Research on the construction method of complex fracture networks based on microseismic data

被引:0
|
作者
Wang, Xulin [1 ]
Lv, Minghui [2 ]
机构
[1] Ocean Univ China, Coll Marine Geosci, Qingdao 266100, Shandong, Peoples R China
[2] Beijing Zhongke Haixun Digital Technol Co Ltd, Qingdao Branch, Qingdao 266100, Shandong, Peoples R China
来源
关键词
Hydraulic fracturing; Fracture network; Seismic source classification; Stress inversion; Oil and gas; SHALE-GAS; TIGHT-OIL; HYDRAULIC FRACTURES; FOCAL MECHANISMS; MODEL; ROCK; OPTIMIZATION; EXTRACTION; SIMULATION; STRESS;
D O I
10.1016/j.geoen.2024.213625
中图分类号
TE [石油、天然气工业]; TK [能源与动力工程];
学科分类号
0807 ; 0820 ;
摘要
Three-dimensional simulation of fracture networks based on microseismic data from hydraulic fracturing is of significant importance and value for obtaining fracture development morphology, studying fracture characteristics, and evaluating fracturing production. It not only helps to understand the development of fractures but also provides references for subsequent fracturing operations. However, existing methods for simulating fracture networks based on microseismic data mainly rely on spatiotemporal clustering analysis of hypocenter locations, which lack theoretical support, leading to unreliable fracture network structures. To address this issue, this paper proposes an innovative method for fracture network modeling. The method first conducts cluster analysis based on the P-axis direction of the hypocenters, dividing the seismic data into different clusters and performing regional stress inversion to determine the principal stress direction of each cluster, which is assumed to be the direction of fracture development. Then, an improved Random Sample Consensus algorithm is used to identify co-planar hypocenters along the direction of fracture development. For hypocenters not identified as co-planar, a fractal dimension method is employed to fit the fracture surfaces. Finally, the new three-dimensional modeling algorithm is used to construct the fracture model. This method has been validated with multiple sets of measured microseismic data, and the results show that it has high accuracy and reliability in predicting fracture development direction, guiding and optimizing fracturing construction plans, calculating effective fracture volume, and predicting oil and gas production capacity. It provides a new method and perspective for understanding the development of hydraulic fracturing reservoirs and evaluating the effects of oil and gas production capacity.
引用
收藏
页数:20
相关论文
共 50 条
  • [31] Research on Neural Network Construction Method Based on Approximate Computational Test Data
    Wang, Lutao
    Wu, Lisha
    Hao, Jinlong
    Chen, Zhenyu
    Jia, Cuiling
    2022 PROGNOSTICS AND HEALTH MANAGEMENT CONFERENCE, PHM-LONDON 2022, 2022, : 428 - 432
  • [32] Research on microseismic location based on fast marching upwind linear interpolation method
    Jiang Ruo-chen
    Xu Nu-wen
    Dai Feng
    Zhou Jia-wen
    ROCK AND SOIL MECHANICS, 2019, 40 (09) : 3697 - 3708
  • [33] Research on Feature Fusion Method of Mine Microseismic Signal Based on Unsupervised Learning
    Liu, Rui
    SHOCK AND VIBRATION, 2021, 2021
  • [34] Integration of Shale-Gas-Production Data and Microseismic for Fracture and Reservoir Properties With the Fast Marching Method
    Xie, Jiang
    Yang, Changdong
    Gupta, Neha
    King, Michael J.
    Datta-Gupta, Akhil
    SPE JOURNAL, 2015, 20 (02): : 347 - 359
  • [35] Research on Feature Fusion Method of Mine Microseismic Signal Based on Unsupervised Learning
    Liu, Rui
    Liu, Rui (bukaopu999@gmail.com), 1600, Hindawi Limited (2021):
  • [36] Research on the Initial Arrival Recognition and Judgment Method of Microseismic Signals Based on PELT
    Wang, Xulin
    Lv, Minghui
    PURE AND APPLIED GEOPHYSICS, 2024, : 1263 - 1278
  • [37] Research on construction method of command and control network model based on complex network theory
    Wang, Jianwei
    Pan, Chengsheng
    IET CONTROL THEORY AND APPLICATIONS, 2024, 18 (18): : 2931 - 2943
  • [38] Research on MSFM-based microseismic source location of rock mass with complex velocities
    Guo L.
    Dai F.
    Xu N.
    Fan Y.
    Li B.
    Yanshilixue Yu Gongcheng Xuebao, 2 (394-406): : 394 - 406
  • [39] Methodology and application of shale-reservoir natural fracture modeling based on microseismic monitoring data
    Liu, Ziwei
    Wu, Jiapeng
    Han, Wenzhong
    Zhang, Yonggui
    Li, Zhenyong
    Ma, Yuehua
    Ma, Kecong
    Zhang, Yao
    Wang, Hu
    INTERPRETATION-A JOURNAL OF SUBSURFACE CHARACTERIZATION, 2020, 8 (04): : SP167 - SP174
  • [40] An Inversion-Based Microseismic Simulator for Fracture Diagnostics
    Cao, Meng
    Sharma, Mukul M.
    ROCK MECHANICS AND ROCK ENGINEERING, 2024,