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joe-1037
Using Adaptive Neuro Fuzzy Inference System to Predict Rate of Penetration from Dynamic Elastic Properties
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Rate of penetration plays a vital role in field development process because the drilling operation is expensive and include the cost of equipment and materials used during the penetration of rock and efforts of the crew in order to complete the well without major problems. It’s important to finish the well as soon as possible to reduce the expenditures. So, knowing the rate of penetration in the area that is going to be drilled will help in speculation of the cost and that will lead to optimize drilling outgoings. In this research, an intelligent model was built using artificial intelligence to achieve this goal.  The model was built using adaptive neuro fuzzy inference system to predict the rate of penetration in Mishrif formation in Nasiriya oil field for the selected wells. The mean square error for the results obtained from the ANFIS model was 0.015. The model was trained and simulated using MATLAB and Simulink platform. Laboratory measurements were conducted on core samples selected from two wells. Ultrasonic device was used to measure the transit time of compressional and shear waves and to compare these results with log records. Ten wells in Nasiriya oil field had been selected based on the availability of the data. Dynamic elastic properties of Mishrif formation in the selected wells were determined by using Interactive Petrophysics (IP V3.5) software and based on the las files and log records provided. The average rate of penetration of the studied wells was determined and listed against depth with the average dynamic elastic properties and fed into the fuzzy system. The average values of bulk modulus for the ten wells ranged between (20.57) and (27.57) . For shear modulus, the range was from (8.63) to (12.95) GPa. Also, the Poisson’s ratio values varied from (0.297) to (0.307). For the first group of wells (NS-1, NS-3, NS-4, NS-5, and NS-18), the ROP values were taken from the drilling reports and the lowest ROP was at the bottom of the formation with a value of (3.965) m/hrs while the highest ROP at the top of the formation with a value (4.073) m/hrs. The ROP values predicted by the ANFIS for this group were (3.181) m/hrs and (4.865) m/hrs for the lowest and highest values respectively. For the second group of wells (NS-9, NS-15, NS-16, NS-19, and NS-21), the highest ROP obtained from drilling reports was (4.032) m/hrs while the lowest value was (3.96) m/hrs. For the predicted values by ANFIS model were (2.35) m/hrs and (4.3) m/hrs for the lowest and highest ROP values respectively.

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Publication Date
Thu Nov 14 2019
Journal Name
Journal Of Physics: Conference Series
Estimate the Rate of Contamination in Baghdad Soils By Using Numerical Method
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Journal of Physics: Conference Series PAPER • THE FOLLOWING ARTICLE ISOPEN ACCESS Estimate the Rate of Contamination in Baghdad Soils By Using Numerical Method Luma Naji Mohammed Tawfiq1, Nadia H Al-Noor2 and Taghreed H Al-Noor1 Published under licence by IOP Publishing Ltd Journal of Physics: Conference Series, Volume 1294, Issue 3 Citation Luma Naji Mohammed Tawfiq et al 2019 J. Phys.: Conf. Ser. 1294 032020 DOI 10.1088/1742-6596/1294/3/032020 DownloadArticle PDF References Download PDF 135 Total downloads 88 total citations on Dimensions. Turn on MathJax Share this article Share this content via email Share on Facebook (opens new window) Share on Twitter (opens new window) Share on Mendeley (opens new window) Hide article and author

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Publication Date
Thu Oct 15 2020
Journal Name
Iop Conf. Series: Journal Of Physics: Conf. Series
Estimate the Rate of Contamination in Baghdad Soils By Using Numerical Method
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The aim of this paper is to evaluate the rate of contamination in soils by using accurate numerical method as a suitable tool to evaluate the concentration of heavy metals in soil. In particular, 2D –interpolation methods are applied in the models of the spread the metals in different direction.The paper illustrates the importance of the numerical method in different applications, especially nvironment contamination. Basically, there are many roles for approximating functions. Thus, the approximating of function namely the analytical expression may be expressed; the most common type being is polynomials, which are the easy implemented and simplest methods of approximation. In this paper the divided difference formula is used and extended

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Publication Date
Thu May 05 2016
Journal Name
Global Journal Of Engineering Science And Researches
EVALUATE THE RATE OF CONTAMINATION SOILS BY COPPER USING NEURAL NETWORK TECHNIQUE
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The aim of this paper is to design suitable neural network (ANN) as an alternative accurate tool to evaluate concentration of Copper in contaminated soils. First, sixteen (4x4) soil samples were harvested from a phytoremediated contaminated site located in Baghdad city in Iraq. Second, a series of measurements were performed on the soil samples. Third, design an ANN and its performance was evaluated using a test data set and then applied to estimate the concentration of Copper. The performance of the ANN technique was compared with the traditional laboratory inspecting using the training and test data sets. The results of this study show that the ANN technique trained on experimental measurements can be successfully applied to the rapid est

