Application of the closed loop industrial internet of things (IIoT)-based control system in enhancing the oil recovery factor and the oil production

IF 1.7 Q3 COMPUTER SCIENCE, INFORMATION SYSTEMS IET Cyber-Physical Systems: Theory and Applications Pub Date : 2023-07-08 DOI:10.1049/cps2.12068
Hossein Malekpour Naghneh, Maryamparisa Amani, Alireza Farhadi, Mohammad Taghi Isaai
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Abstract

A non-linear large scale stochastic optimisation model for enhancing the oil production and the recovery factor of the offshore oil reservoirs is proposed. The model aims at minimising the miss-match between mathematical model and the actual dynamic behaviour of the reservoir and the exploitation time, while maximising the oil production and the recovery factor. The model involves the three dimension (3D) oil reservoirs equipped with a few vertical injection and production wells. The limited number of wells is one of the major features of the common oil reservoirs in the middle-east region. The proposed model consists of the primarily mathematical model of the 3D reservoir, a model update algorithm and a large scale constrained non-linear optimisation algorithm. The input to this model is the daily production rate of the oil, natural gas and water produced from the oil reservoir and the output is the optimal injection rate to be injected to the injection wells in order to maximise the oil production and the recovery factor. In order to evaluate the performance of this model, the authors apply this model on part of one of the Iran's offshore oil reservoirs and study the performance improvement due to the proposed model and compare its performance with the performance of the available Improved Oil Recovery (IOR) technique. It is illustrated that the proposed model can increase the oil production from the reservoir up to 47.96% and reduce the exploitation period up to 66.66% compared with those of the available technique.

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基于工业物联网 (IIoT) 的闭环控制系统在提高采油率和石油产量中的应用
为提高海上油藏的石油产量和采收率,提出了一种非线性大规模随机优化模型。该模型旨在最大限度地减少数学模型与油藏实际动态行为和开采时间之间的不匹配,同时最大限度地提高石油产量和采收率。该模型涉及配备少量垂直注入井和生产井的三维(3D)油藏。油井数量有限是中东地区常见油藏的主要特征之一。所提出的模型主要包括三维油藏数学模型、模型更新算法和大规模约束非线性优化算法。该模型的输入是油藏的石油、天然气和水的日产量,输出是注入井的最佳注入率,以最大限度地提高石油产量和采收率。为了评估该模型的性能,作者将该模型应用于伊朗一个近海油藏的部分区域,研究了所提模型带来的性能改进,并将其性能与现有的提高石油采收率(IOR)技术的性能进行了比较。结果表明,与现有技术相比,建议的模型可将油藏的石油产量提高 47.96%,将开采期缩短 66.66%。
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来源期刊
IET Cyber-Physical Systems: Theory and Applications
IET Cyber-Physical Systems: Theory and Applications Computer Science-Computer Networks and Communications
CiteScore
5.40
自引率
6.70%
发文量
17
审稿时长
19 weeks
期刊最新文献
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