Knowledge of permeability, which is the ability of rocks to transmit the fluid, is important for understanding the flow mechanisms in oil and gas reservoirs.
Permeability is best measured in the laboratory on cored rock taken from the reservoir. Coring is expensive and time-consuming in comparison to the electronic survey techniques most commonly used to gain information about permeability.
Yamama formation was chosen, to predict the permeability by using FZI method. Yamama Formation is the main lower cretaceous carbonate reservoir in southern of Iraq. This formation is made up mainly of limestone. Yamama formation was deposited on a gradually rising basin floor. The digenesis of Yamama sediments is very important due to its direct relation to the porosity and permeability.
In this study permeability has been predicated by using the Flow zone indicator methods.This method attempts to identify the flow zone indicator in un-cored wells using log records. Once the flow zone indicator is calculated from the core data, a relationship between this FZI value and the well logs can be obtained.
There are many images you need to large Khoznah space With the continued evolution of storage technology for computers, there is a need nailed required to reduce Alkhoznip space for pictures and image compression in a good way, the conversion method Alamueja
Abstract
Target costing and cleaner production are among the most important techniques in the field of cost and management accounting, which, when integrated, enable economic units to achieve the goal of cost management by reducing it by calculating cost more accurately than traditional methods.To achieve this, the researcher relied on the inductive approach in writing the theoretical framework for the research, relying on foreign and Arabic books, dissertations and university theses, foreign and Arabic research and periodicals related to the subject of the research, and relying on the descriptive and analytical approach in
... Show MoreIn this study, a fast block matching search algorithm based on blocks' descriptors and multilevel blocks filtering is introduced. The used descriptors are the mean and a set of centralized low order moments. Hierarchal filtering and MAE similarity measure were adopted to nominate the best similar blocks lay within the pool of neighbor blocks. As next step to blocks nomination the similarity of the mean and moments is used to classify the nominated blocks and put them in one of three sub-pools, each one represents certain nomination priority level (i.e., most, less & least level). The main reason of the introducing nomination and classification steps is a significant reduction in the number of matching instances of the pixels belong to the c
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Stone columns are widely used globally due to theirversatility and relative wide applicability to treat different soil and foundation situations but much of the research undertaken to date has focused on their use in soft soils. In countries like Iraq the use of stone columns is still limited from a practical point of view, chiefly as many other soil conditions are commonly encountered. These include collapsible soils: soils that are prone to relatively rapid volume compressions (through collapse of metastable fabrics) that occur due to the action of load and/or increases in water content. Recent work has opened up the possibility to use stone columns in these soils by the use of encasement, thereby overcoming the impact of loss of lateral
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In this paper, we designed a new efficient stream cipher cryptosystem that depend on a chaotic map to encrypt (decrypt) different types of digital images. The designed encryption system passed all basic efficiency criteria (like Randomness, MSE, PSNR, Histogram Analysis, and Key Space) that were applied to the key extracted from the random generator as well as to the digital images after completing the encryption process.
Study of group action of stone columns using FEM
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In the present work, pattern recognition is carried out by the contrast and relative variance of clouds. The K-mean clustering process is then applied to classify the cloud type; also, texture analysis being adopted to extract the textural features and using them in cloud classification process. The test image used in the classification process is the Meteosat-7 image for the D3 region.The K-mean method is adopted as an unsupervised classification. This method depends on the initial chosen seeds of cluster. Since, the initial seeds are chosen randomly, the user supply a set of means, or cluster centers in the n-dimensional space.The K-mean cluster has been applied on two bands (IR2 band) and (water vapour band).The textural analysis is used
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