Preferred Language
Articles
/
ijcpe-742
Using Artificial Neural Network to Predict Rate of Penetration from Dynamic Elastic Properties in Nasiriya Oil Field
...Show More Authors

   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.

Crossref
View Publication Preview PDF
Quick Preview PDF
Publication Date
Wed May 20 2026
Journal Name
Al-rafidain University College For Sciences
Use GARCH model to predict the stock market index, Saudi Arabia
...Show More Authors

In this paper has been building a statistical model of the Saudi financial market using GARCH models that take into account Volatility in prices during periods of circulation, were also study the effect of the type of random error distribution of the time series on the accuracy of the statistical model, as it were studied two types of statistical distributions are normal distribution and the T distribution. and found by application of a measured data that the best model for the Saudi market is GARCH (1,1) model when the random error distributed t. student's .

View Publication Preview PDF
Publication Date
Mon Aug 30 2021
Journal Name
Al-kindy College Medical Journal
Serum Biomarkers are Promising Tools to Predict Traumatic Brain Injury Outcome
...Show More Authors

Traumatic Brain Injury (TBI) is still considered a worldwide leading cause of mortality and morbidity. Within the last decades, different modalities were used to assess severity and outcome including Glasgow Coma Scale (GCS), imaging modalities, and even genetic polymorphism, however, determining the prognosis of TBI victims is still challenging requiring the emerging of more accurate and more applicable tools to surrogate other old modalities

View Publication Preview PDF
Crossref (2)
Crossref
Publication Date
Mon May 01 2023
Journal Name
Ain Shams Engineering Journal
Neural network modeling of rutting performance for sustainable asphalt mixtures modified by industrial waste alumina
...Show More Authors

Scopus (21)
Crossref (12)
Scopus Clarivate Crossref
Publication Date
Sat Feb 14 2026
Journal Name
Architecture Image Studies
The role of artificial intelligence in developing humanities studies from archaeological discovery to historical recording and geographical analysis: Application models
...Show More Authors

The Fourth Industrial Revolution represents an advanced stage of technological development, characterized by the integration of digital, physical, and biological technologies, with a strong focus on smart connectivity and advanced data analysis. At the core of this revolution stands Artificial Intelligence (AI), which enables the processing of vast amounts of data, decision-making with speed and accuracy, automation of processes, and enhancement of productivity and quality. This research examines the transformative role of AI in the humanities, particularly in archaeological, historical, and geographical studies, where traditional methods face limitations in handling complex and extensive datasets.The study aims to highlight these l

... Show More
View Publication Preview PDF
Crossref
Publication Date
Sat Jan 01 2022
Journal Name
Geotechnical Engineering And Sustainable Construction
Dynamic Response of Slender Reinforced Concrete Columns Strengthened by Using CFRP and Circularization Subjected to Seismic Excitation
...Show More Authors

View Publication
Crossref
Publication Date
Thu May 25 2023
Journal Name
Polycyclic Aromatic Compounds
Effect of Modified Nano-Graphene Oxide and Silicon Carbide Nanoparticles on the Mechanical Properties and Durability of Artificial Stone Composites from Waste
...Show More Authors

Sludge from stone-cutting (SSC) factories and stone mines cannot be used as decorative stones, stone powder, etc. These substances are left in the environment and cause environmental problems. This study aim is to produce artificial stone composite (ASC) using sludge from stone cutting factories, cement, unsaturated resin, water, silicon carbide nanoparticles (SiC-NPs), and nano-graphene oxide (NGO) as fillers. Nano graphene oxide has a hydrophobic plate structure that water is not absorbed due to the lack of surface tension on these plates. NGO has a significant effect on the properties of artificial stone due to its high specific surface area and low density in the composite. Its uniform distribution in ASC is very low due to its hydropho

... Show More
View Publication
Scopus (5)
Crossref (4)
Scopus Clarivate Crossref
Publication Date
Sun Jun 01 2025
Journal Name
Methodsx
How mathematical models might predict desertification from global warming and dust pollutants
...Show More Authors

View Publication
Scopus (15)
Crossref (16)
Scopus Clarivate Crossref
Publication Date
Thu Sep 01 2016
Journal Name
Journal Of Engineering
Calculating the Transport Density Index from Some of the Productivity Indicators for Railway Lines by Using Neural Networks
...Show More Authors

The efficiency evaluation of the railway lines performance is done through a set of indicators and criteria, the most important are transport density, the productivity of enrollee, passenger vehicle production, the productivity of freight wagon, and the productivity of locomotives. This study includes an attempt to calculate the most important of these indicators which transport density index from productivity during the four indicators, using artificial neural network technology. Two neural networks software are used in this study, (Simulnet) and (Neuframe), the results of second program has been adopted. Training results and test to the neural network data used in the study, which are obtained from the international in

... Show More
View Publication Preview PDF
Publication Date
Sun Jun 30 2013
Journal Name
Al-kindy College Medical Journal
Measuring Lower Uterine Segment Thickness Using Abdominal Ultrasound to Predict Timing of Cesarean Section in Women with Scarred Uterus at Elwiya Maternity Teaching Hospital
...Show More Authors

Background: Ultrasonography has been used to examine the thickness of the lower uterine segment in women with previous cesarean sections in an attempt to predict the risk of scar dehiscence during subsequent pregnancy. The predictive value of such measurement has not been adequately assessed. Objectives: To correlate lower uterine segment thickness measured by trans abdominal ultrasound in pregnant women with previous cesarean section with that measured during cesarean section by caliper and to find out minimum lower uterine segment thickness indicative of integrity of the scar.Methods: A prospective observational study at Elwyia Maternity Teaching Hospital, from January 2011 to January 2012. A total of 143 women were enrolled in the stu

... Show More
View Publication Preview PDF
Publication Date
Tue Sep 30 2025
Journal Name
Iraqi Journal Of Chemical And Petroleum Engineering
Oxidation desulfurization of model oil using carbon composite derived from peach stone waste
...Show More Authors

     In this study, oxidative desulfurization of dibenzothiophene (DBT) with H2O2 as an oxidant was studied, whereas the catalyst used was zirconium oxide supported on Activated carbon (AC). Zirconium oxide (ZrO2) was impregnated over prepared activated carbon (AC) and characterized by various techniques such as XRD, FTIR, BET, SEM, and EDX. This composite was used as a heterogeneous catalyst for oxidation desulfurization of simulated oil. The results of this study showed that ZrO2/AC composite exhibited significant catalytic activity and stability, effectively lowering sulfur content under mild conditions. Factors such as reaction temperature (30, 40, 50, 60°C), time (5, 10, 15,20,30,60, 80 100 min), catalyst dose (0.3, 0.5,

... Show More
View Publication
Crossref