The Study On Coalbed Methane Logging Evaluation Of Yan'an Formation In Region CL Of Southeastern Ordos Basin

In order to improve logging fine interpretation technology and result of coal seam gas reservoir,based on drilling data,logging data and core analysis data of CL area in the southeast area of Ordos Basin,the coal reservoir logging response characteristic research and the coal seam gas logging series optimization analysis is carried out in this study.Base on wavelet analysis,high resolution structure thickness division of coal seam gas reservoir is realized.The informative coal reservoir industrial composition prediction model,porosity and permeability prediction model is built.Through the analysis of the influencing factors of gas content in coal seam gas reservoir,combining the data of this area,the new gas content prediction model of the coal seam gas reservoir is built.The research shows that in this area the Yan'an formation thickness is relatively stable in landscape,and Fuxian formation thickness is very unstable.The natural gamma-ray curve is the most sensitive to lithologic division,and the density curve is the most sensitive to coal rock recognition.The logging series optimization of the coal seam gas reservoir shows that the spontaneous potential logging,natural gamma ray log and caliper logging can complete the basic lithology identification well in coal seam gas reservoir.Assisted by density logging curve,the accuracy identification of the coal rock can be realized.Compensated density logging,compensated neutron logging and compensated sonic logging is beneficial to the prediction of coal rock porosity and permeability.Lateral logging is appropriate for high resistance coal reservoir and induction logging is appropriate for low resistance coal reservoir.Forward model analysis and real data processing shows that The point of the layer 3 high frequency signal in wavelet coefficient(detail signal),which obtained by the application of sym6 wavelet to wavelet analyze natural gamma ray and density curve can finely mark off the top or bottom interface of the coal reservoir.The modulus variation in coal reservoir of after decomposition wavelet coefficients reveals the longitudinal variation of the coal reservoir.Using the relativity of coal density and logging density as a bridge,the correlation analysis of logging data and coal parameters is carried out,and the coal rock industrial components parameters prediction model from logging data is built.The comparison shows that the coincidence of the actual calculation result of carbon and the experimental result is very high,and the coincidence of the actual calculation result of moisture and ash and the experimental result is higher.The comparison of the volume of rock physical model and probability statistics model shows that the probability statistics computational method of the coal industrial components is very feasible.In view of the coal rock physical property analysis,based on compensated density data,the total porosity of the coal reservoir is calculated.The permeability of the coal reservoir is calculated by F-S algorithm.And the calculation problem of the relevant data is resolved reasonably.The porosity and permeability plane distributive characteristic of the coal reservoir in this area reveals that the porosity and permeability in the middle to the eastern of this area is better.And the northeast and southwest area is worse.Based on the influence factor analysis of coal reservoir gas content,combining the revisional KIM equation using in this study,the coal reservoir gas content of 6 wells is calculated.The result shows that the coal reservoir gas content in the middle to the eastern of this area is high,and the northeast and southwest area is low.