MAY 2016 LUNCHEON MEETING
Patricia A. Santogrossi
of Geophysical Insights
presents
Sub-seismic Resolution of the Stratigraphy and Facies Architecture in the Eagle Ford Group Enabled by Simultaneous Multi-Attribute Analysis
11:30 AM Wednesday, May 18, 2016
at the Cascades
4511 Briarwood Road
Tyler, TX 75709
BIOGRAPHY
Patricia Santogrossi is a geoscientist who has enjoyed 40 years in the oil business. She is currently a Consultant to Geophysical Insights, a Tom Smith company that develops and implements their Paradise software. Formerly she was a Leading Reservoir Geoscientist and Non-operated Projects Manager with Statoil USA E & P and was engaged for nearly nine years in Gulf of Mexico business development, corporate integration, prospect maturation, and multiple appraisal projects.
Patricia has previously worked with domestic and international Shell Companies, Marathon Oil Company, and Arco/Vastar Resources in research, exploration, leasehold and field appraisal as well as staff development. Subsequently, Patricia became Chief Geologist for Chroma Energy, who possessed proprietary 3D voxel visualization technology, and for Knowledge Reservoir, a reservoir characterization and simulation firm that specialized in Deepwater project evaluations.
A longtime member of SEPM, AAPG, GCSSEPM, HGS and SEG, Patricia has assumed various elective and appointed positions. She is currently in service to AAPG as the Chair of the House of Delegates’ Nominations and Elections Committee and is near the end of her third term as a representative to the AAPG House of Delegates from HGS.
Patricia was born, raised, and educated in Illinois before she headed to Texas to work for Shell after she received her MS in Geology from the University of Illinois, Champaign-Urbana. Her other ‘foreign assignments’ have included New Orleans and London. She resides in Houston with her husband of twenty-four years, Joe Delasko.
ABSTRACT
Sub-seismic Resolution of the Stratigraphy and Facies Architecture in the Eagle Ford Group Enabled by Simultaneous Multi-Attribute Analysis
Patricia A. Santogrossi
Geophysical Insights
These days many unconventional plays are being challenged by the low commodity price. During market downturns, many operators look for ways to “squeeze” more information out of their seismic and well control data to reduce risk of a dry hole or a poorly performing well.
Paradise is a triple threat. First, we employ Principal Component Analysis (PCA) to identify and quantify the key attributes of any given class that are the most independent and characteristic in the data set. Usually a dozen or fewer attributes rise to the top and can be included in a Self-Organizing Map (SOM) wherein the learning machine classifies the data by neurons which may reveal natural clusters, form discernable geobodies, and enable specific calibrations or correlations. The third weapon in the arsenal is an interactive 2D ColorMap that can be queried and inverted to “extract” the natural clusters or geobodies from the “forest”.
The conclusions to date in this study allow simple distinction of all of the members of the Eagle Ford (EF): Basal Clay-rich shale, Top EF Ash beds, and the Upper EF (marl). The Eagle Ford Shale target facies previously characterized as High Resistivity and Low Resistivity can now be shown to be comprised and updip, progradational calcite enriched (red) geobody that contains both high and low resistivity pay zones and a downdip, onlapping quartz and clay enriched (gold) facies that also contains both high and low resistivity pay zones. These non-layer-cake zones include one or more previously unrecognized and possibly underdeveloped sweet spots (or geobodies) and can be shown to be offset by numerous, sometimes compression, faults. Spectral Decomposition SOMs show karsts in the overlying Austin Chalk, disconformities with the Eagle Ford, and fine details in the underlying Buda.
These methods can be shown to enable an interpreter to prognose and calibrate wells better, to enhance an engineer’s precision in geo-steering, and to improve one’s confidence in leasehold evaluation.