Experimentally Validated First-Principles Multivariate Modeling for Rheological Study and Design of Complex Drilling Nanofluid Systems

Abstract

The demand for more efficient and reliable oil and gas drilling fluid systems drives their development with unprecedented sophistication: the key challenge is to achieve predictable rheological properties, but also to enable their judicious customization, particularly for High Temperature High Pressure) (HTHP) applications and tough environments. This study presents the development and validation of a first-principles multivariate rheological model, allowing yield stress and viscosity prediction for new drilling fluids with iron oxide nanoparticles (NP). Previous studies show that water-bentonite suspensions of variable Fe3O4 NP concentration exhibit non-Newtonian shear-thinning behavior, accurately captured via a tri-parametric nonisothermal Herschel-Bulkley (HB) rheological model form; nonlinear least squares regression yields reliable parameter sets. The resulting fluid shear stress and viscosity are expressed as explicit functions of independent variables (shear rate, temperature, NP concentration) and the correlations are validated against experimental data. A new parameter set must be computed by nonlinear regression for each combination of conditions, a necessity compromising the predictive potential of this data-driven rheological modeling approach. To obtain truly predictive, first-principles rheological models, a systematic strategy is presented: shear stress and viscosity have now been expressed as physics-based (not data-driven) multivariate correlations of the aforementioned independent variables, using microscopic arguments for colloidal particle behavior, as confirmed by Transmission/Scanning Electron Microscopy (TEM/SEM) images. Shear stress is thus studied by distinguishing key additive contributions, on the basis of explicit bounds on colloidal inter-particle distances: our novel functional forms consistently capture the non-Newtonian fluid behavior, but require only one parameter set computation for the entire dataset.

Nano-Based Drilling Fluids: A Review

“…Gerogiorgis et al [8] started from microstructural arguments and force equilibria assumptions and developed physics-based (not data-driven) correlations. They developed first-principles rheological models of nano-enhanced drilling fluids containing Fe 3 O 4 NP, which are considered to be explicit multivariate functions of temperature, NP volume fraction and shear rate.…”

“…Modeling of the rheology of nano-ehanced drilling fluids, as a function of shear rate, nanoparticle volume fraction and temperature, aspects which are critical toward high-fidelity computational modelling for the design and planning of cost-effective drilling campaigns, has also been reported [6][7][8].…”

A comprehensive review of nanoparticles applications in the oil and gas industry

“…One of these industries is the oil and gas industry, where the revolution of nanotechnology applications covered different areas in both upstream and downstream. A quick look at the recent published applications related to nanotechnology reveals a wide range of nanoterminology such as nanoparticles (Sensoy et al 2009;Ogolo et al 2012;Hafiz et al 2018), nanocomposite (Lecolier et al 2005;Pourafshary et al 2009;Chauhan and Ojha 2016;Kumar et al 2018), nanomembrane (Seland et al 1992; Kong and Ohadi 2010;Shen and Sheng 2016;Guo et al 2013;Ventura et al 2017;Folio et al 2018), nanosensors (Sudarshan et al 2001;Piantanida et al 2013), nanorobot (Singh and Bhat 2006;Joshua 2014), nanofluids (Kanj et al 2009;Alomair et al 2014;Gerogiorgis et al 2017;Yuan and Moghanloo 2018).…”

Nanotechnology and global energy demand: challenges and prospects for a paradigm shift in the oil and gas industry

“…Nanoparticles are considered to be engineered to have at least a dimension in the order of 100 nm. The uniqueness of nanoparticles is tied to its size-dependent properties, which are a consequence of its large surface to volume ratio, thereby enabling surface atoms/molecules to have a significant impact on its properties (Bennetzen and Mogensen 2014;Gerogiorgis et al 2017). Furthermore, due to the small size of nanoparticles, the amount of surface atoms is large compared to the bulk atoms.…”