Yuxuan Liu , Liansong Wu , Jianchun Guo , Yutong Wu , Dingli Yan , Tao Zhang
{"title":"Whole process simulation for efficient proppant placement technology","authors":"Yuxuan Liu , Liansong Wu , Jianchun Guo , Yutong Wu , Dingli Yan , Tao Zhang","doi":"10.1016/j.geoen.2025.214045","DOIUrl":null,"url":null,"abstract":"<div><div>This study used computational fluid dynamics (CFD) and discrete element method (DEM) to simulate the whole process of efficient proppant placement technology. The aggregation, dispersion, and deposition behaviors of fiber-proppant clusters in fractures were analyzed, exploring the mechanisms of fiber influence on proppant transport and flowback, and evaluating fracture conductivity. Fiber geometry is modeled with a multi-node structure, simulating fiber flexibility, while an adhesion force model describes surface modification. Model accuracy is validated with sedimentation and transport experiments in fiber suspensions.</div><div>Results show that forming fiber-proppant clusters changes the proppant placement pattern and improves fracture conductivity. During transport, fibers form a mesh that collides with proppants, reducing settling velocity. This promotes clustering and rapid migration to the fracture's far end, increasing the effective proppant placement area. During flowback, fibers interlace among particles, enhancing inter-particle bonding and stabilizing the sand pack. The cluster structure increases proppant porosity, improving oil and gas flow. Compared to the no-fiber case, adding 0.5 % fibers by proppant mass increases proppant placement by 58.63 %, reduces flowback by 17.2 %, and enhances fracture permeability by 1–2 orders of magnitude. Further analysis reveals the effects of fiber concentration, length, injection method, flowback velocity, and viscosity on proppant transport and flowback. The findings provide theoretical insights for optimizing fracturing parameters and developing modified fibers.</div></div>","PeriodicalId":100578,"journal":{"name":"Geoenergy Science and Engineering","volume":"254 ","pages":"Article 214045"},"PeriodicalIF":0.0000,"publicationDate":"2025-06-24","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"0","resultStr":null,"platform":"Semanticscholar","paperid":null,"PeriodicalName":"Geoenergy Science and Engineering","FirstCategoryId":"1085","ListUrlMain":"https://www.sciencedirect.com/science/article/pii/S2949891025004038","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"0","JCRName":"ENERGY & FUELS","Score":null,"Total":0}
引用次数: 0
Abstract
This study used computational fluid dynamics (CFD) and discrete element method (DEM) to simulate the whole process of efficient proppant placement technology. The aggregation, dispersion, and deposition behaviors of fiber-proppant clusters in fractures were analyzed, exploring the mechanisms of fiber influence on proppant transport and flowback, and evaluating fracture conductivity. Fiber geometry is modeled with a multi-node structure, simulating fiber flexibility, while an adhesion force model describes surface modification. Model accuracy is validated with sedimentation and transport experiments in fiber suspensions.
Results show that forming fiber-proppant clusters changes the proppant placement pattern and improves fracture conductivity. During transport, fibers form a mesh that collides with proppants, reducing settling velocity. This promotes clustering and rapid migration to the fracture's far end, increasing the effective proppant placement area. During flowback, fibers interlace among particles, enhancing inter-particle bonding and stabilizing the sand pack. The cluster structure increases proppant porosity, improving oil and gas flow. Compared to the no-fiber case, adding 0.5 % fibers by proppant mass increases proppant placement by 58.63 %, reduces flowback by 17.2 %, and enhances fracture permeability by 1–2 orders of magnitude. Further analysis reveals the effects of fiber concentration, length, injection method, flowback velocity, and viscosity on proppant transport and flowback. The findings provide theoretical insights for optimizing fracturing parameters and developing modified fibers.