The recent emergence of sophisticated Large Language Models (LLMs) such as GPT-4, Bard, and Bing has revolutionized the domain of scientific inquiry, particularly in the realm of large pre-trained vision-language models. This pivotal transformation is driving new frontiers in various fields, including image processing and digital media verification. In the heart of this evolution, our research focuses on the rapidly growing area of image authenticity verification, a field gaining immense relevance in the digital era. The study is specifically geared towards addressing the emerging challenge of distinguishing between authentic images and deep fakes – a task that has become critically important in a world increasingly reliant on digital med

The regular job of a reservoir engineer is to put a development plan to increase hydrocarbon production as possible and within economic and technical considerations. The development strategy for the giant reservoir is a complex and challenging task through the decision-making analysis process. Due to the limited surface water treatment facility, the reservoir management team focuses on minimizing water cut as low as possible by check the flow of formation and injected water movement through the Mishrif reservoir. In this research, a representative sector was used to make the review of water injection configuration, which is considered an efficient tool to make study in a particular area of the entire field when compared with the ful

   The Compressional-wave (Vp) data are useful for reservoir exploration, drilling operations, stimulation, hydraulic fracturing employment, and development plans for a specific reservoir. Due to the different nature and behavior of the influencing parameters, more complex nonlinearity exists for Vp modeling purposes. In this study, a statistical relationship between compressional wave velocity and petrophysical parameters was developed from wireline log data for Jeribe formation in Fauqi oil field south Est Iraq, which is studied using single and multiple linear regressions. The model concentrated on predicting compressional wave velocity from petrophysical parameters and any pair of shear waves velocity, porosity, density, and

A common field development task is the object of the present research by specifying the best location of new horizontal re-entry wells within AB unit of South Rumaila Oil Field. One of the key parameters in the success of a new well is the well location in the reservoir, especially when there are several wells are planned to be drilled from the existing wells. This paper demonstrates an application of neural network with reservoir simulation technique as decision tool. A fully trained predictive artificial feed forward neural network (FFNNW) with efficient selection of horizontal re-entry wells location in AB unit has been carried out with maintaining a reasonable accuracy. Sets of available input data were collected from the exploited g

   The Compressional-wave (Vp) data are useful for reservoir exploration, drilling operations, stimulation, hydraulic fracturing employment, and development plans for a specific reservoir. Due to the different nature and behavior of the influencing parameters, more complex nonlinearity exists for Vp modeling purposes. In this study, a statistical relationship between compressional wave velocity and petrophysical parameters was developed from wireline log data for Jeribe formation in Fauqi oil field south Est Iraq, which is studied using single and multiple linear regressions. The model concentrated on predicting compressional wave velocity from petrophysical parameters and any pair of shear waves velocity, porosity, density, a

In this study, we fabricated nanofiltration membranes using the electrospinning technique, employing pure PAN and a mixed matrix of PAN/HPMC. The PAN nanofibrous membranes with a concentration of 13wt% were prepared and blended with different concentrations of HPMC in the solvent N, N-Dimethylformamide (DMF). We conducted a comprehensive analysis of these membranes' surface morphology, chemical composition, wettability, and porosity and compared the results. The findings indicated that the inclusion of HPMC in the PAN membranes led to a reduction in surface porosity and fiber size. The contact angle decreased, indicating increased surface hydrophilicity, which can enhance flux and reduce fouling tendencies. Subsequently, we evaluated the e

new Schiff base 4-chlorophenyl)methanimine (6R,7R)-3-methyl-8-oxo-7-(2-phenylpropanamido)-5-thia-1-azabicyclo[4.2.0]oct-2-ene-2-carboxylate= (HL)= C23H20 ClN3O4S) has been synthesized from β-lactam antibiotic (cephalexin mono hydrate(CephH)=(C16H19N3O5S.H2O) and 4-chlorobenzaldehyde . Figure(1) Metal mixed ligand complexes of the Schiff base were prepared from chloride salt of Fe(II),Co(II),Ni(II),Cu(II),Zn(II) and Cd (II), in 50% (v/v) ethanol –water medium (SacH ) .in aqueous ethanol(1:1) containing and Saccharin(C7H5NO3S) = sodium hydroxide. Several physical tools in particular; IR, CHN, 1H NMR, 13C NMR for ligand and melting point molar conductance, magnetic moment. and determination the percentage of the metal in the complexes by fl

A new Schiff base (4-chlorophenyl)(phenyl methanimine (6R,7R)-3-methyl-8-oxo-7-(2-phenylpropanamido)-5-thia-1-azabicyclo[4.2.0]oct-2-ene-2-carboxylate=HL=C29H24ClN3O4S) has been synthesized from β-lactam antibiotic (cephalexin mono hydrate (CephH)=(C16H19N3O5S.H2O) and 4- chlorobenzophenone. Metal mixed ligand complexes of the Schiff base were prepared from chloride salt of Fe(II), Co(II), Ni(II), Cu(II), Zn(II) and Cd(II), in 50% (v/v) ethanol – water medium in aqueous ethanol(1:1) and Saccharin(C7H5NO3S) containing sodium hydroxide. Several physical tools in particular; IR, C:H:N , 1H NMR,13C NMR for ligand, melting point, molar conductance, magnetic moment. and determination of the percentage of the metal in the complexes by flame(AAS