Prediction of penetration rate (ROP) is important process in optimization of drilling due to its crucial role in lowering drilling operation costs. This process has complex nature due to too many interrelated factors that affected the rate of penetration, which make difficult predicting process. This paper shows a new technique of rate of penetration prediction by using artificial neural network technique. A three layers model composed of two hidden layers and output layer has built by using drilling parameters data extracted from mud logging and wire line log for Alhalfaya oil field. These drilling parameters includes mechanical (WOB, RPM), hydraulic (HIS), and travel transit time (DT). Five data set represented five formations gathered from five drilled wells were involved in modeling process.Approximatlly,85 % of these data were used for training the ANN models, and 15% to assess their accuracy and direction of stability. The results of the simulation showed good matching between the raw data and the predicted values of ROP by Artificial Neural Network (ANN) model. In addition, a good fitness was obtained in the estimation of drilling cost from ANN method when compared to the raw data.
The Carbonate-clastic succession in this study is represented by the Shuaiba and Nahr Umr Formations deposited during the Albian - Aptian Sequence. The present study includes petrography, microfacies analyses, and studying reservoir characterizations for 5 boreholes within West Qurna oil field in the study area. According to the type of study succession (clastic – Carbonate) there are two types of facies analyses:-Carbonate facies analysis, which showed five major microfacies were recognized in the succession of the Shuaiba Formation, bioclastic mudstones to wackstone, Orbitolina wackestone to packstone, Miliolids wackestone, Peloidal wackestone to packstone and mudstone to wackestone identified as an open shelf toward the deep basin.
... Show MoreKnowledge of permeability is critical for developing an effective reservoir description. Permeability data may be calculated from well tests, cores and logs. Normally, using well log data to derive estimates of permeability is the lowest cost method. This paper will focus on the evaluation of formation permeability in un-cored intervals for Abughirab field/Asmari reservoir in Iraq from core and well log data. Hydraulic flow unit (HFU) concept is strongly related to the flow zone indicator (FZI) which is a function of the reservoir quality index (RQI). Both measures are based on porosity and permeability of cores. It is assumed that samples with similar FZI values belong to the same HFU. A generated method is also used to calculate permea
... Show MoreWith the spread of globalization, the need for translators and scholars has grown, as translation is the only process that helps bridge linguistic gaps. Following the emergence of artificial intelligence (AI), a strong competitor has arisen to the translators, sweeping through all scientific and professional fields, including translation sector, with a set of tools that aid in the translation process. The current study aims to investigate the capability of AI tools in translating texts rich in cultural variety from one language to another, specifically focusing on English-Arabic translations, through qualitative analysis to uncover cultural elements in the target language and determine the ability of AI tools to preserve, lose, or alter the
... Show MoreArtificial Intelligence Algorithms have been used in recent years in many scientific fields. We suggest employing flower pollination algorithm in the environmental field to find the best estimate of the semi-parametric regression function with measurement errors in the explanatory variables and the dependent variable, where measurement errors appear frequently in fields such as chemistry, biological sciences, medicine, and epidemiological studies, rather than an exact measurement. We estimate the regression function of the semi-parametric model by estimating the parametric model and estimating the non-parametric model, the parametric model is estimated by using an instrumental variables method (Wald method, Bartlett’s method, and Durbin
... Show MoreCrop yield prediction is a critical measurement, especially in the time when parts of the world are suffering from farming issues. Yield forecasting gives an alert regarding economic trading, food production monitoring, and global food security. This research was conducted to investigate whether active optical sensors could be utilized for potato (Solanum tuberosum L.) yield prediction at the mid.le of the growing season. Three potato cultivars (Russet Burbank, Superior, and Shepody) were planted and six rates of N (0, 56, 112, 168, 224, and 280 kg ha−1), ammonium sulfate, which was replaced by ammonium nitrate in the 2nd year, were applied on 11 sites in a randomized complete block design, with four replications. Normalized difference ve
... Show MoreAbstract
A surface fitting model is developed based on calorimeter data for two famous brands of household compressors. Correlation equations of ten coefficient polynomials were found as a function of refrigerant saturating and evaporating temperatures in range of (-35℃ to -10℃) using Matlab software for cooling capacity, power consumption, and refrigerant mass flow rate.
Additional correlations equations for these variables as a quick choice selection for a proper compressor use at ASHRAE standard that cover a range of swept volume range (2.24-11.15) cm3.
The result indicated that these surface fitting models are accurate with in ± 15% for 72 compressors model of cooling cap
... Show MoreGas hydrate formation poses a significant threat to the production, processing, and transportation of natural gas. Accurate predictions of gas hydrate equilibrium conditions are essential for designing the gas production systems at safe operating conditions and mitigating the problems caused by hydrates formation. A new hydrate correlation for predicting gas hydrate equilibrium conditions was obtained for different gas mixtures containing methane, nitrogen and carbon dioxide. The new correlation is proposed for a pressure range of 1.7-330 MPa, a temperature range of 273-320 K, and for gas mixtures with specific gravity range of 0.553 to 1. The nonlinear regression technique was applie
The extracted oil from the Chia seeds white and black were used in the manufacture of certain foods such as mayonnaise. The results of the sensory evaluation showed that the product was acceptable except for the flavor of white chia seed oil. The seeds were fully used in the manufacture of the nutella. The results of the sensory evaluation were encouraging the use of the extracted oil from the black chia seeds in the production of the nutella except the spread property. Chia seeds were also used in the manufacture of pudding. The results of the sensory evaluation showed an excellent and acceptable product of black chia seeds oil can be obtained, while the white seeds did not receive the acceptance in terms of color and flavor.