| 用积分法求取岩石孔隙结构特征值 |
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| 引用本文： | 李 闽,陶正武,刘全稳,吴泽民,李 涛,肖文联,亢 鞠.用积分法求取岩石孔隙结构特征值[J].岩土力学,2015,36(5):1352-1356. |
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| 作者姓名： | 李 闽 陶正武 刘全稳 吴泽民 李 涛 肖文联 亢 鞠 |
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| 作者单位： | 1.西南石油大学 油气藏地质及开发工程国家重点实验室，四川 成都 610500；2.广东石油化工学院 石油工程学院，广东 茂名 525000； 3.中石油长庆油田 超低渗第四项目部，甘肃 庆阳 745000；4.中石化河南油田分公司 勘探开发研究院，河南 南阳 473132； 5.中石油塔里木油田分公司 天然气事业部，新疆 库尔勒 841000 |
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| 基金项目： | 国家自然科学基金项目（No. 41274114，No.51274169）；西南石油大学科研启航计划项目（No. 2014QHZ002）。 |
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| 摘 要： | 针对图解法求取孔隙结构特征值使用条件严格，同时误差较大，而矩法饱和度范围又受限于试验。采用积分法求取特征值，即对孔隙半径进行积分求取特征值。积分法必须先获取孔隙半径数学表达式，即毛管压力数学模型。对毛管压力数学模型进行了探究，在双对数坐标系下推导并建立了毛管压力幂函数模型，采用最小二乘法求取模型参数，并通过对比Sami论文数据验证了推导的模型。深入分析矩法与积分法的联系可知，代入孔隙半径数学表达式即可用积分法求取岩石孔隙结构特征值。最后，对3种方法求取结果进行分析讨论，得出积分法算法严谨，更加接近真实值。这一研究加深了对岩石微观孔隙结构认识。
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| 关 键 词： | 孔隙结构特征值 毛管压力 幂函数模型 最小二乘法 |
| 收稿时间： | 2014-06-17 |
An integral method for calculating pore structure eigenvalue of rock |
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| LI Min,TAO Zheng-wu,LIU Quan-wen,WU Ze-min,LI Tao,XIAO Wen-lian,KANG Ju.An integral method for calculating pore structure eigenvalue of rock[J].Rock and Soil Mechanics,2015,36(5):1352-1356. |
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| Authors: | LI Min TAO Zheng-wu LIU Quan-wen WU Ze-min LI Tao XIAO Wen-lian KANG Ju |
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| Abstract: | Due to the limitations of both the graphic method and the rectangular method in determining the pore structure eigenvalues of rock, an integral method is proposed, in which the pore radius is integrated to determine the eigenvalues. In applying the integral method, the pore radius is first determined through a capillary pressure model. Then a capillary pressure power function is derived and presented in the double logarithmic coordinate system, and the model parameters are acquired using the least square method. The proposed model is validated through comparing the calculations with the data provided in Sami’s paper. A connection between rectangular method and integral method is identified, showing that the pore structure eigenvalue can be calculated using the integral method. Finally, comparison of the proposed method with other two methods indicates that the results calculated by the integral method are closer to the real values. This study can help understand the characteristics of rock micro-pore structure. |
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| Keywords: | pore structure eigenvalue capillary pressure power function model least square method |
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