岩性油气藏 ›› 2026, Vol. 38 ›› Issue (4): 63–76.doi: 10.12108/yxyqc.20260406

• 地质勘探 • 上一篇    下一篇

莺歌海盆地乐东斜坡带中新统黄流组超压储层岩石物理建模方法

陈昊1,2(), 黄捍东1,2(), 张铁铭3, 崔刚4, 彭嘉辉1,2   

  1. 1 中国石油大学(北京) 油气资源与探测国家重点实验室北京 102249
    2 中国石油大学(北京)地球物理学院北京 102249
    3 中国石油集团长城钻探工程有限公司 科技信息部北京 100101
    4 中国石油集团华北油田公司 采油一厂河北 任丘062550
  • 收稿日期:2025-10-17 修回日期:2025-12-26 出版日期:2026-07-01 发布日期:2026-07-06
  • 第一作者:陈昊(1996—),男,中国石油大学(北京)在读博士研究生,研究方向为地震反演方法和储层预测。地址:(102249)北京市昌平区中国石油大学(北京)地球物理学院。Email:ch19up@163.com
  • 通信作者: 黄捍东
  • 基金资助:
    国家自然科学基金“致密砂岩脆性影响因素及多参量-多尺度脆性综合评价研究”(42274140)

Rock physics modeling method for overpressure reservoirs of Miocene Huangliu Formation in Ledong slope, Yinggehai Basin

CHEN Hao1,2(), HUANG Handong1,2(), ZHANG Tieming3, CUI Gang4, PENG Jiahui1,2   

  1. 1 State Key Laboratory of Petroleum Resources and ProspectingChina University of Petroleum (Beijing), Beijing 102249, China
    2 College of GeophysicsChina University of Petroleum (Beijing)Beijing 102249, China
    3 Science & Technology Information DepartmentCNPC Greatwall Drilling Engineering Co., Ltd., Beijing 100101, China
    4 No. 1 Production PlantPetroChina Huabei Oilfield Company, Renqiu 062550Hebei, China
  • Received:2025-10-17 Revised:2025-12-26 Online:2026-07-01 Published:2026-07-06
  • Contact: HUANG Handong E-mail:ch19up@163.com;webhhd@163.com

摘要:

现有岩石物理模型难以准确描述超压条件下储层弹性参数的变化特征,限制了超压储层的刻画精度。以莺歌海盆地乐东斜坡带中新统黄流组超压储层为例,提出了一种多重孔隙结构超压岩石物理模型,对模型应用效果进行了分析;基于模型,对超压储层参数影响因素进行了分析,构建包含地层有效应力和孔隙度参数的岩石物理量版。研究结果表明:①多重孔隙结构超压岩石物理模型建模方法为,基于多重孔隙理论,综合考虑柔性孔隙、刚性孔隙及束缚水的影响,在孔隙空间刚度理论中引入地层压力系数和有效应力,采用梯度优化算法自适应优化孔隙纵横比,进而反映复杂孔隙结构下弹性参数随有效应力的变化规律。②该模型预测的乐东斜坡区黄流组纵、横波速度与测井解释高度吻合,预测误差低于8%,相较于传统模型,其拟合效果最佳,R2最高,分别为0.920、0.937。③超压储层岩石弹性参数受有效应力、柔性孔隙占比、泥质含量、束缚水孔隙度及可动流体孔隙度等5种因素的共同影响,在超压地层中,随着孔隙压力升高、有效应力减小,纵横波速度比呈上升趋势,与砂岩相比,泥岩具有低速、高纵横波速度比特征;纵横波速度比是区分超压碎屑岩储层中砂岩与泥岩的敏感参数,研究区常压段砂、泥岩纵横波速度比的判别阈值约为1.64,超压段为1.70~1.75。④基于多重孔隙结构超压岩石物理模型反演的纵横波速度比剖面预测的砂岩储层分布,与气测解释结论基本一致。

关键词: 超压地层, 有效应力, 弹性参数, 孔隙空间刚度, 柔性孔隙占比, 岩石物理建模, 岩石物理量版, 乐东斜坡带, 莺歌海盆地

Abstract:

