Upcoming Events

Upcoming events

Oklahoma History Center

Events

Upcoming events

    • 27 Jan 2020
    • 11:30 AM - 1:00 PM
    • Oklahoma History Center, 800 Nazih Zuhdi Dr., Oklahoma City, OK 73105
    Register

    Machine Learning Applied to 3D Seismic Data from the Denver-Julesburg Basin Improves Stratigraphic Resolution in the Niobrara

    Carolan (Carrie) Laudon, Sarah Stanley and Patricia Santogrossi

    Geophysical Insights


    Abstract

    Seismic attributes can be both powerful and challenging to incorporate into interpretation and analysis. Recent developments with machine learning have added new capabilities to multi-attribute seismic analysis. In 2018, Geophysical Insights initiated a proof of concept on 100 square miles of multi-client 3D data jointly owned by Geophysical Pursuit, Inc. (GPI) and Fairfield Geotechnologies (FFG) in the Denver-Julesburg Basin (DJ).  The purpose of the study was to evaluate the effectiveness of a machine learning workflow to improve resolution within the reservoir intervals of the Niobrara and Codell formations, the primary targets for development in this portion of the basin.

    The seismic data are from Phase 5 of the GPI/Fairfield Niobrara program in northern Colorado. A preliminary workflow which included synthetics, horizon picking and correlation of 28 wells was completed. Detailed well time-depth charts were created for the Top Niobrara, Niobrara A, B and C benches, Fort Hays and Codell intervals. The interpretations, along with the seismic volume, were loaded into the Paradise® machine learning application, and two suites of attributes were generated, instantaneous and geometric.

    The machine learning workflow first applies Principal Component Analysis (PCA) in order to identify which attributes contribute to the data and what their relative contributions are. PCA aids in the selection of which attributes are appropriate to use in a Self-Organizing Map (SOM). In this case, 15 instantaneous attribute volumes, plus the parent amplitude volume, were used in the PCA and eight were selected to use in SOMs. The SOM is a neural network-based machine learning process that is applied to multiple attribute volumes simultaneously. The SOM produces a non-linear classification of the data in a designated time or depth window. For this study, a 60-ms interval that encompasses the Niobrara and Codell formations was evaluated using several SOM topologies. An 8 X 8 SOM applied to 1 ms seismic data improves the stratigraphic resolution within the target interval. The neuron classification also images small but significant structural variations within the chalk benches. These variations correlate visually with the geometric curvature attributes. This improved resolution allows for precise well planning for horizontals wells. The 17 to 25 foot thick Codell is also seismically resolved via SOM analysis and shows variation with the study area that can be tied to porosity. Petrophysical analyses from wireline logs run in seven wells within the survey by Digital Formation; together with additional results from SOMs show the capability to differentiate a high TOC upper unit within the A marl which presents an additional exploration target.

    The results show that a multi-attribute machine learning workflow adds value to the 3D seismic datasets available in the basin by yielding resolution to 1 ms within the Niobrara and Codell.

    Biography

    Carolan (Carrie) Laudon holds a PhD in geophysics from the University of Minnesota and a BS in geology from the University of Wisconsin Eau Claire. She has worked as a Senior Geophysical Consultant with Geophysical Insights since 2017 working with Paradise®, their machine learning platform.  Prior roles include Vice President of Consulting Services and Microseismic Technology for Global Geophysical Services and 17 years with Schlumberger in technical, management and sales starting in Alaska and including Aberdeen, Scotland, Houston, TX, Denver, CO and Reading, England.  She also spent her first five years out of graduate school with ARCO Alaska, Anchorage in the exploration team as a seismic interpreter.

    • 24 Feb 2020
    • 11:30 AM - 1:00 PM
    • Oklahoma History Center, 800 Nazih Zuhdi Dr., Oklahoma City, OK 73105

    More details TBD


    • 24 Mar 2020
    • 11:30 AM - 7:00 PM
    • Oklahoma History Center, 800 Nazih Zuhdi Dr., Oklahoma City, OK 73105

    Details TBD

    • 20 Apr 2020
    • 11:30 AM - 1:00 PM
    • Oklahoma History Center, 800 Nazih Zuhdi Dr., Oklahoma City, OK 73105

    Factors in the Seismic Method that Distort Determination of Poisson's Ratio

    Mark S. Egan

    Consulting Geophysicist


    Abstract

    Perhaps a more descriptive title for this presentation would have been, “Why is it that even when the seismic data we have are of good quality, Poisson’s ratio values derived from those data don’t necessarily tie the wells?”. This was a question that was poised to me a few years ago by a major oil company. It was of serious concern in a high-profile, onshore field. I gave some opinions, and I did some limited analyses at that time.

