The gas material balance equation (MBE) has been widely used as a practical as well as a simple tool to estimate gas initially in place (GIIP), and the ultimate recovery (UR) factor of a gas reservoir. The classical form of the gas material balance equation is developed by considering the reservoir as a simple tank model, in which the relationship between the pressure/gas compressibility factor (p/z) and cumulative gas production (Gp) is generally appeared to be linear. This linear plot is usually extrapolated to estimate GIIP at zero pressure, and UR factor for a given abandonment pressure. While this assumption is reasonable to some extent for conventional reservoirs, this may incur significant error when applied for unconventional tight gas reservoirs. The implementation of multi-tank, compartmented reservoir models are reported to better represent the behaviour of tight gas reservoirs. This study focus to develop a simple numerical method to solve the MBE using the concept of multi-tank, compartmented reservoir model. A simple and practical computational tool is developed by solving the numerical model using False Position iterative method. The tool is applied to calculate GIIP and UR factor for an Australian tight gas field after validation of tool based on history matching. The results demonstrated that the developed tool can be used for the better estimation of GIIP and UR factor with better accuracy. The program can also be used as an efficient tool, especially in the case of homogenous tight gas reservoir, as an alternative to the reservoir simulation to understand the pressure decline behaviour with cumulative gas production; and to estimate GIIP and UR factor.
Cassava, a significant crop in Africa, Asia, and South America, is a staple food for millions. However, classifying cassava species using conventional color, texture, and shape features is inefficient, as cassava leaves exhibit similarities across different types, including toxic and non-toxic varieties. This research aims to overcome the limitations of traditional classification methods by employing deep learning techniques with pre-trained AlexNet as the feature extractor to accurately classify four types of cassava: Gajah, Manggu, Kapok, and Beracun. The dataset was collected from local farms in Lamongan Indonesia. To collect images with agricultural research experts, the dataset consists of 1,400 images, and each type of cassava has
... Show MoreThe Transformation of environments surrounding human which called (place), formed an intermediate compresser in forming awareness pictures, human knowledge, culture and thought features, and changing the systems and contexts of human societies, which led to a change the rhythm of life as a whole. So according to that the place will be encodes according to these data for psychological connotations, lead to human sense of harmony with the place in different manner format, here the search problem lies when trying to detect how Iraqi artist deliberating with the place concept, wondering how to investing place in the contemporary Iraqi drawing within its reference dimension, and showing mechanisms from comparative study for the works of two a
... Show MoreAbstract: The study of the place is hardly a concern for most researchers in the art generally. It is hardly devoid of any movie of some configuration elements that are essential to him about and place one of them, and we find an echo location consists ago to begin screenwriter put Sightseeing begins features emerge there will be functioning simple scenario what would soon receive a growing Cummings final picture film. Metaphoric place begins to emerge in the form of linguistic scenario is soon to be translated in another language, the language of the image. Which in turn complement the creative process of this art and have a significant impact in terms of content and curriculum and installation in and it even to seek the true meaning fu
... Show MoreThe present study discusses one of the most relevant and required topics in the recent period during globalization, the modern Russian system of terms for the oil and gas industry as a whole acquired a complete form in the second half of the twentieth century. The period of the late XX - early XXI centuries. marked by cardinal transformations in all areas of the political, economic, social and cultural life of Russia. These changes could not but affect industrial production. Transition to a new vector of development of the Russian economy based on the development of commercial trade, on the change and improvement of the development of industrial enterprises in the context of the implementation of national projects and the introduction
... Show MoreUnconfined compressive strength (UCS) of rock is the most critical geomechanical property widely used as input parameters for designing fractures, analyzing wellbore stability, drilling programming and carrying out various petroleum engineering projects. The USC regulates rock deformation by measuring its strength and load-bearing capacity. The determination of UCS in the laboratory is a time-consuming and costly process. The current study aims to develop empirical equations to predict UCS using regression analysis by JMP software for the Khasib Formation in the Buzurgan oil fields, in southeastern Iraq using well-log data. The proposed equation accuracy was tested using the coefficient of determination (R²), the average absolute
... Show MorePurpose: The diagnosis and determine the level of balance between the time available for life and work with the doctors in the hospitals of t the six hospitals in the City of Medicine.
Design / methodology / Approach: It has been relying on ready-scale, to make sure the diagnosis and determine the level of balance between the time available for life and work, where they were distributed on Form 42 doctors in the six hospitals in the City of Medicine, were analyzed by software (Nvivo and SPSS v.22).
Results: The results showed that there is a good level of balance between the time available for life and work with the doctors.
Research limitations: The diffi
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