A 3D Geological model was generated using an advanced geostatistical method for the Cretaceous reservoir in the Bai Hassan oil field. In this study, a 3D geological model was built based on data from four wells for the petrophysical property distribution of permeability, porosity, water saturation, and NTG by using Petrel 2021 software. The geological model was divided into a structural model and a property model. The geological structures of the cretaceous reservoir in the Bai Hassan oil field represent elongated anticline folds with two faults, which had been clarified in the 3D Structural model. Thirteen formations represent the Cretaceous reservoir which includes (Shiranish, Mashurah, U.kometan, Kometan Shale, L. Kometan, Gulneni, Dokan, Mauddud, Jawan/Mud, Batiwah, Shuaiba, Garagu, L.Sarmord). According to the property model, the model for each petrophysical property was constructed based on core data and CPI. By using the geostatistical method, the property model was constructed. The Mauddud Formation is considered one of the most promising hydrocarbon reservoirs in the Bai Hassan oil field based on the results of the property model, where the ratio of water saturation is around 30%, the porosity value is reaching up to 31%, and the net to gross ratio is averaging at 70%.
The research aims to identify the role of strategic improvisation as an independent variable with its dimensions (Building the Solution, Intuition, Adaptation, and Spontaneity) and the Entrepreneurial Orientation as a dependent variable with its dimensions (Identifying Opportunities, Creativity, Adopting risk, and Vision). This research has been applied in the Rafidain Bank and its branches (Sunk, People, Al-Firdaws, and Alawiya); it used the questionnaire as a basic tool for collecting information. The sample was intentionality, which included all the heads of departments in the bank’s branches, which amounted to (33) workers, and data on the questionnaire paragraphs of 28 were processed using the SPSS V.23 and AMOS V.23). The most impor
... Show MorePrecise forecasting of pore pressures is crucial for efficiently planning and drilling oil and gas wells. It reduces expenses and saves time while preventing drilling complications. Since direct measurement of pore pressure in wellbores is costly and time-intensive, the ability to estimate it using empirical or machine learning models is beneficial. The present study aims to predict pore pressure using artificial neural network. The building and testing of artificial neural network are based on the data from five oil fields and several formations. The artificial neural network model is built using a measured dataset consisting of 77 data points of Pore pressure obtained from the modular formation dynamics tester. The input variables
... Show MoreThe electrocardiogram (ECG) is the recording of the electrical potential of the heart versus time. The analysis of ECG signals has been widely used in cardiac pathology to detect heart disease. The ECGs are non-stationary signals which are often contaminated by different types of noises from different sources. In this study, simulated noise models were proposed for the power-line interference (PLI), electromyogram (EMG) noise, base line wander (BW), white Gaussian noise (WGN) and composite noise. For suppressing noises and extracting the efficient morphology of an ECG signal, various processing techniques have been recently proposed. In this paper, wavelet transform (WT) is performed for noisy ECG signals. The graphical user interface (GUI)
... Show MoreThe present study identifies the linguistic means used to realize hyperbole in poetry as a rhetorical device that makes readers experience the beauty of poetic language. To achieve the aim of the study, a model of analysis in accordance with Spitzbardt (1963), Norrick (1982), and McCarthy & Carter (2004) is used. The analysis of data under investigation reveals that hyperbole is a crucial aid used by poets to portrait the real world as imaginative. In conclusion, poets prefer using lexico-grammatical repertoires than lexico-grammatical configurations. Keywords
Discriminant analysis is a technique used to distinguish and classification an individual to a group among a number of groups based on a linear combination of a set of relevant variables know discriminant function. In this research discriminant analysis used to analysis data from repeated measurements design. We will deal with the problem of discrimination and classification in the case of two groups by assuming the Compound Symmetry covariance structure under the assumption of normality for univariate repeated measures data.
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Nanofluids, liquid suspensions of nanoparticles (Np), are an effective agent to alter the wettability of oil-wet reservoirs to water-wet thus promoting hydrocarbon recovery. It can also have an application to more efficient carbon storage. We present a series of contact angle (θ) investigations on initially oil-wet calcite surfaces to quantify the performance of hydrophilic silica nanoparticles for wettability alteration. These tests are conducted at typical in-situ high pressure (CO2), temperature and salinity conditions. A high pressure–temperature (P/T) optical cell with a regulated tilted surface was used to measure the advancing and receding contact angles at the desired conditions. The results showed that silica nanofluids can alte
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