Effect of Nano-SiO2, Nano-TiO2 and Nano-Al2O3 Addition on Fluid Loss in Oil-Well Cement Slurry
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Abstract
Abstract In this article, incorporation of nano-SiO2 (NS), nano-TiO2 (NT) and nano-Al2O3 (NA) particles and their binary and ternary blends on water filtration in oil-well cement slurry was examined. The nanoparticle contents were chosen at proportions corresponding to 1, 2, 3 and 4% based on the weight of cement. The experimental specimens were tested at three various temperatures of 70, 80 and 90 °C using a gas pressure of 1000 psi. The quantity of water filtrate collected was measured in milliliter (mL) at 30 min after the test begins. The results consistently indicate that an additional of NS, NT and NA particles independently, reduced the loss of liquid in cement, and its performance varies with temperature and the nanoparticle dosages. The 3% NS usage delivered strong evidence in lessening fluid loss compared to the other results by reducing the loss up to 72%. When collective impact of nanomaterials was determined, the fluid retainment was also improved. The replacement of 4% NST reduced fluid loss by the most compared to NSA and NTA binary groups. In-case of ternary combination, NSTA showed a highest reduction of the water loss by 58–60% likened to the plain samples at the concentration of 4%. The key investigation of this paper clearly suggested that the efficacy of Class G cement having nanoparticles to trap its water is dependent on the nanoparticle contents. The lessening of water filtration might be explicated by the filling capability of nano-scale particles. Nanoparticles can plug the openings within the oil-well cement slurry matrix, thus promoting the retainability of water. Besides, nanoparticles quickens the hydration products by creating dense interlocking C–S–H gels for bridging cement grains and forming enclosed structure which can stop the liquid from escaping the slurry.
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Research context
OpenAlex topics: Drilling and Well Engineering · Concrete and Cement Materials Research · Tunneling and Rock Mechanics
SciVX discovery tags are terminology-based. OpenAlex topics are source-provided classifications.
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