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 study, high quality ZnO/Ag-NPs thin transparent and conductive film coatings were fabricated
In this research, a group of complexes were prepared which were derived from Schiff base ligands, which is called (1E,1'E)-1,1'-(1,2-phenylene)bis(N-(2,4-dichlorophenyl) methanimine) (L) with ortho-phenanthroline (o-phen).The prepared complexes areM(II) [Co(II),Ni(II),Cu(II), Zn(II), Cd(II),and Hg(II)].A range of spectroscopic and technical techniques have been used to characterizethese materials, including:The FTIR, 1H-NMR, LC-Mass Spectrum, UV-Visbale, molar conductance, and magnaticmoment, atomic absorbtion, chlorid contents. Spectral results obtainedare showen that (ortho-phen) and (L) behave as neutral coordinating to the central metal ion by the donatingatoms(N2)of the both compounds. The geometry sha
... Show MoreN-Benzylidene m-nitrobenzeneamines (Schiff bases) were prepared by condensation of m-nitroaniline with aromatic aldehydes. These Schiff bases were found to react with maleic anhydride to give 2-Aryl-3-(m-nitrophenyl)-2, 3-dihydro [1, 3] oxazepine–4, 7–diones and with phthalic anhydride to give 2-Aryl-3–(m-nitrophenyl)–2, 3–dihydrobenz|| 1, 2-e|||| 1, 3] oxazepine–4, 7-diones which were reacted with pyrrolidine to give the anilide–pyrrolidides of maleic acid and phthalic acid.
(phen) (L(M [formula general a with complexes ligand-mixed new of series A methods analyses different by characterised and synthesised been have ,ligand arysecond as phenanthroline1,10- = phen and ligand primary as dithiocarbamate-1-azolebenzoimid-H-1)sulfinyl)methyl)yl-”-2pyriden)trifluroethoxy2,2,2- “(-4-methyl3-(((2-Sodium = L,ZnIIandCdII,CuII,NiII,CoII= M where,Cl)]phen)(L(Pd [Cland]2)O2H( ligands to metal ,moments magnetic and ,elementalanalysis ,spectrum mass ,surementsmea conductivity ,analysis thermal ,spectroscopy Vis-UV ,IR-FT ,NMR-C,13 H1 such dithiocarbamate the with formed coordination anisobidentate that showed spectra IRFT The.)phen:dithiocarbamate:M) (1:1:1(be to found been has complexes all in ratio nitrogen th
... Show MoreIn this work pyrazolin derivatives were prepared from the diazonium chloride salt of 4-aminobenzoic acid. Azo compounds were prepared from the reaction of an ethanolic solution of sodium acetate and calculated amount of active methylene compound namely, acetyl acetone to obtain the corresponding hydrazono derivative (1). Cyclocondensation reaction of compounds (1) with hydrazine hydrate and phenyl hydrazine in boiling ethanol affording the corresponding pyrazoline-5-one derivatives of 4-aminobenzoic acid (2,3). Then compound (3) was reacted with thionyl chloride to give the corresponding acid chloride derivative(4), followed by conversion into the corresponding acid hydrazide derivative (5) carboxylic acid thiosemicarbazide (11), esters
... Show MoreA new methodology was applied to the synthesis of new imidazolones and oxyazepine derivatives containing imidazo thiazole fused rings. Starting with 5-(4-bromo phenyl) imidazo (2, 1-b) thiazole, which was synthesized using the standard procedure, the Carbaldehyed group was introduced at position 6 of 5-(4-bromo phenyl) imidazo (2, 1-b) thiazole. Then, this 6-carbaldehyed derivative was condensed with different substituted aromatic amines to afford new Schiff bases. The latter were cyclized into new oxazepine and imidazolone derivatives by using phthalic anhydride and glycine, respectively. These new derivatives were characterized by using FT-IR, 1HHNMR, and 13CNMR spectra, as well as examined (evaluated) for anti-bacterial and anti-fungal a
... Show More