1,721,124 research outputs found
A unified metaheuristic and system-theoretic framework for petroleum reservoir management
Get PDFWith phenomenal rise in world population as well as robust economic growth in China, India and other emerging economies; the global demand for energy continues to grow in monumental proportions. Owing to its wide end-use capabilities, petroleum is without doubt, the world’s number one energy resource. The present demand for oil and credible future forecasts – which point to the fact that the demand is expected to increase in the coming decades – make it imperative that the E&P industry must device means to improve the present low recovery factor of hydrocarbon reservoirs. Efficiently tailored model-based optimization, estimation and control techniques within the ambit of a closed-loop reservoir management framework can play a significant role in achieving this objective.
In this thesis, some fundamental reservoir engineering problems such as field development planning, production scheduling and control are formulated into different optimization problems. In this regard, field development optimization identifies the well placements that best maximizes hydrocarbon recovery, while production optimization identifies reservoir well-settings that maximizes total oil recovery or asset value, and finally, the implementation of a predictive controller algorithm which computes corrected well controls that minimizes the difference between actual outputs and simulated (or optimal) reference trajectory. We employ either deterministic or metaheuristic optimization algorithms, such that the choice of algorithm is purely based on the peculiarity of the underlying optimization problem.
Altogether, we present a unified metaheuristic and system-theoretic framework for petroleum reservoir management. The proposed framework is essentially a closed-loop reservoir management approach with four key elements, namely: a new metaheuristic technique for field development optimization, a gradient-based adjoint formulation for well rates control, an effective predictive control strategy for tracking the gradient-based optimal production trajectory and an efficient model-updating (or history matching) – where well production data are used to systematically recalibrate reservoir model parameters in order to minimize the mismatch between actual and simulated measurements.
Central to all of these problems is the use of white-box reservoir models which are employed in the well placement optimization and production settings optimization. However, a simple data-driven black-box model which results from the linearization of an identified nonlinear model is employed in the predictive controller algorithm. The benefits and efficiency of the approach in our work is demonstrated through the maximization of the NPV of waterflooded reservoir models that are subject to production and geological uncertainty. Our procedure provides an improvement in the NPV, and importantly, the predictive control algorithm ensures that this improved NPV are attainable as nearly as possible in practice
Metaheuristic and exact approaches for cost optimization in multi-echelon multimodal transportation network
No full textThis study develops a framework for a multimodal transportation system comprising two different modes of transportation—airways and roadways within a multi-echelon supply chain network in B2C e-commerce platforms. In this study, an optimization model based on mixed-integer quadratic programming was formulated, the objective of which is to minimize the overall transportation cost for B2C e-commerce supply chain networks. The metaheuristic technique incorporating two varied approaches—exact optimization and a genetic algorithm—was employed to provide the solution for this proposed optimization model of multimodal transportation system. This metaheuristic technique-based optimization model was tested on simulated datasets created to develop and analyze different case scenarios for the stated multimodal transportation problem. The comparative analysis of these two solution approaches is provided from the perspective of experimental performance as well as theoretical consideration. The findings of study can be applied to multi-echelon multimodal transportation networks in real practices targeting overall cost reduction and profit maximization of the logistic services for B2C e-commerce platforms
Using Opinionated-Objective Terms to Improve Lexicon Based Sentiment Analysis
Get PDFSentiment analysis (SA) has received huge attention to understand customer perception, especially in the movie review (IMDB) domain. This is due to the availability of large, labelled dataset. This has enhanced the use and development of machine learning (ML) algorithms ranging from the traditional machine learning algorithms, deep learning algorithms to large language models. The ML models have shown great performances. However, the application of ML methods for SA is limited in service industry like banking, due to the unavailability of large training dataset. Thus, we consider the use of lexicon-based sentiment analysis appropriate. We employ 346,000 Nigeria bank customers’ tweets to develop our corpus and thus, propose SentiLeye, a novel lexicon-based algorithm for sentiment analysis. Our algorithm incorporates corpus-based approach and external lexical resources for sentiment lexicon generation of Pidgin English language terms (anon-English under resourced language). Moreover, we demonstrate the use of verbs and adverbs that express opinion on service experience to improve the performance of lexicon-based sentiment analysis. Results show that SentiLeye outperforms popular off-the-shelf sentiment lexicons with macro F1 score of 76%. We conclude that results from domain specific algorithms such as SentiLeye evidence that general purpose lexicons cannot replace them
Mathematical driven model for closed-loop supply chain network design
