Wellbore instability is one of the major issues observed throughout the drilling operation. Various wellbore instability issues may occur during drilling operations, including tight holes, borehole collapse, stuck pipe, and shale caving. Rock failure criteria are important in geomechanical analysis since they predict shear and tensile failures. A suitable failure criterion must match the rock failure, which a caliper log can detect to estimate the optimal mud weight. Lack of data makes certain wells' caliper logs unavailable. This makes it difficult to validate the performance of each failure criterion. This paper proposes an approach for predicting the breakout zones in the Nasiriyah oil field using an artificial neural network. It also presents the optimal mud weight window for this field, which can be used to optimise the mud weights to minimise the wellbore instability issues. The results showed that an artificial neural network is a powerful tool for determining the breakout zones using the input data. The obtaining root mean square error and the determination coefficient were respectively 0.0082 and 0.959, by which the 1D MEM gave a high match between the predicted wellbore instabilities using the Mogi-failure criterion and the predicted breakout using the ANN model. Most borehole enlargements occur due to formation shear failures because of using low mud weights during drilling. The conclusion clarify the1.35 g/cc is the optimal mud weights for drilling new wells in this field of interest with fewer drilling issues.
The Ground Penetrating Radar (GPR) is frequently used in pavement engineering
for road pavement inspection. The main objective of this work is to validate
nondestructive, quick and powerful measurements using GPR for assessment of subgrade
and asphalt /concrete conditions. In the present study, two different antennas
(250, 500 MHz) were used. The case studies are presented was carried in University
of Baghdad over about 100m of paved road. After data acquisition and radar grams
collection, they have been processed using RadExplorer V1.4 software
implementing different filters with the most effective ones (time zero adjustment and
DC removal) in addition to other interpretation tool parameters.
The interpretatio
Longitudinal data is becoming increasingly common, especially in the medical and economic fields, and various methods have been analyzed and developed to analyze this type of data.
In this research, the focus was on compiling and analyzing this data, as cluster analysis plays an important role in identifying and grouping co-expressed subfiles over time and employing them on the nonparametric smoothing cubic B-spline model, which is characterized by providing continuous first and second derivatives, resulting in a smoother curve with fewer abrupt changes in slope. It is also more flexible and can pick up on more complex patterns and fluctuations in the data.
The longitudinal balanced data profile was compiled into subgroup
... Show MoreA two time step stochastic multi-variables multi-sites hydrological data forecasting model was developed and verified using a case study. The philosophy of this model is to use the cross-variables correlations, cross-sites correlations and the two steps time lag correlations simultaneously, for estimating the parameters of the model which then are modified using the mutation process of the genetic algorithm optimization model. The objective function that to be minimized is the Akiake test value. The case study is of four variables and three sites. The variables are the monthly air temperature, humidity, precipitation, and evaporation; the sites are Sulaimania, Chwarta, and Penjwin, which are located north Iraq. The model performance was
... Show MoreABSTRACT : Diabetes mellitus stands for a set of metabolic diseases that if they are not managed, they can initiate threatening life problems. This study hypothesizes that insulin-like growth factor-1 level can be used as a biomarker for early diagnosing renal problems in patients with type 2 diabetic disease. This study included 30 recently identified type 2 diabetic patients with acute renal malfunction who had an entrance in National Diabetic Center,AL-Mustansiriyah University.They have beenin the Center from October 2018 up to end of April 2019. Their age range has been (40-62) years. Comprehensive clinical investigationhas beencompleted for each patient to discount other diabetic complications like cardiac, neurologic and eye complicat
... Show MoreAI in teaching English is reshaping language learning. While interest in AI-supported education is growing worldwide, research in this area is still emerging in Iraq. This review synthesizes empirical AI-based intervention studies to enhance English language learning in Iraqi higher education, and the perceptions of stakeholders regarding AI tools in language instruction. The reviewed intervention studies, comprising studies employed different AI platforms to support grammar instruction, speaking fluency, writing feedback, and pragmatic competence. These interventions yielded improvements in learners’ performance, motivation, and communicative confidence. In parallel, perception-focused studies revealed positive attitudes toward A
... Show MoreIn recent years the interest in fractured reservoirs has grown. The awareness has increased analysis of the role played by fractures in petroleum reservoir production and recovery. Since most Iraqi reservoirs are fractured carbonate rocks. Much effort was devoted to well modeling of fractured reservoirs and the impacts on production. However, turning that modeling into field development decisions goes through reservoir simulation. Therefore accurate modeling is required for more viable economic decision. Iraqi mature field being used as our case study. The key point for developing the mature field is approving the reservoir model that going to be used for future predictions. This can
The researchers have a special interest in studying Markov chains as one of the probability samples which has many applications in different fields. This study comes to deal with the changes issue that happen on budget expenditures by using statistical methods, and Markov chains is the best expression about that as they are regarded reliable samples in the prediction process. A transitional matrix is built for three expenditure cases (increase ,decrease ,stability) for one of budget expenditure items (base salary) for three directorates (Baghdad ,Nineveh , Diyala) of one of the ministries. Results are analyzed by applying Maximum likelihood estimation and Ordinary least squares methods resulting
... Show MoreBackground: The rapid evolution of Artificial Intelligence (AI) has significantly influenced Education, demonstrating substantial potential to transform traditional teaching and learning methods. AI reshapes teacher-student interactions and the relationship with knowledge. Objective: To analyze the potential benefits, ethical challenges, and limitations of AI in Education based on recent scientific literature, emphasizing the balance between technology and human interaction. Methods: A documentary research approach with a descriptive focus was employed, following the PRISMA protocol for systematic reviews. The search strategy involved analyzing evidence from 18 scientific articles published within the last six years. Results:AI o
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