Drilling 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

The food web is a crucial conceptual tool for understanding the dynamics of energy transfer in an ecosystem, as well as the feeding relationships among species within a community. It also reveals species interactions and community structure. As a result, an ecological food web system with two predators competing for prey while experiencing fear was developed and studied. The properties of the solution of the system were determined, and all potential equilibrium points were identified. The dynamic behavior in their immediate surroundings was examined both locally and globally. The system’s persistence demands were calculated, and all conceivable forms of local bifurcations were investigated. With the aid of MATLAB, a numerical simu

In this research Artificial Neural Network (ANN) technique was applied to study the filtration process in water treatment. Eight models have been developed and tested using data from a pilot filtration plant, working under different process design criteria; influent turbidity, bed depth, grain size, filtration rate and running time (length of the filtration run), recording effluent turbidity and head losses. The ANN models were constructed for the prediction of different performance criteria in the filtration process: effluent turbidity, head losses and running time. The results indicate that it is quite possible to use artificial neural networks in predicting effluent turbidity, head losses and running time in the filtration process, wi

In this work, the photodetection performance of polyvinyl alcohol (PVA) nanofibers and its composite with yttrium oxide (Y2O3) at different concentrations (2.5, 5, 10) wt% are examined deposited on p-type Si with (111) orientation. Electrospinning technique was used to create nanofiber composites. Adding Y2O3 significantly impacts the PVA nanofibers where ultraviolet-visible (UV-Vis) spectroscopy optical absorption energy gap decreases with increased concentration (2.8, 2.6, and 2.3) eV. X-ray diffraction was used to investigate crystal structure, which is cubic structure. The chemical composition study was conducted using Fourier transform infrared spectroscopy (FTIR) spectra, which revealed the stretching vibrations related to the Y-O bon

In the field of implantology, peri-implantitis is still a common complication of implant failure. Similar to periodontal disease, this kind of pathological condition is characterized by inflammation of the tissues surrounding dental implants or fillings. The sources of infection have been shown to be chronic periodontitis and poor maintenance of the communion. A thorough examination of the intricate components of peri-implantitis was sought in this review in order to identify common characteristics of the disease with regard to bacteria, biofilm formation, host immunological responses, diagnostic tools, and therapeutic treatments. The aim of this study was to provide a detailed overview of the different bacterial species associated