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An An Accurate Estimation of Shear Wave Velocity Using Well Logging Data for Khasib Carbonate Reservoir - Amara Oil Field
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Shear and compressional wave velocities, coupled with other petrophysical data, are vital in determining the dynamic modules magnitude in geomechanical studies and hydrocarbon reservoir characterization. But, due to field practices and high running cost, shear wave velocity may not available in all wells. In this paper, a statistical multivariate regression method is presented to predict the shear wave velocity for Khasib formation - Amara oil fields located in South- East of Iraq using well log compressional wave velocity, neutron porosity and density. The accuracy of the proposed correlation have been compared to other correlations. The results show that, the presented model provides accurate estimates of shear wave velocity with correlation coefficient of about unity than other currently available methods.

 

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Publication Date
Thu Feb 01 2007
Journal Name
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On Solvability of an Operator Equation-
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Publication Date
Sat Mar 01 2008
Journal Name
The Third International Conference On Mathematical Sciences
On Solvability of an Operator Equation
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Publication Date
Tue Jun 30 2015
Journal Name
Iraqi Journal Of Chemical And Petroleum Engineering
Single Well Coning Problem and Applicable Solutions
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One of the most important and common problems in petroleum engineering; reservoir, and production engineering is coning; either water or gas coning. Almost 75% of the drilled wells worldwide contains this problem, and in Iraq water coning problem is much wider than the gas coning problem thus in this paper we try to clarify most of the reasons causing water coning and some of applicable solutions to avoid it using the simulation program (CMG Builder) to build a single well model considering an Iraqi well in north of Iraq black oil field with a bottom water drive, Coning was decreased by 57% by dividing into sub-layers (8) layers rather than (4) layers, also it was decreased (Coning) by 45% when perforation numbers and positions was chang

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Publication Date
Wed Feb 22 2023
Journal Name
Iraqi Journal Of Science
Facies, Depositional Environment and Cyclicity of the Fatha Formation in East Baghdad Oil Field, Iraq.
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This study deals with establishing the depositional environment of the Fatha Formation through facies analysis. It also deals with dividing the formation into units based on the rhythmic nature. Data from selected shallow wells near Hit area and deep wells at East Baghdad Oil field are used. Five major lithofacies are recognized in this study, namely, greenish grey marl, limestone, gypsum (and/or anhydrite), halite and reddish brown mudstone (with occasional sandstone).The limestone lithofacies is divided into three microfacies: Gastropods bioclastic wackestone microfacies, Gastropods peloidal bioclastic packstone, and Foraminiferal packstone microfacies.The lithofacies of the Fatha are nested in a rhythmic pattern or what is known as sh

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Publication Date
Mon Mar 01 2021
Journal Name
Journal Of Physics: Conference Series
High pollutant levels of produced water around Al-Ahdab oil field in Wasit governorate (Iraq)
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Abstract<p>Exploration activities of the oil and gas industry generate loads of formation water called produced water (PW) up to thousands of tons each day. Depending on the geographic area, formation depth, oil production techniques, and age of oil supply wells, PW from different oil fields contain different chemical compositions. Currently, PW is also known as industrial waste water containing heavy metals that are toxic to humans and the environment, requiring special processing so that they can be disposed of in the environment. To determine the heavy metals content in PW from the Al-Ahdab oil field (AOF), the Ministry of Science and Technology/Agricultural Research Department determined som</p> ... Show More
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Publication Date
Tue May 16 2023
Journal Name
Journal Of Engineering
Traveling Wave Cylindrical Induction Heating System
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The paper deals with the traveling wave cylindrical heating systems. The analysis presented is analytical and a multi-layer model using cylindrical geometry is used to obtain the theoretical results. To validate the theoretical results, a practical model is constructed, tested and the results are compared with the theoretical ones. Comparison showed that the adopted analytical method is efficient in describing the performance of such induction heating systems.

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Publication Date
Sat Apr 01 2017
Journal Name
Ieee Transactions On Microwave Theory And Techniques
A Millimeter-Wave Gyroelectric Waveguide Isolator
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Publication Date
Mon Jan 01 2024
Journal Name
Ieee Transactions On Emerging Topics In Computational Intelligence
Reservoir Network With Structural Plasticity for Human Activity Recognition
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Publication Date
Tue Jun 10 2025
Journal Name
Steel And Composite Structures
Flexural behaviour of prefabricated demountable composite beams with LockBolt shear connectors for accelerated construction
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To promote sustainable steel-concrete composite structures, it is essential to develop special shear connectors that facilitate accelerated construction and deconstruction. A lockbolt demountable shear connector (LBDSC) was recently proposed. While the LBDSC has been evaluated using horizontal and vertical (standard) push-out tests, it is essential to further assess the disassembly mechanism and the positive flexural performance of prefabricated demountable composite beams (PDCBs) under both serviceability and ultimate limit states. Two full-scale test specimens of PDCBs with LBDSC were designed with partial shear connections and assessed using a three or four-point load beam setup under both cyclic and static monotonic loading conditions.

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Publication Date
Sat Jun 01 2019
Journal Name
Periodicals Of Engineering And Natural Sciences (pen)
Lung cancer classification using data mining and supervised learning algorithms on multi-dimensional data set
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These With recent developments in machine learning, data mining and computer vision, there is great potential for improvements in early detection of lung cancer using scans and data available. This paper details the methods and techniques used in our project, where the objective is to develop algorithms to determine whether a patient has or is likely to develop lung cancer using dataset images using data mining and machine learning for the classification and examination. We explore approaches to address the problem. Cancer is the most important cause of death globally. The disease diagnosis is a major process to treat the patients who are affected by cancer disease. The diagnosis process is more difficult comparatively known about t

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