Research On Log Evaluation Of High Rank Coalbed Methane Reservoirs And Some Key Issues

Based on the coal bed experimental analysis data and conventional logging dataof a high rank coalbed methane study area in Southern Qinshui Basin, and takingcoalbed methane reservoir evaluation technique, the geological factors, loggingresponse and well environment as well logging interpreting model are systematicallystudied.In this thesis, the formation of coalbed methane and its reservoir geologicalcharacters are concluded, the reservoir material composition of coal bed, crackstructure, permeability characteristics, and controlling factors of gas contents arestudied, and then yield geological theoretical supports for the model interpretingmethods and parameter selection for coalbed methane logging. For high rank coalbedmethane reservoir, mathematical statistics are introduced to analyze the data fromfield data and experimental data, then deduced the distributions of all kinds of generalanalysis, like proximate analysis, microscopic components, clay minerals, vitrinitereflectance and gas contents, then explored the log response mechanism of coalbedmethane reservoir based on the proximate analysis, pore structure of coalbed, andstorage status of coalbed methane.In order to get high quality logging data with the situation of expanding ofcoalbed methane reservoir, Mont Carlo method is employed to simulate the structureenvironment of small diameter well of coalbed methane, and complete the density logsimulation of different coal bed densities and density logging response in differentexpanding situation, and then the count rate variation in long and short distance arededuced, a “spine-rib-plot” of density logging in different expanding, also solve theparadox of partial high rank coal bed reservoir density is less than1.1g/cc, whichprovides a solution to density expanding correction of coalbed methane reservoir.For issues should be solved during coalbed methane exploration like coal qualityanalysis, coal reservoir properties, natural gas reserves and roof and floor evaluationof coal bed, a quantitative interpretation models about important parameters likeproximate analysis, porosity, gas content, vitrinite reflectance, rock strength are constructed in this thesis. And sum up some developed interpreting method in highrank coalbed methane reservoir. That can be concluded as when calculate theproximate analysis, regression analysis method based on statistical models should beapplied with adequate sample data, meanwhile, if the sample data is not enough, BPneural network algorithm should be used. Finally, constrained optimization algorithmfor high rank coal bed methane quick predicting is proposed based on volume model.Propose stepwise multiple regression analysis method which taking coal bed averagedata as study objects to get the gas contents functions, which can be used to deducethe gas contents with logarithm of proximate components and logarithm of loggingdata respectively. Mechanical parameters of coal bed and surrounding rocks can becalculated via regular logging information like sonic and density data. Also,regression formula of predicting compressive strength via the ratio of compressionalto shear wave velocity is fitted. At last the case study showed that the above methodsworked well in logging evaluation of high rank coalbed methane reservoirs.