Reservoir Prediction Research Of Carboniferous Of SGP Structure

The SGP Carboniferous gas reservoir is bed-pore-type reservoirs. It's West Wing and northern end are fault shielding, and East Wing is Carboniferous formation pinch shielding. So this gas reservoir is also a structure-lithology combination traps reservoir whose eastern, Northern and western part are trapped and southern end is opening. The reservoir-type is fracture-pore and characterized by low-porosity, low-permeability, and strong-heterogeneity. Its structure is complicated. Most faults are reverse and buried, and the velocity variation is not obvious. These characters cause great difficult to the reservoir prediction including demarcation of horizons, establishment of frame structure molds and inversion of attribute.According to the particular structure and reservoir of this area, logging geology and seismic data is collected, and carefully analyzed to ensure its reliability. Based on accurate horizon demarcation, this paper precisely interprets the horizons of XuJiaHe formation and the bottom of the lower Permian which is SGP structure. Then we certify its structural form, distribution of faults, and mutual contact between traps. Through velocity analysis, a reasonable velocity model is made to establish the structure and cover depth of Carboniferous after time-to-depth conversion. Finally, the initial geological model is created using interpreted horizons, velocity model and logging geology data.After appropriate wavelet is extracted, velocity inversion is processed to predict the reservoir. Especially for the buried section, the inversion of upside and underside is inverted independently, which precisely predicts the distribution and thickness of Carboniferous reservoir in this area.Attribute analysis is needed for the prediction Because of that this area is characterized by low-porosity low-permeability and strong-heterogeneity, and the effect of velocity inversion is limited. After comparing the reliability and advantage of several attributes, those which match the logging data best are choosed for prediction. At last, the spatial distribution of SGP buried Carboniferous gas reservoir is confirmed.