Water saturation is the most significant characteristic for reservoir characterization in order to assess oil reserves; this paper reviewed the concepts and applications of both classic and new approaches to determine water saturation. so, this work guides the reader to realize and distinguish between various strategies to obtain an appropriate water saturation value from electrical logging in both resistivity and dielectric has been studied, and the most well-known models in clean and shaly formation have been demonstrated. The Nuclear Magnetic Resonance in conventional and nonconventional reservoirs has been reviewed and understood as the major feature of this approach to estimate Water Saturation based on T2 distribution. Artificial intelligence has recently been used to predict water saturation and other parameters in the reservoir characterization process using seismic data, so the main idea of this technique and a list of the author's researchers have been reviewed. In this review article, the reference approach using core analysis by distillation-extraction and retorting techniques have been explained, as well as the saturation-height method, which is based on the capillary pressure concept and wettability. Finally, alternative experimental approaches based on scanning are expressed in this manner.
The futuristic age requires progress in handwork or even sub-machine dependency and Brain-Computer Interface (BCI) provides the necessary BCI procession. As the article suggests, it is a pathway between the signals created by a human brain thinking and the computer, which can translate the signal transmitted into action. BCI-processed brain activity is typically measured using EEG. Throughout this article, further intend to provide an available and up-to-date review of EEG-based BCI, concentrating on its technical aspects. In specific, we present several essential neuroscience backgrounds that describe well how to build an EEG-based BCI, including evaluating which signal processing, software, and hardware techniques to use. Individu
... Show MoreGum Arabic is a natural gummy exudate gained from the trees of Acacia species (Acacia senegal and Acacia seyal), Family: Fabaceae. Gum Arabic considers as a dietary fiber with a high percentage of carbohydrates and low protein content. Sugars arabinose and ribose were originally discovered and isolated from gum Arabic and it is representing the original source of these sugars. A gum emanation from trees occurs under stress conditions such as heat, poor soil fertility, drought, and injury. Mainly gum is produced in belt region of Africa, mainly Sudan, Chad, and Nigeria. In the food industry, it is used in confectionery; in the pharmaceutical industry, it is used as emulsifier, film coating and others. Traditionally the g
... Show MoreOne of the artificial lightweight aggregates with a wide range of applications is Lightweight Expanded Clay Aggregate. Clay is utilized in the production of light aggregates. Using leftover clay from significant infrastructure development projects to manufacture lightweight aggregates has a favorable environmental impact. This research examines the expanded clay aggregate production process and the impact of processing parameters on its physical and mechanical qualities. It also looks at secondary components that can be used to improve the qualities of concrete with expanded clay aggregates. The effect of the quantity of expanded clay aggregate on the fresh, hardened, and durability qualities of concrete is also studied.
... Show MoreHuman interferon as is the case in all kinds of interferon has complex effects but all share their impact on preventing the proliferation of viruses and preventing or reducing human Alantervjørn conversion occurs if the cell is in preventing the growth of the virus when interferon Balnmstqubl connects
Topology and its applications occupy the interest of many researching centers in the advanced world. From this point of view and because the near open sets play a very important role in general topology and they are now the research topics of many topologists worldwide and its sets doesn’t enter in fibrewise topology yet. Therefore, we use some of the near open sets to be model for introduce results and new spaces in fibrewise topological spaces. Also, there is a very important role of closure operators in constructing a topological spaces, so we introduce a new closure operators on the power set of vertices on graphs and conclusion theorems and new spaces from it. Furthermore, we discuss the relationships of connectedness between some ty
... Show MoreA 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, Gulnen
... Show MoreProblem: Cancer is regarded as one of the world's deadliest diseases. Machine learning and its new branch (deep learning) algorithms can facilitate the way of dealing with cancer, especially in the field of cancer prevention and detection. Traditional ways of analyzing cancer data have their limits, and cancer data is growing quickly. This makes it possible for deep learning to move forward with its powerful abilities to analyze and process cancer data. Aims: In the current study, a deep-learning medical support system for the prediction of lung cancer is presented. Methods: The study uses three different deep learning models (EfficientNetB3, ResNet50 and ResNet101) with the transfer learning concept. The three models are trained using a
... Show MoreFeature selection (FS) constitutes a series of processes used to decide which relevant features/attributes to include and which irrelevant features to exclude for predictive modeling. It is a crucial task that aids machine learning classifiers in reducing error rates, computation time, overfitting, and improving classification accuracy. It has demonstrated its efficacy in myriads of domains, ranging from its use for text classification (TC), text mining, and image recognition. While there are many traditional FS methods, recent research efforts have been devoted to applying metaheuristic algorithms as FS techniques for the TC task. However, there are few literature reviews concerning TC. Therefore, a comprehensive overview was systematicall
... Show MoreThis research was carried out to study the effect of plants on the wetted area for two soil types in Iraq and predict an equation to determine the wetted radius and depth for two different soil types cultivated with different types of plants, the wetting patterns for the soils were predicted at every thirty minute for a total irrigation time equal to 3 hr. Five defferent discharges of emitter and five initial volumetric soil moisture contents were used ranged between field capacity and wilting point were utilized to simulate the wetting patterns. The simulation of the water flow from a single point emitter was completed by utilized HYDRUS-2D/3D software, version 2.05. Two methods were used in developing equations to predict the domains o
... Show MoreConstruction and operation of (2 m) parabolic solar dish for hot water application were illustrated. The heater was designed to supply hot water up to 100 oC using the clean solar thermal energy. The system includes the design and construction of solar tracking unit in order to increase system performance. Experimental test results, which obtained from clear and sunny day, refer to highly energy-conversion efficiency and promising a well-performed water heating system.