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Artificial Intelligent Models for Detection and Prediction of Lost Circulation Events: A Review
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Lost circulation or losses in drilling fluid is one of the most important problems in the oil and gas industry, and it appeared at the beginning of this industry, which caused many problems during the drilling process, which may lead to closing the well and stopping the drilling process. The drilling muds are relatively expensive, especially the muds that contain oil-based mud or that contain special additives, so it is not economically beneficial to waste and lose these muds. The treatment of drilling fluid losses is also somewhat expensive as a result of the wasted time that it caused, as well as the high cost of materials used in the treatment such as heavy materials, cement, and others. The best way to deal with drilling fluid losses is to prevent them. Drilling fluid loss is a complex problem that is difficult to predict using simple and traditional methods. Artificial intelligence represents a modern and accurate technology for solving complex problems such as drilling fluid loss. Artificial intelligence through supervised machine learning provides the possibility of predicting these losses before they occur based on field data such as drilling fluid properties, drilling parameters, rock properties, and geomechanical parameters that are related to the loss of circulation of the wells suffered from losses problem located in the same area.

   In this paper, several supervised machine learning models have been reviewed that were used for detecting and predicting of loss of drilling fluids during the drilling process. The paper provides an inclusive review of drilling fluid prediction and detection from simplest to more complected intelligent models.

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Publication Date
Wed Jun 01 2016
Journal Name
Journal Of Engineering
Seismic Effects and Static Analysis for the Artificial Damped Outrigger Systems in Tall R.C Buildings
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This paper studies the combination fluid viscous dampers in the outrigger system to add supplementary damping into the structure, which purpose to remove the dependability of the structure to lower variable intrinsic damping. It works by connecting the central core, comprising either shear walls or braced frames, to the outer perimeter columns.

     The modal considered is a 36 storey square high rise reinforced concrete building. By constructing a discrete lumped mass model, and using frequency-based response function, two systems of dampers, parallel and series systems are studied. The maximum lateral load at the top of the building is calculated, and  this load  w

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Publication Date
Thu Aug 24 2017
Journal Name
Clinical Case Reports
Primary hypogonadism, partial alopecia, and Müllerian hypoplasia: report of a fifth family and review
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Key Clinical Message<p>Primary hypogonadism combined with Müllerian hypoplasia and partial alopecia are common features of this syndrome, which was reported only in four earlier families from areas where consanguineous marriage is prevalent. An autosomal recessive pattern of inheritance was suggested earlier and is supported by this report.</p>
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Publication Date
Wed Mar 20 2024
Journal Name
Journal Of Petroleum Research And Studies
Advanced Machine Learning application for Permeability Prediction for (M) Formation in an Iraqi Oil Field
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Permeability estimation is a vital step in reservoir engineering due to its effect on reservoir's characterization, planning for perforations, and economic efficiency of the reservoirs. The core and well-logging data are the main sources of permeability measuring and calculating respectively. There are multiple methods to predict permeability such as classic, empirical, and geostatistical methods. In this research, two statistical approaches have been applied and compared for permeability prediction: Multiple Linear Regression and Random Forest, given the (M) reservoir interval in the (BH) Oil Field in the northern part of Iraq. The dataset was separated into two subsets: Training and Testing in order to cross-validate the accuracy

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Publication Date
Mon Dec 30 2019
Journal Name
College Of Islamic Sciences
The matter, its wisdom, and models of its applications In Ahmadiyya interpretations Research drawn from a doctoral thesis
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This study examined the tagged (the matter, its ruling, and examples of its applications in Ahmadiyya interpretations), the study of devising formulas of commissioning, especially the matter from the book of interpretation, which is: (Ahmadiyyeh’s interpretations), and the contemplative of the nature of (Ahmadiyya’s interpretations) realizes that the cognitive, linguistic and juristic knowledge product and the verses of judgments And other is the focus of this immortal travel, as it is truly a comprehensive book containing what the students of knowledge, scholars and the general public need in terms of interpreting the legal verses, and it is not possible to reach an understanding of the Book of God Almighty, and to clarify his purpo

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Publication Date
Sat Dec 31 2011
Journal Name
Al-khwarizmi Engineering Journal
Back stepping-Based-PID-Controller Designed for an Artificial Pancreas model
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Artificial pancreas is simulated to handle Type I diabetic patients under intensive care by automatically controlling the insulin infusion rate. A Backstepping technique is used to apply the effect of PID controller to blood glucose level since there is no direct relation between insulin infusion (the manipulated variable) and glucose level in Bergman’s system model subjected to an oral glucose tolerance test by applying a meal translated into a disturbance. Backstepping technique is usually recommended to stabilize and control the states of Bergman's class of nonlinear systems. The results showed a very satisfactory behavior of glucose deviation to a sudden rise represented by the meal that increase the blood glucose

 

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Publication Date
Thu Dec 16 2021
Journal Name
Journal Of Advance Research In Chemical Sciences
Study of Schiff Bases Complexes of Trimethoprim: A Review
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Trimethoprim derivative Schiff bases are versatile ligands synthesized with carbonyl groups from the condensation of primary amines (amino acids). Because of their broad range of biological activity, these compounds are very important in the medical and pharmaceutical fields. Biological activities such as antibacterial, antifungal and antitumor activity are often seen. Transition metal complexes derived from biological activity Schiff base ligands have been commonly used.

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Publication Date
Sat Oct 16 2021
Journal Name
Journal Of Advance Research In Chemical Sciences
Study of Schiff Bases Complexes of Trimethoprim: A Review
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Publication Date
Thu Sep 16 2021
Journal Name
Journal Of Advance Research In Chemical Sciences
Study of Schiff Bases Complexes of Trimethoprim: A Review
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Trimethoprim derivative Schiff bases are versatile ligands synthesized with carbonyl groups from the condensation of primary amines (amino acids). Because of their broad range of biological activity, these compounds are very important in the medical and pharmaceutical fields. Biological activities such as antibacterial, antifungal and antitumor activity are often seen. Transition metal complexes derived from biological activity Schiff base ligands have been commonly used

Publication Date
Sun Jul 09 2023
Journal Name
Journal Of Engineering
Comparison between Linear and Non-linear ANN Models for Predicting Water Quality Parameters at Tigris River
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In this research, Artificial Neural Networks (ANNs) technique was applied in an attempt to predict the water levels and some of the water quality parameters at Tigris River in Wasit Government for five different sites. These predictions are useful in the planning, management, evaluation of the water resources in the area. Spatial data along a river system or area at different locations in a catchment area usually have missing measurements, hence an accurate prediction. model to fill these missing values is essential.
The selected sites for water quality data prediction were Sewera, Numania , Kut u/s, Kut d/s, Garaf observation sites. In these five sites models were built for prediction of the water level and water quality parameters.

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Publication Date
Sun Mar 17 2019
Journal Name
Baghdad Science Journal
A Study on the Accuracy of Prediction in Recommendation System Based on Similarity Measures
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Recommender Systems are tools to understand the huge amount of data available in the internet world. Collaborative filtering (CF) is one of the most knowledge discovery methods used positively in recommendation system. Memory collaborative filtering emphasizes on using facts about present users to predict new things for the target user. Similarity measures are the core operations in collaborative filtering and the prediction accuracy is mostly dependent on similarity calculations. In this study, a combination of weighted parameters and traditional similarity measures are conducted to calculate relationship among users over Movie Lens data set rating matrix. The advantages and disadvantages of each measure are spotted. From the study, a n

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