Prediction of the formation of pore and fracture pressure before constructing a drilling wells program are a crucial since it helps to prevent several drilling operations issues including lost circulation, kick, pipe sticking, blowout, and other issues. IP (Interactive Petrophysics) software is used to calculate and measure pore and fracture pressure. Eaton method, Matthews and Kelly, Modified Eaton, and Barker and Wood equations are used to calculate fracture pressure, whereas only Eaton method is used to measure pore pressure. These approaches are based on log data obtained from six wells, three from the north dome; BUCN-52, BUCN-51, BUCN-43 and the other from the south dome; BUCS-49, BUCS-48, BUCS-47. Along with the overburden pressure gradient and clay volume, which were also established first, data such as gamma ray, density, resistivity, and sonic log data are also required. A key consideration in the design of certain wells is the forecasting of fracture pressure for wells drilled in the southern Iraqi oilfield of Buzurgan. The pressure abnormality is found in MA, MB21, MC1 and MC2 units by depending on pore pressures calculated from resistivity log. In these units, depths and its equivalent normal and abnormal pressure are detected for all sex selected wells; BUCS-47, BUCS-48, BUCS-49, BUCN-43, BUCN-51 and BBCN-52. For MA, MB21, MC1, and MC2 units, the highest difference in pore pressure values are 1698 psi @ 3750 m (BUCN-51), 3420 psi @ 3900 m (BUCN-51), 788 psi @ 3980 m (BUCS-49), and 5705 psi @ 4020 m (BUCN-52). On other hands, MB11 and MB12 units have normal pressure trend in all studied wells. Finally, the results show that the highest pore and fracture pressure values is existed in North dome, in comparison with that obtained in south dome of Mishrif reservoir at Buzurgan oilfield.
This paper presents a hybrid approach for solving null values problem; it hybridizes rough set theory with intelligent swarm algorithm. The proposed approach is a supervised learning model. A large set of complete data called learning data is used to find the decision rule sets that then have been used in solving the incomplete data problem. The intelligent swarm algorithm is used for feature selection which represents bees algorithm as heuristic search algorithm combined with rough set theory as evaluation function. Also another feature selection algorithm called ID3 is presented, it works as statistical algorithm instead of intelligent algorithm. A comparison between those two approaches is made in their performance for null values estima
... Show MoreThe achievements of the art that we know today are questioned in motives that differ from what art knew before, including dramatic artistic transformations, which he called modern art.
In view of the enormity of such a topic, its ramifications and its complexity, it was necessary to confine its subject to the origin of the motives of the transformations of its first pioneers, and then to stand on what resulted from that of the data of vision in composition and drawing exclusively, and through exploration in that, we got to know the vitality of change from the art of its time.
And by examining the ruling contemporary philosophical concepts and their new standards and their epistemological role in contemporary life, since they includ
This research was aimed to study the pollen morphology for the genus Pterocephalus(Vaill) from Dipsacaceae family in Iraq, and to utilize these feathers in isolating the species as valuable taxonomic traits for enriching Iraqi flora. The study included characteristics of the type, shape, size, sculpturing and apertures, as well as determining the full dimensions using light microscopy as well as numerical analysis of this species and draw polygonal shapes and denderogram convergence between species. The results of the study of pollen and polygonal forms showed significant differences in the characteristics at the level of each species, which helps to identification the genus species, as it was found that the pollen was a tricolp
... Show MoreThe purpose of this study was to evaluate the epidemiological characteristics of the mandibular fractures relating to gender, age, the etiology of injury, and the rendered treatment modalities and complications. The data of the patients who sustained mandibular fractures were retrieved and were analyzed retrospectively, and based on these data a descriptive analysis was conducted. A total of 112 patients were included in this study; the most common cause was road traffic accidents (RTAs) followed by assaults and missile injuries. The most frequently involved age group was 11 to 20 years, treatment modalities included conservative, closed reduction and indirect fixation, and open reduction and internal fixation (ORIF) in 11.6, 79.5, and 8.9%
... Show MoreThis study aims to study the effect of gout disease on complete blood picture and biochemical parameters and some non-enzymatic antioxidants, some tracing elements and lipid peroxidation ,in outpatients with gout disease at Al-Ramadi Teaching-Hospital ,Al-Razi Hospital and the study duration from Octo.2013-to May 2014.(50) blood samples were collected from patients with age groups (30-80 years) from both sexes (28 males,22 females),a (30) blood samples (15 males,15 females) were collected from normal individuals as a control group with age groups (27-75 years). Hematological measurement showed no significant differences in size compressed blood cells, the percentages in ( 45.15 +4.99 and 46.87+6.30) % in patient and control groups respect
... Show MoreThe purpose of this research is defining the main factors influencing on decision of management system on sensitive data in cloud. The framework is proposed to enhance management information systems decision on sensitive information in cloud environment. The structured interview with several security experts working on cloud computing security to investigate the main objective of framework and suitability of instrument, a pilot study conducts to test the instrument. The validity and reliability test results expose that study can be expanded and lead to final framework validation. This framework using multilevel related to Authorization, Authentication, Classification and identity anonymity, and save and verify, to enhance management
... Show MoreSkull image separation is one of the initial procedures used to detect brain abnormalities. In an MRI image of the brain, this process involves distinguishing the tissue that makes up the brain from the tissue that does not make up the brain. Even for experienced radiologists, separating the brain from the skull is a difficult task, and the accuracy of the results can vary quite a little from one individual to the next. Therefore, skull stripping in brain magnetic resonance volume has become increasingly popular due to the requirement for a dependable, accurate, and thorough method for processing brain datasets. Furthermore, skull stripping must be performed accurately for neuroimaging diagnostic systems since neither non-brain tissues nor
... Show MoreSecure information transmission over the internet is becoming an important requirement in data communication. These days, authenticity, secrecy, and confidentiality are the most important concerns in securing data communication. For that reason, information hiding methods are used, such as Cryptography, Steganography and Watermarking methods, to secure data transmission, where cryptography method is used to encrypt the information in an unreadable form. At the same time, steganography covers the information within images, audio or video. Finally, watermarking is used to protect information from intruders. This paper proposed a new cryptography method by using thre
... Show MoreVol. 6, Issue 1 (2025)
Dust is a frequent contributor to health risks and changes in the climate, one of the most dangerous issues facing people today. Desertification, drought, agricultural practices, and sand and dust storms from neighboring regions bring on this issue. Deep learning (DL) long short-term memory (LSTM) based regression was a proposed solution to increase the forecasting accuracy of dust and monitoring. The proposed system has two parts to detect and monitor the dust; at the first step, the LSTM and dense layers are used to build a system using to detect the dust, while at the second step, the proposed Wireless Sensor Networks (WSN) and Internet of Things (IoT) model is used as a forecasting and monitoring model. The experiment DL system
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