原油高温结垢速率测定和预测模型研究进展

doi:10.11885/j.issn.1674-5086.2013.11.21.04

摘要/Abstract

摘要：

综述了原油高温结垢的室内测定和预测模型的研究现状，重点回顾分析了预测模型的发展历程。室内实验和
模型预测是研究原油高温结垢速率的重要方法。常用室内结垢实验装置分为搅拌式和回路式，通过实验可快速获取
大量有效数据，但是实验数据往往存在缺陷，无法直接应用指导现场换热器防垢。结垢预测模型需要反映原油高温结
垢的化学反应本质，体现原油物性、温度、流速等重要因素以及不同过程对结垢速率的影响。目前结垢预测模型，包括
已经取得巨大成果的临界模型，大多属于半经验公式，其精度和适用性始终有限。更精确的模型必须基于对结垢机理
的进一步研究。由于能够成功描述非线性系统特征，人工神经网络模型也将是另一种十分有前景的预测技术。

关键词: 原油结垢, 结垢速率, 实验, 预测模型, 人工神经网络

Abstract:

A comprehensive review in aspect of laboratory measurement and prediction models is conducted in this paper，
and more focus is put on the analysis and development of prediction models. Both experiments and prediction models play
significant role in determining crude oil fouling rate under high temperature. As a quick access to vast amounts of valid data，
laboratory experiments，either batch stirred or recirculation test apparatus cannot directly guide fouling prevention in production.
Proper models must reflect the chemical nature of fouling，the significance of influencing factors such as physical properties，
temperature，flow rate and other different process. Although the threshold models have gained great achievements in field，
which are semi-empirical formula，the precision and applicability of most prediction models at present are limited. More
accurate models must be based on further studies on fouling mechanism. Meanwhile，according to its successful application to
description of the characters of nonlinear systems，the ANN（artificial neural network）will be a new promising prediction skill.

Key words: crude oil fouling, fouling rate, experiments, prediction models, ANN

中图分类号:

TE624.2

袁宗明1，王勇1 *，谢英1，王大鹏2. 原油高温结垢速率测定和预测模型研究进展[J]. 西南石油大学学报(自然科学版), DOI: 10.11885/j.issn.1674-5086.2013.11.21.04.

YUAN Zongming1, WANG Yong1*, XIE Ying1, WANG Dapeng2. Research Advances in Measurement and Prediction Models of Crude#br# Oil Fouling Rate Under High Temperature[J]. 西南石油大学学报(自然科学版), DOI: 10.11885/j.issn.1674-5086.2013.11.21.04.

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