It is well known that the rate of penetration is a key function for drilling engineers since it is directly related to the final well cost, thus reducing the non-productive time is a target of interest for all oil companies by optimizing the drilling processes or drilling parameters. These drilling parameters include mechanical (RPM, WOB, flow rate, SPP, torque and hook load) and travel transit time. The big challenge prediction is the complex interconnection between the drilling parameters so artificial intelligence techniques have been conducted in this study to predict ROP using operational drilling parameters and formation characteristics. In the current study, three AI techniques have been used which are neural network, fuzzy inference system and genetic algorithm. An offset field data was collected from mud logging and wire line log from East Baghdad oil field south region to build the AI models, including datasets of two wells: well 1 for AI modeling and well 2 for validation of the obtained results. The types of interesting formations are sandstone and shale (Nahr Umr and Zubair formations). Nahr Umr and Zubair formations are medium –harder. The prediction results obtained from this study showed that the ANN technique can predict the ROP with high efficiency as well as FIS technique could achieve reliable results in predicting ROP, but GA technique has shown a lower efficiency in predicting ROP. The correlation coefficient and RMSE were two criteria utilized to evaluate and estimate the performance ability of AI techniques in predicting ROP and comparing the obtained results. In the Nahr Umr and Zubair formations, the obtained correlation coefficient values for training processes of ANN, FIS and GA were 0.94, 0.93, and 0.76 respectively. Data sets from another well (well 2) in the same field of interest were utilized to validate of the developed models. Datasets of well 2 were conducted against sandstone and shale formations (Nahr Umr and Zubair formations). The results revealed a good matching between the actual rate of penetration values and the predicted ROP values using two artificial intelligence techniques (neural network, and fuzzy inference technique). In contrast, the genetic algorithm model showed overestimation/ underestimation of the rate of penetration against sandstone and shale formations. This means that the optimum prediction of rate of penetration can be obtained from neural network model rather than using genetic algorithm and genetic algorithm techniques. The developed model can be successfully used to predict the rate of penetration and optimize the drilling parameters, achieving reduce the cost and time of future wells that will be drilled in the East Baghdad Iraqi oil field.
A study has been done to find the optimum separators pressures of separation stations. Stage separation of oil and gas is accomplished with a series of separators operating at sequentially reduced pressures. Liquid discharged from a higher pressure separator into the lower pressure separator. The set of working separators pressures which yield maximum recovery of liquid hydrocarbon from the well fluid is the optimum set of pressures which is the target of this work.
Computer model is used to find the optimum separators pressures. The model employs the Peng-Robinson equation of state for volatile oil. Application of this model shows good improvement of al
Foreign direct investment has seen increasing interest worldwide, especially in developing economies. However, statistics have shown that Yemen received fluctuating FDI inflows during the period under study. Against this background, this research seeks to determine the relationship and impact of interest rates on FDI flows. The study also found other determinants that greatly affected FDI inflows in Yemen for the period 1990-2018. Study data collected from the World Bank and International Monetary Fund databases. It also ensured that the time series were made balanced and interconnected, and then the Auto Regressive Distributed Lag method used in the analysis. The results showed that the interest rates and
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The aim of the research is to measure the effect of changing the exchange rate on bank loans, and in order to achieve this goal, the (official exchange rate) was chosen as an independent variable and its effect was studied on the dependent variable, which is bank credit. Commercial Gulf, Baghdad, A Shore International for Investment (and the financial indicators (growth rate of loans) and the statistical program (Eviews 12) were used to measure the impact of the exchange rate change on the bank credit of banks, the research sample for the period 2012-2022, and the research reached a group Among the conclusions, the most important of which is that the
... Show MoreAbstract: The article aimed to formulate an MLX binary ethosome hydrogel for topical delivery to escalate MLX solubility, facilitate dermal permeation, avoid systemic adverse events, and compare the permeation flux and efficacy with the classical type. MLX ethosomes were prepared using the hot method according to the Box–Behnken experimental design. The formulation was implemented according to 16 design formulas with four center points. Independent variables were (soya lecithin, ethanol, and propylene glycol concentrations) and dependent variables (vesicle size, dispersity index, encapsulation efficiency, and zeta potential). The design suggested the optimized formula (MLX−Ethos−OF) with the highest desirability to perform the
... Show MoreThis study aimed to identidy the role of a professional social worker practice specialist in the field of social care for Corona patients, in light of some demographic variables such as (gender, marital status, economic status,), through a field study at the Iraqi Ministry of Social Affairs. A random sample of (50) social workers in the Iraqi Ministry of Social Affairs in various places affiliated with the ministry was chosen. a questionnaire developed by the researcher about the role of the social worker in the field of social care for Corona patients was administered to the study sample to collect the needed data. The results showed that there is a positive statistically significant correlation relationship at the level (0.01) between
... Show MoreBackground: Normal occlusal features of primary dentition are crucial for normal development of the permanent dentition. Breastfeeding is an important factor for both general and dental health of children. Aim: The aim of the present study is to assess the impact of the breastfeeding duration on the prevalence of normal occlusal features of the primary dentition among preschool children in Baghdad. Materials and Methods: The sample was 630 Iraqi children (270- boys, 360 girls), aged 3-5 years selected from four kindergartens in Baghdad city. The study was carried out through questionnaire and clinical examination. Normal occlusal features were examined as the presence or absence of interincisive spaces (IS) and primate spaces (PS), termi
... Show MoreIn this paper the method of singular value decomposition is used to estimate the ridge parameter of ridge regression estimator which is an alternative to ordinary least squares estimator when the general linear regression model suffer from near multicollinearity.
The regular job of a reservoir engineer is to put a development plan to increase hydrocarbon production as possible and within economic and technical considerations. The development strategy for the giant reservoir is a complex and challenging task through the decision-making analysis process. Due to the limited surface water treatment facility, the reservoir management team focuses on minimizing water cut as low as possible by check the flow of formation and injected water movement through the Mishrif reservoir. In this research, a representative sector was used to make the review of water injection configuration, which is considered an efficient tool to make study in a particular area of the entire field when compared with the ful
... Show MoreUrban land price is the primary indicator of land development in urban areas. Land prices in holly cities have rapidly increased due to tourism and religious activities. Public agencies are usually facing challenges in managing land prices in religious areas. Therefore, they require developed models or tools to understand land prices within religious cities. Predicting land prices can efficiently retain future management and develop urban lands within religious cities. This study proposed a new methodology to predict urban land prices within holy cities. The methodology is based on two models, Linear Regression (LR) and Support Vector Regression (SVR), and nine variables (land price, land area,
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