The estimation of the initial oil in place is a crucial topic in the period of exploration, appraisal, and development of the reservoir. In the current work, two conventional methods were used to determine the Initial Oil in Place. These two methods are a volumetric method and a reservoir simulation method. Moreover, each method requires a type of data whereet al the volumetric method depends on geological, core, well log and petrophysical properties data while the reservoir simulation method also needs capillary pressure versus water saturation, fluid production and static pressure data for all active wells at the Mishrif reservoir. The petrophysical properties for the studied reservoir is calculated using neural network technique from 13 cored and logged wells. The results showed that the reservoir simulation method gave a value of Initial Oil in Place that agrees and close to the value of Initial Oil in Place obtained from the volumetric method with a percentage different around 2%. However, the estimation of Initial Oil in Place by reservoir simulation method offered accurate results during good history matching with observed data as well as making appropriate adjusting for Pc vs. Sw values for the whole reservoir from October 1976 until December2020. MB21 unit own most Initial Oil in Place equal to 525*106 SM3 while MB12 has lowest IOIP equal to 2*106 SM3. Finally, the calculation of Initial Oil in Place by both volumetric and simulation methods presented good results while comparing with previous study at 2013 with discovered different around 1.5% and 0.6% respectively.
The article reflects the results of the analysis of the use of metaphors when creating the image of the main character of the story by D. Rubina "You and me under the peach clouds" - a pet, a dog named Kondraty. Through metaphorization, the image of the dog is filled by the author with purely human qualities, thus passing into the category of a full member of the family. The article is a continuation of the study of the work of D. I. Rubina.
The Sonic Scanner is a multifunctional instrument designed to log wells, assess elastic characteristics, and support reservoir characterisation. Furthermore, it facilitates comprehension of rock mechanics, gas detection, and well positioning, while also furnishing data for geomechanical computations and sand management. The present work involved the application of the Sonic Scanner for both basic and advanced processing of oil-well-penetrating carbonate media. The study aimed to characterize the compressional, shear, Stoneley slowness, rock mechanical properties, and Shear anisotropy analysis of the formation. Except for intervals where significant washouts are encountered, the data quality of the Monopole, Dipole, and Stoneley modes is gen
... Show MoreBACKGROUNDS Nasoalveolar molding (NAM) application is among presurgical management (PSM) techniques used for infants with cleft lip and palate (CLP). It helps to approximate the palatal cleft and to reshape the nasoalveolar complex prior to primary lip repair. This study aimed to explore types of PSM and the dental speciality provision for infants with CLP in Baghdad. The status of NAM usage and surgeons’ perceptions toward NAM usage were assessed. MATERIALS AND METHODS This is a cross-sectional paper-based questionnaire study that collected responses of surgeons perform primary lip and nose repair regarding PSM. The questionnaire was distributed amongst public and private hospitals in Baghdad. Twenty surgeons were enrolled (only those su
... Show MoreCNC machine is used to machine complex or simple shapes at higher speed with maximum accuracy and minimum error. In this paper a previously designed CNC control system is used to machine ellipses and polylines. The sample needs to be machined is drawn by using one of the drawing software like AUTOCAD® or 3D MAX and is saved in a well-known file format (DXF) then that file is fed to the CNC machine controller by the CNC operator then that part will be machined by the CNC machine. The CNC controller using developed algorithms that reads the DXF file feeds to the machine, extracts the shapes from the file and generates commands to move the CNC machine axes so that these shapes can be machined.
This paper proposes a better solution for EEG-based brain language signals classification, it is using machine learning and optimization algorithms. This project aims to replace the brain signal classification for language processing tasks by achieving the higher accuracy and speed process. Features extraction is performed using a modified Discrete Wavelet Transform (DWT) in this study which increases the capability of capturing signal characteristics appropriately by decomposing EEG signals into significant frequency components. A Gray Wolf Optimization (GWO) algorithm method is applied to improve the results and select the optimal features which achieves more accurate results by selecting impactful features with maximum relevance
... Show MoreThe microbend sensor is designed to experience a light loss when force is applied to the sensor. The periodic microbends cause propagating light to couple into higher order modes, the existing higher order modes become unguided modes. Three models of deform cells are fabricated at (3, 5, 8) mm pitchand tested by using MMF and laser source at 850 nm. The maximum output power of (8, 5, 3)mm model is (3, 2.7, 2.55)nW respectively at applied force 5N and the minimum value is (1.9, 1.65, 1.5)nW respectively at 60N.The strain is calculated at different microbend cells ,and the best sensitivity of this sensor for cell 8mm is equal to 0.6nW/N.