Seismic feature extraction using steiner tree methods

• Main Authors: Schmidt, Ludwig (Contributor), Hegde, Chinmay (Contributor), Indyk, Piotr (Contributor), Lu, Ligang (Author), Chi, Xingang (Author), Hohl, Detlef (Author)
• Other Authors: Massachusetts Institute of Technology. Department of Electrical Engineering and Computer Science (Contributor)
• Format: Article
• Language: English
• Published: Institute of Electrical and Electronics Engineers (IEEE), 2018-02-22T19:02:47Z.
• Subjects: Article
• Online Access: Get fulltext

 Identifying "interesting" features, such as faults, unconformities, and other events in subsurface images is a challenging task in seismic data processing. Existing state-of-the-art methods usually involve manual intervention in the form of a visual inspection by an expert, but this is time-consuming, expensive, and error-prone. In this paper, we propose an efficient, automatic approach for seismic feature extraction. The core idea of our approach involves interpreting a given 2D seismic image as a function defined over the vertices of a specially chosen underlying graph. This enables us to formulate the feature extraction task as an instance of the Prize-Collecting Steiner Tree problem encountered in combinatorial optimization. We develop an efficient algorithm to solve this problem, and demonstrate the utility of our method on a number of synthetic and real examples.