Existing rock physics models cannot accurately characterize the variation of elastic parameters in overpressure reservoir, which limits the precision of overpressure reservoir characterization. Taking overpressure re-servoirs of Miocene Huangliu Formation in Ledong slope of Yinggehai Basin as an example, a multi-porosity rock physics model for overpressure reservoirs was proposed, and its application performance was analyzed. Based on the proposed model, the influence factors of elastic parameters in overpressure reservoirs were analyzed, and a rock physics template incorporating formation effective stress and porosity parameters were established. The results show that: (1) The multi-porosity overpressure rock physics modeling method is proposed based on the multi-porosity theory by comprehensively considering effects of soft pores, stiff pores, and bound-water. By introducing the formation pressure coefficient and effective stress into the pore-space stiffness theory, and employing a gradient-based optimization algorithm to adaptively optimize pore aspect ratios, the model captures the variation of elastic parameters with effective stress under complex pore structures. (2) The predicted P-wave and S-wave velocities of Huangliu Formation in Ledong slope area by this model are in high agreement with well logging interpretations, with prediction errors below 8%. Compared with conventional models, the proposed model achieves the best fitting performance, with the highest R2 values of 0.920 and 0.937, respectively. (3) In overpressure reservoirs, rock elastic parameters are jointly controlled by five factors, including effective stress, soft-pore proportion, clay content, bound-water porosity, and movable-fluid porosity. In overpressure formations, with increasing pore pressure and decreasing effective stress, the P-wave to S-wave velo-city ratio (vp/vs) increases. Compared with sandstone, mudstone exhibits lower velocity and higher vp/vs values. The vp/vs ratio is the sensitive parameter for distinguishing sandstone from mudstone in overpressure clastic reservoirs. In the study area, the discriminant threshold of vp/vs for sandstone and mudstone is approximately 1.64 in the normal-pressure section, and 1.70-1.75 in the overpressure section. (4) The sandstone reservoir distribution predicted by the vp/vs section inverted on the basis of the proposed multi-porosity overpressure rock physics model is basically identical with the gas logging interpretation conclusion.

Key words: overpressure formation, effective stress, elastic parameter, pore-space stiffness, soft-pore proportion, rock physics modeling, rock physics template, Ledong slope, Yinggehai Basin

中图分类号: 

  • P631

图1

莺歌海盆地乐东斜坡带构造单元(a)及新生代岩性地层综合柱状图(b)(据文献[26]修改)"

表1

柔性/刚性孔隙与传统孔隙类型的对应关系"

对照项 传统孔隙类型划分 本文孔隙类型划分
分类依据 孔隙成因与几何形态(粒间孔、粒内孔、溶蚀孔、微裂缝等) 孔隙纵横比及其在有效
应力作用下的力学响应
核心判据 孔隙尺度、形态与成因 压力敏感性与压缩行为
与粒间孔
关系
粒间孔为碎屑岩中
主要储集空间
孔隙纵横比较低、弱胶结的
粒间孔通常表现为柔性孔;
孔隙纵横比较高、强胶结的
残余粒间孔多表现为刚性孔
与粒内孔
关系
粒内孔尺度较小、
分布离散
多数情况下孔隙纵横比较高,表现为相对刚性孔;在弱胶
结或连通条件下亦可呈现
一定柔性
与黏土孔/
微裂缝关系
黏土片间孔、微裂缝
尺度小、形态扁平
通常孔隙纵横比较低,对
有效应力高度敏感,
表现为典型柔性孔
分类目的 描述孔隙几何特征
及成因类型
描述孔隙对有效应力变化
的力学响应及其对弹性
参数的影响

图2

模拟刚性孔隙与柔性孔隙随深度的变化特征"

图3

莺歌海盆地乐东斜坡带A井中新统黄流组不同埋藏深度薄片照片"

图4

莺歌海盆地乐东斜坡带中新统黄流组不同泥质含量的样本体积模量(a)、剪切模量(b)随正常有效应力的变化特征"

图5

实验模拟常压地层与超压地层柔性孔隙占比随深度变化特征"

图6

砂岩围压-孔隙压力耦合速度实验模拟不同围压条件下纵、横波速度(a)及纵横波速度比(b)随孔隙压力的变化情况(据文献[32]修改)"

表2

4种孔隙空间刚度理论模型公式"

