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Development of 1D-Synthetic Geomechanical Well Logs for Applications Related to Reservoir Geomechanics in Buzurgan Oil Field
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Knowledge of the distribution of the rock mechanical properties along the depth of the wells is an important task for many applications related to reservoir geomechanics. Such these applications are wellbore stability analysis, hydraulic fracturing, reservoir compaction and subsidence, sand production, and fault reactivation. A major challenge with determining the rock mechanical properties is that they are not directly measured at the wellbore. They can be only sampled at well location using rock testing. Furthermore, the core analysis provides discrete data measurements for specific depth as well as it is often available only for a few wells in a field of interest. This study presents a methodology to generate synthetic-geomechanical well logs for the production section of the Buzurgan oil field, located in the south of Iraq, using an artificial neural network. An issue with the area of study is that shear wave velocities and pore pressure measurements in some wells are missing or incomplete possibly for cost and time-saving purposes. The unavailability of these data can potentially create inaccuracies in reservoir characterization n and production management. To overcome these challenges, this study presents two developed models for estimating the shear wave velocity and pore pressure using ANN techniques. The input parameters are conventional well logs including compressional wave, bulk density, and gamma-ray. Also, this study presents a construction of 1-D mechanical earth model for the production section of Buzurgan oil field which can be used for optimizing the selected mud weights with less wellbore problems (less nonproductive time. The results showed that artificial neural network is a powerful tool in determining the shear wave velocity and formation pore pressure using conventional well logs. The constructed 1D MEM revealed a high matching between the predicted wellbore instabilities and the actual wellbore failures that were observed by the caliper log. The majority of borehole enlargements can be attributed to the formation shear failures due to an inadequate selection of mud weights while drilling. Hence, this study presents optimum mud weights (1.3 to 1.35 g/cc) that can be used to drill new wells in the Buzurgan oil field with less expected drilling problems.

Crossref
Publication Date
Tue Mar 01 2022
Journal Name
Results In Engineering
Predictive model for stress at ultimate in internally unbonded steel tendons based on genetic expression programming
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Crossref (15)
Crossref
Publication Date
Tue Oct 23 2018
Journal Name
Journal Of Economics And Administrative Sciences
Compare some wavelet estimators for parameters in the linear regression model with errors follows ARFIMA model.
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The aim of this research is to estimate the parameters of the linear regression model with errors following ARFIMA model by using wavelet method depending on maximum likelihood and approaching general least square as well as ordinary least square. We use the estimators in practical application on real data, which were the monthly data of Inflation and Dollar exchange rate obtained from the (CSO) Central Statistical organization for the period from 1/2005 to 12/2015. The results proved that (WML) was the most reliable and efficient from the other estimators, also the results provide that the changing of fractional difference parameter (d) doesn’t effect on the results.

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Crossref
Publication Date
Tue Jul 30 2024
Journal Name
Iraqi Journal Of Science
N-Acetyl Cysteine-Cadmium Telluride NAC-CdTe QDs for Detecting the Damaged DNA in Cancerous Diseases
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In this study water-soluble N-Acetyl Cysteine Capped-Cadmium Telluride QDs (NAC/CdTe nanocrystals) using N-acetyl cysteine as a stabilizer were prepared to investigate the utility of quantum dots (QDs) in distinguishing damaged DNA, (extracted from blood samples of leukaemia patients), from intact DNA (extracted from blood samples of healthy individuals) to be used for biosensing application. Based on the optical characterization of the prepared QDs, the XRD results revealed the formation of the NAC-CdTe-QDs with a grain size of 7.1nm. Whereas, the SEM test showed that the spherical size of the NAC-CdTe-QDs lies within 11~33nm. NAC-CdTe-QDs have superior PL emission properties at of 550nm and UV-Vis absorption peak at 300nm. The energy gap

