Improvements in imaging faults and flexures - multispectral coherence and aberancy
Kurt J. Marfurt, Xuan Qi, and Fangyu Li
The University of Oklahoma
One of the key takes of a seismic interpreter is to map lateral changes in surfaces, including not only faults, folds, and flexures, but also incisements, diapirism, and dissolution features. Volumetrically, coherence provides rapid visualization of faults while curvature provides rapid visualization of folds and flexures.
In general, one wishes to interpret the most broadband data possible. However, because of the thickness tuning effects, certain spectral components often better illuminate a given feature with higher signal-to-noise ratio than others. Clear images of channels and other stratigraphic features that may be buried in the broad-band data may “light up” at certain spectral components. For the same, coherence attributes computed from spectral voice components (equivalent to a filter bank) also often provide sharper images, with the “best” component being a function of tuning thickness and reflector alignment across faults. While one can co-render three coherence images using RGB blending, display of the information contained in more than three volumes in a single image is difficult. We address this problem by summing a suite of structure-oriented covariance matrices computed from spectral voices resulting in a “multi-spectral” coherence algorithm.
Aberrancy measures the lateral change (or gradient) of curvature along a picked or inferred surface. Aberrancy is complementary to curvature and coherence. In normally faulted terrains, the aberrancy anomaly will track the coherence anomaly and fall between the most-positive curvature anomalies defining the footwall and the most-negative curvature anomalies defining the hanging wall. Aberrancy can delineate faults whose throw falls below seismic resolution, or is distributed across a suite of smallr conjugate faults, which do not exhibit a coherence anomaly. Previously limited to horizon computations, we extend aberrancy to uninterpreted seismic data volumes.
To demonstrate the “uplift” of these new algorithms over more well-established workflows, we apply our volumetric aberrancy calculation to a megamerge data volume acquired over the Oklahoma STACK play and to a more modern survey acquired over the Barnett Shale gas reservoir of the Fort Worth Basin, Texas. Multispectral coherence provides images that are both sharper and less noisy than conventional coherence computed from the broadband data, while also illuminating Red Fork channel edges that were previously not seen. Aberrancy delineates small karst features, which are in many places too smoothly varying to be detected by coherence. Equally important, aberrancy provides the azimuthal orientation of the flexure anomalies allowing them to be processed to be evaluated as potential fracture sets.
Kurt J. Marfurt joined The University of Oklahoma in 2007 where he serves as the Frank and Henrietta Schultz Professor of Geophysics within the ConocoPhillips School of Geology and Geophysics. Marfurt’s primary research interest is in the development and calibration of new seismic attributes to aid in seismic processing, seismic interpretation, and reservoir characterization. Recent work has focused on applying coherence, spectral decomposition, structure-oriented filtering, and volumetric curvature to mapping fractures and karst with a particular focus on resource plays. Marfurt earned a Ph.D. in applied geophysics at Columbia University’s Henry Krumb School of Mines in New York in 1978 where he also taught as an Assistant Professor for four years. He worked 18 years in a wide range of research projects at Amoco’s Tulsa Research Center after which he joined the University of Houston for eight years as a Professor of Geophysics and the Director of the Allied Geophysics Lab. He has received the SEG best paper (for coherence), SEG best presentation (for seismic modeling), as a coauthor with Satinder Chopra best SEG poster (one on curvature, one on principal component analysis) and best AAPG technical presentation, and as a coauthor with Roderick Perez Altimar, SEG/AAPG Interpretation best paper (on brittleness) awards. Marfurt also served as the EAGE/SEG Distinguished Short Course Instructor for 2006 (on seismic attributes). He will go on tour again in 2018 for the SEG, presenting a one-day course on “Seismic attributes as the framework for data integration throughout the oil field lifespan”. In addition to teaching and research duties at OU, leading short courses on attributes for the SEG and AAPG, Marfurt currently serves as Editor in Chief of the AAPG/SEG Journal Interpretation.