POSTPONED - HGS General Lunch - Thin Bed Resolution of the Stratigraphy & Architecture of the Eagle Ford Group
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Wednesday, May 27, 2020
The Petroleum Club of Houston
1201 Louisiana Street, 35th floor, Houston, TX
- If you valet park we can give you a discount coupon, the Petroleum Club does NOT validate parking
Social 11:15 AM, Luncheon 11:30 AM- 1:00 PM
Cost: $35 pre-registered members; $40 for non-members/ALL walk-ups;
$35 for Emeritus/Life/Honorary; $15 for HGS student members if pre-registered and pre-paid.
To guarantee a seat, you must pre-register on the HGS website and pre-pay with a credit card. You may walk up and pay at the door if extra seats are available. Please cancel by phone or email within 24 hours before the event for a refund. Online & pre-registration closes Wednesday, May 27 at 5:00 AM
Speaker: Patricia Santogrossi
Company: Geophysical Insights
Patricia Santogrossi is a geoscientist who has enjoyed nearly 45 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 multi-attribute visualization technology, and for Knowledge Reservoir, a reservoir characterization and simulation firm that specialized in Deepwater project evaluations.
A longtime member of SEPM (Emeritus), AAPG (Emeritus), GCSSEPM (Lifetime), HGS (Emeritus), and SEG, Patricia has assumed various elective and appointed positions. She has recently stepped down after her fourth three-year term as a representative to the AAPG House of Delegates from HGS. In addition, she sits by invitation on the University of Illinois’ Department of Geology Alumni Board.
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-eight years, Joe Delasko.
Thin Bed Resolution of the Stratigraphy & Architecture of the Eagle Ford Group
Many unconventional plays are challenged by low commodity price. During market downturns, operators must work with limited budgets. Companies look for ways to “squeeze” more information from seismic and well control data to reduce the risk of a dry hole or a poorly performing well. Methods that produce detailed reservoir characterization such as those applied herein are required so that Eagle Ford’s and other shale plays’ operators can account for changing stratigraphy and facies to properly place horizontal wells and plan optimum perforation intervals. To accurately understand the geologic distribution of key facies requires resolution on 3D seismic data from machine learning multi-attribute analysis techniques used and described here.
Principal Component Analysis (PCA) is used to identify and quantify the key seismic attributes of any given class that are the most independent and prominent in the data set. Usually ten or fewer seismic attributes are selected and are included in the a Self-Organizing Map (SOM). The latter is a machine learning classification process wherein “winning neurons”, that is Neural Classes that have sorted seismic samples, reveal natural clusters, form discernable systems tracts, and enable specific calibrations or visual correlations. In this application, the seismic data quality was unusually high; known pitfalls of coherent noise such as the presence of multiples or acquisition footprints were not detected. A third weapon in the arsenal is an interactive 2D Color Map that can be queried and inverted to “extract” the natural clusters or facies tracts from the “forest” of 3D data.
Eagle Ford stratigraphy is often associated with thin beds and facies well below conventional seismic resolution that change both vertically and laterally. Over this seismic survey area, the extent of which is 15 miles in the dip direction and 14.5 miles in the strike direction (216 sq. mi.), an optimal group of simultaneous instantaneous attributes were used to identify 16 different Neural Classes that represent the various facies present in the Eagle Ford shale over a 14-29ms window (66-161 ft.) in a single trough to peak half cycle.
The value of new tools such as seismic data volume sculpting and geobody extraction and quantification will also be demonstrated from the Eagle Ford shale complex. Analyses of Spectral Decomposition-based classifications show karsts in the overlying Austin Chalk, disconformities between the Austin Chalk and the Eagle Ford and within the Eagle Ford Group, as well as rapid facies changes and fine details in the underlying Buda.
The facies architecture of the entire Eagle Ford Group (Fairbanks et al., 2016), which includes the underlying Basal Clay shale, Eagle Ford shale, and the overlying Eagle Ford marl, are defined by 26 different winning neurons over 24-39ms (128-242 ft). Individual facies units as thin as one sample interval of 2ms (10-12 ft.) can be resolved and are calibrated in nine vertical wells by time depth corrections that were carefully computed and then applied to formation tops and edited log curves. Well data were further calibrated by ties to the facies tracts of a classification result set. The careful analysis of X-ray diffraction (XRD) and saturation information from five cores, whose variations were found to be both systematic and compelling, were incorporated in corroboration of the SOM results.
The Eagle Ford shale target facies, which were previously characterized as simply High Resistivity or Low Resistivity, can now be shown to be comprised updip of two lower High Resistivity progradational carbonate regressions overlain by two Low Resistivity aggraded ashy beds. Downdip four onlapping laminated clastic and carbonate facies also contain two basal High Resistivity and two overlying Low Resistivity pay zones. These downdip, non-layer-cake zones encapsulate one or more previously unrecognized, and possibly underdeveloped, “sweet spots” that can be shown to be offset by numerous, sometimes compressional, faults.
In Part II, the value of new tools such as seismic data volume sculpting and geobody extraction and quantification are demonstrated from the Eagle Ford shale complex. Also, analyses of Spectral Decomposition-based classifications show karsts in the overlying Austin Chalk, disconformities between the Austin Chalk and the Eagle Ford and within the Eagle Ford Group, and rapid facies changes and fine details in the underlying Buda.
In summary, the findings of this study are that stratigraphy – genetic units and facies tracts – can be mapped more precisely; previously unresolved non-reservoir can be readily distinguished from high-quality reservoir; drilling outcomes can be prognosed and calibrated more exactly; and results provide important information to geosteer dynamically. There is no doubt that these methods allow an operator to evaluate their leasehold and scout for new opportunities with more confidence.
1201 Louisiana St
|Emeritus/Honorary Life||$ 35.00|
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