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Automatic Recognition of Lithological Units in Gas-bearing Shale Complex with Neural Networks (the Baltic Basin, Poland)
- Publisher: European Association of Geoscientists & Engineers
- Source: Conference Proceedings, Petroleum Geostatistics 2019, Sep 2019, Volume 2019, p.1 - 5
Abstract
The study was performed to check the possibility of automatic recognition of lithological units of shale complex and testing their heterogeneity in different parts of the Baltic Basin. For this purpose, two separate neural network models have been trained based on geophysical logs datasets: one for perspective units recognition, and second for tuffite interbeds detection. Obtained results have compared with units distinguished by sedimentologists in continuous core profiles. The performance of trained networks has been checked for two boreholes B-7 and B-1 not included in the training process. In case of the borehole B-7, the units predicted by the model match well to those distinguished manually in borehole core. In contrary, the score of model performance for the B-1 borehole was unsatisfactory. Significant differences in the lithological profile of this borehole were also recognized by sedimentologists. Due to the location of borehole B-1 in the marginal part of the basin, most of the properties of the studied units differ relevantly from recognized in other investigated boreholes. The performance of the network trained for tuffite interbeds detection is considered satisfactory. The results imply that the trained models might be applied in the boreholes where the core profiles are modest or non-existent.