Optimized Random Vector Functional Link network to predict oil production from Tahe oil field in China

IF 16.4 1区化学 Q1 CHEMISTRY, MULTIDISCIPLINARY

Accounts of Chemical Research Pub Date : 2020-12-17 DOI:10.2516/ogst/2020081

Ahmed Alalimi, Lin Pan, M. A. Al-qaness, A. Ewees, Xiao Wang, M. A. Abd Elaziz

引用次数: 11

Abstract

In China, Tahe Triassic oil field block 9 reservoir was discovered in 2002 by drilling wells S95 and S100. The distribution of the reservoir sand body is not clear. Therefore, it is necessary to study and to predict oil production from this oil field. In this study, we propose an improved Random Vector Functional Link (RVFL) network to predict oil production from Tahe oil field in China. The Spherical Search Optimizer (SSO) is applied to optimize the RVFL and to enhance its performance, where SSO works as a local search method that improved the parameters of the RVFL. We used a historical dataset of this oil field from 2002 to 2014 collected by a local partner. Our proposed model, called SSO-RVFL, has been evaluated with extensive comparisons to several optimization methods. The outcomes showed that, SSO-RVFL achieved accurate predictions and the SSO outperformed several optimization methods.

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优化随机向量函数链接网络预测中国塔河油田产油量

2002年，通过S95井和S100井发现了中国塔河三叠系油田9区块油藏。储层砂体分布不清楚。因此，有必要对该油田的产油量进行研究和预测。本文提出了一种改进的随机向量函数链(RVFL)网络来预测中国塔河油田的产量。采用球面搜索优化器(Spherical Search Optimizer, SSO)优化RVFL并提高其性能，SSO作为一种局部搜索方法，改善了RVFL的参数。我们使用了当地合作伙伴收集的该油田2002年至2014年的历史数据集。我们提出的模型，称为SSO-RVFL，已经与几种优化方法进行了广泛的比较。结果表明，SSO- rvfl实现了准确的预测，并且SSO优于几种优化方法。

本文章由计算机程序翻译，如有差异，请以英文原文为准。

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来源期刊

Accounts of Chemical Research 化学-化学综合

CiteScore

31.40

自引率

1.10%

发文量

312

审稿时长

2 months

期刊介绍： Accounts of Chemical Research presents short, concise and critical articles offering easy-to-read overviews of basic research and applications in all areas of chemistry and biochemistry. These short reviews focus on research from the author’s own laboratory and are designed to teach the reader about a research project. In addition, Accounts of Chemical Research publishes commentaries that give an informed opinion on a current research problem. Special Issues online are devoted to a single topic of unusual activity and significance. Accounts of Chemical Research replaces the traditional article abstract with an article "Conspectus." These entries synopsize the research affording the reader a closer look at the content and significance of an article. Through this provision of a more detailed description of the article contents, the Conspectus enhances the article's discoverability by search engines and the exposure for the research.