Fines Migration Control in Sandstone Reservoirs: DLVO Modeling for Critical Salt Concentration and Critical Flow Rate Prediction

Author:

Muneer Rizwan1,Pourafshary Peyman1,Hashmet Muhammad Rehan2

Affiliation:

1. School of Mining and Geosciences, Nazarbayev University, Astana, Kazakhstan

2. Department of Chemical & Petroleum Engineering, United Arab Emirates University, Al Ain, United Arab Emirates

Abstract

Summary Critical salt concentration (CSC) is the minimum salt concentration of injected water, below which fines migration occurs in sandstone reservoirs. Sand grains and fine particles experience Van der Waals attraction, electric double-layer repulsion, and hydrodynamic forces. Injection brine salinity and flow rate affect repulsion and hydrodynamic forces. Accurate CSC and critical flow rate prediction are crucial to prevent formation damage. This research presents a novel DLVO modeling approach for predicting and controlling fines migration in sandstone reservoirs. DLVO models are developed to predict fines migration initiation and CSCs for monovalent and divalent brines at different reservoir salinities. The models incorporate 0.1wt% silica nanofluid, resulting in reduced CSC. Zeta potentials are measured for sand-fine-brine (SFB) systems with and without silica nanofluid. Surface forces between fines and sand are calculated at varying salinities to predict CSC. A fines detachment model is also developed using zeta potentials and electrostatic, gravitational, and hydrodynamic forces to predict critical flow rate under changing salinity. Models are validated through core flood experiments conducted on Berea Upper Gray sandstone cores. The zeta potentials of SFB systems are measured at room temperature using a zeta-sizer. In pre-nanofluid application, zeta potentials range from -35 mV to -27 mV, while post-application, they range from -28.6 mV to -27 mV. Zeta potentials and corresponding ionic strengths are used in the DLVO model to calculate the total interaction potential (PT). The DLVO model predicts a CSC of around 0.11 M for NaCl brine, where total DLVO interactions shift from negative to positive. Incorporating silica nanofluid reduces CSC further to 0.075 M, showcasing the effectiveness of nanoparticles. CSCs of 0.0001 M are predicted for MgCl2 and CaCl2 brines. The novel fines detachment model, using zeta potentials, electrostatic, gravitational, and hydrodynamic forces, predicts critical flow rates of 0.9 cc/min, 2.9 cc/min, and 3.8 cc/min for NaCl concentrations of 0.15 M, 0.2 M, and 0.25 M, respectively. Core flood experiments validate the models, closely matching predictions: CSCs of 0.11 M and 0.075 M before and after nanofluid treatment, and critical flow rates of 1 cc/min, 3 cc/min, and 4 cc/min for NaCl concentrations of 0.15 M, 0.2 M, and 0.25 M. This validation confirms the reliability and applicability of the models in fines migration control and reservoir management. Estimating CSC and critical flow rate is essential to prevent formation damage during oil recovery processes, such as waterflooding and alkaline flooding. The proposed DLVO models serve as valuable tools for predicting CSC and critical flow rates for different salinities, minimizing the need for extensive experimentation. Incorporating nanotechnology and its experimental validation offers new insights for controlling fines migration within the practical limits of fluid salinity and injection rates.

Publisher

SPE

同舟云学术

1.学者识别学者识别

2.学术分析学术分析

3.人才评估人才评估

"同舟云学术"是以全球学者为主线,采集、加工和组织学术论文而形成的新型学术文献查询和分析系统,可以对全球学者进行文献检索和人才价值评估。用户可以通过关注某些学科领域的顶尖人物而持续追踪该领域的学科进展和研究前沿。经过近期的数据扩容,当前同舟云学术共收录了国内外主流学术期刊6万余种,收集的期刊论文及会议论文总量共计约1.5亿篇,并以每天添加12000余篇中外论文的速度递增。我们也可以为用户提供个性化、定制化的学者数据。欢迎来电咨询!咨询电话:010-8811{复制后删除}0370

www.globalauthorid.com

TOP

Copyright © 2019-2024 北京同舟云网络信息技术有限公司
京公网安备11010802033243号  京ICP备18003416号-3