Wellbore instability is one of the major issues observed throughout the drilling operation. Various wellbore instability issues may occur during drilling operations, including tight holes, borehole collapse, stuck pipe, and shale caving. Rock failure criteria are important in geomechanical analysis since they predict shear and tensile failures. A suitable failure criterion must match the rock failure, which a caliper log can detect to estimate the optimal mud weight. Lack of data makes certain wells' caliper logs unavailable. This makes it difficult to validate the performance of each failure criterion. This paper proposes an approach for predicting the breakout zones in the Nasiriyah oil field using an artificial neural network. It also presents the optimal mud weight window for this field, which can be used to optimise the mud weights to minimise the wellbore instability issues. The results showed that an artificial neural network is a powerful tool for determining the breakout zones using the input data. The obtaining root mean square error and the determination coefficient were respectively 0.0082 and 0.959, by which the 1D MEM gave a high match between the predicted wellbore instabilities using the Mogi-failure criterion and the predicted breakout using the ANN model. Most borehole enlargements occur due to formation shear failures because of using low mud weights during drilling. The conclusion clarify the1.35 g/cc is the optimal mud weights for drilling new wells in this field of interest with fewer drilling issues.
A 3D geological model for Mishrif Reservoir in Nasiriyah oil field had been invented "designed" "built". Twenty Five wells namely have been selected lying in Nasiriyah Governorate in order to build Structural and petrophysical (porosity and water saturation) models represented by a 3D static geological model in three directions .Structural model showed that Nasiriyah oil field represents anticlinal fold its length about 30 km and the width about 10 km, its axis extends toward NW–SE with structural closure about 65 km . After making zones for Mishrif reservoir, which was divided into 5 zones i.e. (MA zone, UmB 1zone,MmB1 zone ,L.mB1 zone and mB2zone) .Layers were built for each zone depending on petrophysical propertie
... Show MoreArtificial 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
... Show MoreThe problem of internal sulfate attack in concrete is widespread in Iraq and neighboring countries.This is because of the high sulfate content usually present in sand and gravel used in it. In the present study the total effective sulfate in concrete was used to calculate the optimum SO3 content. Regression models were developed based on linear regression analysis to predict the optimum SO3 content usually referred as (O.G.C) in concrete. The data is separated to 155 for the development of the models and 37 for checking the models. Eight models were built for 28-days age. Then a late age (greater than 28-days) model was developed based on the predicted optimum SO3 content of 28-days and late age. Eight developed models were built for all
... Show More<p>Analyzing X-rays and computed tomography-scan (CT scan) images using a convolutional neural network (CNN) method is a very interesting subject, especially after coronavirus disease 2019 (COVID-19) pandemic. In this paper, a study is made on 423 patients’ CT scan images from Al-Kadhimiya (Madenat Al Emammain Al Kadhmain) hospital in Baghdad, Iraq, to diagnose if they have COVID or not using CNN. The total data being tested has 15000 CT-scan images chosen in a specific way to give a correct diagnosis. The activation function used in this research is the wavelet function, which differs from CNN activation functions. The convolutional wavelet neural network (CWNN) model proposed in this paper is compared with regular convol
... Show More<p>Analyzing X-rays and computed tomography-scan (CT scan) images using a convolutional neural network (CNN) method is a very interesting subject, especially after coronavirus disease 2019 (COVID-19) pandemic. In this paper, a study is made on 423 patients’ CT scan images from Al-Kadhimiya (Madenat Al Emammain Al Kadhmain) hospital in Baghdad, Iraq, to diagnose if they have COVID or not using CNN. The total data being tested has 15000 CT-scan images chosen in a specific way to give a correct diagnosis. The activation function used in this research is the wavelet function, which differs from CNN activation functions. The convolutional wavelet neural network (CWNN) model proposed in this paper is compared with regular convol
... Show MoreTight oil reservoirs have been a concerned of the oil industry due to their substantial influence on oil production. Due to their poor permeability, numerous problems are encountered while producing from tight reservoirs. Petrophysical and geomechanical rock properties are essential for understanding and assessing the fracability of reservoirs, especially tight reservoirs, to enhance permeability. In this study, Saadi B reservoir in Halfaya Iraqi oil field is considered as the main tight reservoir. Petrophysical and geomechanical properties have been estimated using full-set well logs for a vertical well that penetrates Saadi reservoir and validated with support of diagnostic fracture injection test data employing standard equations
... Show MoreThis study aims at making formation evaluation for Mishrif Formation in three wells within Noor Oilfield which are: No-1, No-2 and No-5. The study includes calculations of shale volume and porosity, water saturation using Archie method, measuring the bulk volume of water (BVW) and using Buckle plot, as well as measuring the movable and residual hydrocarbons. These calculations were carried out using Interactive Petrophysics (IP) version 3.5 software as well as using Petrel 2009 software for structural map construction and correlation purposes. It was found that the Mishrif Formation in Noor Oilfield is not at irreducible water saturation, though it is of good reservoir characteristics and hydrocarbon production especially at the upper pa
... Show MoreFormation evaluation is a critical process in the petroleum industry that involves assessing the petrophysical properties and hydrocarbon potential of subsurface rock formations. This study focuses on evaluating the Mauddad Formation in the Bai Hassan oil field by analyzing data obtained from well logs and core samples. Four wells were specifically chosen for this study (BH-102, BH-16, BH-86, and BH-93). The main objectives of this study were to identify the lithology of the Mauddud Formation and estimate key petrophysical properties such as shale volume, porosity, water saturation, and permeability. The Mauddud Formation primarily consists of limestone and dolomite, with some anhydrites present. It is classified as a clean for
... Show MoreThe instant global trend towards developing tight reservoir is great; however, development can be very challenging due to stress and geomechanical properties effect in horizontal well placement and hydraulic fracturing design. Many parameters are known to be important to determine the suitable layer for locating horizontal well such as petrophysical and geomechanical properties. In the present study, permeability sensitivity to stress is also considered in the best layer selection for well placement. The permeability sensitivity to the stress of the layers was investigated using measurements of 27 core sample at different confining stress values. 1-D mechanical earth model (MEM) was built and converted to a 3-D full-field geomechanical mode
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