A Rapid Method for Information Extraction from Borehole Log Images

Abstract

Borehole logs are very important for geological analysis and application. Extracting structured information from borehole logs in the image format is the key to any analysis and application based on borehole data. The current method has defects in solving the beard phenomenon of the borehole log and the identification of special geological symbols. This paper proposes an automatic extraction method for borehole log information by combining the structural analysis based on the corner mark, as well as the structural understanding based on deep learning. The principles and key technologies of the method are described in detail. The performance of the method was tested by specific examples. This method is implemented on a geological information platform called QuantyView. The information extraction of 100 borehole logs with the same specification is used to verify the effectiveness of the proposed method. The results show that the method can not only effectively solve the inconsistency between the thickness and the description information in the borehole log but it can also address the low recognition efficiency of professional vocabulary, which can improve the extraction efficiency and accuracy of the borehole log information.

Keywords

• borehole log
• structural analysis
• information extraction
• deep learning