A fracture modeling method for ultra-deep reservoirs based on geologic information fusion: an application to a low porosity sandstone reservoirs in X gas field of a basin in western China

被引:1
|
作者
Wang, Rujun [1 ]
Tang, Yongliang [1 ]
Yang, Fenglai [1 ]
She, Jiaofeng [1 ]
Li, Xiaorui [1 ]
Chen, Naidong [1 ]
Ji, Ce [2 ,3 ]
He, Yingzheng [2 ,3 ]
机构
[1] Tarim Oilfield Co, PetroChina, Korla, Peoples R China
[2] Univ Petr Beijing, State Key Lab Petr Resources & Prospecting, Beijing, Peoples R China
[3] China Univ Petr, Coll Geosci, Beijing, Peoples R China
基金
中国国家自然科学基金;
关键词
ultra-deep sandstone reservoirs; fracture modeling; seismic attribute; probability fusion; PR model; HYDROCARBON RESOURCES;
D O I
10.3389/feart.2023.1351264
中图分类号
P [天文学、地球科学];
学科分类号
07 ;
摘要
The reservoirs of ultra-deep and low-permeability sandstones typically exhibit characteristics of lithological tightness and poor physical properties. Fractures control the oil and gas content as well as the productivity of such reservoirs. However, the distribution of fractures is complex, exhibiting strong heterogeneity. Therefore, a systematic study on reservoir fracture modeling can provide geological foundations for the development of such reservoirs. Due to the considerable burial depth of these reservoirs, conventional methods relying solely on seismic information have limited reliability, and the established discrete network models of fractures are often less dependable. In this paper, taking the X gas reservoir in a basin in western China as an example, we discuss a fracture modeling method based on the integration of geological information to enhance the efficiency and accuracy of fracture modeling. The modeling method primarily involves the use of deterministic methods to obtain large-scale fractures, while random simulation is employed for small and medium-scale fractures. The fracture development control factors and seismic attribute information are integrated using permanence of ratios (PR) model to establish a fracture development probability field model. Subsequently, the geometric parameters of fractures and the fracture density model are used as input parameters to generate a discrete network model of small and medium-scale fractures using a object-based modeling method. Finally, based on the fracture equivalent property model and verified through geological understanding, analysis of production dynamics, and numerical simulation of the gas reservoir, it is demonstrated that the fracture model established using the proposed method aligns with geological understanding and exhibits high reliability.
引用
收藏
页数:12
相关论文
共 50 条
  • [21] Deep learning-based geological modeling of ultra-deep fault-karst reservoirs in Shunbei oilfield, Tarim Basin
    Duan T.
    Zhang W.
    He Z.
    Liu Y.
    Ma Q.
    Li M.
    Lian P.
    Huang Y.
    Oil and Gas Geology, 2023, 44 (01): : 203 - 212
  • [22] Diagenesis of tight sandstone reservoirs of Xujiahe Formation (Upper Triassic), the Xinchang Gas Field, western Sichuan Basin, China
    Zhong, Yi-Jiang
    Huang, Ke-Ke
    Ye, Li-Ming
    Lan, Ye-Fang
    Liu, Lei
    GEOLOGICAL JOURNAL, 2020, 55 (06) : 4604 - 4624
  • [23] Subsurface fracture characterization in a folded ultra-deep tight-gas sandstone reservoir: A case study from the Keshen gas field, Tarim Basin, China
    Wang, Junpeng
    Yang, Xianzhang
    Zhang, Jie
    Wang, Ke
    Zhang, Ronghu
    Wang, Qiqi
    Ren, Bo
    Ukar, Estibalitz
    JOURNAL OF STRUCTURAL GEOLOGY, 2023, 172
  • [24] Characteristics and genetic mechanisms of fault-controlled ultra-deep carbonate reservoirs: A case study of Ordovician reservoirs in the Tabei paleo-uplift, Tarim Basin, western China
    Zhao, Xueqin
    Wu, Changda
    Ma, Bingshan
    Li, Fei
    Xue, Xiaohong
    Lv, Congcong
    Cai, Quan
    JOURNAL OF ASIAN EARTH SCIENCES, 2023, 254
  • [25] Fluid evolution and hydrocarbon accumulation model of ultra-deep gas reservoirs in Permian Qixia Formation of northwest Sichuan Basin, SW China
    LI Jianzhong
    BAI Bin
    BAI Ying
    LU Xuesong
    ZHANG Benjian
    QIN Shengfei
    SONG Jinmin
    JIANG Qingchun
    HUANG Shipeng
    Petroleum Exploration and Development, 2022, 49 (04) : 719 - 730
  • [26] Fluid evolution and hydrocarbon accumulation model of ultra-deep gas reservoirs in Permian Qixia Formation of northwest Sichuan Basin, SW China
    Li, Jianzhong
    Bai, Bin
    Bai, Ying
    Lu, Xuesong
    Zhang, Benjian
    Qin, Shengfei
    Song, Jinmin
    Jiang, Qingchun
    Huang, Shipeng
    PETROLEUM EXPLORATION AND DEVELOPMENT, 2022, 49 (04) : 719 - 730
  • [27] Techniques for improving fracture-controlled stimulated reservoir volume in ultra-deep fractured tight reservoirs: A case study of Kuqa piedmont clastic reservoirs, Tarim Basin, NW China
    Qun, Lei
    Zhanwei, Yang
    Dingwei, Weng
    Hongtao, Liu
    Baoshan, Guan
    Bo, Cai
    Haifeng, Fu
    Zhaolong, Liu
    Yaoyao, Duan
    Tiancheng, Liang
    Zeyuan, Ma
    PETROLEUM EXPLORATION AND DEVELOPMENT, 2022, 49 (05) : 1169 - 1184
  • [28] Seismic Wave Field Anomaly Identification of Ultra-Deep Heterogeneous Fractured-Vuggy Reservoirs: A Case Study in Tarim Basin, China
    Li, Xiangwen
    Li, Jingye
    Li, Lei
    Wan, Zhonghong
    Liu, Yonglei
    Ma, Peiling
    Zhang, Ming
    APPLIED SCIENCES-BASEL, 2021, 11 (24):
  • [29] Techniques for improving fracture-controlled stimulated reservoir volume in ultra-deep fractured tight reservoirs: A case study of Kuqa piedmont clastic reservoirs, Tarim Basin, NW China
    Lei Q.
    Yang Z.
    Weng D.
    Liu H.
    Guan B.
    Cai B.
    Fu H.
    Liu Z.
    Duan Y.
    Liang T.
    Ma Z.
    Shiyou Kantan Yu Kaifa/Petroleum Exploration and Development, 2022, 49 (05): : 1012 - 1024
  • [30] Techniques for improving fracture-controlled stimulated reservoir volume in ultra-deep fractured tight reservoirs: A case study of Kuqa piedmont clastic reservoirs, Tarim Basin, NW China
    LEI Qun
    YANG Zhanwei
    WENG Dingwei
    LIU Hongtao
    GUAN Baoshan
    CAI Bo
    FU Haifeng
    LIU Zhaolong
    DUAN Yaoyao
    LIANG Tiancheng
    MA Zeyuan
    Petroleum Exploration and Development, 2022, 49 (05) : 1169 - 1184