrained optimization problem and reduced order dynamics

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constrained Portfolio Selection Using Multiple Swarms

Constrained Portfolio Selection Using Multiple Swarms

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2010 IEEE World Congress on Computational Intelligence

作者： Niu, Ben Tan, Lijing Xue, Bing Li, Li Chai, Yujuan Shenzhen Univ Coll Management Shenzhen 518060 Guangdong Peoples R China Shenzhen Univ Measurement Specialties Inc Shenzhen 518107 Guangdong Peoples R China McMaster Univ Fac Sci Hamilton ON L8S 4L8 Canada

ISBN: (纸本)9781424481262

Markowitz mean-variance model is one of the best known models that has been heavily studied in modern world of finance. However, the model is considered to be too basic in practice, as it ignores many of the constraints that real-world investors have to face with. In this paper we focused on a complex constrained portfolio selection model with additional constraining factors including the transaction fee, the minimal transaction unit, the maximal transaction quantity of every assets and the minimum/maximum of the investment. When taken these complex constraints in to account, the process became a high-dimensional constrained optimization problem. In our study, based on the study of symbiosis phenomenon in natural ecosystem, a multiple-swarm approach (SMPSO) was proposed to solve the resulting model. A numerical experimental study of a portfolio selection problem was conducted to illustrate our proposed method. The simulation results demonstrated that our proposed method is more efficient than PSO based method in solving the complex constrained portfolio selection problem.

关键词： Markowitz mean-variance model constrained optimization problem constrained portfolio selection finance financial management investment investment maximal transaction quantity minimal transaction unit multiple swarms natural ecosystem optimisation real-world investor transaction fee

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A Barrier Function Based Feedback Linearization Method for On-line Output Tracking Control of Non-minimum Phase Systems 29

A Barrier Function Based Feedback Linearization Method for O...

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29th Iranian Conference on Electrical Engineering (ICEE)

作者： Jahangiri, Fatemeh Talebi, Ali Menhaj, Mohammad Bagher Shahid Beheshti Univ Dept Elect Engn Tehran Iran Amirkabir Univ Technol Dept Elect Engn Tehran Iran

ISBN: (纸本)9781665433655

This paper presents a new method for solving the output tracking problem in nonlinear non-minimum phase systems using feedback linearization method. The proposed method converts the problem to an equivalent optimization problem where the constraints of which include minimum phase conditions and the cost function is the Euclidean distance between the system output and the parameterized redefined output. To solve this constrained optimization problem, it is first approximated to an unconstrained one using the barrier method and then, through the steepest descent algorithm, optimization parameters (the redefined output parameters) are iteratively obtained in an on-line manner such that at each time the minimum phase conditions are satisfied. Indeed, solving the optimization problem leads to find a minimum phase output as close as possible to the system output. On the other hand, since this minimum phase output tracks the reference signal using feedback linearization method, the system output converges to the reference signal.

关键词： barrier function method steepest descent algorithm constrained optimization problem

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Nonlinear Elasticity Imaging

Nonlinear Elasticity Imaging

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IEEE 37th Annual Northeast Bioengineering Conference (NEBEC)

作者： Goenezen, Sevan Oberai, Assad A. Dord, Jean-Francois Sink, Zac Barbone, Paul Rensselaer Polytech Inst MANE Dept Troy NY 12180 USA Boston Univ Dept Engn Mech Boston MA 02215 USA

ISBN: (纸本)9781612848266

We present the solution of the nonlinear inverse elasticity problem, wherein we image the linear and nonlinear hyperelastic properties of soft tissues in-vivo. For this, we solve a constrained optimization problem iteratively. The discrepancy between measured and predicted displacement fields is minimized in the objective function in the presence of regularization. The predicted displacement fields satisfy the equilibrium equations of elasticity from the current estimate of the elastic properties. The measured displacement fields are determined from a sequence of ultrasound radio frequency data while the tissue is slowly compressed. We model the tissue to have an exponential stress-stretch relation and capture its nonlinear response with a nonlinear parameter at large deformations.

关键词： Displacement measurement Elasticity Image reconstruction Imaging Inverse problems Strain Ultrasonic imaging biological tissues biomechanics biomedical ultrasonics breast lesions cancer compression constrained optimization problem deformation displacement fields elasticity equilibrium equations exponential stress-stretch relation inverse problems iterative methods mammography medical image processing nonlinear hyperelastic properties nonlinear inverse elasticity patient reconstructions physiological models regularization soft tissues stress-strain relations ultrasound radio frequency

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A Cost Effective Two-Step Exploration for constrained Two-Dimensional Packing problems 43rd

A Cost Effective Two-Step Exploration for Constrained Two-Di...

