| 考虑温度因素的储层敏感性预测方法 |
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| 引用本文： | 李怀科,鄢捷年,耿铁.考虑温度因素的储层敏感性预测方法[J].钻井液与完井液,2011,28(1). |
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| 作者姓名： | 李怀科 鄢捷年 耿铁 |
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| 作者单位： | 1. 中海油田服务股份有限公司油田化学事业部,河北燕郊
2. 中国石油大学石油工程教育部重点实验室,北京昌平 |
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| 摘 要： | 通过研究温度对储层黏土矿物、孔隙度以及渗透率的影响规律,发现温度对储层孔隙度的影响较小,渗透率随温度的变化与孔隙度之间存在一定关系.在BP神经网络模型的基础上,将温度作为一个新的神经元引入到输入层中,通过对网络隐层数的优化设计和误差分析,提出了考虑温度影响的储层敏感性预测新方法,编写了相应的计算程序实现了敏感性预测的智能化.通过与室内实验结果对比,该方法精度大于83%,且受人为因素影响小,具有较高的预测精度,为高温条件下储层敏感性预测提供了一种新的手段.
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| 关 键 词： | 储层敏感性 防止地层损害 BP神经网络 温度 |
Study on Reservoir Sensitivity Prediction Method Considering the Effect of Temperature |
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| LI Huaike,YAN Jienian,GENG Tie.Study on Reservoir Sensitivity Prediction Method Considering the Effect of Temperature[J].Drilling Fluid & Completion Fluid,2011,28(1). |
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| Authors: | LI Huaike YAN Jienian GENG Tie |
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| Affiliation: | LI Huaike,YAN Jienian,GENG Tie Oilfield Chemicals R & D Center,China Oilfield Services Limited,Yanjiao,Hebei 065201,China |
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| Abstract: | The effect of temperature on clay mineral,porosity as well as permeability was studied in this paper,and the results showed that the temperature had little influence on porosity and permeability,also a relationship between alternation of permeability with time and porosity was obtained.Based on BP neural network of reservoir sensitivity,the temperature was introduced in input-layer as a new nerve cell.A new method was proposed to predict reservoir sensitivity considering the effect of temperature according ... |
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| Keywords: | Temperature BP neural network Reservoir sensitivity Prediction Reservoir protection |
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