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.
In this work, Schiff base ligands L1: N, N-bis (2-hydroxy-1-naphthaldehyde) hydrazine, L2: N, N-bis (salicylidene) hydrazine, and L3:N –salicylidene- hydrazine were synthesized by condensation reaction. The prepared ligands were reacted with specific divalent metal ions such as (Mn2+, Fe2+, Ni2+) to prepare their complexes. The ligands and complexes were characterized by C.H.N, FT-IR, UV-Vis, solubility, melting point and magnetic susceptibility measurements. The results show that the ligands of complexes (Mn2+, Fe2+) have octahedral geometry while the ligands of complexes (Ni2+) have tetrahedral geometry.
A new Schiff base [1-((2-(1H-indol-3-yl)ethylimino)methyl)naphthalene-2-ol] (HL) has been synthesized by condensing (2-hydroxy-1-naphthaldehyde) with (2-(1H-indol-3-yl)ethylamine). In turn, its transition metal complexes were prepared having the general formula; [Pt(IV)Cl2(L)2], [Re(V)Cl2(L)2]Cl and [Pd(L)2], 2K[M(II)Cl2(L)2] where M(II) = Co, Ni, Cu] are reported. Ligand as well as metal complexes are characterized by spectroscopic techniques such as FT-IR, UV-visible, 13C & 1H NMR, mass, elemental analysis. The results suggested that the ligand behaves like a bidentate ligand for all the synthesized complexes. On the other hand, theoretical studies of the ligand as well its metal complexes were conducted at gas phase using Hyp
... Show MoreIn this study, poly4-(nicotinamido)-4-oxo-2-butenoic acid (PNOE) was prepared by the electro polymerization of 4-(nicotinamido)-4-oxo-2-butenoic acid (NOE) monomer on a 316 stainless steel (St.St) which acts as an anticorrosion coating. Fourier transforms infrared (FTIR), atomic force microscopy (AFM), scanning electron microscopy (SEM), and cyclic voltammetry were used to diagnose the structure and the properties of the prepared polymer layer. The corrosion behavior of the uncoated and coated 316 St.St were evaluated by using an electro chemical polarization technique in 0.2 M hydrochloric acid solution as a corrosive medium at a temperature range of 293 to 323 K. Nano materials, such as nano ZnO and graphene were added in di
... Show MoreThe present work reports an approach of hydrothermal growth of ZnO nanorods, which simplifies the production of low cost films with controlled morphology for H2S gas sensor application. The prepared ZnO nanorods exhibit a hexagonal wurtzite phase analyzed by the X-ray diffraction analysis. The FTIR spectra provide information that the band located between 465-570 cm-1 corresponds to the stretching bond of Zn-O, which confirms the creation of ZnO. PL spectroscopic studies showed that the doping of Ag NPs and f-MWCNT in the ZnO matrix leads to the tuning of the bandgap. The SEM analysis showed the morphology of ZnO was the nanorods. The nanocomposites Ag/ZnO and F-MWCNT/ZnO which prepared, sep
... Show MoreRecommendation systems are now being used to address the problem of excess information in several sectors such as entertainment, social networking, and e-commerce. Although conventional methods to recommendation systems have achieved significant success in providing item suggestions, they still face many challenges, including the cold start problem and data sparsity. Numerous recommendation models have been created in order to address these difficulties. Nevertheless, including user or item-specific information has the potential to enhance the performance of recommendations. The ConvFM model is a novel convolutional neural network architecture that combines the capabilities of deep learning for feature extraction with the effectiveness o
... Show MoreThe [2-hydroxy -1,2-diphynel-ethanone oxime] was reacted with 1,2- dichloroethan to give the new ligand [H2L].this ligand was reacted with some metal ions (Co(II),Ni(II),Cu(II),Zn(II) and Cd(II) in methanol as a solvent to give a series of new (1:1)complexes of the general formula [ M(HL)]Cl ,( where : M= Co(II),Ni(II),Cu(II),Zn(II) and Cd(II)) are isolated All compounds have been characterized by spectroscopic methods [ I.R , U.V -Vis ] atomic absorption . Chloride content along with conductivity measurements. From the above data the proposed molecular structure for (Co, Cu, Ni, Zn and Cd) complexes adopting a tetrahedral structure.
The [2-hydroxy-1, 2-diphynel-ethanone oxime] was reacted with 1, 2-dichloroethan to give the new ligand [H2L]. this ligand was reacted with some metal ions (Co (II), Ni (II), Cu (II), Zn (II) and Cd (II) in methanol as a solvent to give a series of new (1: 1) complexes of the general formula [M (HL)] Cl,(where: M= Co (II), Ni (II), Cu (II), Zn (II) and Cd (II)) are isolated All compounds have been characterized by spectroscopic methods [IR, UV-Vis] atomic absorption. Chloride content along with conductivity measurements. From the above data the proposed molecular structure for (Co, Cu, Ni, Zn and Cd) complexes adopting a tetrahedral structure
In study of effective bioactive compounds, we have synthesized the Co((ІІ), Mn(ІІ), Fe(ІІ), Cu(ІІ), Ni(ІІ), and Zn(ІІ) complexes of the Schiff base derived from trimethoprim and2'-amino-4-chlorobenzophenone and characterized by spectroscopic (NMR, IR, Mass, UV–vis,), analytical, TGA studies and magnetic data .The solution electronic spectral study suggests the stoichiometry of the synthesized complexes and Elemental analysis detected the square planer and octahedral geometry of the compounds. The prepared metal complexes presented promoted efficiency versus the screened bacterial (Escherichia Coli and Staphylococcus aureus) antibacterial efficacy against (Staphylococcus aureus, Salmonella spp., E. coli, Vibrio spp., Pseud
... Show MoreIn this work, the preparation of new multidentate Schiff-base lig and and its metal complexes are described. The formation of the lig and{ 2,2`((5-methyl-1,3-phenylene)-bis-(oxy))-bis-N`(E`)-2- hydroxybenzylideneacetohydrazide}[H2L] was prepared from the reaction {2,2-((5-methyl-1,3-phenylene)-bis-(oxy))- di-(acetohydrazide)}[M]precursor and salicylaldehyde in a 1:2 mole ratio, respectively. The reaction of the lig and [H2L] with (Cr+3 , Mn+2 and Fe+2 )metal ions in a 1:2 (L:M) mole ratio. Ligand and complexes were characterised via spectroscopic analyses; [FT-IR, UV-Vis spectroscopy,(C.H.N) microanalysis, chloride content, thermal analysis(TG), electrospray mass, magnetic susceptibility and conductivity measurements. The characterisation d
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