Shear wave prediction using committee fuzzy model constrained by lithofacies, Zagros basin, SW Iran

- The geological constraint specially lithofacies information improves estimation shear wave velocity utilizing Fuzzy machine system.
- Predicting shear wave velocity from post-stack seismic attributes is an efficient and inexpensive strategy when real data of shear wave velocity are not accessible in some wells.
- Fuzzy inference systems provide a cost-effective and accurate way to estimate shear wave velocity from seismic attributes. Amongst fuzzy inference systems, OFIS has provided more accurate results.
- Combining the results of fuzzy inference systems in a power law structure of committee machine, improves the results of individual fuzzy models.
- The BA is a fast and exact method to optimize the OFIS and CFM methods. The grouping of data based on lithofacies significantly enhanced the prediction accuracy spacially with lower error in sand.

The main purpose of this study is to introduce the geological controlling factors in improving an intelligence-based model to estimate shear wave velocity from seismic attributes. The proposed method includes three main steps in the framework of geological events in a complex sedimentary succession located in the Persian Gulf. First, the best attributes were selected from extracted seismic data. Second, these attributes were transformed into shear wave velocity using fuzzy inference systems (FIS) such as Sugeno's fuzzy inference (SFIS), adaptive neuro-fuzzy inference (ANFIS) and optimized fuzzy inference (OFIS). Finally, a committee fuzzy machine (CFM) based on bat-inspired algorithm (BA) optimization was applied to combine previous predictions into an enhanced solution. In order to show the geological effect on improving the prediction, the main classes of predominate lithofacies in the reservoir of interest including shale, sand, and carbonate were selected and then the proposed algorithm was performed with and without lithofacies constraint. The results showed a good agreement between real and predicted shear wave velocity in the lithofacies-based model compared to the model without lithofacies especially in sand and carbonate.