Nanoparticles (NPs) have unique capabilities that make them an eye-opener opportunity for the upstream oil industry. Their nano-size allows them to flow within reservoir rocks without the fear of retention between micro-sized pores. Incorporating NPs with drilling and completion fluids has proved to be an effective additive that improves various properties such as mud rheology, filtration, thermal conductivity, and wellbore stability. However, the biodegradability of drilling fluid chemicals is becoming a global issue as the discharged wetted cuttings raise toxicity concerns and environmental hazards. Therefore, it is urged to utilize chemicals that tend to break down and susceptible to biodegradation. This research presents the practical application of bio-based Zinc Oxide nanoparticles (ZnO NPs) prepared chemically from celery leaf plant extract as green additive in water-based mud drilling fluid (WBM). The study aimed to evaluate the filtration and thermal stability of WBM using green-synthesized ZnO NPs. The results showed that the ZnO NPs have minimal effect of mud density, but significant improvement in mud thermal stability and filtration properties were attained with concentrations lower than 1g. The fluid loss rate was reduced by 33% with 0.45g of ZnO nanoparticles, and the thinnest mud cake was obtained as well. In terms of thermal stability, the bio-based ZnO NPs greatly enhanced the rheological properties of WBM at elevated temperatures. The rate of increment in plastic viscosity (PV) or decrement in yield point (YP) and gel strength occurred in a controllable manner compared to the rheological properties of base mud at high temperatures reaching 90°C. This study provides insight into the effect of green-synthesized ZnO nanoparticles on the performance of water-based mud and highlights their potential as an effective and environmentally friendly additive for the oil and gas industry.
Background: Colonization of soft denture liners by Candida albicans and other microorganisms continued to be a serious problem. The aim of this study was to evaluate the effect of incorporating silver nanoparticles into heat cured acrylic-based soft denture liner on the antifungal activity, and on water sorption, solubility, shear bond strength and color change of the soft lining material. Furthermore, evaluating the amount of silver released. Materials and methods: Silver nanoparticles were incorporated into soft denture liner in different percentages (0.05%, 0.1% and 0.2% by weight). Four hundred and twenty specimens were prepared and divided into five groups according to the test to be performed. The antifungal activity of the soft liner
... Show MoreGreen synthesis of silver nanoparticles (AgNPs) using different plant parts has shown a great potential in medicinal and industrial applications. In this study, AgNPs were in vitro green synthesized using A. graecorum, and its antifungal and antitumoractivities were investigated. Scanning electron microscopy (SEM) image result indicated spherical shape of AgNPs with a size range of 22-36 nm indicated by using Image J program. The functional groups indicated by Fourier-transform infrared spectroscopy (FTIR) represented the groups involved in the reduction of silver ion into nanoparticles. Alhagi graecorum AgNPs inhibited MCF-7 breast cancer cell line growth in increased concentration depend manner, significant differences shown at
... Show MoreAntibiotics resistant bacteria have become a global problem as a result of the unprogrammed use of antibiotics, resulting in bacterial strains resistant to many antibiotics, or to all available antibiotics. Plants are a good source of primary and secondary metabolites that have a major role in reducing silver nitrate to silver nanoparticles (AgNPs). The production of these nanoparticles were carried out by using aqueous extract of Carthamus oxycantha M.Bieb. This can be verified by color change of the reaction solution from yellow to dark brown because of the excitation of the surface plasmon resonance. AgNPs were characterized by UV-Vis spectroscopy, where they recorded the peak at 420 nm. Fourier Transformation-infrared (FTIR)
... Show MoreThis study was conducted in fruit production lathe house of the Department Of Horticulture And Landscape Gardening, in the station (B), College Of Agricultural Engineering Sciences, University Of Baghdad, Al-Jaadria for 8 months, began from 1/3/2019 to 1/9/2019 to investigate the responses of C35 Citrus rootstock to influence of foliar spraying of zinc and irrigation with smoking-water at 2 years old saplings. the study included two factors, first factor was three concentrations of Zinc Element Z0(0 mg.l-1), Z1(50 mg.l-1) and Z2(75 mg.l-1) that sprays at leave. The second factor was watering saplings with smoke-water in three concentrations S0(0 vol.vol-1), S1(0.1 vol.vol-1) and (0.2vol.vol-1), and their interaction. The experiment was fact
... Show MoreDrilling deviated wells is a frequently used approach in the oil and gas industry to increase the productivity of wells in reservoirs with a small thickness. Drilling these wells has been a challenge due to the low rate of penetration (ROP) and severe wellbore instability issues. The objective of this research is to reach a better drilling performance by reducing drilling time and increasing wellbore stability.
In this work, the first step was to develop a model that predicts the ROP for deviated wells by applying Artificial Neural Networks (ANNs). In the modeling, azimuth (AZI) and inclination (INC) of the wellbore trajectory, controllable drilling parameters, unconfined compressive strength (UCS), formation
... Show MoreDrilling deviated wells is a frequently used approach in the oil and gas industry to increase the productivity of wells in reservoirs with a small thickness. Drilling these wells has been a challenge due to the low rate of penetration (ROP) and severe wellbore instability issues. The objective of this research is to reach a better drilling performance by reducing drilling time and increasing wellbore stability.
In this work, the first step was to develop a model that predicts the ROP for deviated wells by applying Artificial Neural Networks (ANNs). In the modeling, azimuth (AZI) and inclination (INC) of the wellbore trajectory, controllable drilling parameters, unconfined compressive strength (UCS), formation
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