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Publication Date
Sat May 01 2021
Journal Name
Journal Of Physics: Conference Series
The classification of fetus gender based on fuzzy C-mean using a hybrid filter
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This paper proposes a new approach, of Clustering Ultrasound images using the Hybrid Filter (CUHF) to determine the gender of the fetus in the early stages. The possible advantage of CUHF, a better result can be achieved when fuzzy c-mean FCM returns incorrect clusters. The proposed approach is conducted in two steps. Firstly, a preprocessing step to decrease the noise presented in ultrasound images by applying the filters: Local Binary Pattern (LBP), median, median and discrete wavelet (DWT),(median, DWT & LBP) and (median & Laplacian) ML. Secondly, implementing Fuzzy C-Mean (FCM) for clustering the resulted images from the first step. Amongst those filters, Median & Laplace has recorded a better accuracy. Our experimental evaluation on re

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Publication Date
Wed Jan 01 2025
Journal Name
Journal Of Cybersecurity And Information Management
A New Automated System Approach to Detect Digital Forensics using Natural Language Processing to Recommend Jobs and Courses
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A resume is the first impression between you and a potential employer. Therefore, the importance of a resume can never be underestimated. Selecting the right candidates for a job within a company can be a daunting task for recruiters when they have to review hundreds of resumes. To reduce time and effort, we can use NLTK and Natural Language Processing (NLP) techniques to extract essential data from a resume. NLTK is a free, open source, community-driven project and the leading platform for building Python programs to work with human language data. To select the best resume according to the company’s requirements, an algorithm such as KNN is used. To be selected from hundreds of resumes, your resume must be one of the best. Theref

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Publication Date
Mon Jan 01 2024
Journal Name
Journal Of Medicine And Life
An overview of neuro-ophthalmic disorders at Jenna Ophthalmic Center, Baghdad, Iraq (2021-2022)
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Neuro-ophthalmic disorders are often documented individually for each illness, with little data available on their overall incidence and pattern. The overall incidence of neuro-ophthalmic illnesses in Iraq is still not recorded. This study aimed to evaluate the clinical, demographic, and etiological features of patients seeking consultation at an Iraqi neuro-ophthalmology clinic. A prospective cross-sectional observational research was conducted at the Janna Ophthalmic Center in Baghdad, Iraq. The center serves a diverse patient population from various governorates. All newly diagnosed patients with neuro-ophthalmic disorders who visited the neuro-ophthalmological clinic, regardless of gender or age group, were included. The neuro-ophthalmo

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Publication Date
Tue Sep 08 2020
Journal Name
Baghdad Science Journal
Turbid of Water By Using Fuzzy C- Means and Hard K- Means
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In this research two algorithms are applied, the first is Fuzzy C Means (FCM) algorithm and the second is hard K means (HKM) algorithm to know which of them is better than the others these two algorithms are applied on a set of data collected  from the Ministry of Planning on the water turbidity of five areas in Baghdad to know which of these areas are less turbid in clear water to see which months during the year are less turbid in clear water in the specified area.

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Publication Date
Fri Sep 30 2011
Journal Name
Al-khwarizmi Engineering Journal
Fuzzy Control of the Robotic Hands Catching Force Using Muscle Wires Actuator
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The aim of this research is controlling the amount of the robotic hand catching force using the artificial muscle wire as an actuator to achieve the desired response of the robotic hand in order to catch different things without destroying or dropping them; where the process is to be similar to that of human hand catching way. The proper selection of the amount of the catching force is achieved through out simulation using the fuzzy control technique. The mechanism of the arrangement of the muscle wires is proposed to achieve good force selections. The results indicate the feasibility of using this proposed technique which mimics human reasoning where as the weight of the caught peace increases, the force increases also with approximatel

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Publication Date
Sun Sep 02 2012
Journal Name
Baghdad Science Journal
New Fuzzy Normed Spaces
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In this paper the research introduces a new definition of a fuzzy normed space then the related concepts such as fuzzy continuous, convergence of sequence of fuzzy points and Cauchy sequence of fuzzy points are discussed in details.

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Publication Date
Wed Sep 01 2021
Journal Name
Baghdad Science Journal
An Efficient Image Encryption Using a Dynamic, Nonlinear and Secret Diffusion Scheme
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The growing use of tele

This paper presents a new secret diffusion scheme called Round Key Permutation (RKP) based on the nonlinear, dynamic and pseudorandom permutation for encrypting images by block, since images are considered particular data because of their size and their information, which are two-dimensional nature and characterized by high redundancy and strong correlation. Firstly, the permutation table is calculated according to the master key and sub-keys. Secondly, scrambling pixels for each block to be encrypted will be done according the permutation table. Thereafter the AES encryption algorithm is used in the proposed cryptosystem by replacing the linear permutation of ShiftRows step with the nonlinear and secret pe

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