Experimental study and artificial neural network simulation of the wettability of tight gas sandstone formation
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- 作者：Yayun Zhanga ; Mian Chena ; Yan Jina ; jinyancup@163.com" class="auth_mail" title="E-mail the corresponding author ; Yunhu Lua ; Chuan Lianga ; Wenda Lia ; Yanchen Wangb ; Peng Tana ; Daiwu Zoua
- 关键词：Artificial neural network simulation ; Nonlinear response relationship ; Predict ; Tight gas sandstone ; Wettability
- 刊名：Journal of Natural Gas Science and Engineering
- 出版年：2016
- 出版时间：August 2016
- 年：2016
- 卷：34
- 期：Complete
- 页码：387-400
- 全文大小：2580 K
文摘
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The effects of rock mineral composition and fluid characteristics on wettability are studied through experiment.
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A quantitative characterization model for wettability is established to fit the nonlinear response.
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Rock mineral composition and fluid characteristics are considered in the GRNN model.
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The GRNN model can be utilized to predict the wettability of rocks and optimize fluid performance.