Well log rock physics and seismic facies analysis was carried out with a view to enhancing reservoir sand characterization of Mafe Field of Niger Delta. Lithofacies were identified using suites of well logs and correlated across the block. Rock properties were estimated from wireline logs using empirical methods. Vp-porosity crossplot was used to characterize the delineated sandstone reservoirs by comparing observed clusters and trends with various rock physics models. Seismic attribute analysis was employed to detect lateral changes in lithology across the field. Reservoir A is a relatively clean sand, with low average volume of shale of 0.4, average thickness of 55m, good average porosity of 0.26 and average water saturation of 0.45. Reservoir B is also a relatively clean sand with low average volume of shale of 0.35, average thickness of 85m, high average porosity of 0.27 and average water saturation of 0.54. Reservoir C has an estimated volume of shale of 0.21 average total porosity of 0.23, and an average thickness of 70m with average water saturation of 0.65. Reservoir A conforms to the friable sand model while Vp-porosity crossplot cluster trend for both reservoir B and C show trend and properties imitating the contact cement model. The time slices extracted at different time intervals from the envelope and instantaneous frequency cubes show lateral variation in lithofacies across the delineated sandstones. Instantaneous frequency decreases from southwest to northeast which corresponds to decrease in shalines. Reservoir quality information can be predicted or even derived from the estimated petrophysical properties since these parameters such as porosity and volume of shale are sometimes closely associated with rock properties such as sorting, lithofacies and grain maturity.
Machine learning has a significant advantage for many difficulties in the oil and gas industry, especially when it comes to resolving complex challenges in reservoir characterization. Permeability is one of the most difficult petrophysical parameters to predict using conventional logging techniques. Clarifications of the work flow methodology are presented alongside comprehensive models in this study. The purpose of this study is to provide a more robust technique for predicting permeability; previous studies on the Bazirgan field have attempted to do so, but their estimates have been vague, and the methods they give are obsolete and do not make any concessions to the real or rigid in order to solve the permeability computation. To
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3D seismic reflection structural study of (250) km² of Balad Oil field located in central part of Iraq within Salah Al-din province (Balad area) was carried out.
Faults were picked using instantaneous phase attribute of seismic sections and variance attribute of seismic time slices across 3D seismic volume.
A Listric growth normal fault is affecting the succession of Cretaceous Formation and cut by strike slip fault. In addition, minor normal faults (Dendritic and tension faults) are developed on the listric normal growth fault. As a result, a major graben is separated by Strike slip fault into two parts (north and south parts) and trend in NW-SE direction.
Constructing 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
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Constructing 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
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Comics is a visual art (Still and motion pictures) it seeks to provide a Training courses are a series of intensive important educational and complementary programs, based on previous foundation experiences. Create to development the participants in aspects of specialization according to the requirements of the educational system to continue developing the previous scientic and practical experiences. Personally, or adopted by the trainee institution, where the trainee gets a professional skill certicate that contributes to the development his work.Development and Continuous Education Center (DCEC) at the University of Baghdad (UoBaghdad) is a center dedicated to continuing education courses in which the participant is awarded a cert
... Show MoreThe current issues in spam email detection systems are directly related to spam email classification's low accuracy and feature selection's high dimensionality. However, in machine learning (ML), feature selection (FS) as a global optimization strategy reduces data redundancy and produces a collection of precise and acceptable outcomes. A black hole algorithm-based FS algorithm is suggested in this paper for reducing the dimensionality of features and improving the accuracy of spam email classification. Each star's features are represented in binary form, with the features being transformed to binary using a sigmoid function. The proposed Binary Black Hole Algorithm (BBH) searches the feature space for the best feature subsets,
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The current research deals with studying the petrophysical properties represented by the porosity and its distribution on the level of all units of the top and bottom of the Kirkuk Formation Group. The study area is located in Maysan province in the south-eastern part of Iraq in the Amara field. The Kirkuk Group was deposited in the Tertiary Age. The post-stack method using seismic inversion and creating a relationship between seismic data was accomplished using Hampson-Russel software at well Am-1 and Seismic lines Ama 20 and 30. The research results indicate high porosity values on top of the formation with a decrease in acoustic impedance (Z) and, therefore, a reduction in the density. At the same time, low porosity values were indica
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Twitter data analysis is an emerging field of research that utilizes data collected from Twitter to address many issues such as disaster response, sentiment analysis, and demographic studies. The success of data analysis relies on collecting accurate and representative data of the studied group or phenomena to get the best results. Various twitter analysis applications rely on collecting the locations of the users sending the tweets, but this information is not always available. There are several attempts at estimating location based aspects of a tweet. However, there is a lack of attempts on investigating the data collection methods that are focused on location. In this paper, we investigate the two methods for obtaining location-based dat
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A geological model is a spatial representation of the distribution of sediments and rocks in the subsurface. Where this study on Halfaya oil field; it is located in Missan governorate, 35 km southeast of the city of Amara. It is one of the main fields in Iraq because it is production high oil. This model contains the structure, and petrophysical properties (porosity, water saturation) in three directions. To build 3D geological models of petroleum reservoirs. Khasib, Tanuma, and Sa’di formations in Halfaya oil field have been divided into many layers depending on petrophysical properties and facies.