Apparent and plastic viscosities prediction of water-based drilling fluid using response surface methodology

A comprehensive review of viscoelastic polymer flooding in sandstone and carbonate rocks

Polymer flooding is a proven chemical Enhanced Oil Recovery (cEOR) method that boosts oil production beyond waterflooding. Thorough theoretical and practical knowledge has been obtained for this technique through numerous experimental, simulation, and field works. According to the conventional belief, this technique improves macroscopic sweep efficiency due to high polymer viscosity by producing moveable oil that remains unswept after secondary recovery. However, recent studies show that in addition to viscosity, polymer viscoelasticity can be effectively utilized to increase oil recovery by mobilizing residual oil and improving microscopic displacement efficiency in addition to macroscopic sweep efficiency. The polymer flooding is frequently implemented in sandstones with limited application in carbonates. This limitation is associated with extreme reservoir conditions, such as high concentrations of monovalent and divalent ions in the formation brine and ultimate reservoir temperatures. Other complications include the high heterogeneity of tight carbonates and their mixed-to-oil wettability. To overcome the challenges related to severe reservoir conditions, novel polymers have been introduced. These new polymers have unique monomers protecting them from chemical and thermal degradations. Monomers, such as NVP (N-vinylpyrrolidone) and ATBS (2-acrylamido-2-methylpropane sulfonic acid), enhance the chemical resistance of polymers against hydrolysis, mitigating the risk of viscosity reduction or precipitation in challenging reservoir conditions. However, the viscoelasticity of these novel polymers and their corresponding impact on microscopic displacement efficiency are not well established and require further investigation in this area. In this study, we comprehensively review recent works on viscoelastic polymer flow under various reservoir conditions, including carbonates and sandstones. In addition, the paper defines various mechanisms underlying incremental oil recovery by viscoelastic polymers and extensively describes the means of controlling and improving their viscoelasticity. Furthermore, the polymer screening studies for harsh reservoir conditions are also included. Finally, the impact of viscoelastic synthetic polymers on oil mobilization, the difficulties faced during this cEOR process, and the list of field applications in carbonates and sandstones can also be found in our work. This paper may serve as a guide for commencing or performing laboratory- and field-scale projects related to viscoelastic polymer flooding.

Achieving Practical Venue Recycle of Waste Oil-Based Drilling Fluids with Vacuum Distillation Technology

Drilling fluids are essential operating additives for extracting oil and shale gas. Thus, their pollution control and recycling utilization are significant to petrochemical development. Vacuum distillation technology was used in this research to handle waste oil-based drilling fluids and achieve reutilization. Briefly, recycled oil and recovered solids can be obtained from waste oil-based drilling fluids whose density is 1.24-1.37 g/cm³ by vacuum distillation under the condition of an external heat transfer oil temperature of 270 ± 5 °C and a reaction pressure below 5 × 10³ Pa. Meanwhile, recycled oil has excellent apparent viscosity (AV, 21 mPa·s) and plastic viscosity (PV, 14 mPa·s), which could be used as a substitute for 3# white oil. Furthermore, PF-ECOSEAL prepared by recycled solids exhibited better rheological properties (27.5 mPa·s AV, 18.5 mPa·s PV, and 9 Pa yield point) and plugging performance (32 mL V₀, 1.90 mL/min^1/2V_sf) than drilling fluids prepared with the conventional plugging agent PF-LPF. Our work confirmed that vacuum distillation is a valid technology in innocuity treatment and resource utilization of drilling fluids and has great value in industrial applications.

