Laponite nanoparticle as a multi-functional additive in water-based drilling fluids
Source abstract
Abstract
In recent years, shale gas has been an important fossil fuel. However, drilling in porous and water-sensitive shale using water-based drilling fluids (WBDs) can cause various problems, such as cuttings sedimentation, water penetration into the shale and drill pipe sticking. To solve these problems, this study demonstrated a two-dimensional nano-material (Laponite) as a multi-functional additive in WBDs for rheological control, nano-crack plugging and decreased drill pipe sticking. First, during rheological testing, the 2% Laponite suspension maintained good shear-thinning behavior in the elastic modulus (G′) and apparent viscosity after hot rolling at 150 °C compared with 6% sodium bentonite (Na-BT). Additionally, transmission electron microscopy analysis of the Laponite suspension demonstrated that the nano-sized Laponite layers maintained a better spatial network. Second, the Brunner–Emmet–Teller analysis of shale nano-pores indicated that shale immersed in the 2% Laponite suspension maintained a lower 10–100 nm nano-pore volume compared with 2% nano-SiO2 and 4% Na-BT. Furthermore, scanning electron microscopy of the shale showed that the Laponite layers plugged into the nano-pores, prevented free water from penetrating into the nano-cracks and decreased shale swelling in water. Third, the American Petroleum Institute filtration test showed that the Laponite suspension formed a far more smooth and compact filtrate cake than the Na-BT suspension. These unique abilities suggest that Laponite has the potential to be a multi-functional additive in WBDs for shale drilling to greatly improve rheological and nano-crack plugging properties and filtrate cake quality.
Source: openaire · Quality: candidate unverified · Source record ↗
Research context
OpenAlex topics: Drilling and Well Engineering · Hydraulic Fracturing and Reservoir Analysis · Hydrocarbon exploration and reservoir analysis
SciVX discovery tags are terminology-based. OpenAlex topics are source-provided classifications.
References (50)
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