It is well known that the rate of penetration is a key function for drilling engineers since it is directly related to the final well cost, thus reducing the non-productive time is a target of interest for all oil companies by optimizing the drilling processes or drilling parameters. These drilling parameters include mechanical (RPM, WOB, flow rate, SPP, torque and hook load) and travel transit time. The big challenge prediction is the complex interconnection between the drilling parameters so artificial intelligence techniques have been conducted in this study to predict ROP using operational drilling parameters and formation characteristics. In the current study, three AI techniques have been used which are neural network, fuzzy inference system and genetic algorithm. An offset field data was collected from mud logging and wire line log from East Baghdad oil field south region to build the AI models, including datasets of two wells: well 1 for AI modeling and well 2 for validation of the obtained results. The types of interesting formations are sandstone and shale (Nahr Umr and Zubair formations). Nahr Umr and Zubair formations are medium –harder. The prediction results obtained from this study showed that the ANN technique can predict the ROP with high efficiency as well as FIS technique could achieve reliable results in predicting ROP, but GA technique has shown a lower efficiency in predicting ROP. The correlation coefficient and RMSE were two criteria utilized to evaluate and estimate the performance ability of AI techniques in predicting ROP and comparing the obtained results. In the Nahr Umr and Zubair formations, the obtained correlation coefficient values for training processes of ANN, FIS and GA were 0.94, 0.93, and 0.76 respectively. Data sets from another well (well 2) in the same field of interest were utilized to validate of the developed models. Datasets of well 2 were conducted against sandstone and shale formations (Nahr Umr and Zubair formations). The results revealed a good matching between the actual rate of penetration values and the predicted ROP values using two artificial intelligence techniques (neural network, and fuzzy inference technique). In contrast, the genetic algorithm model showed overestimation/ underestimation of the rate of penetration against sandstone and shale formations. This means that the optimum prediction of rate of penetration can be obtained from neural network model rather than using genetic algorithm and genetic algorithm techniques. The developed model can be successfully used to predict the rate of penetration and optimize the drilling parameters, achieving reduce the cost and time of future wells that will be drilled in the East Baghdad Iraqi oil field.
The aims of this study are to measure the defect rate and analyze the problems of production of ready concrete mixture plant by using Six Sigma methodology which is a business strategy for operations improvement depending basically on the application of its sub-methodology DMAIC improvement cycle and the basic statistical tools where the process sigma level of concrete production in the case study was 2.41 σ.
A New ligand, N-(2-oxo-1,2- Dihydropyrimidin-4- ylcarbamothioyl) Acetamide (DPA) was prepared by reaction of iso thiosyanate derivative with Cytosine. The ligand has been characterized through elemental analysis, H1 NMR, C13NMR, FT-IR, and UV Visible spectra, such ligand’s transition metal complexes have been characterized through conductivity measurement, FT-IR, UV Visible spectra and magnetic susceptibility, all the complexes of this ligand are solid crystal and molar ratio (2:1) (ligand: metal). The form of molecular for these complexes octa hedral. The general formula [M(DPA)2Cl2], where M+2 = (Mn, Co, Ni, Cu, Zn, Cd, Hg).
The synthesis of ligands with N2S2 donor sets that include imine, an amide, thioether, thiolate moieties and their metal complexes were achieved. The new Schiff-base ligands; N-(2-((2,4-diphenyl-3-azabicyclo[3.3.1]nonan-9-ylidene)amino)ethyl)-2-((2-mercaptoethyl)thio)-acetamide (H2L1) and N-(2-((2,4-di-p-tolyl-3-azabicyclo[3.3.1]nonan-9-ylidene)amino)ethyl)-2-((2-mercaptoethyl)thio) acetamide (H2L2) were obtained from the reaction of amine precursors with 1,4-dithian-2-one in the presence of triethylamine as a base in the CHCl3 medium. Complexes of the general formula K2<
Estimation of the unknown parameters in 2-D sinusoidal signal model can be considered as important and difficult problem. Due to the difficulty to find estimate of all the parameters of this type of models at the same time, we propose sequential non-liner least squares method and sequential robust M method after their development through the use of sequential approach in the estimate suggested by Prasad et al to estimate unknown frequencies and amplitudes for the 2-D sinusoidal compounds but depending on Downhill Simplex Algorithm in solving non-linear equations for the purpose of obtaining non-linear parameters estimation which represents frequencies and then use of least squares formula to estimate
... Show MoreTo prepare a new ligand, many compounds were used to synthesize Schiff-Mannich base, such as isatin, Para chloro Aniline, 2-mercaptobenzimidazole and indole. The resulting compound 1-((2-((1H-indol-1-ylthio)-1H-benzo[d]imidazol1-yl)methyl)-3-(4-chlorophenylimino)indolin-2-one (L). (L) was used to create a series of metal ion complexes with Co (II), Ni (II), Cu (II), Pd (II), Pt (IV), and Au (III). C.H.N.S., FTIR, mass spectra UV-ViS, 1H-NMR, 13CNMR, magnetic moment, and molar conductivity were used to characterize all of these compounds. Except for the palladium(II) and gold(III) complexes, all of the produced complexes had an octahedral geometry, according to the data. The antibacterial activity of the produced compounds was tested by usin
... Show MoreA novel Schiff base ligand (DBC) synthesized from 4-chlorobenzoic acid, along with its Cu (II) and Co (II) complexes, was prepared and characterized using FT-IR, 1H and 13C-NMR, UV-Vis spectroscopy, as well as magnetic and conductivity measurements. Based on this, a tetrahedral structure of [M(DBC)Cl2] was proposed for the complexes. Antioxidant activity of the compounds was assessed and compared to ascorbic acid, revealing that the copper complex exhibited superior antioxidant properties compared to the cobalt complex and the ligand. Furthermore, the antibiofilm potential of the copper and cobalt complexes was assessed against five clinically relevant bacterial species (P.aeruginosa, E.coli, K.pneumoniae, S.aureus and S.typhi) usin
... Show MoreDapagliflozin is a novel sodium-glucose cotransporter type 2 inhibitor. This work aims to develop a new
validated sensitive RP-HPLC coupled with a mass detector method for the determination of dapagliflozin, its
alpha isomer, and starting material in the presence of dapagliflozin major degradation products and an internal
standard (empagliflozin). The separation was achieved on BDS Hypersil column (length of 250mm, internal
diameter of 4.6 mm and 5-μm particle size) at a temperature of 35℃. Water and acetonitrile were used as
mobile phase A and B by gradient mode at a flow rate of 1 mL/min. A wavelength of 224nm was selected to
perform detection using a photo diode array detector. The method met the