Digital model of surface equipment within the Digital Oilfield Framework

DOI

10.2991/acaai-18.2018.37How to use a DOI?

Keywords

Digital oilfield, energy flow, reservoir modeling, neural networks

Abstract

In the paper we describe a new approach to the construction of a model, applied for a complex for the extraction and processing of hydrocarbon raw materials. The basis of the model is a group of independently functioning components, organized on the basis of modern Arificial Intelligence methods, including various neural network solutions. The integration of the modules is carried out by introducing into the model of the digital oilfield the concept of energy flows transmitted between the simulated components. We propose to consider the joint transfer and transformation of several independent types of energy, including electrical energy, fluid energy, and also mass-volume transfer values by each independent block. While applying components of neural network structures, the values of the input and output energy fluxes must complement the vector quantities characterizing the internal parameters of the model.

Copyright

© 2018, the Authors. Published by Atlantis Press.

Open Access

This is an open access article distributed under the CC BY-NC license (http://creativecommons.org/licenses/by-nc/4.0/).

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TY  - CONF
AU  - S. Iakov Korovin
AU  - Maxim G. Tkachenko
PY  - 2018/03
DA  - 2018/03
TI  - Digital model of surface equipment within the Digital Oilfield Framework
BT  - Proceedings of the 2018 International Conference on Advanced Control, Automation and Artificial Intelligence (ACAAI 2018)
PB  - Atlantis Press
SP  - 159
EP  - 162
SN  - 1951-6851
UR  - https://doi.org/10.2991/acaai-18.2018.37
DO  - 10.2991/acaai-18.2018.37
ID  - Korovin2018/03
ER  -