Constant improvements in seismic acquisition, processing, and conditioning technologies, allow geoscientists to obtain detailed seismic volumes. However, the useful and expensive information contained in these volumes is not always fully harnessed due to traditional seismic interpretation limitations. Common interpretation techniques of seismic “digitization” usually fall behind the need of digesting the necessary amount of data to provide a robust and integrated analysis. The proposed workflow quickly translates into an outstanding strategic advantage for multidisciplinary teams interested in effectively finding, characterizing, and maturing multiple and different types of targets in seismic volumes. We used the Teapot Dome 3D seismic survey as input for demonstrating the use of the Model-Grid and unique approach of the Relative Geological Time Model on a US onshore dataset. From these models, we obtained a series of stratal slices where several attributes were mapped and found some interesting geological features and patterns. Since there are several formations with economic interests at different stratigraphic levels, these workflows proved to be of strategic advantage to make quicker and more accurate economical decisions in multidisciplinary teams that commonly require outputs from seismic interpretation.
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SEG/AAPG International Meeting for Applied Geoscience & Energy
August 28–September 1, 2022
Houston, Texas, USA
Paper Contents
Benefits of semi-automatic seismic interpretation workflow for fast-paced decision-making environments: A U.S. onshore case study
Paper presented at the SEG/AAPG International Meeting for Applied Geoscience & Energy, Houston, Texas, USA, August 2022.
Paper Number:
SEG-2022-3725837
Published:
November 01 2022
Citation
Fernandez, Alfredo, Marson, Jake, Savajol, Vianney, and Christi Gell. "Benefits of semi-automatic seismic interpretation workflow for fast-paced decision-making environments: A U.S. onshore case study." Paper presented at the SEG/AAPG International Meeting for Applied Geoscience & Energy, Houston, Texas, USA, August 2022. doi: https://doi.org/10.1190/image2022-3725837.1
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