Minimizing Adsorption of Anionic Surfactant in Alkaline-Surfactant-Polymer System: Effects of pH and Surfactant Concentration

Key Engineering Materials(2023)

引用 0|浏览1
暂无评分
摘要
Alkaline-surfactant-polymer (ASP) flooding has been identified as the most effective enhanced oil recovery (EOR) technique to boost up the production of crude oil and improve the recoverable reserves. However, surfactant loss into the formation due to adsorption has been one of the issues, which could degrade the efficiency of the process. This study highlights the static adsorption of anionic sodium dodecyl sulphate (SDS) surfactant on the quartz sand with presences of alkaline and polymer at different pH and surfactant concentration. The critical micellar concentration (CMC) of SDS was determined using surface tension method and found at 0.22wt%. Three different systems were formulated namely A, B and C referring to the Surfactant formulation, Alkaline-Surfactant (AS) formulation and Alkaline-Surfactant-Polymer (ASP) formulation, respectively. For static adsorption tests, ASP system was formulated by adding 10,000 ppm sodium carbonate (Na 2 CO 3 ) and 500 ppm of anionic Hydrolyzed Polyacrylamide (HPAM) polymer into the surfactant solution. The formulation was then mixed with the quartz sand at a fixed mass to volume ratio of 1:5. The adsorption tests involved shaking the mixtures, centrifuging, and analysing the supernatant solutions using UV-Visible spectrophotometer for adsorption measurement. The adsorption tests resulted in low adsorption at higher pH and low surfactant concentration. It was discovered that the lowest surfactant adsorption exhibited by ASP system with approximate reductions of 65% and 63% as compared to surfactant formulation at ~pH 12 and 2000 ppm surfactant concentration, respectively. Thus, anionic surfactant has a great performance in ASP system compared to its individual formulation, resulting in lower surfactant adsorption.
更多
查看译文
关键词
anionic surfactant,adsorption,alkaline-surfactant-polymer
AI 理解论文
溯源树
样例
生成溯源树,研究论文发展脉络
Chat Paper
正在生成论文摘要