Maximizing the net present value (NPV) of oil field development is heavily dependent on optimizing well placement. The traditional approach entails the use of expert intuition to design well configurations and locations, followed by economic analysis and reservoir simulation to determine the most effective plan. However, this approach often proves inadequate due to the complexity and nonlinearity of reservoirs. In recent years, computational techniques have been developed to optimize well placement by defining decision variables (such as well coordinates), objective functions (such as NPV or cumulative oil production), and constraints. This paper presents a study on the use of genetic algorithms for well placement optimization, a type of stochastic optimization technique that has proven effective in solving various problems. The results of the study show significant improvements in NPV when using genetic algorithms compared to traditional methods, particularly for problems with numerous decision variables. The findings suggest that genetic algorithms are a promising tool for optimizing well placement in oil field development, improving NPV, and reducing the risk of project failure.
A modified water injection technique has organized by this study to improve oil recovery of the Mishrif reservoirs using polymerized alkaline surfactant water (PAS-Water) injection. It is planned to modify the existing water injection technology, first to control and balance the hazardous troublemaker reservoir facies of fifty-micron pore sizes with over 500 millidarcies permeability, along with the non-troublemaker types of less than twenty micron pore sizes with 45 to 100 millidarcies permeability. Second to control Mishrif reservoirs rock-wettability. Special core analysis under reservoir conditions of 2250 psi and 90 °C has carried out on tens of standard core plugs with heterogeneous buildup, using the proposed renewal water f
... Show MoreBuilding numerical reservoir simulation model with a view to model actual case requires enormous amount of data and information. Such modeling and simulation processes normally require lengthy time and different sets of field data and experimental tests that are usually very expensive. In addition, the availability, quality and accessibility of all necessary data are very limited, especially for the green field. The degree of complexities of such modelling increases significantly especially in the case of heterogeneous nature typically inherited in unconventional reservoirs. In this perspective, this study focuses on exploring the possibility of simplifying the numerical simulation pr
Housing finance is one of the main components of housing, and it is relied upon to help families buy, build, add building, and housing improve. Accordingly, different countries all over the world set policies and strategies for the purpose of organizing and developing the financial sector to solve quantitative and qualitative housing problems.
This research aims to identify housing finance policies and strategies in Iraq and Baghdad governorate.
The most prominent sources of housing financing are the Real Estate Bank and the Housing Fund, and accordingly the focus has been on the role of these two institutions in filling
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For sparse system identification,recent suggested algorithms are
-norm Least Mean Square (
-LMS), Zero-Attracting LMS (ZA-LMS), Reweighted Zero-Attracting LMS (RZA-LMS), and p-norm LMS (p-LMS) algorithms, that have modified the cost function of the conventional LMS algorithm by adding a constraint of coefficients sparsity. And so, the proposed algorithms are named
-ZA-LMS,
Today with increase using social media, a lot of researchers have interested in topic extraction from Twitter. Twitter is an unstructured short text and messy that it is critical to find topics from tweets. While topic modeling algorithms such as Latent Semantic Analysis (LSA) and Latent Dirichlet Allocation (LDA) are originally designed to derive topics from large documents such as articles, and books. They are often less efficient when applied to short text content like Twitter. Luckily, Twitter has many features that represent the interaction between users. Tweets have rich user-generated hashtags as keywords. In this paper, we exploit the hashtags feature to improve topics learned
Abstract— The growing use of digital technologies across various sectors and daily activities has made handwriting recognition a popular research topic. Despite the continued relevance of handwriting, people still require the conversion of handwritten copies into digital versions that can be stored and shared digitally. Handwriting recognition involves the computer's strength to identify and understand legible handwriting input data from various sources, including document, photo-graphs and others. Handwriting recognition pose a complexity challenge due to the diversity in handwriting styles among different individuals especially in real time applications. In this paper, an automatic system was designed to handwriting recognition
... Show MoreEnhancing quality image fusion was proposed using new algorithms in auto-focus image fusion. The first algorithm is based on determining the standard deviation to combine two images. The second algorithm concentrates on the contrast at edge points and correlation method as the criteria parameter for the resulted image quality. This algorithm considers three blocks with different sizes at the homogenous region and moves it 10 pixels within the same homogenous region. These blocks examine the statistical properties of the block and decide automatically the next step. The resulted combined image is better in the contras
... Show MoreThe purpose of this study is to investigate the research on artificial intelligence algorithms in football, specifically in relation to player performance prediction and injury prevention. To accomplish this goal, scholarly resources including Google Scholar, ResearchGate, Springer, and Scopus were used to provide a systematic examination of research done during the last ten years (2015–2025). Through a systematic procedure that included data collection, study selection based on predetermined criteria, categorisation based on AI applications in football, and assessment of major research problems, trends, and prospects, almost fifty papers were found and analysed. Summarising AI applications in football for performance and injury p
... Show MoreThe importance of kick tolerance in well operations has recently increased due to its implications in well design, in drilling and well control. To study a simple method for the application of kick tolerance concept in an effective way on the basis of field data, this research purpose is to improve knowledge about Kick Tolerance and represents a technical basis for the discussion on revision of standard procedure.
The objective of this work is to review and to present a methodology of determination the kick tolerance parameters using the circulation kicks tolerance concepts.
The proposed method allows to know, to evaluate and to analyze the kick tolerance problem in order to make the drilling exe
... Show MoreAneurysms of the cortical branches of the middle cerebral artery (MCA) are rare. They usually are secondary to traumatic or infectious etiologies and are rarely idiopathic. The specific characteristics of idiopathic aneurysms in such location are not well defined in the literature. The authors report a rare case of a ruptured giant idiopathic cortical MCA aneurysm with review of the available literature on this clinical entity.
A 24-year-old female presented with headache, disturbed level of consciousness, and right-sided weakness. Imaging studies showed a left frontoparietal intracer