Preferred Language
Articles
/
JIa4RIYBIXToZYALgYGp
Development of Artificial Intelligence Models for Estimating Rate of Penetration in East Baghdad Field, Middle Iraq
...Show More Authors

It is well known that the rate of penetration is a key function for drilling engineers since it is directly related to the final well cost, thus reducing the non-productive time is a target of interest for all oil companies by optimizing the drilling processes or drilling parameters. These drilling parameters include mechanical (RPM, WOB, flow rate, SPP, torque and hook load) and travel transit time. The big challenge prediction is the complex interconnection between the drilling parameters so artificial intelligence techniques have been conducted in this study to predict ROP using operational drilling parameters and formation characteristics. In the current study, three AI techniques have been used which are neural network, fuzzy inference system and genetic algorithm. An offset field data was collected from mud logging and wire line log from East Baghdad oil field south region to build the AI models, including datasets of two wells: well 1 for AI modeling and well 2 for validation of the obtained results. The types of interesting formations are sandstone and shale (Nahr Umr and Zubair formations). Nahr Umr and Zubair formations are medium –harder. The prediction results obtained from this study showed that the ANN technique can predict the ROP with high efficiency as well as FIS technique could achieve reliable results in predicting ROP, but GA technique has shown a lower efficiency in predicting ROP. The correlation coefficient and RMSE were two criteria utilized to evaluate and estimate the performance ability of AI techniques in predicting ROP and comparing the obtained results. In the Nahr Umr and Zubair formations, the obtained correlation coefficient values for training processes of ANN, FIS and GA were 0.94, 0.93, and 0.76 respectively. Data sets from another well (well 2) in the same field of interest were utilized to validate of the developed models. Datasets of well 2 were conducted against sandstone and shale formations (Nahr Umr and Zubair formations). The results revealed a good matching between the actual rate of penetration values and the predicted ROP values using two artificial intelligence techniques (neural network, and fuzzy inference technique). In contrast, the genetic algorithm model showed overestimation/ underestimation of the rate of penetration against sandstone and shale formations. This means that the optimum prediction of rate of penetration can be obtained from neural network model rather than using genetic algorithm and genetic algorithm techniques. The developed model can be successfully used to predict the rate of penetration and optimize the drilling parameters, achieving reduce the cost and time of future wells that will be drilled in the East Baghdad Iraqi oil field.

Crossref
Publication Date
Wed Feb 05 2020
Journal Name
Political Sciences Journal
Populism in the Middle East: Discourse and Comparative Characteristics
...Show More Authors

Abstract: The premise of the study is that populism is a process of building political views and critical intellectual orientations among the general public. It is transformed into mass beliefs by mobilizing the society ideologically and continuously in order to reach or control the circle of authority. We distributed the study topics to four sections: In the second, we will discuss the contents of contemporary populism and how other forms of populism evolved historically. The third is to discuss the political discourse of populism among the military regimes and the comparative Islamic parties in the Middle East, especially in terms of the essence and the intellectual foundations. The fourth section seeks to examine the characteristics o

... Show More
View Publication Preview PDF
Crossref (1)
Crossref
Publication Date
Tue Nov 09 2021
Journal Name
Journal Of Accounting And Financial Studies ( Jafs )
Artificial intelligence in accounting education and its role in achieving sustainable development goals in the Kingdom of Bahrain/University of Applied Sciences as a model
...Show More Authors

The research aims to show the relationship between artificial intelligence in accounting education and its role in achieving sustainable development goals in the Kingdom of Bahrain. The research dealt with the role of artificial intelligence applications in accounting education at the University of Applied Sciences as a model for Bahraini universities to achieve sustainable development goals. The application of artificial intelligence in accounting education achieves seven of the seventeen sustainable development goals. It also concludes that there is an artificial intelligence infrastructure in the Kingdom of Bahrain, as it occupies a leading regional position in digital transformation, as Bahrain ranks first in the Arab world i

... Show More
View Publication Preview PDF
Publication Date
Sun Dec 01 2019
Journal Name
Computers And Electronics In Agriculture
Meteorological data mining and hybrid data-intelligence models for reference evaporation simulation: A case study in Iraq
...Show More Authors

View Publication
Crossref (111)
Crossref
Publication Date
Sat Dec 17 2022
Journal Name
Applied Sciences
A Hybrid Artificial Intelligence Model for Detecting Keratoconus
...Show More Authors

