Estimating Reservoir Properties from 3D Seismic Attributes Using Simultaneous Prestack Inversion: A Case Study of Lufeng Oil Field, South China Sea

Lufeng oil field was discovered in the 1980s in the Pearl River Mouth Basin (PRMB) of the South China Sea and has entered the stage of secondary oil recovery. One major problem that has restricted the subsequent exploration of the oil field is the unclear regional reservoir and caprock distribution, because practitioners have been using post-stack attributes and acoustic impedance inversion to analyze the distribution of sandstone (reservoir) and mudstone (caprock). In current geophysical research on reservoirs and caprocks, prestack inversion has been widely used because of its advantage over post-stack inversion. However, the accuracy of using single P/S-wave velocity ratio (V-P/V-S) or density (V-den) inverted by prestack to predict lithology is still insufficient. In this study, we created a new attribute VRDEN, the sum of V-P/V-S and the weighted V-den, to capture the lithology variation of the reservoir. We integrated 3D seismic data and well log data and applied simultaneous prestack inversion and multiattribute regression analysis to determine reservoir properties, such as sand thickness, effective porosity, and distribution of sandstone and mudstone of the Lufeng oil field. Then, we calculated the new attribute VRDEN from V-P/V-S and V-den obtained from simultaneous prestack inversion to determine the lithology variation. The multiattribute regression analysis, combining prestack attributes and post-stack attributes, indicates the effective porosity and sand volume in the Enping Formation, which contains the main oil-bearing reservoirs in the Lufeng oil field. Results show that when the sandstone thickness is greater than 12.5 m, the prediction error of VRDEN is the lowest compared with V-P/V-S and V-den. In En-2 member of the Lower Enping Formation, medium- to high-porosity (14 to 17%) sandstone (19.5 m thickness) is widely distributed in the west and middle of the study area, with an area of nearly 300 km(2). The high-porosity sand zones stretch from the east of the Lower Enping Formation to the west of the Upper Enping Formation, which is the result of westward progradation of the braided delta. Our workflow used a novel seismic attribute VRDEN in the simultaneous prestack inversion and multiattribute regression process to provide a more predictive spatial distribution of reservoir-nonreservoir features. The improved reservoir understanding will allow more efficient exploitation of the Lufeng oil field, and the improved workflow will facilitate exploration of other oil fields in the world.

Automated summary

The Lufeng oil field in the South China Sea has faced challenges in the exploration due to the unclear distribution of reservoirs and caprocks. This study proposes a new seismic attribute VRDEN and a workflow combining prestack inversion and multiattribute regression analysis to improve the prediction of lithology and reservoir distribution. The results show a more accurate understanding of reservoir properties and a more efficient exploitation of the Lufeng oil field.