Well log analysis and production testing in coal are the initial requirements to judge the prospectivity of a coalbed methane (CBM) reservoir. The process of prospect identification through laboratory studies is accurate although it is time-consuming and expensive. Therefore, we developed a methodology to identify prospective coal seam by establishing multiple regression models of geophysical well log parameters vs. organic/inorganic contents from laboratory-tested core samples for one seam. The Langmuir’s equation and methane adsorption isotherm were used to estimation of gas and saturation content by developing a regression model from organic content. Gas and coal contents (ash, moisture, fixed carbon, and volatile matter) were obtained from the subsequent propagation of the established equations to other wells. Gas saturation increased with depth from 60 to 69%. Mapped seam thickness and gas content were in the ranges of 10.0–54.0 m and 6.1–28.2 cc/g, respectively. Overlaying of seam thickness and gas content identified the sweet spots in releasing potential future well locations. Errors within the permissible limit between the predicted and observed values indicate the gas estimation to be reliable. Another application for electro-facies classification was demonstrated by applying multi-resolution graph-based clustering architecture to capture texture parameters from histogram and auto-covariance function in resistivity image log. Determination of lithology by correlation of resistivity image and geophysical well log corroborated with the depositional environment having fining upward formational sequence. Thus, this study helps in estimating proximate components, gas content, and saturation with depth in coal seam for production optimization to better understand its implications on the dewatering and gas production periods in the Bokaro CBM reservoir situated in India.

煤的测井分析和生产测试是判断煤层气（CBM）储层前景的初步要求。通过实验室研究确定前景的过程是准确的，尽管既耗时又昂贵。因此，我们通过建立一个地球物理测井参数与实验室测试岩心样品中有机/无机含量相对于一个煤层的多个回归模型，开发了一种识别潜在煤层的方法。通过建立有机物含量的回归模型，使用Langmuir方程和甲烷吸附等温线估算气体和饱和物含量。气体和煤的含量（灰分，水分，固定碳和挥发性物质）是从已建立的方程式随后传播到其他井中获得的。气体饱和度随深度从60％增加到69％。映射的煤层厚度和瓦斯含量分别在10.0-54.0 m和6.1-28.2 cc / g的范围内。煤层厚度和瓦斯含量的叠加确定了释放潜在的未来油井位置的最佳点。预测值和观察值之间的允许范围内的误差表明气体估计值是可靠的。通过应用基于多分辨率图的聚类体系结构从电阻率图像测井中的直方图和自协方差函数捕获纹理参数，证明了电相分类的另一个应用。通过电阻率图像与地球物理测井曲线的相关性来确定岩性，这与具有精细向上构造层序的沉积环境相吻合。因此，