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Using Artificial Neural Network to Predict Rate of Penetration from Dynamic Elastic Properties in Nasiriya Oil Field
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   The time spent in drilling ahead is usually a significant portion of total well cost. Drilling is an expensive operation including the cost of equipment and material used during the penetration of rock plus crew efforts in order to finish the well without serious problems. Knowing the rate of penetration should help in speculation of the cost and lead to optimize drilling outgoings. Ten wells in the Nasiriya oil field have 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 based on the las files and log record provided. The average rate of penetration and average dynamic elastic properties for the studied wells was determined and listed with depth. Laboratory measurements were conducted on core samples selected from two wells from the studied wells. Ultrasonic device was used to measure the transit time of compressional and shear waves and to compare these results with log records. The reason behind that is to check the accuracy of the Greenberg-Castagna equation that was used to estimate the shear wave in order to calculate dynamic elastic properties. The model was built using Artificial Neural Network (ANN) to predict the rate of penetration in Mishrif formation in the Nasiriya oil field for the selected wells. The results obtained from the model were compared with the provided rate of penetration from the field and the Mean Square Error (MSE) of the model was 3.58 *10-5.

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Publication Date
Sat Jun 01 2024
Journal Name
Pakistan Journal Of Criminology
Artificial Intelligence Technology in the Field of Modern Forensic Evidence: Brain Fingerprinting as a Model
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Brain Fingerprinting (BF) is one of the modern technologies that rely on artificial intelligence in the field of criminal evidence law. Brain information can be obtained accurately and reliably in criminal procedures without resorting to complex and multiple procedures or questions. It is not embarrassing for a person or even violates his human dignity, as well as gives immediate and accurate results. BF is considered one of the advanced techniques related to neuroscientific evidence that relies heavily on artificial intelligence, through which it is possible to recognize whether the suspect or criminal has information about the crime or not. This is done through Magnetic Resonance Imaging (EEG) of the brain and examining

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Publication Date
Tue Jan 01 2019
Journal Name
Spe Europec Featured At 81st Eage Conference And Exhibition
Development of Artificial Neural Networks and Multiple Regression Analysis for Estimating of Formation Permeability
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Publication Date
Sat Sep 30 2023
Journal Name
Iraqi Geological Journal
Radiological Effects Assessment in East Baghdad Oil Field, Southern Area
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Radiological assessment for the East Baghdad oilfield-southern part was conducted in the current study. 10 samples (scale, soil, sludge, water, and oil) from the different stages of oil production were collected. 232Th, 226Ra, and 40K in the samples were analyzed with 40% efficiency for Gamma spectrometry. system based on HPGe. The findings indicated that the examined sites exhibit comparatively lower levels of NORM contamination, in contrast to other global oilfields. Nevertheless, certain areas, particularly those within separation stages, demonstrate relatively elevated NORM concentrations exceeding the global average in soil and sludge. The maximum value of 226Ra, 232Th, was found in sludge sample the findings indicated that ove

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Publication Date
Thu Apr 21 2022
Journal Name
Journal Of Petroleum Research And Studies
Smart Well Modelling for As Reservoir in AG Oil Field
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Intelligent or smart completion wells vary from conventional wells. They have downhole flow control devices like Inflow Control Devices (ICD) and Interval Control Valves (ICV) to enhance reservoir management and control, optimizing hydrocarbon output and recovery. However, to explain their adoption and increase their economic return, a high level of justification is necessary. Smart horizontal wells also necessitate optimizing the number of valves, nozzles, and compartment length. A three-dimensional geological model of the As reservoir in AG oil field was used to see the influence of these factors on cumulative oil production and NPV. After creating the dynamic model for the As reservoir using the program Petrel (2017.4), we

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Publication Date
Sat Dec 31 2022
Journal Name
Iraqi Journal Of Market Research And Consumer Protection
RELATIONSHIP OF LHX3 GENE POLYMORPHISM TO FERTILITY RATE IN LOCAL AND SHAMI GOATS: RELATIONSHIP OF LHX3 GENE POLYMORPHISM TO FERTILITY RATE IN LOCAL AND SHAMI GOATS
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ABSTRACT

