基于灰色关联与层次分析的脆性指数预测方法——以准噶尔盆地吉木萨尔凹陷芦草沟组致密储层为例

doi:10.11720/wtyht.2023.1242

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吉木萨尔凹陷致密储层因储层物性差,需要水力压裂才能获得工业油流。开展对应的岩石力学特性研究及脆性评价可为水力压裂工艺提供参考依据。本文通过三轴力学试验获得吉木萨尔致密地层的力学特性。开展脆性指数的测井敏感性相关性分析,确定对岩石脆性潜在敏感的测井参数,依据灰色关联理论,确定敏感参数的初始序列并对筛选的参数归一化处理,继而将筛选出的敏感参数对脆性指数潜在敏感性进行量化关联分析,获得各参数对脆性指数的关联度大小,确定各关联度的次序。在此基础上,基于层次分析法构造敏感参数的两两比较判断矩阵,确定权重向量,构建了脆性指数与敏感参数间的函数关系模型,从而建立了新的脆性指数预测模型,将测井模型与基于力学特性的脆性模型、室内测试的脆性指数进行比较。研究表明:吉木萨尔致密地层具有较强的脆性特征,基于全过程应力—应变曲线表征的综合脆性指数符合实际岩石的脆性特征:灰色关联法确定的对脆性指数敏感的测井参数的关联度大小的顺序依次为自然伽马(GR)、电阻率(R_t)、密度(ρ)、中子(CNL)、声波时差(ΔT);层次分析法构建的新预测模型中上述敏感参数的权重系数分别是0.33、0.22、0.18、0.16、0.11;将该法应用于吉木萨尔芦草沟组,预测的脆性指数与实验室测试的相对比,能够较真实地反映实际地层的脆性,吻合度高。试油结果表明,米采油指数与脆性指数呈正比,脆性指数高的层段,压裂后的产能高。因此,新方法为脆性指数预测提供了新的思路,为储层的压裂改造提供了参数指导。

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	刘庆
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关键词 ：灰色关联, 层次分析, 脆性指数, 致密储层, 芦草沟组

Abstract：

Owing to the poor physical properties,the tight reservoirs in the Jimusaer Sag can yield industrial oil flow only through hydraulic fracturing.The research on mechanical properties and the brittleness assessment of rocks can provide a certain reference for hydraulic fracturing.This study obtained the mechanical properties of the tight strata in the Jimusaer sag using triaxial mechanical tests and determined the log parameters potentially sensitive to rock brittleness by analyzing the correlation between the sensitivity of the brittleness index and logs.Then,based on the grey correlation theory,this study determined the initial sequence of sensitivity parameters and normalized the parameters selected.Then,it quantitatively correlated the selected parameters with the potential sensitivity to the brittleness index and determined the degrees of correlation and their order.On this basis,this study established a matrix for the pair-wise comparison of the sensitivity parameters using the analytic hierarchy process (AHP) and determined the weight vector.Then,it established the functional relationship model between the brittleness index and the sensitivity parameters,thus developing a new prediction model for the brittleness index.Finally,this study compared the log models with the brittleness model established based on mechanical properties and the brittleness index determined through laboratory tests.The study results are as follows.The tight strata in the Jimusaer Sag have high brittleness,and the comprehensive brittleness index characterized using the whole-process stress-strain curve agreed with the actual brittleness characteristics of rocks.The degree of correlation of the sensitivity parameters determined using the grey correlation method was in the order of natural gamma-ray(GR)>resistivity(R_t)>density(ρ)>neutron(CNL)>sonic interval transit time(ΔT),which had a weight coefficient of 0.33,0.22,0.18,0.16, and 0.11,respectively in the new prediction model.The prediction method proposed in this study was applied to the Lucaogou Formation in the Jimusaer Sag.Compared with that determined through laboratory tests,the brittleness index predicted can reflect the actual brittleness of the formation,exhibiting a high consistency.As shown by the results from well tests,the productivity index of oil was proportional to the brittleness index,and a higher brittleness index was associated a high production capacity after fracturing.Therefore,the new method provides a new approach to brittleness index prediction and guides the parameter selection for the fracturing of reservoirs.

