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| 基于逾渗模型的泥页岩导电机理模拟 | |
| 引用本文： | 赵军, 代新雲, 卢一凡, 唐深华. 2017. 基于逾渗模型的泥页岩导电机理模拟. 地球物理学报, 60(5): 2020-2028, doi: 10.6038/cjg20170533 |
| 作者姓名： | 赵军 代新雲 卢一凡 唐深华 |
| 作者单位： | 1. 西南石油大学地球科学与技术学院, 成都 610500; 2. 贵州天然气能源投资股份有限公司, 贵阳 550000 |
| 基金项目： | 国家自然科学基金项目“页岩气储层微观结构及岩石物理响应数值模拟研究”（41202110）资助. |
| 摘 要： |  泥页岩储层储集空间以纳米/微米级的微孔隙和微裂缝为主，结构复杂，加之干酪根和黏土矿物含量较高，并含有一定量的黄铁矿等导电矿物，造成储层导电机理异于常规储层，岩电实验I-Sw曲线呈现非线性特征，阿尔奇公式等传统评价模型适用性较差.针对上述问题，根据实际岩心实验资料，结合随机算法建立三维逾渗模型并通过数值模拟和超松弛迭代法进行求解，分析泥页岩储层非阿尔奇性产生原因以及泥页岩储层电性的影响因素及规律.模拟结果显示，岩石孔隙拓扑结构和形状尺寸、矿物组成以及地层水电阻率等因素均对泥页岩储层电阻率产生不同程度的影响，通过改变上述因素的设定值，可以建立储层电阻率与各因素的单相关关系，并据此建立修正模型，实现储层含水饱和度的计算.该模型在四川某页岩气产区取得了较好的效果，具有良好的应用前景，为利用逾渗模型模拟方法解决油田勘探开发中的复杂问题提供了新思路. |
| 关 键 词： | 逾渗 网络模型 页岩气 导电机理 数值模拟 |
| 收稿时间： | 2016-03-01 |
| 修稿时间： | 2017-03-25 |
Shale reservoir conductive mechanism simulation based on percolation network |
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| ZHAO Jun, DAI Xin-Yun, LU Yi-Fan, TANG Shen-Hua. 2017. Shale reservoir conductive mechanism simulation based on percolation network. Chinese Journal of Geophysics (in Chinese), 60(5): 2020-2028, doi: 10.6038/cjg20170533 | |
| Authors: | ZHAO Jun DAI Xin-Yun LU Yi-Fan TANG Shen-Hua |
| Affiliation: | 1. School of Geoscience and Technology, Southwest Petroleum University, Chengdu 610500, China; 2. Guizhou Natural Gas Energy Investment Co.Ltd, Guiyang 550000, China |
| Abstract: | The shale gas reservoir storage space mainly includes micro pores and cracks of micron and nano scale. Owing to the complex pore network, as well as high content of kerogen and clay minerals in shale matrix and existence of conductive minerals, especially pyrite, the shale reservoir conductive mechanism is quite different from that of conventional reservoir, and the I-Sw curve obtained by core electricity experiment is non-linear which makes traditional evaluation models such as Archie's law not suitable. Aiming at these issues, according to actual core experiment and CT scan data, a three dimensional percolation network is established with randomized algorithm and node voltage and current calculated through over-relaxation iteration algorithm. With this network, the reasons for non-Archie property and influence factors of shale reservoir is analyzed. Simulation results show that pore structure, shape and size, mineral composition and formation water resistivity have different effects on the reservoir resistivity. By changing the setting value, single-correlation between the reservoir resistivity and these factors can be built, and percolation correction model is also developed to calculate shale reservoir water saturation. The method has achieved a good effect in a certain shale gas field in Sichuan, China, which presents a good application prospect and provides a new thought on solving complex problems in shale gas field exploration and development with network simulation methods. |
| Keywords: | Percolation Network simulation Shale gas Conductive mechanism Numerical simulation |
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