This study has been accomplished by testing three different models to determine rocks type, pore throat radius, and flow units for Mishrif Formation in West Qurna oilfield in Southern Iraq based on Mishrif full diameter cores from 20 wells. The three models that were used in this study were Lucia rocks type classification, Winland plot was utilized to determine the pore throat radius depending on the mercury injection test (r35), and (FZI) concepts to identify flow units which enabled us to recognize the differences between Mishrif units in these three categories. The study of pore characteristics is very significant in reservoir evaluation. It controls the storage mechanism and reservoir fluid properties of the permeable units while pore structure is a critical controlling factor for the petrophysical properties and multiphase-flow characteristics in reservoir rocks. Flow zone indicator (FZI) has been used to identify the hydraulic flow units approach (HFUs). Each (HFU) was reproduced by certain FZI and was supposed to have similar geological and petrophysical properties. The samples were from four lithofacies, mA, CRII, mB1, and mB2. Because of the wide range of cored-wells samples (20 wells), this paper is updated the previous studies and indicated some differences in the resulting categories. It was noticed as results of this study that the rocks types of the lower Mishrif were mostly ranged from wackestone to packstone in the upper part of mB2 which reflected mid-ramp facies while the upper part of mB2 referred to shoal facies and for the mB1 unit the rocks types mostly range from packstone to grainstone with some points as wackestone marked as shoal and rudist bioherm facies. Grainstone relatively decreases with the increasing of depth from upper to lower Mishrif while wackestone and packstone indicated increasing in the same direction. The unit mA is marked as mesopores and macropores, while megapores and macropores feature increased in mB1 which has been noticed in the northern part of West Qurna oilfield due to increasing shoal and rudist bioherm facies, the mB2 unit revealed increasing in mesoporous and decreasing in megaporous. The upper Mishrif (mA) has three flow units, while the lower Mishrif (mB1, mB2) has eight flow units four for each reservoir unit.
The Turonian-Lower Companian succession at Majnoon Oil Field is represented by the Khasib, Tanuma, and Saadi formations. Four major paleoenvironments were recognized within the studied succession, there are: Shallow open marine environment, shoal environment, deep marine environment, and basinal environment. They reflect deposition on a carbonate platform of homoclinal ramp setting. The studied succession represents two second order supersequences (A) and (B). Supersequence (A) includes both the Khasib and Tanuma formations. The Saadi Formation represents cycle (B). These second order cycles can be divided each into two third order cycles, This subdivision may reflect the effect of eustacy being the major controlling factor of cycles dev
... Show MoreThe cathodic deposition of zinc from simulated chloride wastewater was used to characterize the mass transport properties of a flow-by fixed bed electrochemical reactor composed of vertical stack of stainless steel nets, operated in batch-recycle mode. The electrochemical reactor employed potential value in such a way that the zinc reduction occurred under mass transport control. This potential was determined by hydrodynamic voltammetry using a borate/chloride solution as supporting electrolyte on stainless steel rotating disc electrode. The results indicate that mass transfer coefficient (Km) increases with increasing of flow rate (Q) where .The electrochemical reactor proved to be efficient in removing zinc and was abl
... Show MoreThese With recent developments in machine learning, data mining and computer vision, there is great potential for improvements in early detection of lung cancer using scans and data available. This paper details the methods and techniques used in our project, where the objective is to develop algorithms to determine whether a patient has or is likely to develop lung cancer using dataset images using data mining and machine learning for the classification and examination. We explore approaches to address the problem. Cancer is the most important cause of death globally. The disease diagnosis is a major process to treat the patients who are affected by cancer disease. The diagnosis process is more difficult comparatively known about t
... Show MoreThe current paper proposes a new estimator for the linear regression model parameters under Big Data circumstances. From the diversity of Big Data variables comes many challenges that can be interesting to the researchers who try their best to find new and novel methods to estimate the parameters of linear regression model. Data has been collected by Central Statistical Organization IRAQ, and the child labor in Iraq has been chosen as data. Child labor is the most vital phenomena that both society and education are suffering from and it affects the future of our next generation. Two methods have been selected to estimate the parameter
... Show MoreThe term "tight reservoir" is commonly used to refer to reservoirs with low permeability. Tight oil reservoirs have caused worry owing to its considerable influence upon oil output throughout the petroleum sector. As a result of its low permeability, producing from tight reservoirs presents numerous challenges. Because of their low permeability, producing from tight reservoirs is faced with a variety of difficulties. The research aim is to performing hydraulic fracturing treatment in single vertical well in order to study the possibility of fracking in the Saady reservoir. Iraq's Halfaya oil field's Saady B reservoir is the most important tight reservoir. The diagnostic fracture injection test is determined for HF55using GOHFER soft
... Show MoreVariable selection is an essential and necessary task in the statistical modeling field. Several studies have triedto develop and standardize the process of variable selection, but it isdifficultto do so. The first question a researcher needs to ask himself/herself what are the most significant variables that should be used to describe a given dataset’s response. In thispaper, a new method for variable selection using Gibbs sampler techniqueshas beendeveloped.First, the model is defined, and the posterior distributions for all the parameters are derived.The new variable selection methodis tested usingfour simulation datasets. The new approachiscompared with some existingtechniques: Ordinary Least Squared (OLS), Least Absolute Shrinkage
... Show MoreIntelligent or smart completion wells vary from conventional wells. They have downhole flow control devices like Inflow Control Devices (ICD) and Interval Control Valves (ICV) to enhance reservoir management and control, optimizing hydrocarbon output and recovery. However, to explain their adoption and increase their economic return, a high level of justification is necessary. Smart horizontal wells also necessitate optimizing the number of valves, nozzles, and compartment length. A three-dimensional geological model of the As reservoir in AG oil field was used to see the influence of these factors on cumulative oil production and NPV. After creating the dynamic model for the As reservoir using the program Petrel (2017.4), we
... Show MoreIn this research, several estimators concerning the estimation are introduced. These estimators are closely related to the hazard function by using one of the nonparametric methods namely the kernel function for censored data type with varying bandwidth and kernel boundary. Two types of bandwidth are used: local bandwidth and global bandwidth. Moreover, four types of boundary kernel are used namely: Rectangle, Epanechnikov, Biquadratic and Triquadratic and the proposed function was employed with all kernel functions. Two different simulation techniques are also used for two experiments to compare these estimators. In most of the cases, the results have proved that the local bandwidth is the best for all the
... Show MoreAmplitude variation with offset (AVO) analysis is an 1 efficient tool for hydrocarbon detection and identification of elastic rock properties and fluid types. It has been applied in the present study using reprocessed pre-stack 2D seismic data (1992, Caulerpa) from north-west of the Bonaparte Basin, Australia. The AVO response along the 2D pre-stack seismic data in the Laminaria High NW shelf of Australia was also investigated. Three hypotheses were suggested to investigate the AVO behaviour of the amplitude anomalies in which three different factors; fluid substitution, porosity and thickness (Wedge model) were tested. The AVO models with the synthetic gathers were analysed using log information to find which of these is the
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