Key words： grey correlation analytic hierarchy process brittleness index tight reservoir Lucaogou Formation

收稿日期: 2022-05-20 修回日期: 2023-03-21 出版日期: 2023-08-20

ZTFLH:

P631.4

基金资助:国家自然科学基金项目(51974332)

通讯作者: 张镇(1990-),男,新疆油田公司油气田开发(地质)专业工程师,工商管理硕士,地质勘探学士。Email:hs_zhz@petrochina.com.cn

作者简介: 刘庆(1987-),男,新疆油田公司地质勘探专业工程师,本科学历,主要研究方向为测井、地质勘探。Email:dxlq@petrochina.com.cn

引用本文:

刘庆, 张镇, 杨帅, 李枫凌. 基于灰色关联与层次分析的脆性指数预测方法——以准噶尔盆地吉木萨尔凹陷芦草沟组致密储层为例[J]. 物探与化探, 2023, 47(4): 944-953.
LIU Qing, ZHANG Zhen, YANG Shuai, LI Feng-Ling. Method for brittleness index prediction based on grey correlation and analytic hierarchy process:A case study of the tight reservoirs in the Lucaogou Formation of the Jimusaer Sag,Junggar Basin. Geophysical and Geochemical Exploration, 2023, 47(4): 944-953.

链接本文:

https://www.wutanyuhuatan.com/CN/10.11720/wtyht.2023.1242 或 https://www.wutanyuhuatan.com/CN/Y2023/V47/I4/944

Fig.1 吉木萨尔凹陷构造位置

Fig.2 芦草沟组地层物性分布

原理分类	公式	变量说明	获取方法
基干硬度或坚固性	BI₁= (H_m - H)/K	H为硬度,GPa;H_m为微观硬度,GPa;K为体枳模量,GPa	硬度测试
	BI₂ = H/K_IC	K_IC为断裂韧性,MPa·m^1/2	硬度和韧性测试
	BI₃ = HE/ $K I C 2$	E为静态杨氏模量,GPa	陶质材料测试
	BI₄=qσ_c	q为直径小于0.6 mm碎屑百分比,%;σ_c为抗压强度,MPa	兽氏冲击实絵
	BI₅ = c/d	c为裂纹长度,μm;d为韦氏测试特定载荷下贯入尺寸,μm	贯入实验
	BI₆= t_dec/t_inc	t_dec为平均载荷减少时间,s;t_inc为平均载荷增加时间,s
	BI₇ = F_max/P	F_max为试件所受最大载荷,kN;P为相应的贯入深度,mm
基于强度比值	BI₈ = σ_c/σ_t	σ_c为抗压强度,MPa;σ_t为抗拉强度,MPa	单轴抗压測试和巴西劈裂实验
	BI₉ = (σ_c-σ_t)/(σ_c+σ_t)
	BI₁₀ = σ_cσ_t/2
	BI₁₁ = (σ_cσ_t)^0.5/2
基于全应力—应变特征	BI₁₂ = (τ_pτ_r)/τ_p	τ_p为剪切强度峰值,MPa;τ_r为残余剪切强度,MPa	应力—应变测试
	BI₁₃ = ε_r/ε_t	ε_r为可恢复应变,无量纲;ε_t为总应变,无量纲
	BI₁₄= W_r/W_t	W_r为可恢更应变能,J;W_t为总应变能,J
	BI₁₅ =ε_ux·100%	ε_ux为不可恢复轴向应变,无量纲
	BI₁₆ = (ε_p -ε_r)/ε_p	ε_p为应变峰值,无量纲;ε_r为残余应变,无量纲
	BI₁₇ = π/4 +φ/2	φ为内摩擦角,rad	应力应变测试或声波测井数据
	BI₁₈ = sinφ	φ为内摩擦角,rad	应力应变测试或声波测井数据
基于弹性力学参数	BI₁₉ = (E_n+v_n)/2	E_n为归一化杨氏模量,无量纲;v_n为归一化泊松比,无量纲	密度与声波测井
基于岩石矿物组分	BI₂₀ =W_qtz/W_τot BI₂₁ =(W_qtz+W_dot)/W_τot BI₂₂ =(W_QFM+W_Car)W_τot	W_qtz为石英含量,%;W_τot为矿物总量,% W_dot为白云岩含量,% W_QFM为硅酸盐岩含量,%;W_Car为脆性碳酸盐岩含量,%	实验室XRD测试或矿物含量测井

Table 1 现有脆性指数评价方法统计

Fig.3 基于全过程应力—应变的脆性指数计算方法

Fig.4 脆性指数各参数取值示意

Fig.5 部分岩样的三轴应力—应变曲线

Table 2 利用实验方法获得的岩样综合脆性指数

Fig.6 岩样被压缩后的形态

Fig.7 实验室测定的脆性指数与测井参数交会

Table 3 各因素与脆性指数的关联度及排序

Table 4 对比矩阵标度及含义

Table 5 判断矩阵

Table 6 随机一致性取值

Fig.8 脆性指数预测对比

Fig.9 脆性指数与米采油指数关系

Fig.10 水力压裂微地震监测结果

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