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Productivity index prediction of alluvial fan coarse-grained clastic reservoirs with low porosity and low permeability:a case from Triassic Baikouquan Formation reservoir in Y-region at northwestern margin of Junggar Basin
Pages: 556-561
Year: Issue:  4
Journal: Oil & Gas Geology

Keyword:  3D seismic inversionproductivity index predictioncoarse-grained clastic reservoirnorthwestern margin of Junggar Basin;
Abstract: In order to use 3D seismic data for productivity index prediction of alluvial fan coarse-grained clastic reservoirs with low porosity and low permeability , we chose the Triassic Baikouquan Formation reservoir in Y-region at the north-western margin of Junggar Basin as a case .Based on traditional reservoir prediction such as thickness and porosity of coarse-grained clastic reservoirs ,we analyzed in detail factors influencing permeability and oil-bearing properties ,and in-troduced the average monthly production data at the early stage of development into 3D seismic inversion to predict the productivity index .The following work flow was established:‘finding coarse-grained clastic reservoirs through typical curve inversion ,finding high quality coarse-grained clastic reservoirs through porosity inversion ,finding permeable coarse-grained clastic reservoirs through spontaneous potential inversion , finding oil-bearing coarse-grained clastic reservoirs through resistivity inversion ,and predicting reservoir productivity index with the combination of several methods ’ .A pro-ductivity index cube was finally generated through Neural Network modeling by using the monthly productivity as hard da -ta and wave impedance,porosity,resistivity,spontaneous potential inversion data cube and time domain structure as trai-ning samples.The result shows that there is a positive correlation (R2 =0.948 7)between the predicted monthly produc-tivity and initial average monthly production .For wells with an initial monthly average production more than 300 ton,the error of prediction is less than 10%.The data cube contains various information controlling hydrocarbon distribution ,such as lithology ,reservoir property ,oil-bearing property and permeability .The oil production of three appraisal wells deployed based on this research in Y-region reached more than 5 ton per day,which verified the accuracy and practicability of this productivity index prediction technology .
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