Hydrocarbon production might cause changes in dynamic reservoir properties. Thus the consideration of the mechanical stability of a formation under different conditions of drilling or production is a very important issue, and basic mechanical properties of the formation should be determined. There is considerable evidence, gathered from laboratory measurements in the field of Rock Mechanics, showing a good correlation between intrinsic rock strength and the dynamic elastic constant determined from sonic-velocity and density measurements. The values of the mechanical properties determined from log data, such as the dynamic elastic constants derived from the measurement of the elastic wave velocities in the material, should be more accurate than that determined by direct strength tests with core samples. This can be attributed to the scale effect and sampling disturbances. The aim of this study was to present methods of determining measures of some mechanical properties, from available well log data (conventional sonic, density, and gamma ray) for a well in North Rumaila field. The mechanical properties include formation strength and Poisson’s ratio. For the formation strength, combined elastic modulus (Ec) and shear modulus (G) were determined. The Poisson’s ratio was determined by using three different techniques to permit the accuracy of their values. The elastic modulus, shear modulus, and Poisson’s ratio were then correlated with depth and effective stress. The results show that combined correlations are important source of the prediction of overpressure zones which represent a major problem encountered in drilling and production process.
Artificial neural networks usage, as a developed technique, increased in many fields such as Auditing business. Contemporary auditor should cope with the challenges of the technology evolution in the business environment by using computerized techniques such as Artificial neural networks, This research is the first work made in the field of modern techniques of the artificial neural networks in the field of auditing; it is made by using thesample of neural networks as a sample of the artificial multi-layer Back Propagation neural networks in the field of detecting fundamental mistakes of the financial statements when making auditing. The research objectives at offering a methodology for the application of theartificial neural networks wi
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EMS in accordance with ISO 14001: 2015 is considered an entry point to reduce environmental impacts, especially the effects resulting from the oil industry, which is the main source of environmental pollution and waste of natural resources, since the second revision of the standard took place in September 2015. The problem of the research was manifested in the weakness in understanding the correct guidelines that must be followed in order to obtain and maintain the standard. The purpose of this research was to give a general picture of what is behind ISO14001:2015 and how it is possible to create a comprehensive base for understanding its application by seeking the gap between the actually achieved reality, standards requirements
... Show MoreCadmium oxide (CdO) thin films were deposited using the sequencing ion layer adsorption and reaction (SILAR) method. In this study, the effect of the pH value of an aqueous solution of cadmium acetate at a concentration of 0.2 mol of the cadmium oxide film was determined. The solution source for the cadmium oxide film was cadmium ions and an aqueous ammonia solution. The CdO films were deposited on glass substrates at a temperature of 90 ℃. The cadmium oxide film thickness was determined by the weight difference method at pH values (7.2, 8.2). X-ray diffraction (XRD) and scanning electron microscopy (SEM) showed that the size of the crystals increased with the increase in the solution (pH). While the UV-visible spectra of the fil
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Baghdad Lake Touristic is suffering from a lake of tourism and entertainment services
efficiency provided to their visitors , knowing that this type of services as they are the basics
to achieve economic and socialist development because of their indicators where their goal is
to serve human in city as they represent lungs which population breathe within .
The Parks are resorted as human usually in search of quiet and funny places , away from
the noise of the city and its complex , as well as they give the city a beauty manifestations ,
that give happiness.
The study reached that there is deficiencies in service present, inability to provide
services and inadequate for the population and bad distribution. So the s
Spatial Autoregressive Model (SAR) is one of the modeling frameworks that indicates a spatial dependence in the response variable. SAR model has a weakness, which is represented by the unknown variance of the residuals. Therefore, an alternative model has used titled Spatial Autoregressive Quantile Regression (SARQR) model That which is obtained by combining SAR and Quantile Regression (QR) models, is a regression method with the approach of dividing the data into particular quantiles that are likely to have different estimate values. This alternative model addresses the variance issues in SAR models. Additionally, the SARQR model not only resolves the issue of spatial variance but also serves as a solution for dealing with non-normal data
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In this paper, we propose a method using continuous wavelets to study the multivariate fractional Brownian motion through the deviations of the transformed random process to find an efficient estimate of Hurst exponent using eigenvalue regression of the covariance matrix. The results of simulations experiments shown that the performance of the proposed estimator was efficient in bias but the variance get increase as signal change from short to long memory the MASE increase relatively. The estimation process was made by calculating the eigenvalues for the variance-covariance matrix of Meyer’s continuous wavelet details coefficients.
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Estimating an individual's age from a photograph of their face is critical in many applications, including intelligence and defense, border security and human-machine interaction, as well as soft biometric recognition. There has been recent progress in this discipline that focuses on the idea of deep learning. These solutions need the creation and training of deep neural networks for the sole purpose of resolving this issue. In addition, pre-trained deep neural networks are utilized in the research process for the purpose of facial recognition and fine-tuning for accurate outcomes. The purpose of this study was to offer a method for estimating human ages from the frontal view of the face in a manner that is as accurate as possible and takes
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In this paper, we propose a method using continuous wavelets to study the multivariate fractional Brownian motion through the deviations of the transformed random process to find an efficient estimate of Hurst exponent using eigenvalue regression of the covariance matrix. The results of simulations experiments shown that the performance of the proposed estimator was efficient in bias but the variance get increase as signal change from short to long memory the MASE increase relatively. The estimation process was made by calculating the eigenvalues for the variance-covariance matrix of Meyer’s continuous wavelet details coefficients.
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The electrical properties of pure NiO and NiO:Au Films which are
deposited on glass substrate with various dopant concentrations
(1wt.%, 2wt%, 3wt.% and 4wt.%) at room temperature 450 Co
annealing temperature will be presented. The results of the hall effect
showed that all the films were p-type. The Hall mobility decreases
while both carrier concentration and conductivity increases with the
increasing of annealing temperatures and doping percentage, Thus,
indicating the behavior of semiconductor, and also the D.C
conductivity from which the activation energy decrease with the
doping concentration increase and transport mechanism of the charge
carriers can be estimated.
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