Computer 3D Simulation of Proppant Particles

被引:1
作者
Li, Ke [1 ,2 ]
Guo, Dali [1 ]
Guo, Zixi [3 ]
Zhao, Yunxiang [4 ]
机构
[1] Southwest Petr Univ, Sch Sci, Chengdu 610500, Peoples R China
[2] Sichuan Univ Sci & Engn, Coll Management Sci, Zigong 643002, Peoples R China
[3] Tsinghua Univ, Dept Math Sci, Beijing 100084, Peoples R China
[4] Civil Aviat Flight Univ China, Sch Sci, Deyang 618307, Peoples R China
来源
APPLIED SCIENCES-BASEL | 2024年 / 14卷 / 13期
关键词
proppant; 3D simulation; Monte Carlo stochastic method; optimization model; DISCRETE ELEMENT MODEL; ALGORITHM;
D O I
10.3390/app14135462
中图分类号
O6 [化学];
学科分类号
0703 ;
摘要
Proppants are one of the key materials for hydraulic fracturing, whose main role is to support fractures and create a channel through which oil and gas can flow. The nature of proppants is the most talked about feature besides their cost, for example, their sphericity, turbidity, particle size, or strength. The porosity, permeability, and fracture conductivity of proppants in fractures are also the main indicators to measure the performance of them. These indicators are usually obtained through physical experiments. However, experimental results often differ depending on the experimental scheme. Different stacking methods of proppant particles lead to this phenomenon. The nature of proppant particles in fractures varies with the way they accumulate. This paper will start with the microscopic arrangement of proppant particles. Considering the randomness and certainty of three-dimensional particle stacking and arrangement, the Monte Carlo stochastic method and an optimization model were used to conduct three-dimensional computer simulation of proppant particles. This lays an important foundation for revealing the randomness and regularity of the micro arrangement of proppant particles.
引用
收藏
页数:15
相关论文
共 24 条
[1]   An algorithm to generate random dense arrangements for discrete element simulations of granular assemblies [J].
Bagi, K .
GRANULAR MATTER, 2005, 7 (01) :31-43
[2]   IN RETROSPECT On the Six-Cornered Snowflake [J].
Ball, Philip .
NATURE, 2011, 480 (7378) :455-455
[3]   Proppant Crushing Mechanisms Under Reservoir Conditions: Insights into Long-Term Integrity of Unconventional Energy Production [J].
Bandara, K. M. A. S. ;
Ranjith, P. G. ;
Rathnaweera, T. D. .
NATURAL RESOURCES RESEARCH, 2019, 28 (03) :1139-1161
[4]   Geometrical modeling of granular structures in two and three dimensions. Application to nanostructures [J].
Benabbou, A. ;
Borouchaki, H. ;
Laug, P. ;
Lu, J. .
INTERNATIONAL JOURNAL FOR NUMERICAL METHODS IN ENGINEERING, 2009, 80 (04) :425-454
[5]   Numerical modeling of nanostructured materials [J].
Benabbou, Azeddine ;
Borouchaki, Houman ;
Laug, Patrick ;
Lu, Jian .
FINITE ELEMENTS IN ANALYSIS AND DESIGN, 2010, 46 (1-2) :165-180
[6]   A computational model for the simulation of dry granular materials [J].
Campello, Eduardo M. B. .
INTERNATIONAL JOURNAL OF NON-LINEAR MECHANICS, 2018, 106 :89-107
[7]   Numerical simulation of the migration and deposition of fine particles in a proppant-supported fracture [J].
Fan, Ming ;
Chen, Cheng .
JOURNAL OF PETROLEUM SCIENCE AND ENGINEERING, 2020, 194
[8]   Algorithm with hybrid method based for sphere packing in two-dimensional region [J].
Fang X.-W. ;
Liu Z.-Y. ;
Tan J.-R. .
Zhejiang Daxue Xuebao (Gongxue Ban)/Journal of Zhejiang University (Engineering Science), 2011, 45 (04) :650-655
[9]   Filling domains with disks: an advancing front approach [J].
Feng, YT ;
Han, K ;
Owen, DRJ .
INTERNATIONAL JOURNAL FOR NUMERICAL METHODS IN ENGINEERING, 2003, 56 (05) :699-713
[10]   CFD-DEM model to assess stress-induced anisotropy in undrained granular material [J].
Foroutan, Talat ;
Mirghasemi, Ali Asghar .
COMPUTERS AND GEOTECHNICS, 2020, 119