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

Summary 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 (VP/VS) or density (Vden) inverted by prestack to predict lithology is still insufficient. In this study, we created a new attribute VRDEN, the sum of VP/VS and the weighted Vden, 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 VP/VS and Vden 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 VP/VS and Vden. 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 km2. 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.

Prestack Inversion Identification of Dolomite Reservoirs in the Fourth Member of the Sinian Dengying Formation in Moxi Area, Sichuan Basin, SW China

The dolomite reservoir of the fourth member of Dengying Formation in Moxi area of Sichuan Basin is thin, is fast in lateral variation, and has P-impedance difference from the surrounding rock; it is difficult to identify and predict the dolomite reservoir and fluid properties by conventional poststack seismic inversion. Through the correlation analysis of core test data and logging P-S-wave velocity, this work proposed a formula to calculate the shear wave velocity in different porosity ranges and solved the issue that some wells in the study area have no S-wave logging data. AVO forward analysis reveals that whether the gas reservoir of dolomite reservoir is located at the top of the fourth member of Dengying Formation is the main factor affecting the variation of AVO type. Through cross-plotting analysis of elastic parameters, it is found that P-S-wave velocity ratio and fluid factor are sensitive parameters to gas-bearing property of dolomite reservoir in the study area. By comparing the inversion results of prestack parameters such as density, P-wave impedance, S-wave impedance, P-S-wave velocity ratio, and fluid factor, it is found that the gas-bearing prediction of dolomite reservoir by using P-S-wave velocity ratio and fluid factor obtained from simultaneous prestack inversion had the highest coincidence rate with actual drilling data. At last, according to the distribution characteristics of fluid factor and P-S-wave velocity ratio, the favorable gas-bearing areas of dolomite reservoir in the fourth member of Dengying Formation in the study area are finely predicted, and the next favorable exploration areas were pointed out.

Direct inversion for reservoir parameters from prestack seismic data

Reliably estimating reservoir parameters is the final target in reservoir characterisation. Conventionally, estimating reservoir characters from seismic inversion is implemented by indirect approaches. The indirect estimation of reservoir parameters from inverted elastic parameters, however, will produce large bias due to the propagation of errors in the procedure of inversion. Therefore, directly obtaining reservoir parameters from prestack seismic data through a rock-physical model and prestack amplitude variation with offset (AVO) inversion is proposed. A generalised AVO equation in terms of oil-porosity (OP), sand indicator (SI) and density is derived by combining a physical rock model and the Aki–Richards equation in a whole system. This makes it possible to perform direct inversion for reservoir parameters. Next, under Bayesian theorem, we develop a robust prestack inversion approach based on the new AVO equation. Tests on synthetic seismic gathers show that it can dramatically reduce the prediction error of reservoir parameters. Furthermore, field data application illustrates that reliable reservoir parameters can be directly obtained from prestack inversion.