No full textThe closed-loop supply chain (CLSC) has gained popularity as a practical way to improve sustainability and resource efficiency in various industries. Unlike a linear supply chain, a CLSC adopts reverse logistics to recover, recycle, and reuse items or their components. This study creates a mathematical model for a reliable and effective CLSC model that integrates forward and reverse logistics operations to reduce costs, boost profits, and reduce environmental impact. A metaheuristic approach (Genetic Algorithm) is used to solve the model. The experimental findings show that the suggested strategy contributes in enhancing CLSC performance
System-Information Models of Digital Twins
No full textTo represent the production process, a digital twin model is used, which takes into account the real parameters of technological processes. Management of product life cycle processes is implemented on the basis of a digital twin of the Unified System Information Space (USIS), built on system-information models of processes and systems. It is used as a platform for management using software products Product Lifecycle System Information (PLSI), which are system-compatible with technological system software Product Lifecycle Management (PLM). The digital twin describes the functional dependence of the expanded uncertainty of the normalized information space on the values of the nominal parameters for a specific production technology using a software product (USIS + PLSI + PLM). This allows you to use software products for designing CAD, CAM, and CAE systems when solving production problems on one information platform. Using a system-information approach to modeling digital twins of production allows you to effectively solve problems related to the analysis, synthesis, management, and forecasting of production.peerReviewe
Automated detection of fully and partially riped mango by machine vision
No full textMango quality assessment is important in meeting market requirements. The quality of the mango can be judge by its length, thickness, width, area, etc. In this paper on the basis of simple mathematical calculations different parameters of a number of mango are calculated. The present paper focused on the classification of mangoes using morphological Operations. A video containing mangoes hanging from the trees is made and used as the input to this algorithm. The video is read frame by frame and the within one frame morphological operations, watershed algorithm and analysis and segmentation are applied. The mango types used in this study were Ripe Mango, Unripe Mango. In this paper the application of neural network is used for assessment of mango. The contours of ripe and unripe mangoes have been extracted, precisely normalised and then used as input data for the neural network. The network optimisation has been carried out and then the results have been analysed in the context of response values worked out by the output neurons.</p
Three Echelon Supply Chain Design with Supplier Evaluation
No full textAn effective supply chain management (SCM) facilitates companies to react to changing demand by swiftly communicating their needs to the supplier. Optimizing a supply chain (SC) performance is a key factor for success in long term SC relationships. Substantial information such as price, delivery time percentage and acceptance percentage are discussed in the process. Imprecise demand as one of the factors is added in the same process that fuzzifies coordination between buyer and supplier. The paper considers non-deterministic conditions in the environment of business, coordination in procurement and distribution in a supplier selection problem and a fuzzy model with two objectives is defined. The proposed model is a “fuzzy bi-objective mixed integer nonlinear” problem. To process the solution the fuzzy model is converted into crisp and further fuzzy goal programming approach is employed. The model is validated with the help of a real case problem.</p
Going Beyond Counting First Authors in Author Co-citation Analysis
Get PDFThe present study examines one of the fundamental aspects of author co-citation analysis (ACA) - the way co-citation
counts are defined. Co-citation counting provides the data on which all subsequent statistical analyses and mappings
are based, and we compare ACA results based on two different types of co-citation counting - the traditional type that
only counts the first one among a cited work's authors on the one hand and a non-traditional type that takes into
account the first 5 authors of a cited work on the other hand. Results indicate that the picture produced through this non-traditional author co-citation counting contains more coherent author groups and is therefore considerably clearer. However, this picture represents fewer specialties in the research field being studied than that produced through the traditional first-author co-citation counting when the same number of top-ranked authors is selected and analyzed. Reasons for these effects are discussed
Variations on the Author
Get PDF“Variations on the Author” discusses two of Eduardo Coutinho’s recent films (Um Dia na Vida, from 2010, and Últimas Conversas, posthumously released in 2015) and their contribution to the general question of documentary authorship. The director’s filmography is characterized by a consistent yet self-effacing form of authorial self-inscription: Coutinho often features as an interviewer that rather than express opinions propels discourses; an interviewer that is good at listening. This mode of self-inscription characterizes him as an author who is not expressive but who is nonetheless markedly present on the screen. In Um Dia na Vida, however, Coutinho is completely absent form the image, while Últimas Conversas, on the contrary, includes a confessional prologue that moves the director from the margins to the center of his films. This article examines the ways in which these works stand out in the filmography of a director who offers new insights into the notion of cinematic authorship
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