Square wave voltammetric approach to leptin immunosensing and optimization of driving parameters with chemometrics

Square wave voltammetry serves as an effective analytical means to evaluate antigen-antibody coupling at the solid-liquid interface. Herein, we describe 3-aminopropyltrimethoxysilane (APTMS) induced irreversible immobilization of anti-leptin to micellar gold nanoparticles (AuNPs). Antibodies (Abs) were orthogonally loaded on micellized AuNP assemblies via amino residual groups. The ratio of bound Ab molecules was determined by the Bradford assay. The AuNP/Ab layer modified electrodes with variable antibody surface coverage (∼400 ± 55-200 ± 30 Ab/NP) were analyzed in terms of change in backward, net current (Ip) components. The rate of antigen coupling was found to be consistent with the variation in antibody density as well as the binding affinity. The lowest detection limit was observed at the femtomolar level (0.25 fM/mL) over a wide range of antigen concentration (6.2 ng/mL to 0.12 fg/mL). The variables affecting the epitope-paratope interaction were further optimized using a chemometric approach and a response surface methodology (RSM).

An Inverse Emulsion Polymer as a Highly Effective Salt- and Calcium-Resistant Fluid Loss Reducer in Water-Based Drilling Fluids

To control the fluid loss of water-based drilling fluids (WBDFs) in salt-gypsum formations, a nano-SiO₂ graft copolymer was prepared by inverse emulsion polymerization. The polymer (EAANS) was prepared with acrylamide, 2-acrylamido-2-methyl-1-propane sulfonic acid, N-vinylpyrrolidone, and KH570-modified nano-silica (M-SiO₂) as raw materials. The molecular structure and morphology of EAANS were characterized by Fourier transform infrared spectroscopy, nuclear magnetic resonance, thermogravimetric analysis, transmission electron microscopy (TEM), and other methods. In the temperature range of 150 °C, 2 wt % EAANS can reduce the API filtration volume of the base slurry to within 20 mL and the HP-HT filtration volume at 150 °C to 21.8 mL. More importantly, 2 wt % EAANS can maintain the API filtration volume less than 10 mL even when the concentration of NaCl or CaCl₂ was as high as 36 or 30 wt %, and as the salt/calcium content increased, the amount of filtration continued to decrease. The results of TEM, X-ray diffraction, particle size distribution, and scanning electron microscopy showed that the fluid loss control mechanism of EAANS was that EAANS can form a crosslinked network structure in the solution and adsorb on the clay surface, so as to reduce the particle size of clay particles, increase the proportion of fine particles in drilling fluids, and finally form a dense filter cake to reduce the filtration volume. Because of the excellent filtration performance of EAANS at high Na⁺/Ca²⁺ concentration, EAANS can become a promising WBDF fluid loss reducer in salt-gypsum formations.

Prediction of the Rheological Properties of Invert Emulsion Mud Using an Artificial Neural Network

Successful drilling operations require optimum well planning to overcome the challenges associated with geological and environmental constraints. One of the main well design programs is the mud program, which plays a crucial role in each drilling operation. Researchers focus on modeling the rheological properties of the drilling fluid seeking for accurate and real-time predictions that confirm its crucial potential as a research point. However, only substantial studies have real impact on the literature. Several AI-based models have been proposed for estimating mud rheological properties. However, most of them suffer from non-being field applicable attractive due to using non-readily field parameters as input variables. Some other studies have not provided a comprehensive description of the model to replicate or reproduce results using other datasets. In this study, two novel robust artificial neural network (ANN) models for estimating invert emulsion mud plastic viscosity and yield point have been developed using actual field data based on 407 datasets. These datasets include mud plastic viscosity (PV), yield point (YP), mud temperature (T), marsh funnel viscosity (MF), and solid content. The mathematical base of each model has been provided to provide a clear means for models' replicability. Results of the evaluation criteria depicted the outstanding performance and consistency of the proposed models over extant ANN models and empirical correlations. Statistical evaluation revealed that the plastic viscosity ANN model has a coefficient of determination (R ²) of 98.82%, a root-mean-square error (RMSE) of 1.37, an average relative error (ARE) of 0.12, and an absolute average relative error of 2.69, while for yield point, this model has a coefficient of determination (R ²) of 94%, a root-mean-square error (RMSE) of 0.76, an average relative error (ARE) of -0.67, and an absolute average relative error of 3.18.