Preferred Language
Articles
/
nxbXw4gBVTCNdQwCO4Ft
Evaluating Machine Learning Techniques for Carbonate Formation Permeability Prediction Using Well Log Data
...Show More Authors

Machine learning has a significant advantage for many difficulties in the oil and gas industry, especially when it comes to resolving complex challenges in reservoir characterization. Permeability is one of the most difficult petrophysical parameters to predict using conventional logging techniques. Clarifications of the work flow methodology are presented alongside comprehensive models in this study. The purpose of this study is to provide a more robust technique for predicting permeability; previous studies on the Bazirgan field have attempted to do so, but their estimates have been vague, and the methods they give are obsolete and do not make any concessions to the real or rigid in order to solve the permeability computation. To verify the reliability of training data for zone-by-zone modeling, we split the scenario into two scenarios and applied them to seven wells' worth of data. Moreover, all wellbore intervals were processed, for instance, all five units of Mishrif formation. According to the findings, the more information we have, the more accurate our forecasting model becomes. Multi-resolution graph-based clustering has demonstrated its forecasting stability in two instances by comparing it to the other five machine learning models.

Scopus Crossref
View Publication
Publication Date
Sun Feb 24 2019
Journal Name
Iraqi Journal Of Physics
High spatial resolution digital elevation model (DEM) production using different interpolations techniques
...Show More Authors

DEMs, thus, simply regular grids of elevation measurements over the land surface.The aim of the present work is to produce high resolution DEM for certain investigated region (i.e. Baghdad University Campus\ college of science). The easting and northing of 90 locations, including the ground-base and buildings of the studied area, have been obtained by field survey using global positioning system (GPS). The image of the investigated area has been extracted from Quick-Bird satellite sensor (with spatial resolution of 0.6 m). It has been geo-referenced and rectified  using 1st order polynomial transformation. many interpolation methods have been used to estimate the elevation such as ordinary Kriging, inverse distance weight

... Show More
View Publication Preview PDF
Crossref
Publication Date
Wed Sep 01 2021
Journal Name
Egyptian Journal Of Petroleum
Identification of the best correlations of permeability anisotropy for Mishrif reservoir in West Qurna/1 oil Field, Southern Iraq
...Show More Authors

View Publication
Scopus (16)
Crossref (11)
Scopus Crossref
Publication Date
Tue Dec 01 2020
Journal Name
Baghdad Science Journal
A Modified Support Vector Machine Classifiers Using Stochastic Gradient Descent with Application to Leukemia Cancer Type Dataset
...Show More Authors

Support vector machines (SVMs) are supervised learning models that analyze data for classification or regression. For classification, SVM is widely used by selecting an optimal hyperplane that separates two classes. SVM has very good accuracy and extremally robust comparing with some other classification methods such as logistics linear regression, random forest, k-nearest neighbor and naïve model. However, working with large datasets can cause many problems such as time-consuming and inefficient results. In this paper, the SVM has been modified by using a stochastic Gradient descent process. The modified method, stochastic gradient descent SVM (SGD-SVM), checked by using two simulation datasets. Since the classification of different ca

... Show More
View Publication Preview PDF
Scopus (11)
Crossref (6)
Scopus Clarivate Crossref
Publication Date
Tue Nov 19 2024
Journal Name
Aip Conference Proceedings
CT scan and deep learning for COVID-19 detection
...Show More Authors

View Publication
Scopus Crossref
Publication Date
Mon Dec 20 2021
Journal Name
Baghdad Science Journal
Generative Adversarial Network for Imitation Learning from Single Demonstration
...Show More Authors

Imitation learning is an effective method for training an autonomous agent to accomplish a task by imitating expert behaviors in their demonstrations. However, traditional imitation learning methods require a large number of expert demonstrations in order to learn a complex behavior. Such a disadvantage has limited the potential of imitation learning in complex tasks where the expert demonstrations are not sufficient. In order to address the problem, we propose a Generative Adversarial Network-based model which is designed to learn optimal policies using only a single demonstration. The proposed model is evaluated on two simulated tasks in comparison with other methods. The results show that our proposed model is capable of completing co

... Show More
View Publication Preview PDF
Scopus Clarivate Crossref
Publication Date
Wed Sep 09 2009
Journal Name
University Of Baghdad
Estimation of Reservoir Rock Properties from Well Measurements
...Show More Authors

Porosity and permeability are the most difficult properties to determine in subsurface reservoir characterization. The difficulty of estimating them arising from the fact that porosity and permeability may vary significantly over the reservoir volume, and can only be sampled at well location. Secondly, the porosity values are commonly evaluated from the well log data, which are usually available from most wells in the reservoir, but permeability values, which are generally determined from core analysis, are not usually available. The aim of this study is: First, to develop correlations between the core and the well log data which can be used to estimate permeability in uncored wells, these correlations enable to estimate reservoir permeabil

... Show More
Preview PDF
Publication Date
Tue Aug 01 2023
Journal Name
Journal Of Engineering
Geomechanics Analysis of Well Drilling Instability: A Review
...Show More Authors

Wellbore instability is a significant problem faced during drilling operations and causes loss of circulation, caving, stuck pipe, and well kick or blowout. These problems take extra time to treat and increase the Nonproductive Time (NPT). This paper aims to review the factors that influence the stability of wellbores and know the methods that have been reached to reduce them. Based on a current survey, the factors that affect the stability of the wellbore are far-field stress, rock mechanical properties, natural fractures, pore pressure, wellbore trajectory, drilling fluid chemicals, mobile formations, naturally over-pressured shale collapse, mud weight, temperature, and time. Also, the most suitable ways to reduce well

... Show More
View Publication Preview PDF
Crossref (1)
Crossref
Publication Date
Sun Apr 12 2009
Journal Name
Journal Of Engineering
Correlations of Reservoir Rock Properties from Well Measurements
...Show More Authors

Publication Date
Wed Nov 13 2019
Journal Name
International Journal Of Research In Pharmaceutical Sciences
Prediction of maternal diabetes and adverse neonatal outcome in normotensive pregnancy using serum uric acid
...Show More Authors

Diabetes mellitus, with adverse neonatal events are challenging issues to all obstetricians and pediatricians, where uric acid could play a vital role. We aimed to assess the relationship and prognostic benefits of serum uric acid measured at about 20 weeks’ gestation in normotensive pregnancy, with subsequent maternal diabetes, and neonatal complications. All singleton normotensive pregnant women with normal blood glucose, serum creatinine, and weight before pregnancy, whom attended Medical City Hospital, Department of Obstetrics and Gynecology in Baghdad, were involved and regarded as the case group, on the condition that their serum uric acid measured at 20 weeks’ gestation > 3 mg/dl, but if ≤ 3 mg/dl, they would be regi

... Show More
View Publication Preview PDF
Scopus (8)
Crossref (5)
Scopus Crossref
Publication Date
Thu Oct 01 2020
Journal Name
Journal Of Engineering Science And Technology
Water quality assessment and sodium adsorption ratio prediction of Tigris River using artificial neural network
...Show More Authors