作者 Kd模型 $\frac{{K}_{\varphi }}{{K}_{m}}$ μd模型
Russell[13] ${K}_{d}=\frac{{K}_{m}}{1+\frac{\varphi }{k}}$ $k=\frac{{K}_{\varphi }}{{K}_{m}}=f\left({P}_{e}\right)=M+N\cdot ln\left({P}_{e}\right)$ ${\mu }_{d}=\frac{{\mu }_{m}{K}_{d}}{{K}_{m}}$
Dinh等[14] ${K}_{d}=\frac{{K}_{m}}{1+\frac{\varphi }{k}}$ $k=\frac{{K}_{\varphi }}{{K}_{m}}=f\left({P}_{e}\right)=L+H\cdot {P}_{e}$ μd=P+Q⋅Pe
刘仕友等[16] ${K}_{d}=\frac{{K}_{m}}{1+\frac{\varphi }{k}}$ $k=\frac{{K}_{\varphi }}{{K}_{m}}=f\left({P}_{e}\right)=R+S\cdot ln\left({P}_{e}\right)$ ${\mu }_{d}=\frac{{\mu }_{m}{K}_{d}}{T{K}_{m}}$
本文模型 ${K}_{d}=\frac{{K}_{m}}{1+\frac{\varphi }{k}}$ $k=\frac{{K}_{\varphi }}{{K}_{m}}=f\left({P}_{e}, {P}_{c}\right)=\left(D+E\cdot {e}^{F\cdot {P}_{e}}\right)\cdot {P}_{c}$ ${\mu }_{d}=\frac{{\mu }_{m}\cdot {K}_{d}\cdot ln(G\cdot {P}_{c})}{{K}_{m}}$

图7

GBO优化多重孔隙结构超压岩石物理模型流程图"

图8

乐东斜坡带A井中新统黄流组孔隙压力及地层压力系数预测"

表3

乐东斜坡带A井中新统黄流组岩石骨架各矿物相关参数设定"

矿物成分 体积模量/GPa 剪切模量/GPa 密度/(g·cm-3
石英 39.000 30 2.65
黏土 32.000 19 2.82
方解石 27.000 20 2.85
2.650 0 1.03
0.001 0 0.38

图9

乐东斜坡带A井中新统黄流组不同岩石物理模型预测结果对比"

图10

乐东斜坡带A井中新统黄流组不同岩石物理模型预测误差对比"

图11

乐东斜坡带A井中新统黄流组梯度优化(GBO)多重孔隙结构岩石物理模型预测效果及误差分布直方图"

表4

乐东斜坡带A井中新统黄流组不同岩石物理模型在同一测试集上的速度预测误差统计"

模型 RMSE/(m·s-1) R2
纵波
速度
横波
速度
纵波
速度
横波
速度
Xu-White模型
(未考虑地层压力影响)
334.69 192.01 -0.824 0.147
传统孔隙空间刚度理论模型
(未考虑束缚水影响)
163.81 93.094 0.563 0.799
改进孔隙空间刚度理论模型
(未考虑束缚水影响)
146.49 74.366 0.651 0.872
多重孔隙结构超压岩石物理
模型(考虑束缚水影响)
91.938 58.919 0.862 0.919
GBO优化多重孔隙结构超压
岩石物理模型(最终优化模型)
70.220 52.176 0.920 0.937

表5

多重孔隙结构超压岩石物理模型敏感性分析参数设置"

输入参数 取值
泥质含量占骨架比例/% 10~90
压力系数 0.4~2.3
有效应力/MPa 10~80
可动流体孔隙度/% 0.1~10.0
束缚水孔隙度/% 0.1~10.0
柔性孔隙占比/% 10~90
束缚水孔隙纵横比 0.05
柔性孔隙纵横比 0.08
刚性孔隙纵横比 0.50

图12

多重孔隙结构超压岩石物理模型模拟弹性参数随柔性孔隙占比和有效应力变化"

图13

多重孔隙结构超压岩石物理模型模拟弹性参数随泥质含量和有效应力的变化"

图14

多重孔隙结构超压岩石物理模型模拟弹性参数随束缚水孔隙度和可动流体孔隙度变化"

表6

乐东斜坡带中新统黄流组有效应力-地层压力系数统计"

有效应力/
MPa
70 65 60 55 50 45 40 35 30 25 20
地层压力
系数
0.70 0.85 0.98 1.12 1.25 1.38 1.51 1.64 1.77 1.90 2.04

图15

乐东斜坡带中新统黄流组超压砂泥岩储层岩石物理量版"

图16

乐东斜坡带过A井中新统黄流组纵横波速度比反演剖面"

图17

乐东斜坡带过A井中新统黄流组孔隙度反演剖面"

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