Developing accurate and high resolution reservoir models imply integration of data from different sources in varying scales, which is one of the major challenges in reservoir characterization. Relatively low resolution of seismic data could only offer a structural model for the reservoir but its availability and areal coverage suggests that it has valuable information to constrain the reservoir model. This information could be extracted by the process of seismic inversion that transforms seismic data into a quantitative rock property, descriptive of the reservoir. In this study a novel intelligent seismic inversion workflow is presented to achieve a desirable correlation between low-frequency seismic signals, and the much higher frequency well log data with reducing uncertainties.
The proposed logical workflow consists of a systematic progression from well data analysis to rock physics modelling to seismic inversion and finally reservoir property estimation. The results reveals that optimization of seismic inversion workflow must be handled in unique manner. By using a series of simple examples to complicated case histories it will be demonstrated that significant benefits can be obtained by following an optimized workflow that is tailored to deal with the uncertainties that impact the end product.
It can be concluded that relative inversion should be performed first so that one should be crystal clear about what information can be extracted only from the seismic without bias from logs. The next step is absolute inversion which implies logs as geologic context and broadens the inversion band to establish the relation between log and seismic. At final stage one should consider more advanced techniques such as model base inversion, elastic inversion, simultaneous and geostatistical inversion. The ultimate goal is optimum reservoir characterization and management which leads to success and reduce uncertainties.
