Study On Logging Interpretation Of Coalbed Methane Reservoir In T Area

In order to serve the evaluation of coalbed methane reservoir in T area,based on the CBM logging interpretation standard issued in 2015,the comprehensive well logging interpretation of coalbed methane in T area is carried out through the collected coal rock test data and logging data on the premise of understanding the geological situation of the area.Firstly,the collected data are preprocessed,the lithology identification and logging response characteristics of reservoir are analyzed.Secondly,combined with the key beds,the detailed stratigraphic division and correlation of the target layer in the study area are carried out.Finally,based on the preprocessed logging data and test data,the interpretation model of industrial components,physical parameters and gas content in T area is constructed,and the distribution characteristics of coalbed methane reservoir parameters in the study area are revealed.The study shows that the logging response characteristics of the 2# coal seam in T area are "two high,two low and one negative",that is,the acoustic wave value is high,the resistivity value is high,the gamma value is low,the density value is low,and the spontaneous potential value is negative;The sensitivity of natural gamma,density and acoustic logging curves to identify coal and rock is good.From northwest to southeast,the thickness of Yan'an formation in the study area tends to be thick in the middle and thin on both sides,with an average of 94.1m;From northeast to southwest,the 2# coal seam is thick in the middle and thin on both sides,with an average value of 3.84 m.The volume model method,regression analysis method and BP neural network method are used to calculate the industrial component parameters of the 2# coal seam in T area,by comparing the calculated results of the three methods with the measured values,it can be concluded that the BP neural network method is more suitable for the prediction of industrial components in the study area,the results show that from northwest to southeast,the ash and volatile content of the 2# coal seam are characterized by low middle value and high two side value,while the fixed carbon content is characterized by high middle value and low two side value;From west to east,the water content is high in the middle and low on both sides.According to the prediction of physical properties of the 2# coal seams in this area,the difference ratio method of true density and apparent density is used to calculate the total porosity of coal seam,and the results show that the porosity of 2# coal seam shows the characteristics of low middle value and high value on both sides from west to east;The simplified Archie formula is used to calculate the fracture porosity of coal seam,the results show that the fracture porosity of the 2# coal seam is low in the middle and high on both sides from northwest to southeast;The F-S method and regression analysis method are used to calculate the fracture permeability of coal seam,and the regression analysis method is optimized to establish the prediction model of fracture permeability of the 2# coal seam in T area,the results show that from northwest to southeast,the fracture permeability of 2# coal seam presents the characteristics of low middle value and high two sides value.Based on the analysis of the characteristics of the 2# coal seams in T area,Kim equation calculation method,regression analysis method and BP neural network method are selected to carry out the modeling work of gas content prediction according to the collected test data and logging data,by comparing the calculation results of the three methods,it is found that the accuracy of BP neural network method is higher,the results show that the gas content of the 2# coal seam in the study area tends to be high in the middle and low on both sides from northwest to southeast,and the content of coal seam gas is mainly affected by coal quality,coal rank,coal seam buried depth and other factors.