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Numerical Approach for the Prediction of Formation and Hydraulic Fracture Properties Considering Elliptical Flow Regime in Tight Gas Reservoirs
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Abstract<p>As tight gas reservoirs (TGRs) become more significant to the future of the gas industry, investigation into the best methods for the evaluation of field performance is critical. While hydraulic fractured well in TRGs are proven to be most viable options for economic recovery of gas, the interpretation of pressure transient or well test data from hydraulic fractured well in TGRs for the accurate estimation of important reservoirs and fracture properties (e.g. fracture length, fracture conductivity, skin and reservoir permeability) is rather very complex and difficult because of the existence of multiple flow profiles/regimes. The flow regimes are complex in TGRs due to the large hydraulic fractures near the wellbore, combined with low matrix permeability and reservoir heterogeneity; and consequently the interpretation of well test or pressure transient data using the classical approaches usually used for conventional reservoirs can produce wrong results with high level of uncertainties. In addition, the time required to achieve radial flow regimes for such tight reservoir, as key condition to use classical approaches, is impractically long and not feasible from the context of both economic and practical operation viewpoint. These inherent causes and the operating limitations require amendment of the well test technique to analyse linear or elliptical flow regimes to accurately estimate the reservoir and fracture properties.</p><p>This paper proposed a simplified numerical approach to predict the reservoir and fracture parameters based upon well test or production data from hydraulic fractured vertical well in tight gas reservoir considering elliptical flow regime. Emphases are given on the development of simple computation tool that can be used as a handy, efficient and accurate tool to supplement the need for commercial simulators; yet can provide with estimation of reservoir and fracture properties with high level of accuracy especially in the case when limited pressure transient data is available.</p>
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Publication Date
Tue Nov 01 2022
Journal Name
Al-adab Journal
A Pragmatic Analysis of Implicatures in Covid-19 Coronavirus English Jokes: A Neo-Gricean Approach
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Publication Date
Sat Jan 01 2022
Journal Name
Journal Of Pharmaceutical Negative Results
Phytocompound of pure thymol inhibit COVID-19 by binding to ACE2 receptor: In silico approach
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Publication Date
Tue May 31 2022
Journal Name
Journal Of Positive School Psychology
Investigating Ideologies of Women Empowerment in Amy Poehler`s Moxie (2021): A Critical Stylistic Approach
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Publication Date
Thu Aug 27 2026
Journal Name
Journal Of Baghdad College Of Dentistry
Acceleration of canine movement by laser assisted flapless corticotomy [An innovative approach in clinical orthodontics]
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Background: Corticotomy-assisted orthodontic treatment is done to induce a state of increased tissue turnover and transient osteopenia, which is followed by a faster rate of orthodontic tooth movement. It considered as an adjunct treatment option for orthodontic treatment of adults. The aim of this Study was to elucidate the effectiveness of a new surgical approach for acceleration of maxillary canine retraction in human with laser assisted flapless corticotomy and evaluate its effect on vitality of pulp and gingival sulcus depth. Materials and methods: the sample comprised of 15 Iraqi patients (9 females and 6 males; mean age 21.7), who were required extraction for their maxillary first premolars followed by retraction of the canines as pa

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Publication Date
Fri Jan 01 2016
Journal Name
Computational Intelligence And Neuroscience
A New Artificial Neural Network Approach in Solving Inverse Kinematics of Robotic Arm (Denso VP6242)
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This paper presents a novel inverse kinematics solution for robotic arm based on artificial neural network (ANN) architecture. The motion of robotic arm is controlled by the kinematics of ANN. A new artificial neural network approach for inverse kinematics is proposed. The novelty of the proposed ANN is the inclusion of the feedback of current joint angles configuration of robotic arm as well as the desired position and orientation in the input pattern of neural network, while the traditional ANN has only the desired position and orientation of the end effector in the input pattern of neural network. In this paper, a six DOF Denso robotic arm with a gripper is controlled by ANN. The comprehensive experimental results proved the appl

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Publication Date
Tue Jan 01 2019
Journal Name
International Journal Of Civil Engineering And Technology
PREDICTION OF BEARING CAPACITY, ANGLE OF INTERNAL FRICTION, COHESION, AND PLASTICITY INDEX USING ANN (CASE STUDY OF BAGHDAD, IRAQ)
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In the last few years, the use of artificial neural network analysis has increased, particularly, in geotechnical engineering problems and has demonstrated some success. In this research, artificial neural network analysis endeavors to predict the relationship between physical and mechanical properties of Baghdad soil by making different trials between standard penetration test, liquid limit, plastic limit, plasticity index, cohesion, angle of internal friction, and bearing capacity. The analysis revealed that the changes in natural water content and plastic limit have a great effect on the cohesion of soil and the angle of internal friction, respectively. . On the other hand, the liquid limit has a great impact on the bearing capacity and

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Publication Date
Tue Jan 01 2019
Journal Name
International Journal Of Civil Engineering And Technology
Prediction of bearing capacity, angle of internal friction, cohesion, and plasticity index using ANN (case study of Baghdad, Iraq)
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In the last few years, the use of artificial neural network analysis has increased, particularly, in geotechnical engineering problems and has demonstrated some success. In this research, artificial neural network analysis endeavors to predict the relationship between physical and mechanical properties of Baghdad soil by making different trials between standard penetration test, liquid limit, plastic limit, plasticity index, cohesion, angle of internal friction, and bearing capacity. The analysis revealed that the changes in natural water content and plastic limit have a great effect on the cohesion of soil and the angle of internal friction, respectively. . On the other hand, the liquid limit has a great impact on the bearing capacity and

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Publication Date
Tue Jan 01 2019
Journal Name
International Journal Of Civil Engineering And Technology
PREDICTION OF BEARING CAPACITY, ANGLE OF INTERNAL FRICTION, COHESION, AND PLASTICITY INDEX USING ANN (CASE STUDY OF BAGHDAD, IRAQ).
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In the last few years, the use of artificial neural network analysis has increased, particularly, in geotechnical engineering problems and has demonstrated some success. In this research, artificial neural network analysis endeavors to predict the relationship between physical and mechanical properties of Baghdad soil by making different trials between standard penetration test, liquid limit, plastic limit, plasticity index, cohesion, angle of internal friction, and bearing capacity. The analysis revealed that the changes in natural water content and plastic limit have a great effect on the cohesion of soil and the angle of internal friction, respectively. . On the other hand, the liquid limit has a great impact on the bearing capacity and

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Publication Date
Wed Mar 10 2021
Journal Name
Baghdad Science Journal
the effect of doping ratio on the opical properties
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the films of cdse pure and doped with copper ratio glass substrate effect od cucomcentration technique thikness doped with copper is an anonmg and the density of state increases

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Publication Date
Mon Sep 01 2014
Journal Name
Ain Shams Engineering Journal
Performance of polyacrylamide as drag reduction polymer of crude petroleum flow
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