ADAPTIVE INFORMATION AND MEASUREMENT SYSTEM FOR MONITORING PHYSICAL AND CHEMICAL PROCESS BEHAVIOR

The relevance of the research is caused by the need of profitability improving in oil and gas sector with automated control of petroleum-containing fluid separation, particularly, energy cost reduction without tank oil quality loss. The automated control can be built on the basis of mathematical mod...

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Main Authors: Alexey V. Tsavnin, Alexander A. Filipas, Alexander S. Belyaev, Nikita V. Rozhnev
Format: Article
Language:Russian
Published: Tomsk Polytechnic University 2020-09-01
Series:Известия Томского политехнического университета: Инжиниринг георесурсов
Subjects:
Online Access:http://izvestiya.tpu.ru/archive/article/view/2814/2308
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spelling doaj-4411732cebc644f29c50d9660969b1ad2021-01-21T06:05:22ZrusTomsk Polytechnic UniversityИзвестия Томского политехнического университета: Инжиниринг георесурсов2500-10192413-18302020-09-01331912212910.18799/24131830/2020/9/2814ADAPTIVE INFORMATION AND MEASUREMENT SYSTEM FOR MONITORING PHYSICAL AND CHEMICAL PROCESS BEHAVIORAlexey V. Tsavnin0Alexander A. Filipas1Alexander S. Belyaev2Nikita V. Rozhnev3National Research Tomsk Polytechnic UniversityNational Research Tomsk Polytechnic UniversityNational Research Tomsk Polytechnic UniversityNational Research Tomsk Polytechnic UniversityThe relevance of the research is caused by the need of profitability improving in oil and gas sector with automated control of petroleum-containing fluid separation, particularly, energy cost reduction without tank oil quality loss. The automated control can be built on the basis of mathematical models that can be obtained with natural experiment. The main aim of the research is to develop adaptive automated information and measurement system for experimental petroleum-containing fluid separation dynamics estimation with different water-in-oil emulsion layer stability and interbed diffusion for data collection for mathematical model development. Object: technological process of petroleum-containing fluid separation in the context of lab bench on the gravity type separation basis. Methods: natural experiment, computer vision, convolutional neural networks, machine learning, digital image segmentation problem, volume ration calculation, transient processes, physics and chemistry experiment automation. Results. The authors have developed an adaptive information and measurement system on computer vision and convolutional neural networks basis, which allows estimating petroleum-containing fluid separation dynamics with different water-in-oil emulsion layer stability and sharpness of layers borders. The basis of functioning of adaptive information measurement system is software, that allows performing experiment considering different qualitative and quantitative conditions. The paper considers the algorithm for discretization period with respect to reaction length. The system was tested on lab bench and layers volume ratio was calculated in real-time.http://izvestiya.tpu.ru/archive/article/view/2814/2308separatorpetroleum-containing fluidemulsioncomputer visionconvolutional neural networksadaptive measurement
collection DOAJ
language Russian
format Article
sources DOAJ
author Alexey V. Tsavnin
Alexander A. Filipas
Alexander S. Belyaev
Nikita V. Rozhnev
spellingShingle Alexey V. Tsavnin
Alexander A. Filipas
Alexander S. Belyaev
Nikita V. Rozhnev
ADAPTIVE INFORMATION AND MEASUREMENT SYSTEM FOR MONITORING PHYSICAL AND CHEMICAL PROCESS BEHAVIOR
Известия Томского политехнического университета: Инжиниринг георесурсов
separator
petroleum-containing fluid
emulsion
computer vision
convolutional neural networks
adaptive measurement
author_facet Alexey V. Tsavnin
Alexander A. Filipas
Alexander S. Belyaev
Nikita V. Rozhnev
author_sort Alexey V. Tsavnin
title ADAPTIVE INFORMATION AND MEASUREMENT SYSTEM FOR MONITORING PHYSICAL AND CHEMICAL PROCESS BEHAVIOR
title_short ADAPTIVE INFORMATION AND MEASUREMENT SYSTEM FOR MONITORING PHYSICAL AND CHEMICAL PROCESS BEHAVIOR
title_full ADAPTIVE INFORMATION AND MEASUREMENT SYSTEM FOR MONITORING PHYSICAL AND CHEMICAL PROCESS BEHAVIOR
title_fullStr ADAPTIVE INFORMATION AND MEASUREMENT SYSTEM FOR MONITORING PHYSICAL AND CHEMICAL PROCESS BEHAVIOR
title_full_unstemmed ADAPTIVE INFORMATION AND MEASUREMENT SYSTEM FOR MONITORING PHYSICAL AND CHEMICAL PROCESS BEHAVIOR
title_sort adaptive information and measurement system for monitoring physical and chemical process behavior
publisher Tomsk Polytechnic University
series Известия Томского политехнического университета: Инжиниринг георесурсов
issn 2500-1019
2413-1830
publishDate 2020-09-01
description The relevance of the research is caused by the need of profitability improving in oil and gas sector with automated control of petroleum-containing fluid separation, particularly, energy cost reduction without tank oil quality loss. The automated control can be built on the basis of mathematical models that can be obtained with natural experiment. The main aim of the research is to develop adaptive automated information and measurement system for experimental petroleum-containing fluid separation dynamics estimation with different water-in-oil emulsion layer stability and interbed diffusion for data collection for mathematical model development. Object: technological process of petroleum-containing fluid separation in the context of lab bench on the gravity type separation basis. Methods: natural experiment, computer vision, convolutional neural networks, machine learning, digital image segmentation problem, volume ration calculation, transient processes, physics and chemistry experiment automation. Results. The authors have developed an adaptive information and measurement system on computer vision and convolutional neural networks basis, which allows estimating petroleum-containing fluid separation dynamics with different water-in-oil emulsion layer stability and sharpness of layers borders. The basis of functioning of adaptive information measurement system is software, that allows performing experiment considering different qualitative and quantitative conditions. The paper considers the algorithm for discretization period with respect to reaction length. The system was tested on lab bench and layers volume ratio was calculated in real-time.
topic separator
petroleum-containing fluid
emulsion
computer vision
convolutional neural networks
adaptive measurement
url http://izvestiya.tpu.ru/archive/article/view/2814/2308
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