​​Synthesis of graphene oxide using modified hammers method as fluid loss control additive for water-based drilling fluid (WBDF)​

Nik Khairul Irfan Nik Ab Lah, Wan Al Harrif Alif Wan Zaini,Nur Hidayati Othman,Nur Hashimah Alias,Munawar Zaman Shahruddin, M. Sayuti

Malaysian Journal of Chemical Engineering and Technology (MJCET)(2023)

引用 0|浏览1
暂无评分
摘要
Water-based drilling fluid (WBDF) is one of the commonly used fluids in drilling operations due to its low cost and environmental advantages compared to oil-based fluid (OBF) and synthetic-based fluid (SBF). The effectiveness of a drilling fluid is mainly dependent on its rheological and filtration properties and these properties are strongly correlated to the type of additives used during the formulation of drilling mud. This study aims to investigate the use of graphene oxide (GO) as a nano-additive in WBDF and evaluate its influence on the rheology and filtration properties of the drilling fluid. Basic rheological properties such as plastic viscosity, yield point, filter cake thickness and density were examined. GO was synthesised using modified Hummer’s method and characterised using x-ray diffractometer (XRD), Fourier transform infrared spectroscopy (FTIR), thermogravimetric analyser (TGA) and scanning electron microscope (SEM) to confirm the properties of GO. XRD analysis shows that graphite was successfully oxidised and exfoliated to GO. The FTIR analysis confirms the presence of C–O, C=C, and O–H bonds in the synthesised GO. The amount of GO added to the WBDF was varied and changes in the rheological properties (density, plastic viscosity, yield point and mud cake thickness) were studied. It was observed that drilling fluid developed using GO has better rheological and filtration properties than drilling fluid formulated without GO. The mud thickness was reduced after the addition of GO, indicating that GO-WBDFs have the capability to control fluid loss into the formation during drilling activities.
更多
查看译文
关键词
graphene oxide,drilling fluid,hammers method,fluid loss control,water-based
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