Abstract: A method and system is provided for detection of carbonate core features from core images. An input carbonate core image is separated into a plurality of first blocks, each of the plurality of first blocks having a first block size. An image of each of the separated plurality of first blocks is input into an artificial intelligence (AI) model. The AI model being trained to predict for each first block, one of a plurality of carbonate core features and a corresponding confidence value indicating a confidence of the predicted carbonate core feature being imaged in the first block. Any bounding boxes of a first set of bounding boxes are detected in the input core image based on the predicted one of the plurality of carbonate core features and the corresponding confidence values for each first block.

Abstract: A method and system is provided for detection of carbonate core features from core images. An input carbonate core image is separated into a plurality of first blocks, each of the plurality of first blocks having a first block size. An image of each of the separated plurality of first blocks is input into an artificial intelligence (AI) model. The AI model being trained to predict for each first block, one of a plurality of carbonate core features and a corresponding confidence value indicating a confidence of the predicted carbonate core feature being imaged in the first block. Any bounding boxes of a first set of bounding boxes are detected in the input core image based on the predicted one of the plurality of carbonate core features and the corresponding confidence values for each first block.