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Scopus Crossref
Publication Date
Sun Jun 01 2025
Journal Name
Journal Of Physics: Conference Series
Optimal Variational Iteration Method for Solving Nonlinear Ordinary Differential Equations Appeared in Engineering and Applied Sciences
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Physics and applied mathematics form the basis for understanding natural phenomena using differential equations depicting the flow in porous media, the motion of viscous liquids, and the propagation of waves. These equations provide a thorough study of physical processes, enhancing the understanding of complex applications in engineering, technology, and medicine. This paper presents novel approximate solutions for the Darcy-Brinkmann-Forchheimer moment equation, the Blasius equation and the FalknerSkan equation with initial / boundary conditions by using two iterative methods: the variational iteration method and the optimal variational iteration method. The variational iteration method is effectively developed by adding a control paramete

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Scopus Crossref
Publication Date
Fri Jan 07 2022
Journal Name
International Journal Of Early Childhood Special Education
Hierarchical learning and its effect on learning some basic skills in fencing for third stage students.
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MH Hamzah, AF Abbas, International Journal of Early Childhood Special Education, 2022

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Publication Date
Sat Sep 01 2018
Journal Name
J Indian Soc Periodontol.
Osteoporosis effect on posterior mandible in preimplanted area for postmenopausal females using cone-beam computed tomography
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Scopus (2)
Scopus
Publication Date
Sun Apr 08 2018
Journal Name
Al-khwarizmi Engineering Journal
Energy Consumption Analyzing in Single hop Transmission and Multi-hop Transmission for using Wireless Sensor Networks
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Wireless sensor networks (WSNs) are emerging in various application like military, area monitoring, health monitoring, industry monitoring and many more. The challenges of the successful WSN application are the energy consumption problem. since the small, portable batteries integrated into the sensor chips cannot be re-charged easily from an economical point of view. This work focusses on prolonging the network lifetime of WSNs by reducing and balancing energy consumption during routing process from hop number point of view. In this paper, performance simulation was done between two types of protocols LEACH that uses single hop path and MODLEACH that uses multi hop path by using Intel Care i3 CPU (2.13GHz) laptop with MATLAB (R2014a). Th

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Crossref (3)
Crossref
Publication Date
Mon Jun 01 2020
Journal Name
Journal Of Planner And Development
Mapping Paddy Rice Fields Using Landsat and Sentinel Radar Images in Urban Areas for Agriculture Planning
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     This research develops a new method based on spectral indices and random forest classifier to detect paddy rice areas and then assess their distributions regarding to urban areas. The classification will be conducted on Landsat OLI images and Landsat OLI/Sentinel 1 SAR data. Consequently, developing a new spectral index by analyzing the relative importance of Landsat bands will be calculated by the random forest. The new spectral index has improved depending on the most three important bands, then two additional indices including the normalized difference vegetation index (NDVI), and standardized difference built-up index (NDBI) have been used to extract paddy rice fields from the data. Several experiments being

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Publication Date
Fri Mar 29 2024
Journal Name
Iraqi Journal Of Science
Finding the Best Route for Connecting Citizens with Service Centers in Baghdad Based on NN Technology
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     A geographic information system (GIS) is a very effective management and analysis tool. Geographic locations rely on data. The use of artificial neural networks (ANNs) for the interpretation of natural resource data has been shown to be beneficial. Back-propagation neural networks are one of the most widespread and prevalent designs. The combination of geographic information systems with artificial neural networks provides a method for decreasing the cost of landscape change studies by shortening the time required to evaluate data. Numerous designs and kinds of ANNs have been created; the majority of them are PC-based service domains. Using the ArcGIS Network Analyst add-on, you can locate service regions around any network

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Scopus Crossref
Publication Date
Tue Jul 01 2014
Journal Name
Bulletin Of The Iraq Natural History Museum (p-issn: 1017-8678 , E-issn: 2311-9799)
A NEW HOST RECORD FOR TOMATO LEAF MINER TUTA ABSOLUTA (MEYRICK, 1917) IN BAGHDAD PROVINCE, IRAQ
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  In 2010, the tomato leaf miner Tuta absoluta (Meyrick, 1917) was reported for the first time in Iraq. The larvae can feed on all parts of tomato plants and can damage all the growth stages. The main host plant is tomato, Lycopersicon esculentum, but it can also attack other plants in Solanaceae family. In this study it was found attacking alfalfa plants, Medicago sativa in Baghdad Province. This finding reveals that alfalfa also serves as a host plant for T. absoluta in Iraq.

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