Permeability estimation is a vital step in reservoir engineering due to its effect on reservoir's characterization, planning for perforations, and economic efficiency of the reservoirs. The core and well-logging data are the main sources of permeability measuring and calculating respectively. There are multiple methods to predict permeability such as classic, empirical, and geostatistical methods. In this research, two statistical approaches have been applied and compared for permeability prediction: Multiple Linear Regression and Random Forest, given the (M) reservoir interval in the (BH) Oil Field in the northern part of Iraq. The dataset was separated into two subsets: Training and Testing in order to cross-validate the accuracy and the performance of the algorithms. The random forest algorithm was the most accurate method leading to lowest Root Mean Square Prediction Error (RMSPE) and highest Adjusted R-Square than multiple linear regression algorithm for both training and testing subset respectively. Thus, random Forest algorithm is more trustable in permeability prediction in non-cored intervals and its distribution in the geological model.
<p><span>A Botnet is one of many attacks that can execute malicious tasks and develop continuously. Therefore, current research introduces a comparison framework, called BotDetectorFW, with classification and complexity improvements for the detection of Botnet attack using CICIDS2017 dataset. It is a free online dataset consist of several attacks with high-dimensions features. The process of feature selection is a significant step to obtain the least features by eliminating irrelated features and consequently reduces the detection time. This process implemented inside BotDetectorFW using two steps; data clustering and five distance measure formulas (cosine, dice, driver & kroeber, overlap, and pearson correlation
... Show MoreThe research aims to enhance the level of evaluation of the performance of banking transactions control policies and procedures. The research is based on the following hypothesis: efficient transactions control policies and procedures contribute enhancing financial reporting, by assessing non-application gap of those policies and procedures in a manner that helps to prevent, discover, and correct material misstatements. The researchers designed an examination list that includes the control policies and procedures related to the transactions, as a guide to the bank audit program prepared by the Federal Financial Supervision Bureau. The research methodology is
... Show MoreTerrorism is a global phenomenon that engulfs most regions of the world to varying degrees. Media outlets are aware of the many incidents of violence and terrorism that have increased in recent times. The differences between the size of the phenomenon in different societies are the causes and severity of the phenomenon. On the role of local satellite channels in shaping the knowledge and trends of the Iraqi public towards the events of terrorism, in light of the assumptions of reliance on the media. The importance of this study is that it assesses the role of local satellite channels in the formation of knowledge and trends The study seeks to know the extent of exposure of the Iraqi public to local satellite channels, and to reveal the e
... Show MoreFerritin is a key organizer of protected deregulation, particularly below risky hyperferritinemia, by straight immune-suppressive and pro-inflammatory things. , We conclude that there is a significant association between levels of ferritin and the harshness of COVID-19. In this paper we introduce a semi- parametric method for prediction by making a combination between NN and regression models. So, two methodologies are adopted, Neural Network (NN) and regression model in design the model; the data were collected from مستشفى دار التمريض الخاص for period 11/7/2021- 23/7/2021, we have 100 person, With COVID 12 Female & 38 Male out of 50, while 26 Female & 24 Male non COVID out of 50. The input variables of the NN m
... Show MoreIn many oil fields only the BHC logs (borehole compensated sonic tool) are available to provide interval transit time (Δtp), the reciprocal of compressional wave velocity VP.
To calculate the rock elastic or inelastic properties, to detect gas-bearing formations, the shear wave velocity VS is needed. Also VS is useful in fluid identification and matrix mineral identification.
Because of the lack of wells with shear wave velocity data, so many empirical models have been developed to predict the shear wave velocity from compressional wave velocity. Some are mathematical models others used the multiple regression method and neural network technique.
In this study a number of em
... Show MoreWith the escalation of cybercriminal activities, the demand for forensic investigations into these crimeshas grown significantly. However, the concept of systematic pre-preparation for potential forensicexaminations during the software design phase, known as forensic readiness, has only recently gainedattention. Against the backdrop of surging urban crime rates, this study aims to conduct a rigorous andprecise analysis and forecast of crime rates in Los Angeles, employing advanced Artificial Intelligence(AI) technologies. This research amalgamates diverse datasets encompassing crime history, varioussocio-economic indicators, and geographical locations to attain a comprehensive understanding of howcrimes manifest within the city. Lev
... Show MoreIn this research، a comparison has been made between the robust estimators of (M) for the Cubic Smoothing Splines technique، to avoid the problem of abnormality in data or contamination of error، and the traditional estimation method of Cubic Smoothing Splines technique by using two criteria of differentiation which are (MADE، WASE) for different sample sizes and disparity levels to estimate the chronologically different coefficients functions for the balanced longitudinal data which are characterized by observations obtained through (n) from the independent subjects، each one of them is measured repeatedly by group of specific time points (m)،since the frequent measurements within the subjects are almost connected an
... Show MoreThe petrophysical characteristics of five wells drilled into the Sa'di Formation in the Halfaya oil field were evaluated using IP software to determine a reservoir and explore hydrocarbon reserve zones. The lithology was evaluated using the M-N cross-plot method. The diagram showed that the Sa'di Formation was mainly composed of calcite (represented by the limestone region) is the main mineral in the Sa′di Reservoir. Using a density-neutron cross plot to identify the lithology showed that the formation mainly consists of limestone with minor shale. Gamma-ray logs were employed to calculate the shale quantity in each well. The porosity at weak hole intervals was calculated using a sonic log and neutron-density log at the reservoir
... Show MoreRadiological assessment for the East Baghdad oilfield-southern part was conducted in the current study. 10 samples (scale, soil, sludge, water, and oil) from the different stages of oil production were collected. 232Th, 226Ra, and 40K in the samples were analyzed with 40% efficiency for Gamma spectrometry. system based on HPGe. The findings indicated that the examined sites exhibit comparatively lower levels of NORM contamination, in contrast to other global oilfields. Nevertheless, certain areas, particularly those within separation stages, demonstrate relatively elevated NORM concentrations exceeding the global average in soil and sludge. The maximum value of 226Ra, 232Th, was found in sludge sample the findings indicated that ove
... Show MoreSome of the main challenges in developing an effective network-based intrusion detection system (IDS) include analyzing large network traffic volumes and realizing the decision boundaries between normal and abnormal behaviors. Deploying feature selection together with efficient classifiers in the detection system can overcome these problems. Feature selection finds the most relevant features, thus reduces the dimensionality and complexity to analyze the network traffic. Moreover, using the most relevant features to build the predictive model, reduces the complexity of the developed model, thus reducing the building classifier model time and consequently improves the detection performance. In this study, two different sets of select
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