Carbonate cavity reservoirs have been a challenge in the industry for hydrocarbon exploration and production. Seismic imaging is able to find the cavities using the ‘beam string’ reflections. However, it lacks the detail of the cavities and the faults, sub-faults and fractures around them. During the production phase, it turns out that the cavity structures and their related sub-faults and fractures could be critical. This means that the understanding of connectivity between cavities could help improve production. Also, due to its cavity nature, the geo-model is difficult to be used for reservoir simulation. However, the model serves a good tool for analytical analysis such as material balance. The goal of this work is to build a geo-model by using a Bayesian approach. By extracting the relative reflection strength such as RMS, the cavities can be identified more easily. Using steerable pyramid processing, the faults and sub-faults are recognized. By merging the cavities and sub-faults, we devised a ‘cotton tree’ display scheme. This structure and the corresponding inversion of its seismic form the constraints of geological modeling. The reservoir model is built using a strong seismic-constrained approach. Furthermore, the model is used to analyze the dynamic performance and for better reserves estimation. The connectivity between cavities is analyzed using the model and ‘cotton tree’ structure. The procedure demonstrates a valid tool for cavity connectivity analysis.
Presentation Date: Wednesday, October 14, 2020
Session Start Time: 8:30 AM
Presentation Time: 10:35 AM
Presentation Type: Oral