Achieving an accurate and optimal rate of penetration (ROP) is critical for a cost-effective and safe drilling operation. While different techniques have been used to achieve this goal, each approach has limitations, prompting researchers to seek solutions. This study’s objective is to conduct the strategy of combining the Bourgoyne and Young (BYM) ROP equations with Bagging Tree regression in a southern Iraqi field. Although BYM equations are commonly used and widespread to estimate drilling rates, they need more specific drilling parameters to capture different ROP complexities. The Bagging Tree algorithm, a random forest variant, addresses these limitations by blending domain knowledge and capturing non-linear relationships. Its ensemble nature also mitigates the impact of outliers. This approach combines physics-based equations with machine learning to enable more accurate ROP predictions in drilling operations. It enhances drilling efficiency, reduces expenses, and improves decision-making in the oil and gas sector. Extensive testing on actual drilling datasets has demonstrated outstanding performance compared to the multiple linear regression (MLR) method. With the increased R2 and zero P-value. positive findings show that this tool can benefit precise future ROP prediction in southern Iraqi oil well drilling.
This research discussed, the process of comparison between the regression model of partial least squares and tree regression, where these models included two types of statistical methods represented by the first type "parameter statistics" of the partial least squares, which is adopted when the number of variables is greater than the number of observations and also when the number of observations larger than the number of variables, the second type is the "nonparametric statistic" represented by tree regression, which is the division of data in a hierarchical way. The regression models for the two models were estimated, and then the comparison between them, where the comparison between these methods was according to a Mean Square
... Show MoreIt 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 i
... Show MoreThe main objective of this study is to develop a rate of penetration (ROP) model for Khasib formation in Ahdab oil field and determine the drilling parameters controlling the prediction of ROP values by using artificial neural network (ANN).
An Interactive Petrophysical software was used to convert the raw dataset of transit time (LAS Readings) from parts of meter-to-meter reading with depth. The IBM SPSS statistics software version 22 was used to create an interconnection between the drilling variables and the rate of penetration, detection of outliers of input parameters, and regression modeling. While a JMP Version 11 software from SAS Institute Inc. was used for artificial neural modeling.
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... Show MoreYoung people represent the power and cornerstone of societies and their superiority is linked to their well-being. Their empowerment is as essential as the heart to the body, if it is corrupt, then the whole body is corrupt, and vice versa. The exposure to extremism and pressure from their families leads to violent acts and crimes for obtaining money through unknown organized bodies. This will drive them to fail in their life in an attempt to fulfill their most basic needs, which they have been deprived of by their families, the government, and other institutions. Therefore, governments should provide job opportunities for young people and provide entertainment centers, sports clubs, and family education centers that raise awareness of s
... Show MoreConstructing a fine 3D geomodel for complex giant reservoir is a crucial task for hydrocarbon volume assessment and guiding for optimal development. The case under study is Mishrif reservoir of Halfaya oil field, which is an Iraqi giant carbonate reservoir. Mishrif mainly consists of limestone rocks which belong to Late Cenomanian age. The average gross thickness of formation is about 400m. In this paper, a high-resolution 3D geological model has been built using Petrel software that can be utilized as input for dynamic simulation. The model is constructed based on geological, geophysical, pertophysical and engineering data from about 60 available wells to characterize the structural, stratigraphic, and properties distribution along
... Show MoreConstructing a fine 3D geomodel for complex giant reservoir is a crucial task for hydrocarbon volume assessment and guiding for optimal development. The case under study is Mishrif reservoir of Halfaya oil field, which is an Iraqi giant carbonate reservoir. Mishrif mainly consists of limestone rocks which belong to Late Cenomanian age. The average gross thickness of formation is about 400m. In this paper, a high-resolution 3D geological model has been built using Petrel software that can be utilized as input for dynamic simulation. The model is constructed based on geological, geophysical, pertophysical and engineering data from about 60 available wells to characterize the structural, stratigraphic, and properties distri
... Show MoreThe depth conversion process is a significant task in seismic interpretation to establish the link between the seismic data in the time domain and the drilled wells in the depth domain. To promote the exploration and development of the Subba oilfield, more accurate depth conversion is required. In this paper, three approaches of depth conversions: Models 1, 2, and 3 are applied from the simplest to the most complex on Nahr Umr Reservoir in Suba oilfield. This is to obtain the best approach, giving less mistakes with the actual depth at well locations and good inter/extrapolation between or away from well controls. The results of these approaches, together with the uncertainty analysis provide a reliable velocity model
... Show MoreBackground:This is a prospective study of three children presented to us in the Orbital clinic in AL ShahidGazi Al Hariri Hospital with painless proptosiswith suspension of Hydatid disease.Objectives: : Orbital hydatid disease is a rare lesion accounting for less than 1% of the total lesions of the body (1, 2). Orbital cysts presented as a primary lesion in our study which is rare to have such lesion without involvement of other organs (3). Humans represent the intermediate host where the commonly affected organ are liver and the lung (10-15%) (4). Methods:This is a prospective study of three Children presented to us in the Orbital clinic in Al Shahid Ghazi Alhariri Hospital with painless proptosis with suspension of Hydatid disease, dep
... Show MoreMicrofinance Institutions (MFIs) offers small loans with easy repayment system and till now these institutions have served millions of needy people around the globe. This study highlights the hurdles influence the smooth working and growth of Microfinance institution in Egypt. The structured interviews were conducted from the top and mid-level managers of MFI's. This study revealed that interest rate, political and economic conditions, corruption, customer outreach, competition and technology are the important elements for MFI's success. It is evident that lack of use of technology and less importance drawn on customer outreach programs are the main challenges of MFI's in Egypt. This study provides a roadmap for practitioners and strategic
... Show MoreIn 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
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