Reservoir permeability plays a crucial role in characterizing reservoirs and predicting the present and future production of hydrocarbon reservoirs. Data logging is a good tool for assessing the entire oil well section's continuous permeability curve. Nuclear magnetic resonance logging measurements are minimally influenced by lithology and offer significant benefits in interpreting permeability. The Schlumberger-Doll-Research model utilizes nuclear magnetic resonance logging, which accurately estimates permeability values. The approach of this investigation is to apply artificial neural networks and core data to predict permeability in wells without a nuclear magnetic resonance log. The Schlumberger-Doll-Research permeability is used to train the model, where the model prediction result is validated with core permeability. Seven oil well logs were used as input parameters, and the model was constructed with Techlog software. The predicted permeability with the model compared with Schlumberger-Doll-Research permeability as a cross plot, which results in the correlation coefficient of 94%, while the predicted permeability validated with the core permeability of the well, which obtains good agreement where R2 equals 80%. The model was utilized to forecast permeability in a well that did not have a nuclear magnetic resonance log, and the predicted permeability was cross-plotted against core permeability as a validation step, with a correlation coefficient of 77%. As a result, the low percentage of matching was due to data limitations, which demonstrated that as the amount of data used to train the model increased, so did the precision.
The problem of research is the need to find out the obstacles and difficulties facing women in accessing leadership positions at the University of Baghdad from their point of view. The importance of research comes from the importance of women in the university and their vital role in the development of society. The research objectives summarized the most important obstacles facing women Access to the leadership positions in the university and the relative weight of these obstacles as well as trying to identify differences in their view of these obstacles according to the variables of specialization (scientific, human) and the scientific title (Professor, Assistant Professor, Teacher, Assistant Lecturer). They were (144) university female
... Show MoreMachine learning is considered a powerful technique in many applications such as classification, clustering, recognition and prediction. Deep learning is a modern, vital and superior machine learning that gives stunning performance, especially with huge data. Stock market price prediction is the process of determining the future value of a prospect of a financial instrument traded in the market, to gain a great profit a successful prediction must be conducted, in order to achieve that machine learning is used, in this article, two approaches are proposed to predict the stock market prices and movement using two datasets, the first approach employs two machine learning models (J48 & logistic regression) while the second approach based on rec
... Show MoreThe research aims to demonstrate the dual use of analysis to predict financial failure according to the Altman model and stress tests to achieve integration in banking risk management. On the bank’s ability to withstand crises, especially in light of its low rating according to the Altman model, and the possibility of its failure in the future, thus proving or denying the research hypothesis, the research reached a set of conclusions, the most important of which (the bank, according to the Altman model, is threatened with failure in the near future, as it is located within the red zone according to the model’s description, and will incur losses if it is exposed to crises in the future according to the analysis of stress tests
... Show MoreRecommender Systems are tools to understand the huge amount of data available in the internet world. Collaborative filtering (CF) is one of the most knowledge discovery methods used positively in recommendation system. Memory collaborative filtering emphasizes on using facts about present users to predict new things for the target user. Similarity measures are the core operations in collaborative filtering and the prediction accuracy is mostly dependent on similarity calculations. In this study, a combination of weighted parameters and traditional similarity measures are conducted to calculate relationship among users over Movie Lens data set rating matrix. The advantages and disadvantages of each measure are spotted. From the study, a n
... Show MoreThe purpose of this article is to introduce reverse engineering procedure (REP). It can achieved by developing an industrial mechanical product that had no design schemes throughout the 3D-Scanners. The aim of getting a geometric CAD model from 3D scanner is to present physical model. Generally, this used in specific applications, like commercial plan and manufacturing tasks. Having a digital data as stereolithography (STL) format. Converting the point cloud be can developed as a work in programming by producing triangles between focuses, a procedure known as triangulation. Then it could be easy to manufacture parts unknown documentation and transferred the information to CNC-machines. In this work, modification was proposed and used in RE
... Show MoreThrough his female characters, Walt Disney was able to reflect the
development of the general outlook upon women in the Western world over a period
of sixty years.
This paper sheds light in how the cartoon characters changed in their reaction
to problems and means of solving them from the 30s through to the 90s of the
previous century. The main characters will be seen according to the films’ dates of
production and release.
Background: In this work, a fingerprint powder was used to reveal latent fingerprints from different surfaces. This powder was derived from the Date fronds as activated carbon. Methods: In preparing the activated carbon, three parameters were studied: activation time, activation temperature, and impregnation ratio. Fourier Transform Infrared Spectroscopy (FTIR) was used to characterize the prepared Date frond activated carbon (DFAC) as well as the raw material (Date frond plant). Brunauer-Emmett-Teller (BET) was used to measure the specific surface area of DFAC. The surface shape and the element composition of the prepared powder were investigated using (SEM-EDS) analysis. A Central Composite Design (CCD) was employed to determine th
... Show MoreCancer remains a leading cause of mortality and morbidity worldwide. Advances in cancer therapies—including immunotherapies (e.g., checkpoint inhibitors, gene-targeted therapies), antibody-based cancer toxins, chemotherapy, radiotherapy, and surgery—have significantly improved survival rates 1,2. However, this progress has led to a surge in the prevalence of cardiovascular disease (CVD) among cancer survivors, now recognised as a leading cause of mortality in this population 3,4. These intersecting burdens highlight the growing need to prevent, detect, and manage cardiovascular complications in cancer care pathways and call for important initiatives in establishing cardio-oncology services globally.