优化随机向量函数链接网络预测中国塔河油田产油量

IF 1.8 4区工程技术 Q4 ENERGY & FUELS

Oil & Gas Science and Technology – Revue d’IFP Energies nouvelles 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

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引用次数: 11

摘要

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

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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来源期刊

Oil & Gas Science and Technology – Revue d’IFP Energies nouvelles 工程技术-工程：化工

CiteScore

2.70

自引率

0.00%

发文量

审稿时长

2.7 months

期刊介绍： OGST - Revue d''IFP Energies nouvelles is a journal concerning all disciplines and fields relevant to exploration, production, refining, petrochemicals, and the use and economics of petroleum, natural gas, and other sources of energy, in particular alternative energies with in view of the energy transition. OGST - Revue d''IFP Energies nouvelles has an Editorial Committee made up of 15 leading European personalities from universities and from industry, and is indexed in the major international bibliographical databases. The journal publishes review articles, in English or in French, and topical issues, giving an overview of the contributions of complementary disciplines in tackling contemporary problems. Each article includes a detailed abstract in English. However, a French translation of the summaries can be provided to readers on request. Summaries of all papers published in the revue from 1974 can be consulted on this site. Over 1 000 papers that have been published since 1997 are freely available in full text form (as pdf files). Currently, over 10 000 downloads are recorded per month. Researchers in the above fields are invited to submit an article. Rigorous selection of the articles is ensured by a review process that involves IFPEN and external experts as well as the members of the editorial committee. It is preferable to submit the articles in English, either as independent papers or in association with one of the upcoming topical issues.