1. 中国石油大学(北京), 北京 102249西南石油大学,四川,成都,610500
2. 西南石油大学,四川 成都 610500中国石油川庆钻探工程有限公司长庆井下技术作业公司,陕西,西安,710018
3. 中国石油川庆钻探工程有限公司长庆井下技术作业公司,陕西 西安710018中国石油大港油田公司勘探开发研究院,天津,300280
4. 中国石油大港油田公司勘探开发研究院,天津,300280
[ "王佳营(1993—),女,博士,工程师,从事提高油气采收率研究。地址:北京市昌平区中国石油大学(北京),邮政编码:102249。E-mail:Wangjiayingswpu@163.com" ]
纸质出版:2022
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王佳营, 赵仁保, 李姝璇, 等. 一种新型泡点压力预测模型的建立和应用——以塔里木油区为例[J]. 油气藏评价与开发, 2022,12(6):927-934.
WANG Jiaying, ZHAO Renbao, LI Shuxuan, et al. A new model to predict bubble point pressure: Its establishment and application in Tarim Oildom[J]. Petroleum Reservoir Evaluation and Development, 2022, 12(6): 927-934.
王佳营, 赵仁保, 李姝璇, 等. 一种新型泡点压力预测模型的建立和应用——以塔里木油区为例[J]. 油气藏评价与开发, 2022,12(6):927-934. DOI: 10.13809/j.cnki.cn32-1825/te.2022.06.012.
WANG Jiaying, ZHAO Renbao, LI Shuxuan, et al. A new model to predict bubble point pressure: Its establishment and application in Tarim Oildom[J]. Petroleum Reservoir Evaluation and Development, 2022, 12(6): 927-934. DOI: 10.13809/j.cnki.cn32-1825/te.2022.06.012.
地层原油泡点压力(
p
b
)是确定油藏类型、制定油藏开发方案和进行油藏工程计算必不可少的重要参数,也是计算油田储量及选择油井工作制度的基础。为了方便、快速预测油藏流体泡点压力值,在大量PVT(高压物性)实验测试数据基础上,对深层复杂油藏流体确定泡点压力值的经验模型进行了描述,分析并确定了影响塔里木油区深层复杂油气藏地层原油泡点压力值的主控因素,建立了一种快速预测油藏流体泡点压力的模型。基于塔里木油区132组样品数据,利用数模软件进行回归分析,得出了泡点压力新模型的10个影响因素和相关参数的取值,并通过对后续10支地层流体样品的补充PVT实验数据进行实例验证。对比已有经验公式,该预测模型具有更好的预测效果。
Bubble point pressure(
p
b
) is an essential parameter for determining reservoir type
formulating reservoir development scheme and reservoir engineering calculation. It is also the basis for calculating oilfield reserves and selecting oil well working system. In order to conveniently and rapidly predict the bubble point pressure value of reservoir fluid
the empirical model for determining the bubble point pressure value of deep complex reservoir fluid is described based on a large number of PVT high-pressure physical property test data. And the main controlling factors affecting the bubble point pressure of oil in deep complex reservoir of Tarim oildom are analyzed and determined. Meanwhile
A model for rapid prediction o
f reservoir fluid bubble point pressure is established. Based on 132 groups of sample data in Tarim oil area
the regression analysis is carried out by using digital simulation software
and the values of 10 influencing factors and related parameters of the new bubble point pressure model are obtained. It is verified by the supplementary PVT experimental data of 10 subsequent formation fluid samples. Compared with the existing empirical formula
the prediction model has better prediction effect.
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