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43rd IFIP WG 5.7 International Conference on Advances in Production Management Systems (APMS)

作者： Pyeon, Hyeongoo Son, SookYoung HD Korea Shipbldg & Ocean Engn Co AI Ctr 477 Bundangsuseo Ro Seongnam Si Gyeonggi Do South Korea Seoul Natl Univ Dept Naval Architecture & Ocean Engn 1 Gwanak Ro Seoul South Korea

ISBN: (纸本)9783031716478;9783031716454;9783031716447

A combinatorial optimization problem, particularly an NP-hard challenge, aims to find an optimal solution within a discrete search space and has been applied across diverse industries. However, practical use-cases often involve numerous constraints, making the optimization problem significantly more complex as the search space expands. To address this issue, this paper presents a new methodology that efficiently solves two-dimensional bin packing problems with multiple constraints. We propose a two-step exploration technique, consisting of combination and permutation, and apply it to the practical design of LNG vessels. The proposed methodology not only enhances efficiency in search time and space but also ensures the discovery of global optimal solutions without requiring additional exploration. Our results demonstrate remarkable improvements in both time and spatial efficiency compared to brute-force global searches. The methodology proposed in this paper is expected to contribute significantly to technological advancements in solving combinatorial optimization problems.

关键词： combinatorial optimization packing problem NP-hard constrained optimization problem two-step exploration time and spatial efficiency optimal solution

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Effect-Selection Tool using Visual Saliency Maps and its Evaluations 10

Effect-Selection Tool using Visual Saliency Maps and its Eva...

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Joint 10th International Conference on Soft Computing and Intelligent Systems (SCIS) / 19th International Symposium on Advanced Intelligent Systems (ISIS)

作者： Suzuki, Natsumi Nakada, Yohei Meiji Univ Grad Sch Adv Math Sci Tokyo Japan

ISBN: (纸本)9781538626337

This paper proposes an effect-selection tool using a visual saliency map to improve the visual appeal of an object in a target image. In the proposed tool, an optimization problem is considered that constructs an effect sequence for editing the target image. Here, "effect" means an editing process such as a blur effect on the background of the target image. To construct the effect sequence, this tool considers the effect set that comprises effects frequently used by image designers and/or image editors. This optimization problem is formulated with an objective function calculated via a saliency map and a constraint condition concerning the image distance between the original image and the edited image. A heuristic method based on a greedy algorithm is applied to obtain an approximate solution. Thus, the proposed tool can improve the visual appeal of the target object without changing the original image into an unacceptably edited image in reasonable computational time. For validation of the proposed tool, evaluations were conducted via a questionnaire survey and time measurement.

关键词： image-editing tool visual saliency map effect selection constrained optimization problem heuristics

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A computationally efficient model predictive control scheme for space debris rendezvous 21

A computationally efficient model predictive control scheme ...

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21st International-Federation-of-Automatic-Control (IFAC) Symposium on Automatic Control in Aerospace (ACA)

作者： Larsen, Alexander Korsfeldt Chen, Yutao Bruschetta, Mattia Carli, Ruggero Cenedese, Angelo Varagnolo, Damiano Felicetti, Leonard Lulea Univ Technol Kiruna Sweden Eindhoven Univ Technol Eindhoven Netherlands Univ Padua Padua Italy Norwegian Univ Sci & Technol Trondheim Norway Cranfield Univ Cranfield Beds England

We propose a non-linear model predictive scheme for planning fuel efficient maneuvers of small spacecrafts that shall rendezvous space debris. The paper addresses the specific issues of potential limited on-board computational capabilities and low-thrust actuators in the chasing spacecraft, and solves them by using a novel MatLab-based toolbox for real-time non-linear model predictive control (MPC) called MATMPC. This tool computes the MPC rendezvous maneuvering solution in a numerically efficient way, and this allows to greatly extend the prediction horizon length. This implies that the overall MPC scheme can compute solutions that account for the long time-scales that usually characterize the low-thrust rendezvous maneuvers. The so-developed controller is then tested in a realistic scenario that includes all the nearEarth environmental disturbances. We thus show, through numerical simulations, that this MPC method can successfully be used to perform a fuel-efficient rendezvous maneuver with an uncontrolled object, plus evaluate performance indexes such as mission duration, fuel consumption, and robustness against sensor and process noises. Copyright (C) 2019. The Authors. Published by Elsevier Ltd. All rights reserved.

关键词： Non Linear Model Predictive Control Non-cooperative Rendezvous Space Debris Removal Low-Thrust Maneuvers constrained optimization problem Real-time Control

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