The study was conducted at the ruminant research station of the general commission for agricultural research/Ministry of Agriculture, as well as the laboratory of genetic resources of the department of livestock/Ministry of Agriculture and the laboratory of the college of agriculture engineering science, with the aim of determine the genotypic of the expression region (intron 2 and part of exon 3) of the LHX3 gene And its relationship to the fertility rate in local and Shami goats. For this purpose, the RFLP technique was used, and the percentages of genotypes for the LHX3 gene in the local goat sample were 29.17, 50.00, 20.83 for the TT, AT, and AA genotypes, respectively, while in the Shami goa

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Publication Date
Wed Mar 05 2025
Journal Name
Lecture Notes In Networks And Systems
Using Artificial Intelligence to Enhance Family Cohesion and Promote Positive Social Values
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Publication Date
Wed Jan 01 2025
Journal Name
Lecture Notes In Networks And Systems
Diagnosis of Diabetes Using Artificial Intelligence Programs
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Scientific development has occupied a prominent place in the field of diagnosis, far from traditional procedures. Scientific progress and the development of cities have imposed diseases that have spread due to this development, perhaps the most prominent of which is diabetes for accurate diagnosis without examining blood samples and using image analysis by comparing two images of the affected person for no less than a period. Less than ten years ago they used artificial intelligence programs to analyze and prove the validity of this study by collecting samples of infected people and healthy people using one of the Python program libraries, which is (Open-CV) specialized in measuring changes to the human face, through which we can infer the

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Publication Date
Fri Nov 09 2018
Journal Name
Iraqi National Journal Of Nursing Specialties
Feeding Problems in Children with Congenital Heart Diseases in Nasiriya Heart Center
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Objective: To identify feeding problems of children with congenital heart disease.
Methodology: Non probability (purposive) sample of (65) were selected of 225 children who visit Al Nasiriya
heart center during the period of conducting the pilot study, previously diagnosed with congenital heart
disease.
Results: The study results indicated that children with congenital heart disease have feeding difficulties, low
birth weight , repeated diarrhea , more than half of the sample taking medication for heart disease which cause
repeated vomiting, difficulty taking liquids and refusal of feeding or eating.(64.6%) of study sample suffered
from wasting. (78.5%) suffered from stunting. Almost half of the study sample suffered

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Publication Date
Thu Apr 01 2021
Journal Name
Complexity
Bayesian Regularized Neural Network Model Development for Predicting Daily Rainfall from Sea Level Pressure Data: Investigation on Solving Complex Hydrology Problem
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Prediction of daily rainfall is important for flood forecasting, reservoir operation, and many other hydrological applications. The artificial intelligence (AI) algorithm is generally used for stochastic forecasting rainfall which is not capable to simulate unseen extreme rainfall events which become common due to climate change. A new model is developed in this study for prediction of daily rainfall for different lead times based on sea level pressure (SLP) which is physically related to rainfall on land and thus able to predict unseen rainfall events. Daily rainfall of east coast of Peninsular Malaysia (PM) was predicted using SLP data over the climate domain. Five advanced AI algorithms such as extreme learning machine (ELM), Bay

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Publication Date
Mon Feb 01 2021
Journal Name
Indonesian Journal Of Electrical Engineering And Computer Science
Comparative study of logistic regression and artificial neural networks on predicting breast cancer cytology
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<p>Currently, breast cancer is one of the most common cancers and a main reason of women death worldwide particularly in<strong> </strong>developing countries such as Iraq. our work aims to predict the type of tumor whether benign or malignant through models that were built using logistic regression and neural networks and we hope it will help doctors in detecting the type of breast tumor. Four models were set using binary logistic regression and two different types of artificial neural networks namely multilayer perceptron MLP and radial basis function RBF. Evaluation of validated and trained models was done using several performance metrics like accuracy, sensitivity, specificity, and AUC (area under receiver ope

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