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 generally good in the open-hole sections. The vertical resolution of reliable Compressional, Shear, and Stoneley values is enhanced by the application of Receiver Multi-shot processing. The analysis of rock mechanical properties, including formation Poisson's ratio, compressional-to-shear velocity ratio, Bulk Modulus, Shear Modulus, and Young's modulus, directly utilised the outputs of compressional and shear slowness data. Acoustic processing and interpretation can make further use of the extracted slowness. Anisotropy analysis of Sonic Scanner data in the well under investigation showed that the formation was mostly isotropic throughout most of the recorded interval. Stress-induced and fracture-induced anisotropy has been detected in a limited number of locations. The maximum horizontal stress extends in a direction ranging from NE 20-80 degrees.
The current study included the separation of three alkaloid compounds from Anastatica Hierochuntica and studied the effect of the these compounds on cancerous cells , specifically liver cancer it was found that compound number one is the most influential or inhibiting at 50 percent followed by compound number three when using concentration of 400 μg/mL.
A new simple and sensitive spectrophotometric method is described for quantification of Nifedipine (NIF) and their pharmaceutical formulation. The selective method was performed by the reduction of NIF nitro group to yield primary amino group using zinc powder with hydrochloric acid. The produced aromatic amine was submitted to oxidative coupling reaction with pyrocatechol and ammonium ceric nitrate to form orange color product measured spectrophotometrically with maximum absorption at 467nm. The product was determined through flow injection analysis (FIA) system and all the chemical and physical parameters were optimized. The concentration range from 5.0 to 140.0 μg.mL-1 was obeyed Beer’s law with a limit of detection and quantitatio
... Show MoreBackground: Dental implant considers a unique treatment option for the replacement of missing dentition. The new trend of implants is looking for materials which accelerate bone formation in bone implant interface and enhance osseointegration to provide immediate loading directly after placement and decrease the time period which is disturbs patients and uncomfortable. The aim of the study was to evaluate the effect of nano zirconium oxide (ZrO2) and nano hydroxyapatite (Hap) mixture coating of screw shaped commercially pure titanium (cpTi) implants on bond strength at the bone implant interface with torque removal test and histological analysis in comparison with non coated implants. Materials and methods: Forty screws were machined from c
... Show MoreAttacking a transferred data over a network is frequently happened millions time a day. To address this problem, a secure scheme is proposed which is securing a transferred data over a network. The proposed scheme uses two techniques to guarantee a secure transferring for a message. The message is encrypted as a first step, and then it is hided in a video cover. The proposed encrypting technique is RC4 stream cipher algorithm in order to increase the message's confidentiality, as well as improving the least significant bit embedding algorithm (LSB) by adding an additional layer of security. The improvement of the LSB method comes by replacing the adopted sequential selection by a random selection manner of the frames and the pixels wit
... Show MoreTraffic classification is referred to as the task of categorizing traffic flows into application-aware classes such as chats, streaming, VoIP, etc. Most systems of network traffic identification are based on features. These features may be static signatures, port numbers, statistical characteristics, and so on. Current methods of data flow classification are effective, they still lack new inventive approaches to meet the needs of vital points such as real-time traffic classification, low power consumption, ), Central Processing Unit (CPU) utilization, etc. Our novel Fast Deep Packet Header Inspection (FDPHI) traffic classification proposal employs 1 Dimension Convolution Neural Network (1D-CNN) to automatically learn more representational c
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