Research On Logging Evaluation And 3D Geological Modeling Of Coalbed Methane Reservoirs In Yan'an Formation In HSD Area

At present,it is the most promising method to evaluate the gas content of coal reservoirs through logging methods.Using the principle of "core calibration logging" can improve the accuracy of logging data to evaluate the gas content of coal reservoirs.This paper takes 5#coal,6#coal,and 8#coal in the Jurassic Yan'an Formation in the HSD area of the southwestern margin of the Ordos Basin as the research object.Based on logging data,borehole data,and core analysis test data,the study area has been studied for the formation characteristics,coal rock logging response characteristics,and coal reservoir thickness high-resolution logging identification,and the industrial composition of the coal reservoirs in the study area has been established,Logging prediction model.Quantitative analysis of the factors affecting the gas content of coal reservoirs in the study area through the analysis method of gray correlation theory.Combining a variety of mathematical methods,a prediction model for the gas content of coal reservoirs in the study area is established.Finally,a three-dimensional geological model is established to reveal the spatial distribution of the relevant attributes of coalbed methane reservoirs in the study area.The results show that the thickness of each layer in the study area varies greatly,and the anticline and syncline obviously control the lateral distribution of the strata in the study area.The 5#coal,6#coal and 8#coal have similar burial depth characteristics.They all show that the burial depth is shallower at the developed anticline and larger at the syncline developed,which maintains a high degree of consistency with the characteristics of the coal seam thickness.The response characteristics of coal and rock logging show that it is mainly based on density,natural gamma,sonic time difference,and long-distance gamma logging curves,combined with other logging curves,and can be accurately identified by establishing histograms,intersection diagrams,and logging spider diagrams.Coal seam and its division lithology.The high-frequency signal of the fifth layer after the decomposition of the natural gamma and density logging curves by Dmey wavelet can realize the division of the top and bottom interfaces of the coal seam,and the decomposed high-frequency signal changes in the curve shape of the coal seam section,indicating that the coal seam section coal The uneven quality and coal body structure are different.Based on the coal reservoir industry component test data and logging data,the log data and coal quality parameters are analyzed,and the coal industry parameter prediction model is established through the BP neural network.The results show that the BP neural network is more accurate in predicting moisture,ash and volatile content,with low overall error,while the fixed carbon prediction result is relatively poor and the overall error is lower,indicating that its network has higher prediction accuracy and generalization ability.The rock and mineral characteristics of coal reservoirs indicate that the sulfur content,mineral content,and ash composition index in the study area all show that the study area is dominated by marine-continent transitional facies deposits.Based on the analysis of the influencing factors of the gas content of coal reservoirs,the main controlling factors of the coalbed methane content in the study area are determined by the grey relational analysis method.The buried depth of the coal reservoir is the main controlling factor of the gas content of 5#coal and 8#coal,and the thickness of the coal reservoir.It is the main controlling factor of 6#coal gas content.Comparing the multiple regression statistical model method,the BP neural network method,the support vector regression method and the deep learning network method and other gas content evaluation methods,it is concluded that the deep confidence network model has an accurate prediction of the gas content in the study area.The 8#coal seam in the study area contains The gas volume is high and the enrichment range is large.Using sequential Gaussian stochastic simulation method,a three-dimensional geological model of Yan'an Formation stratum and gas content,ash content,and calorific value properties was established.The gas content changes slowly along the NW-SE direction on the plane,and changes quickly in the NE-SW direction.There are spatial differences in the primary and secondary directions,while the vertical spatial differences are not obvious.8#coal storage The gas content of the seam is higher than other coal seams,and the continuity is better.The ash content changes slowly along the NW-SE direction on the plane,and changes faster in the NE-SW direction,but it changes more slowly than the gas content in the primary and secondary directions.The ash content of the 8#coal reservoir is lower than the others Coal seam,and the overall distribution of ash is not obvious.The calorific value changes on the plane without directionality,and the heterogeneity is not obvious.8#coal has a higher calorific value,but the calorific value spreads in a relatively narrow range with little difference,and the overall distribution of calorific properties is not obvious.