Petrophysical inversion predicts favorable Permian reservoirs

Research tasks

The research area of this project is a Carboniferous-Permian uplift, which belongs to the reservoir rich area, which has been located in the oil and gas transport directional zone for a long time. It has a superior structural location. The Permian multilayer reservoir has been discovered in this area and adjacent areas, where a certain target layer has obtained high production with great exploration potential. The depleted mud and gravel facies in the leading waterway of the fan delta developed in the destination strata are the most favorable reservoir collectives, so this research task aims to identify the distribution of lean sludge pore grit reservoirs as the core goal.

Research ideas

First of all, the geological goal of this project is clarified, that is, to identify the distribution of sedimentary gravel reservoirs in the pores of lean mud as the core goal, so the first step is to determine the interpretation of logging reservoirs through nmromag control, and then quantitatively characterize the reservoirs through petrophysical positive and negative evolution, and finally comprehensively evaluate the preferred targets. The specific implementation step is to perform T2 spectrum inversion on the basis of the input NMR data, interpret the total porosity by THE NMR data, and then obtain the effective porosity and clay content of NMR.

Vcl curve was obtained by rock physics modeling

On this basis, the longitudinal wave impedance and longitudinal wave velocity ratio obtained by preimpossed geostatistics inversion are used as inputs, and porosity and slurry content are obtained through petrophysical inversion, so as to realize quantitative reservoir evaluation.

Comparison of reservoir section and Vcl section from rock physics inversion

Vcl from inversion reflects the lithologic distribution structure of the target layer

Research Results

This study effectively controls the evaluation of logging formations through the results of NMR interpretation, improves the accuracy of the logging volume model, lays a solid foundation for petrophysics modeling, and the effective porosity interpretation of reservoirs is more quantitative. The slurry content and effective porosity of petrophysical inversion quantitatively depict the structure of high-quality reservoirs, and the application of inversion results is flexible, and the reservoir can be flexibly evaluated according to specific production needs. The technical processes established in this study are feasible and effective for reservoir forecasting in the region.