严巡;王长权;袁肖肖;石立红;

• 1:长江大学石油工程学院
• 2:大港油田采油工艺研究院

摘要(Abstract)：

盐水中CO_2的溶解度参数对CO_2地质封存至关重要,通过实验方法获取溶解度数据耗时费力,因此,需要建立理论模型来进行预测,而神经网络由于能够关联复杂变量之间的情况而广受关注。BP神经网络是1种应用最广泛的前馈神经网络,利用实验数据建立1个三层结构的BP神经网络模型用于预测盐水中CO_2的溶解度,并对网络的结构参数进行优化设计,得到1种盐水中CO_2溶解度预测的BP神经网络模型。同时,利用修正后的亨利定律计算不同条件下的溶解度,并将实验数据、BP模型预测结果与亨利定律做对比,为确定盐水中CO_2的溶解度提供了1种新方法。

关键词(KeyWords)： 油气田开发工程;BP人工神经网络;CO2封存;溶解度;预测

Abstract:

Keywords:

基金项目(Foundation): 国家自然科学基金资助项目(51404037)

作者(Author): 严巡;王长权;袁肖肖;石立红;

Email:

DOI:

参考文献(References)：

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