The drill bit is the most essential tool in drilling operation and optimum bit selection is one of the main challenges in planning and designing new wells. Conventional bit selections are mostly based on the historical performance of similar bits from offset wells. In addition, it is done by different techniques based on offset well logs. However, these methods are time consuming and they are not dependent on actual drilling parameters. The main objective of this study is to optimize bit selection in order to achieve maximum rate of penetration (ROP). In this work, a model that predicts the ROP was developed using artificial neural networks (ANNs) based on 19 input parameters. For the modeling part, a one-dimension mechanical earth model (1D MEM) parameters, drilling fluid properties, and rig- and bit-related parameters, were included as inputs. The optimizing process was then performed to propose the optimum drilling parameters to select the drilling bit that provides the maximum possible ROP. To achieve this, the corresponding mathematical function of the ANNs model was implemented in a procedure using the genetic algorithm (GA) to obtain operating parameters that lead to maximum ROP. The output will propose an optimal bit selection that provides the maximum ROP along with the best drilling parameters. The statistical analysis of the predicted bit types and optimum drilling parameters comparing the actual flied measured values showed a low root mean square error (RMSE), low average absolute percentage error (AAPE), and high correction coefficient (R2). The proposed methodology provides drilling engineers with more choices to determine the best-case scenario for planning and/or drilling future wells. Meanwhile, the newly developed model can be used in optimizing the drilling parameters, maximizing ROP, estimating the drilling time, and eventually reducing the total field development expenses.
Background: Hypothyroidism is the most abundant thyroid disorder worldwide. For decades, levothyroxine was the main effective pharmacological treatment for hypothyroidism. A variety of factors can influence levothyroxine dose, such as genetic variations. Studying the impact of genetic polymorphisms on the administration of medications was risen remarkably. Different genetic variations were investigated that might affect levothyroxine dose requirements, especially the deiodinase enzymes. Deiodinase type 2 genetic polymorphisms’ impact on levothyroxine dose was studied in different populations. Objective: To examine the association of the two single nucleotide polymorphism (SNP)s of deiodinase type 2 (rs225013 and rs225014) and le
... Show MoreBackground: Hypothyroidism is the most abundant thyroid disorder worldwide. For decades, levothyroxine was the main effective pharmacological treatment for hypothyroidism. A variety of factors can influence levothyroxine dose, such as genetic variations. Studying the impact of genetic polymorphisms on the administration of medications was risen remarkably. Different genetic variations were investigated that might affect levothyroxine dose requirements, especially the deiodinase enzymes. Deiodinase type 2 genetic polymorphisms’ impact on levothyroxine dose was studied in different populations.
Objective: To examine the association of the two single nucleotide polymorphism (SNP)s of deiodinase t
... Show MoreA discussion about the repercussions of the exchange rate on the behavior of stock markets became one of the basic principles of financial economics. The Istanbul Stock Exchange , considered one of the fastest financial markets growing in the region, driven by solid economic activity, for a diversified economy which classified as one of the the fastest growing economies in the world. However, the aforementioned market witnessed sharp fluctuations in the past few months, coinciding with the continuous fluctuations in the exchange rate of the Turkish lira, posing a serious challenge to the economic and investment environment in a c
... Show MoreThe map of permeability distribution in the reservoirs is considered one of the most essential steps of the geologic model building due to its governing the fluid flow through the reservoir which makes it the most influential parameter on the history matching than other parameters. For that, it is the most petrophysical properties that are tuned during the history matching. Unfortunately, the prediction of the relationship between static petrophysics (porosity) and dynamic petrophysics (permeability) from conventional wells logs has a sophisticated problem to solve by conventional statistical methods for heterogeneous formations. For that, this paper examines the ability and performance of the artificial intelligence method in perme
... Show MoreIn high-dimensional semiparametric regression, balancing accuracy and interpretability often requires combining dimension reduction with variable selection. This study intro- duces two novel methods for dimension reduction in additive partial linear models: (i) minimum average variance estimation (MAVE) combined with the adaptive least abso- lute shrinkage and selection operator (MAVE-ALASSO) and (ii) MAVE with smoothly clipped absolute deviation (MAVE-SCAD). These methods leverage the flexibility of MAVE for sufficient dimension reduction while incorporating adaptive penalties to en- sure sparse and interpretable models. The performance of both methods is evaluated through simulations using the mean squared error and variable selection cri
... Show MoreDouble skin ventilated roof is one of the important passive cooling techniques that aims to reduce solar heat gain through roofs by reducing both the conduction and convection heat transfer from the roof to the ceiling of buildings. On the other hand, radiant barrier system (RBS) is very powerful in blocking the radiation heat transfer between the two skins. In this research,the effect of placing a thin layer of aluminium foil at different locations on the thermal insulation performance of a double skin ventilated roof model is investigated experimentally and the optimum location that transmits less heat flux from the lower skinis specified.The model is made of two parallel inclined galvanized steel plates. Galvanized steel has been used
... Show MoreThe Financial systems can be classified into two types. The first is the market–oriented, which is applied in United States and United Kingdom. While the second is bank-oriented as in Japan and Germany.
This study tries to explain the reasons which make some countries adopt the first one instead of the second, and the contrary. So the study consists of three sections. The first deals with the concept of financial system and it are functions. The second displays the indicators which are used to classify the financial systems, while the third one is devoted to the factors that determine the type of financial system .These sections followed by some conclusions.
Wind energy is considered one of the most important sources of renewable energy in the world, because it contributes to reducing the negative effects on the environment. The most important types of wind turbines are horizontal and vertical axis wind turbines. This work presents the full details of design for vertical axis wind turbine (VAWT) and how to find the optimal values of necessary factors. Additionally, the results shed light on the efficiency and performance of the VAWT under different working conditions. It was taken into consideration the variety of surrounding environmental conditions (such as density and viscosity of fluid, number of elements of the blade, etc.) to simulate the working of vertical wind turbines under di
... Show MoreBackground: The treatment of schizophrenia typically involves the use of olanzapine (OLZ), a typical antipsychotic drug that has poor oral bioavailability due to its low solubility and first-pass effect. Objective: To prepare and optimize OLZ as nanoparticles for transdermal delivery to avoid problems with oral administration. Methods: The nanoprecipitation technique was applied for the preparation of eight OLZ nanoparticles by using different polymers with various ratios. Nanoparticles were evaluated using different methods, including particle size, polydispersity index (PDI), entrapment efficiency (EE%), zeta potential and an in vitro release study. The morphology was evaluated by a field emission scanning electron microscope (F
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