Daniudi gas field is a large scale lithologic gas field discovered by SINOPEC during the tenth five-year plan and its pooling is mainly controlled by the level of reservoir development. The reservoirs in Daniudi gas field are tight clastic rocks featuring in low permeability, low porosity, strong heterogeneity and rapid variation. The seismic responses of these sandbodies are not significant due to low seismic resolution, small contrast of acoustic impedance between sandstone and shale, and strong shielding of coal layers, increasing the difficulty of the reservoir prediction and constraining exploration of gas reservoirs. So it is very important to select appropriate reservoir prediction techniques for reservoir description. The overall technical rout of this paper is to qualitatively – semi-qualitatively – quantitatively characterize the reservoirs with seismic reservoir forecasting based on study of sedimentary facies. The paper focuses on two parts: sedimentary facies recognition and seismic reservoir prediction techniques. Study of sedimentary facies is the basis of seismic prediction. Comprehensive study with geologic data and well data reveals that two major channel sandbodies are developed in the Permian Shanxi Formation and the Lower Shihezi Formation in the southwest part of Daniudi gas field. The sandbodies are superimposed vertically and their lateral distribution is controlled by the channels. Daniudi gas field Permian System XIASHIHEZI group and SHANXI formation reservoir are predicted based on sedimentary faices recognition. Three core techniques are used. The first one is facies-controlled seismic attribute analysis technique which is used to identify the reservoir macroscopically through seismic data; the second one is the reservoir inversion description technique which is based on geostatistics theory, it can predict the reservoir semiquantitatively; the last one is the multi information interfused reservoir model building technique, it can predict the lithology, the physical property and contain gas property of the reservoir quantitatively. The sensitive seismic attributes reflecting channel sand selected through attribute optimization are amplitude, coherence, separate frequency and wave shape. Attribute forecasting has a definite understand for macro distribution of reservoir. Reconfiguration curve of Gr-neutron is used to identify lithology and reconfiguration curve of neutron-density is used to identify gas layers. Reservoirs are predicted semi-quantitatively through Lithology inversion and gas bearing inversion forecast. Inputting sedimentary facies study, attribute forecasting and seismic inversion forecast lithology, physical property and gas bearing of the reservoir through the multi information interfused reservoir model building in order to quantify the reservoir. Macroscopic-microscopic and qualitativel-quantitative prediction of the tight clastic reservoirs are successfully realized through the above study.
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