Often there is no well drilling without problems. The solution lies in managing and evaluating these problems and developing strategies to manage and scale them. Non-productive time (NPT) is one of the main causes of delayed drilling operations. Many events or possibilities can lead to a halt in drilling operations or a marginal decrease in the advancement of drilling, this is called (NPT). Reducing NPT has an important impact on the total expenditure, time and cost are considered one of the most important success factors in the oil industry. In other words, steps must be taken to investigate and eliminate loss of time, that is, unproductive time in the drilling rig in order to save time and cost and reduce wasted time. The data of six oil wells were approved for the purpose of the study, where it was noted that there are many factors affecting the NPT, which differ from one well to another. Its impact was limited to drilling rig, mud pump and equipment failure. There is also a difference between the planned program and what is actually happening on the ground, due to several reasons, including human errors during the implementation of the drilling program and others due to technical errors, Misuse of equipment, in addition to human errors related to the failure to implement the drilling program.
Background: Removal of bacteria from the pulp system by instrumentation of an infected root canal, will be significantly reduced the number of bacteria, but it is well documented that instrumentation alone can-not clean and kill all bacteria found on the root canal walls. Antibacterial irrigants are needed to kill the remaining microorganisms. The aims of this study was to assess antibacterial effect of titanium tetrafluoride (TiF4) solution and brewing green tea against root canal bacteria and to compare with sodium hypochlorite and normal saline through microbiological and molecular studies. Materials and methods: Microbiological study was carried out to determine the concentration of titanium tetrafluoride and brewing green tea at which
... Show MoreBackground Commonly heard statements such as “Christmas comes around more quickly each year” suggest that the passage of time between annual events can become distorted, leading to the sensation of time passing more quickly than normal. At present however, it is unclear how prevalent such beliefs are and, what factors are predictive of it. Aim To explore the prevalence of beliefs that annual events such as Christmas (Study 1 UK sample) and Ramadan (Study 2 Iraqi sample) feel like they come around more quickly each year. To establish the association between distortions to the passage of time between annual events and emotional wellbeing, event specific enjoyment, memory function and self-reported attention to time. Methods Participants c
... Show MoreIn order to select the optimal tracking of fast time variation of multipath fast time variation Rayleigh fading channel, this paper focuses on the recursive least-squares (RLS) and Extended recursive least-squares (E-RLS) algorithms and reaches the conclusion that E-RLS is more feasible according to the comparison output of the simulation program from tracking performance and mean square error over five fast time variation of Rayleigh fading channels and more than one time (send/receive) reach to 100 times to make sure from efficiency of these algorithms.
This paper presents a computer simulation model of a thermally activated roof (TAR) to cool a room using cool water from a wet cooling tower. Modeling was achieved using a simplified 1-D resistance-capacitance thermal network (RC model) for an infinite slab. Heat transfer from the cooling pipe network was treated as 2-D heat flow. Only a limited number of nodes were required to obtain reliable results. The use of 6th order RC-thermal model produced a set of ordinary differential equations that were solved using MATLAB - R2012a. The computer program was written to cover all possible initial conditions, material properties, TAR system geometry and hourly solar radiation. The cool water supply was considered time
... Show MoreThis study proposes a hybrid predictive maintenance framework that integrates the Kolmogorov-Arnold Network (KAN) with Short-Time Fourier Transform (STFT) for intelligent fault diagnosis in industrial rotating machinery. The method is designed to address challenges posed by non-linear and non-stationary vibration signals under varying operational conditions. Experimental validation using the FALEX multispecimen test bench demonstrated a high classification accuracy of 97.5%, outperforming traditional models such as SVM, Random Forest, and XGBoost. The approach maintained robust performance across dynamic load scenarios and noisy environments, with precision and recall exceeding 95%. Key contributions include a hardware-accelerated K
... Show MoreA field trial was conducted at Abu-Ghraib research station , Baghdad , Iraq . The objectives were to study the effect of nitrogen fertilizer and planting space on the performance of rape seed. A split-plot in a randomized complete of block design with three replications were used. Five levels of nitrogen fertilizer ( 120,160,200,240,280 Kg / ha ) were assigned to main plots, where as planting space in sub-plots. The result obtained confirmed that 280,240 kg / ha nitrogen maximized seed yield 1.830 , 1.773 ton/ha, oil yield,0.843,0.824 ton/ha .Results showed that planting space 30 cm produced the highest seed yield 1.90 ton / ha and oil yield , 0.884 ton / ha . Interactions between nitrogen fertilizer and p
... Show MoreThe aim of the research to apply TD-ABC technology to determine the idle capacity of the central oil companies (oil field east of Baghdad), as a modern cost management technology based on time-oriented activities (TD-ABC) is used by industrial companies in general and oil companies on In particular to build a sustainable Calvinist pillar and make future decisions by identifying idle energy to gain it a competitive advantage, the descriptive analytical approach has been adopted in calculating and analyzing the company’s data for 2018, and the most prominent conclusions of this research are managing idle energy and the task of applying cost technology on the basis of time-oriented activities and providing Convenient spatial infor
... Show MoreOil industry played a major role in delineating the course and type o development in both imported and exported Arabic countries alike where its revenues has perform an essential role in forming programs and plans of development on both national and international level in addition to anticipation of future consuming.
Iraq, as an oil producer country with a revenues –based economy depends on oil in building its economy totally including its infrastructure having a the greatest conformed reservoir which make the government budget depends largely on oil revenues where its strategic importance lies in funding all aspects of expenders as it is considered the prime source of foreign currency. The chall
... Show MoreGas-lift technique plays an important role in sustaining oil production, especially from a mature field when the reservoirs’ natural energy becomes insufficient. However, optimally allocation of the gas injection rate in a large field through its gas-lift network system towards maximization of oil production rate is a challenging task. The conventional gas-lift optimization problems may become inefficient and incapable of modelling the gas-lift optimization in a large network system with problems associated with multi-objective, multi-constrained, and limited gas injection rate. The key objective of this study is to assess the feasibility of utilizing the Genetic Algorithm (GA) technique to optimize t
The investigation of machine learning techniques for addressing missing well-log data has garnered considerable interest recently, especially as the oil and gas sector pursues novel approaches to improve data interpretation and reservoir characterization. Conversely, for wells that have been in operation for several years, conventional measurement techniques frequently encounter challenges related to availability, including the lack of well-log data, cost considerations, and precision issues. This study's objective is to enhance reservoir characterization by automating well-log creation using machine-learning techniques. Among the methods are multi-resolution graph-based clustering and the similarity threshold method. By using cutti
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