Multilateral wells require a sophisticated type of well model to be applied in reservoir simulators to represent them. The model must be able to determine the flow rate of each fluid and the pressure throughout the well. The production rate calculations are very important because they give an indication about some main issues associated with multi-lateral wells such as one branch may produce water or gas before others, no production rate from one branch, and selecting the best location of a new branch for development process easily.                                &nbsp

The present article includes an experimental study of the behavior of dry and saturated dense sandy soil under the action of a single impulsive load. Dry and saturated dense sand models were tested under impact loads. Different falling masses from different heights were conducted using the falling weight deflectometer (FWD) to provide the single pulse energy. The responses of dense soils were evaluated at surface of soil under impact load. These responses include; displacements, velocities, and accelerations that are developed due to the impact acting at top and the displacement at different depths within the soil using the falling weight deflectometer (FWD) and accelerometers (ARH-500A waterproof, and low capacity acceleration tran

The: currency Auction is one of the monetary policy tools created after 2003, in order to keep pace with the changes that the monetary and financial policies will witness from financial openness and expectations of high levels of liquidity after international economic restrictions. It is necessary to re-evaluate the work of the currency Auction from time to time and observation its efficiency in adjustment the exchange rate And its reflection on the general level of prices as one of the objectives of its inception, and during the analytical aspect, it was confirmed that the currency Auction for selling the currency had a major role in adjustment the exchange rate and controlling inflation levels, due to the market’s dependence

Five different bacterial isolates [ Vibrio cholera (Ogawa) , Vibrio cholera (Inaba) , Salmonella typhi , Salmonella paratyphi and ? Salmonella typhimurium ] were obtained from the Central Health Laboratory . Both sensitivity tests (MIC , MBC and wells method ) against these bacteria were performed by using the aqueous of leaves extract of Marjoram plant. The results cleared that the values of MIC for Vibrio cholera serotypes Ogawa and Inaba were 100 mg/ml , while the value of MBC was 200 mg/ml. The value of the Inhibition zone at 100 mg /ml concentration for both Ogawa and Inaba were 13 mm and 9 mm respectively. Our results showed that the three types of Salmonella didn’t show any inhibition zone at 200 mg/ml .

In this paper we used frequentist and Bayesian approaches for the linear regression model to predict future observations for unemployment rates in Iraq. Parameters are estimated using the ordinary least squares method and for the Bayesian approach using the Markov Chain Monte Carlo (MCMC) method. Calculations are done using the R program. The analysis showed that the linear regression model using the Bayesian approach is better and can be used as an alternative to the frequentist approach. Two criteria, the root mean square error (RMSE) and the median absolute deviation (MAD) were used to compare the performance of the estimates. The results obtained showed that the unemployment rates will continue to increase in the next two decade

In this article, a numerical method integrated with statistical data simulation technique is introduced to solve a nonlinear system of ordinary differential equations with multiple random variable coefficients. The utilization of Monte Carlo simulation with central divided difference formula of finite difference (FD) method is repeated n times to simulate values of the variable coefficients as random sampling instead being limited as real values with respect to time. The mean of the n final solutions via this integrated technique, named in short as mean Monte Carlo finite difference (MMCFD) method, represents the final solution of the system. This method is proposed for the first time to calculate the numerical solution obtained fo

In this study, the response and behavior of machine foundations resting on dry and saturated sand was investigated experimentally. A physical model was manufactured to simulate steady state harmonic load applied on a footing resting on sandy soil at different operating frequencies. Total of (84) physical models were performed. The parameters that were taken into consideration include loading frequency, size of footing and different soil conditions. The footing parameters are related to the size of the rectangular footing and depth of embedment. Two sizes of rectangular steel model footing were used. The footings were tested by changing all parameters at the surface and at 50 mm depth below model surface. Meanwhile, the investigated paramete

In recent years, Bitcoin has become the most widely used blockchain platform in business and finance. The goal of this work is to find a viable prediction model that incorporates and perhaps improves on a combination of available models. Among the techniques utilized in this paper are exponential smoothing, ARIMA, artificial neural networks (ANNs) models, and prediction combination models. The study's most obvious discovery is that artificial intelligence models improve the results of compound prediction models. The second key discovery was that a strong combination forecasting model that responds to the multiple fluctuations that occur in the bitcoin time series and Error improvement should be used. Based on the results, the prediction acc

. In recent years, Bitcoin has become the most widely used blockchain platform in business and finance. The goal of this work is to find a viable prediction model that incorporates and perhaps improves on a combination of available models. Among the techniques utilized in this paper are exponential smoothing, ARIMA, artificial neural networks (ANNs) models, and prediction combination models. The study's most obvious discovery is that artificial intelligence models improve the results of compound prediction models. The second key discovery was that a strong combination forecasting model that responds to the multiple fluctuations that occur in the bitcoin time series and Error improvement should be used. Based on the results, the prediction a