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The present paper describes the algorithm and working method for detection and estimation of proximate parameters of coal beds based on digital well-log data. Designed and developed by the authors in Visual Studio using C#, ProxInLAS is used to define a threshold value on each log to distinguish between coal and non-coal layers, followed by estimating each of the coal proximate parameters by importing...
In this paper, the algorithm and working method of the software are described, which allows the detection of depth and thickness of coal beds by digital information in well-logs. The software known as COALINLAS is designed and developed in Visual Studio using C# by the authors. In this software, a boundary value of each log is defined for detection of coal and non-coal layers, by importing the data...
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