Machine learning models have recently provided great promise in diagnosis of several ophthalmic disorders, including keratoconus (KCN). Keratoconus, a noninflammatory ectatic corneal disorder characterized by progressive cornea thinning, is challenging to detect as signs may be subtle. Several machine learning models have been proposed to detect KCN, however most of the models are supervised and thus require large well-annotated data. This paper proposes a new unsupervised model to detect KCN, based on adapted flower pollination algorithm (FPA) and the k-means algorithm. We will evaluate the proposed models using corneal data collected from 5430 eyes at different stages of KCN severity (1520 healthy, 331 KCN1, 1319 KCN2, 1699 KCN3 a

... Show More
View Publication
Scopus (1)
Crossref (3)
Scopus Clarivate Crossref
Publication Date
Wed Jul 01 2020
Journal Name
Journal Of Engineering
Using Adaptive Neuro Fuzzy Inference System to Predict Rate of Penetration from Dynamic Elastic Properties
...Show More Authors

Rate of penetration plays a vital role in field development process because the drilling operation is expensive and include the cost of equipment and materials used during the penetration of rock and efforts of the crew in order to complete the well without major problems. It’s important to finish the well as soon as possible to reduce the expenditures. So, knowing the rate of penetration in the area that is going to be drilled will help in speculation of the cost and that will lead to optimize drilling outgoings. In this research, an intelligent model was built using artificial intelligence to achieve this goal.  The model was built using adaptive neuro fuzzy inference system to predict the rate of penetration in

... Show More
View Publication Preview PDF
Crossref
Publication Date
Mon Jul 31 2017
Journal Name
Journal Of Engineering
Rigid Trunk Sewer Deterioration Prediction Models using Multiple Discriminant and Neural Network Models in Baghdad City, Iraq
...Show More Authors

View Publication Preview PDF
Publication Date
Tue Aug 01 2017
Journal Name
Journal Of Engineering
Rigid trunk sewer deterioration prediction models using multiple discriminant and neural network models in Baghdad city, Iraq
...Show More Authors

The deterioration of buried sewers during their lifetime can be affected by several factors leading to bad performance and can damage the infrastructure similar to other engineering structures. The Hydraulic deterioration of the buried sewers caused by sewer blockages while the structural deterioration caused by sewer collapses due to sewer specifications and the surrounding soil characteristics and the groundwater level. The main objective of this research is to develop deterioration models, which are used to predict changes in sewer condition that can provide assessment tools for determining the serviceability of sewer networks in Baghdad city. Two deterioration models were developed and tested using statistical software SPSS, the

... Show More
Publication Date
Tue Dec 01 2009
Journal Name
Journal Of Economics And Administrative Sciences
Using Artificial Neural Network Models For Forecasting & Comparison
...Show More Authors

The Artificial Neural Network methodology is a very important & new subjects that build's the models for Analyzing, Data Evaluation, Forecasting & Controlling without depending on an old model or classic statistic method that describe the behavior of statistic phenomenon, the methodology works by simulating the data to reach a robust optimum model that represent the statistic phenomenon & we can use the model in any time & states, we used the Box-Jenkins (ARMAX) approach for comparing, in this paper depends on the received power to build a robust model for forecasting, analyzing & controlling in the sod power, the received power come from

... Show More
View Publication Preview PDF
Crossref
Publication Date
Fri Mar 31 2023
Journal Name
Iraqi Geological Journal
Subsurface Structural Image of Galabat Field, North East of Iraq Using 2D Seismic Data
...Show More Authors

This research had been achieved to identify the image of the subsurface structure representing the Tertiary period in the Galabat Field northeast of Iraq using 2D seismic survey measurements. Synthetic seismograms of the Galabat-3 well were generated in order to identify and pick the reflectors in seismic sections. Structural Images were drawn in the time domain and then converted to the depth domain by using average velocities. Structurally, seismic sections illustrate these reflectors are affected by two reverse faults affected on the Jeribe Formation and the layers below with the increase in the density of the reverse faults in the northern division. The structural maps show Galabat field, which consists of longitudinal Asymmetrical narr

... Show More
View Publication
Scopus (2)
Scopus Crossref
Publication Date
Wed Jan 30 2019
Journal Name
Journal Of The College Of Education For Women
Turkish and Iranian attitudes toward Political changes in Middle East
...Show More Authors

There are many developments in political, strategic aspects in the middle east either in
international field which represented by U.S.A as first polar in world or territorial field which
represent by Turkey and Iran, as territorial powers in the region, Turkish role is fit with
American position in order to draw new map of middle east, Turkey advocate new policy to
confirm its attitude in Euro peen Union and its relation with U.S.A.
Iran adopted policy of Expansion in Iraq, Yamen, Lebanon and Syria, in addition Iran
enlist all it efforts to develop its Nuclear program and enter Nuclear club which make Iran,
Super power in middle east and the world, each Turkey and Iran have certain attitudes toward
all political c

... Show More
View Publication Preview PDF