A fracture identification method for low-permeability sandstone based on R/S analysis and the finite difference method: A case study from the Chang 6 reservoir in Huaqing oilfield, Ordos Basin
A fracture identification method for low-permeability sandstone based on R/S analysis and the finite difference method: A case study from the Chang 6 reservoir in Huaqing oilfield, Ordos Basin
复制标题
DOI：
10.1016/j.petrol.2018.12.017
复制
发表时间：
2019-03
影响因子：
--
通讯作者：
Zikang Xiao;W. Ding;Jingshou Liu;Mingzhi Tian;Shuai Yin;Xuehui Zhou;Yang Gu
中科院分区：
文献类型：
--
作者：
Zikang Xiao;W. Ding;Jingshou Liu;Mingzhi Tian;Shuai Yin;Xuehui Zhou;Yang Gu
低渗透油藏具有物性差、非均质性强、天然裂缝等特点。准确识别裂缝展布对于低渗透油藏勘探开发具有重要意义。现场露头、岩心及成像测井分析表明，华庆油田长6组裂缝以层控垂直裂缝和高角度构造裂缝为主。裂缝方向包括 NE-SW、NNE-SSW、NW-SE 和 NNW-SSE。北东—东南走向的裂缝形成于喜马拉雅期，北西—东南走向的裂缝形成于燕山期，其他裂缝来源于喜马拉雅构造活动期间燕山期的压裂。本研究通过引入有限差分（FD）方法对传统的重标度范围（R/S）分析方法进行升级，新提出的方法称为R/S-FD方法。岩心数据表明，R/S-FD方法能够准确识别垂直裂缝和大角度裂缝。通过对比成像测井上的裂缝发育剖面，发现裂缝判别参数F与裂缝线密度和裂缝面密度均具有良好的线性关系。通过动态数据（注水剖面）和静态数据（图像测井）对该方法进行验证，结果表明，当F下限为0.5时，识别误差得到消除，裂缝识别准确率达到76.9%。将R/S和有限差分方法相结合，减少了传统R/S方法的人工识别误差，识别过程自动化、智能化。 R/S-FD方法可以与多条测井曲线结合使用。该方法仅利用常规测井曲线即可实现较高的裂缝识别精度，对于一些缺乏影像测井资料的低渗透油田具有重要的现实意义。
Low-permeability reservoirs are characterized by poor physical properties, strong heterogeneity and natural fractures. Accurate identification of the fracture distribution is of great significance for the exploration and development of low-permeability reservoirs. Field outcrop, core and imaging log analyses show that stratabound vertical and high-angle structural fractures are the main types of fractures in the Chang 6 formation in the Huaqing oilfield. The fracture orientations include NE-SW, NNE-SSW, NW-SE, and NNW-SSE. The NE-SE-oriented fractures formed in the Himalayan stage, while the NW-SE fractures formed in the Yanshan period, and the other fractures derived from the fracturing in the Yanshan period during the Himalayan tectonic activity. The traditional rescaled range (R/S) analysis method is upgraded by introducing the finite difference (FD) method in this research, and the newly proposed method is called the R/S-FD method. Core data show that the R/S-FD method can accurately recognize vertical fractures and high-angle fractures. By comparing the fracture development section on the imaging log, it is found that fractures discrimination parameter F has a good linear relationship with both the fracture linear density and the fracture surface density. This method is verified by dynamic data (water injection profiles) and static data (image logging), and the results show that the recognition error is eliminated when the lower limit of F is 0.5, resulting in a crack identification accuracy of 76.9%. Combining the R/S and finite difference methods reduces the artificial recognition error of the traditional R/S method, and the recognition process is automated and intelligent. The R/S-FD method can be used in combination with multiple logging curves. A high fracture recognition accuracy could be accomplished by using this proposed method with only conventional logging curves, of great practical significance to some low-permeability oilfields that lack image logging data.