Compact And Low Permeability Reservoir Prediction Research Of Daniudi Gas Field

The transartic lithology of the Daniudi area is intense,and the vertical sand and mud are superimposed,and it has very strong heterogeneity and belongs to the dense low permeability gas field.During the development of the gas field,the location of the well,especially the design of the horizontal well trajectory,is very important and requires very precise prediction of the target sand body depth.This paper focuses on the study of tight and low-permeability reservoirs in the J72 area.According to the geological characteristics of the area,it is determined that the inversion method of well-seismic combination can be used to realize reservoir sand body prediction in the J72 area.And by improving the general geostatistical inversion process,a depth-domain inversion method is proposed,which is used as a suitable reservoir inversion method in the working area.Firstly,the seismic data and well logging data were collated,the logging curve preparation for the 15 wells and the seismic data quality analysis in the whole area,and the seismic synthesis record calibration were completed.With four seismic reflection horizons(T9f,T9 e,T9d,and T9b)as constraints,a three-dimensional stratigraphic framework was constructed and sparse pulse wave impedance inversion was performed on this basis.Secondly,through lithologic physical analysis and geostatistical analysis,the basis for the division of sand and mudstone in the study area was determined,and the compensated neutron curve was selected as the lithology inversion parameter.Thirdly,using the control experiment method,the reservoir of the study area is first subjected to the conventional time domain inversion,then the impedance data body is converted to the depth domain,and then a random simulation inversion is performed in the depth domain.Comparing the inversion results,the results show that the depth-domain inversion can effectively eliminate the influence of time-depth calibration errors,and the inversion results can more accurately predict the tight and low-permeability reservoir sand bodies.