涪陵地区页岩总孔隙度测井预测

doi:10.7623/syxb201705006

石油学报 ›› 2017, Vol. 38 ›› Issue (5): 533-543.DOI: 10.7623/syxb201705006

涪陵地区页岩总孔隙度测井预测

徐壮¹, 石万忠^1,2, 翟刚毅³, 包书景³, 彭女佳¹, 张晓明¹, 王超¹, 徐清海¹, 王任¹

1. 中国地质大学资源学院湖北武汉 430074;
2. 构造和油气资源教育部重点实验室湖北武汉 430074;
3. 中国地质调查局油气资源调查中心北京 100029

收稿日期:2016-12-05 修回日期:2017-03-18 出版日期:2017-05-25 发布日期:2017-06-07
通讯作者: 石万忠,男,1973年1月生,1996年获中国地质大学(武汉)学士学位,2006年获中国地质大学(武汉)博士学位,现为中国地质大学(武汉)教授,主要从事层序地层,成藏动力学及页岩气研究。Email:shiwz@cug.edu.cn
作者简介:徐壮,男,1989年10月生,2013年获中国石油大学(华东)学士学位,现为中国地质大学(武汉)博士研究生,主要从事页岩气储层评价研究。Email:xuzhuang@cug.edu.cn
基金资助:
国家重大油气专项子课题"页岩气区域选区评价方法研究"（2016ZX05034-002-003）、国家基础地质调查项目"南方页岩气综合评价参数优选及地球物理表征方法"（12120114055801）、111引智项目"沉积盆地动力学与油气富集机理"（B14031）及国家自然科学基金"页岩气储层总孔隙度的定量化表征及预测"（No.41672134）资助。

Well logging prediction for total porosity of shale in Fuling area

Xu Zhuang¹, Shi Wanzhong^1,2, Zhai Gangyi³, Bao Shujing³, Peng Nüjia¹, Zhang Xiaoming¹, Wang Chao¹, Xu Qinghai¹, Wang Ren¹

1. Faculty of Earth Resources, China University of Geosciences, Hubei Wuhan 430074, China;
2. MOE Key Laboratory of Tectonics and Petroleum Resources, Hubei Wuhan 430074, China;
3. Oil and Gas Survey Center, China Geological Survey, Beijing 100029, China

Received:2016-12-05 Revised:2017-03-18 Online:2017-05-25 Published:2017-06-07

摘要/Abstract

摘要：

页岩孔隙度是决定页岩储层含气性的关键因素，对页岩孔隙度进行定量化表征是实现利用地震资料进行孔隙度预测的前提条件，也是开展页岩气评价的基础。涪陵地区是中国页岩气勘探与开发的重点区块，以涪陵地区测井、测试资料为基础，探讨利用测井资料预测孔隙度的方法。基于研究区测试资料和测井资料，建立起孔隙度的测井识别及其响应模型，研究区孔隙度与声波时差AC具有很好的相关性，相关系数达到83.4%，以此确定了声波时差作为孔隙度的地球物理响应参数。随后结合人造岩心的声波等测试数据，建立起单参数（孔隙度、矿物组分、围压、孔隙流体）影响的地层速度预测方程，通过分析单参数对地层速度的影响率，建立起单参数影响的孔隙度预测方程。结合涪陵地区A井的实测数据，构建起适合涪陵地区的孔隙度定量化表征方程。将涪陵地区B井的测井数据等代入方程，对方程进行检验。通过计算出的孔隙度与实测孔隙度进行对比，发现计算的孔隙度与研究区实测孔隙度吻合度高，相关性好，孔隙度预测的结果与实际情况吻合。

关键词: 页岩, 人造岩心, 孔隙度, 测井, 涪陵地区

Abstract:

Shale porosity is a critical factor for determining shale reservoir gas-bearing property; quantitative representation of shale porosity is not only the prerequisite for porosity prediction based on seismic data, but also the basis of shale gas evaluation. Since Fuling area is the focus of shale gas exploration and development in China. Based on Fuling well logging and testing data, this paper explores the method for predicting porosity based on well logging data. On this basis, porosity logging recognition is achieved and its response model is constructed; it is discovered through analysis that a good correlation exists between porosity and interval transit time (AC), and the correlation coefficient is up to 83.4%, so internal transit time is determined as the geophysical response parameter of porosity. In combination with testing data such as the acoustic wave of artificial core, this paper also establishes a prediction equation for stratal velocity under the single parameter (porosity, mineral composition, confining pressure, and pore fluid) influence; by analyzing the influence rate of single parameter to stratal velocity, the porosity prediction equation is established in case of single-parameter influence. Then an applicable quantitative representation equation for porosity is created based on the actual measured data of Fuling Well A. The equation can be verified by substituting logging data of Fuling Well B in the equation. Though comparison between the actually measured porosity and calculated results, it is found the actually measured porosity has high conformity and good correlation with the calculated results in research region, and the porosity prediction results are in coincidence with the actual situation.

Key words: shale, artificial core, porosity, well logging, Fuling area

中图分类号:

TE122.2

徐壮, 石万忠, 翟刚毅, 包书景, 彭女佳, 张晓明, 王超, 徐清海, 王任. 涪陵地区页岩总孔隙度测井预测[J]. 石油学报, 2017, 38(5): 533-543.

Xu Zhuang, Shi Wanzhong, Zhai Gangyi, Bao Shujing, Peng Nüjia, Zhang Xiaoming, Wang Chao, Xu Qinghai, Wang Ren. Well logging prediction for total porosity of shale in Fuling area[J]. Acta Petrolei Sinica, 2017, 38(5): 533-543.

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涪陵地区页岩总孔隙度测井预测

Well logging prediction for total porosity of shale in Fuling area

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