Open AccessBased on the Optimal Learning Algorithm of Vortex Search, the Prediction of Oil Field Development Index is Studied
Author(s) -
Tian Jin
Publication year - 2021
Publication title -
journal of physics. conference series
Language(s) - English
Resource type - Journals
SCImago Journal Rank - 0.21
H-Index - 85
eISSN - 1742-6596
pISSN - 1742-6588
DOI - 10.1088/1742-6596/1881/3/032095
Subject(s) - field (mathematics) , oil field , index (typography) , computer science , algorithm , vortex , stability (learning theory) , petroleum industry , petroleum engineering , industrial engineering , artificial intelligence , environmental science , engineering , machine learning , mathematics , meteorology , physics , environmental engineering , world wide web , pure mathematics
Nowadays, with the development of the times, many times we will use high-tech to enrich and facilitate our lives, and as the backbone of our energy system - the oil industry, is no exception. Especially in the current oil field oil storage is insufficient, but also to strictly control oil exploration in the field to ensure the stability of the entire national system. Therefore, in order to strictly control the development forecast of oil fields, this paper uses the optimization learning algorithm based on vortex search to control this. In this paper, with the support of existing technology, sandbox simulation and eddy current algorithm are used to model the future oil field development without disclosing oil field information and actual reserves. The experimental results show that the selection of a suitable algorithm can predict the development index of oil field within a certain range, and the general error rate is not more than 5%.