This research aims to study the methods of reduction of dimensions that overcome the problem curse of dimensionality when traditional methods fail to provide a good estimation of the parameters So this problem must be dealt with directly . Two methods were used to solve the problem of high dimensional data, The first method is the non-classical method Slice inverse regression ( SIR ) method and the proposed weight standard Sir (WSIR) method and principal components (PCA) which is the general method used in reducing dimensions,    (SIR ) and (PCA) is based on the work of linear combinations of a subset of the original explanatory variables, which may suffer from the problem of heterogeneity and the problem of linear

Mishrif Formation is the main reservoir in oil-fields (North Rumaila, South Rumaila, Majnoon, Zubair and West Qurna) which located at Basrah southern Iraq. The Inductively coupled plasma-Mass spectrometer (ICP-MS) was used for the water chemistry analysis and Scanning Electron Microprobe (SEM) for the purpose of mineralogy diagnosis. A weak acidic water of salinity six-time greater than seawater plays a role in generating the formation pressure and controlling the fluid flow. The potentiometric subsurface maps were modeled and the direction of super-pressure sites that are of a great importance in the oil exploration were marked to pay attention during future drilling.

Gumbel distribution was dealt with great care by researchers and statisticians. There are traditional methods to estimate two parameters of Gumbel distribution known as Maximum Likelihood, the Method of Moments and recently the method of re-sampling called (Jackknife). However, these methods suffer from some mathematical difficulties in solving them analytically. Accordingly, there are other non-traditional methods, like the principle of the nearest neighbors, used in computer science especially, artificial intelligence algorithms, including the genetic algorithm, the artificial neural network algorithm, and others that may to be classified as meta-heuristic methods. Moreover, this principle of nearest neighbors has useful statistical featu

Accurate rock typing is essential for reservoir characterization because heterogeneous carbonate reservoirs exhibit complex pore systems that weaken conventional porosity- permeability relationships. This study presents a comprehensive comparative evaluation of conventional and machine learning-based rock typing techniques for the Jeribe-Euphrates carbonate reservoir in the Fauqi Oil Field, southern Iraq. Unlike previous studies that focused on a single classification approach, this work systematically compares Hydraulic Flow Units, Discrete Rock Types, the Winland (R35) method, Lorenz curve analysis, Accumulated Correlation analysis, and machine learning clustering techniques using a unified dataset. The analysis was conducted on 1

In this research, we studied the multiple linear regression models for two variables in the presence of the autocorrelation problem for the error term observations and when the error is distributed with general logistic distribution. The auto regression model is involved in the studying and analyzing of the relationship between the variables, and through this relationship, the forecasting is completed with the variables as values. A simulation technique is used for comparison methods depending on the mean square error criteria in where the estimation methods that were used are (Generalized Least Squares, M Robust, and Laplace), and for different sizes of samples (20, 40, 60, 80, 100, 120). The M robust method is demonstrated the best metho

In this research, we studied the multiple linear regression models for two variables in the presence of the autocorrelation problem for the error term observations and when the error is distributed with general logistic distribution. The auto regression model is involved in the studying and analyzing of the relationship between the variables, and through this relationship, the forecasting is completed with the variables as values. A simulation technique is used for comparison methods depending

Entropy define as uncertainty measure has been transfared by using the cumulative distribution function and reliability function for the Burr type – xii. In the case of data which suffer from volatility to build a model the probability distribution on every failure of a sample after achieving limitations function, probabilistic distribution. Has been derived formula probability distribution of the new transfer application entropy on the probability distribution of continuous Burr Type-XII and tested a new function and found that it achieved the conditions function probability, been derived mean and function probabilistic aggregate in order to be approved in the generation of data for the purpose of implementation of simulation