Saudi Arabian Oil Company

Maan A Hawi

Weihua Wang

Yunsheng Li

Ibrahim A Makrami

Systems and methods for generating synthetic borehole image logs include logging rate of penetration (ROP) data, resistivity data, and gamma ray data while drilling a borehole in a subsurface formation to generate logged data. The generating includes determining an effective dip angle of the subsurface formation along the borehole and generating a depth shift table based on the effective dip angle and a well deviation angle, the well deviation angle being between the borehole and a vertical reference. Datasets are generated based on the ROP data, resistivity data, and gamma ray data, the generated datasets having higher sampling rates than the logged data. Synthetic borehole images are generated based on the generated datasets and the depth shift table, and the synthetic borehole images are oriented with respect to a reference point of the borehole.

Generating synthetic borehole image logs

A computer-implemented method that enables lithofacies guided core description using unsupervised machine learning is described herein. The method includes obtaining well log curves for a wells in a zone. The method also includes predicting lithofacies for the wells using a machine learning model. The machine learning model is trained with input data comprising additional well log curves and well cores. The method includes grouping the wells based on the predicted lithofacies, and updating core descriptions of the wells based on the grouped wells.

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Dhahran, Saudi Arabia

Maan A Hawi