Mapping the Distribution and Characterization of Sandstone Reservoir Using Simultaneous Inversion Method in “OA” Field at Northern Bonaparte Basin

Abstract

The sandstone reservoir in the “OA” Field is situated in the Northern Bonaparte Basin, which is gas-saturated sandstone. Mineral diagenesis is also causing several reservoir zone areas to become tight sand. The inversion method using acoustic impedance (AI) is less sensitive in distinguishing sandstone and clay rock lithology since they have almost the same impedance. Simultaneous Inversion overcomes this problem by simultaneously inversing partial angle data (near, mid, far) to obtain physical parameters besides acoustic impedance which are expected to be more sensitive in distinguishing lithology and predicting the presence of gas fluids such as shear impedance (SI) and density. These three parameters can be derived as Lame (LMR) parameters. Cross plot analysis shows sensitive physical parameters to predict the distribution of lithology and the presence of gas fluid. Density sensitive in distinguishing lithology which is then inverted, obtaining sandstone cutoff values are 2.3-2.5 (g/cc), tight sand with cutoff 2.5-2.625 (g/cc) and clay stones with cutoff 2.625-2.8 (g/cc). The presence of gas fluid is predicted by inversing the parameter Vp/Vs which has a cutoff of >1.6 and Lambda-rho cutoff of >25 (Gpa)*(g/cc). Analysis of the parameter distribution map shows the distribution of sandstones and the presence of dominant gas fluids in the northern area of the research zone with relatively clean sandstone, compared to relatively more southern regions.

Implementation of the Poisson Impedance Inversion to Improve Hydrocarbon Reservoir Characterisation in the Poseidon Field, Browse Basin, Australia

“…Pre-inversion analysis needs to be done before the inversion process is carried out so that the inversion results produced are in accordance with the well data. The results of this analysis affect how well the correlation will be between the log data of the low-frequency model and the inversion results for each well [19]. A good correlation provides more accurate inversion results [20].…”

“…A good correlation provides more accurate inversion results [20]. When the correlation is low and the error is still high, an inversion analysis is carried out, such as initial modelling, wavelet selection or inversion parameters [19]. The results of the preinversion analysis can be seen in Figure 2.…”