The Geological Modeling Of Coalbed Methane In The Exploration Area Of The Dacun Coalfield In South Sicuan

In the increasing demand for resources today,conventional oil and natural gas have been unable to meet our needs.Thus,the exploration and development of unconventional natural gas is imminent.The geological modeling of CBM and favorable coalbed gas prediction can effectively guide the further development of coalbed methane,which is crucial for coal-bed gas exploration.Most of the coal fields have the matter lacking of coring data in coal seam.Coring and laboratory analysis not only requires a lot of manpower,material resources,but it also is difficult to carry out in the region coalfield.Relative to the lack of coring data,it is quick to get ample logging data.Summarizing the law by relying on a small amount of coal seam coring data,flexible usage of logging data,exploring reliable CBM interpretation model is needed for further research in the development of coalbed methane at present.The development of the village area coalbed gas has entered the test wells of ground drainage work.After a preliminary economic evaluation,it is believed that it has a good prospect for commercial development.For the next step in the development of the work,we need to consider is the reservoir characteristics of the region,physical characteristics,geological characteristics of whether are conducive to the large-scale development of coalbed methane.In this paper,based on systematical collection of the geological data,laboratory of coal core analysis data and the logging data,the village area carried out including coal seam identification,thin layer division,industrial component calculation,calculation of physical parameters,3D geological modeling,prediction of favorable zones.The results obtained are as follows.Through identifying coal seam by the direct recognition method of coal seam,coal seam thickness standards is established in the village area,according to the analysis of crossplot,the lithology of coal and non coal are identified in study area.Based on the identification of single well coal seam,the coal of the whole village area is thin,that the area deposited nine sets of coal layer,it includes seven mining coal seam,and the thickest coal is the number ten seam,and the coal of the thickness of thin is the number three,five and nine seams.Combined with the sedimentary data of the study area,the cut-off point is depended on the end of each sedimentary cycle,it divided into six layers,and including nine coal seam and nine non coal seam,then drawing the small layer correlation chart and the plane thickness distribution map of coal,it revealed that the sedimentary thickness of the study area gradually becomes thick from north to south,and sedimentary thickness becomes thin from west to East,realized that the West area is plants flourish than East,and the duration of deposition time is long,the rate of deposition is fast,it lead that the coal seam thickness of west is higher than the East.Based on the analysis of logging data and the industry date of laboratory test of coal core,there is a good correlation between ash and density,the ash calculation model is established during the regression analysis method.And using the volume-based method calculate the industrial components,then established the industrial components volume model.The correlation coefficent is high by analysised the measured value and the calculation value,the computing results are reliable.Using the logging method of the traditional dual lateral calculate the coal fracture porosity,amd using the variable density formula calculate the total porosity of the coal.When using the F-S method calculate the opening-closing degrees of cracks,based on Darcy's law derived the formula of fracture permeability.Selection the logging curve that is high sensitivity with the physical properties coal seam,included natural gamma,acoustic wave,density,resistance,neutron curve as the input curve,a neural network prediction model of porosity and permeability are built by using neural network algorithm,through the analysis of error statistics that the absolute error of the average porosity prediction using neural network is less than 1%,and the relative error of the average permeability is less than 20%,it proves that the The effect of network prediction and the laboratory analysis date are quite effective,so the forecast model is reliable.Using logging method,KIM equation and industry component calculation method calculate the CBM content,then analyse the relationship between the measured gas content value and calculate gas content value,based on the above researches the comprehensive method that is suitable for the region containing is summed.According to the above calculation parameters,using petrel modeling software,during the variogram analysis,the facies model,industrial component model,content model,porosity model of the study area are established.The lithologic distribution law,distribution of fixed carbon and ash content,porosity distribution,distribution of gas content are realized.According to the calculation date of industrial components,the physical parameters,gas content,then put forward the coalbed gas favorable area forecast is used by the application of fuzzy mathematics method,established a multi-level fuzzy evaluation model,and obtained the area of index prediction,drawed a prediction index distribution map,found that in the north and south of Dacun area are the favorable development zone of Coalbed methane.