    Over the last few years I made a more concerted effort to investigate this. The causes I focused on were not the usual topics of noise, anisotropy, and imaging. Those already received much of the industry’s attention. Instead, I looked at the pitfalls of linear inversion, as well as pitfalls of ignoring the effects of “surface angle projections”. These latter effects refer to the angles at which seismic energy enters the earth at the source, and the angles at which the energy emerges at the receivers.

    The methodology that was followed was to generate seismic gathers for 50 earth models that were constructed using well logs from all over the world. The true-amplitude gathers as well as the corresponding gathers that were perturbed by the angle effects alluded above were then inverted with linear and nonlinear inversion routines. The values of Poisson’s ratios that were then derived from the inverted results were compared with the true values. Successes and failures were then analyzed to determine the reasons why Poisson’s ratios are correctly computed in some seismic surveys, while not in others.

    The findings will be discussed in the presentation. They impact everything from survey design to final inversion.

    Biography

    Mark Egan is a consulting geophysicist. He worked for Schlumberger and its heritage companies from 1975 to 2016, at which time he retired. Egan’s last position at Schlumberger was as global chief area geophysicist in the Land Unconventionals Group within the WesternGeco segment. His previous postings included chief geophysicist positions in North America, Saudi Arabia, Dubai, and London.

    Egan holds a PhD degree in geophysics, an MS degree in acoustics, and a BS degree in physics and mathematics. He is a member of the SEG, the EAGE, the SPE, and various local societies. For several years, Egan has additionally been a member of the Editorial Committee for the Journal of Petroleum Technology – a publication of the SPE. He can be reached at [email protected]

    • 18 May 2020
    • 5:30 PM - 9:00 PM
    • Oklahoma History Center, 800 Nazih Zuhdi Dr., Oklahoma City, OK 73105

    GSOC Annual Spouse Night and Awards


    Details TBD

Past events

16 Dec 2019 2019 GSOC Holiday Party
18 Nov 2019 2019 SEG Distinguished Lecturer: Heloise Lynn
22 Oct 2019 2019 GSOC Annual Golf Tournament
21 Oct 2019 2019 October Luncheon
23 Sep 2019 2019 September Luncheon: Bryan DeVault
12 Jun 2019 GSOC Annual Spouse Night and Awards
15 Apr 2019 April Luncheon
26 Mar 2019 Continuing Education and Shrimp Boil
25 Feb 2019 February Luncheon
28 Jan 2019 January Luncheon: Dr. Jyoti Behura
17 Dec 2018 GSOC Holiday Party
26 Nov 2018 November Technical Luncheon
22 Oct 2018 October Luncheon
18 Sep 2018 2018 GSOC Annual Golf Tournament
17 Sep 2018 SEG Honorary Lecture - September Luncheon
21 May 2018 2018 Annual Spouse and Awards Night
16 Apr 2018 April Technical Luncheon
20 Mar 2018 2018 Continuing Education and Shrimp Boil
26 Feb 2018 February Technical Luncheon
22 Jan 2018 January Technical Luncheon
18 Dec 2017 2017 Holiday Party
06 Nov 2017 SEG Honorary Lecturer Mirko van der Baan
24 Oct 2017 2017 GSOC Annual Golf Tournament
23 Oct 2017 October luncheon
18 Sep 2017 September luncheon: Dr. Mark Mack Sigma3
22 May 2017 2017 Annual Spouse and Awards Night
24 Apr 2017 April Seminar and Luncheon
21 Mar 2017 2017 Continuing Education and Shrimp Boil
27 Feb 2017 February Seminar and Luncheon
23 Jan 2017 January Seminar and Luncheon
15 Dec 2016 2016 Holiday Party
24 Oct 2016 October Seminar and Luncheon
13 Sep 2016 2016 GSOC Annual Golf Tournament
12 Sep 2016 September Seminar and Luncheon
23 May 2016 Annual Spouse and Awards Night
09 May 2016 Continuing Education and Shrimp Boil
11 Apr 2016 SEG Distinguished Lecturer Joe Dellinger
28 Mar 2016 March Seminar and Luncheon
22 Feb 2016 February Seminar: PSDM Case Study, Dr. Morgan Brown
25 Jan 2016 GSOC Seminar and Lunch Featuring Bob Hardage
14 Dec 2015 Holiday Party
16 Nov 2015 GSOC November Luncheon. Clint Barefoot, Eagleford Case Study
26 Oct 2015 GSOC October Luncheon. Paul Constance, Multicomponent Surface Seismic and VSP for Reservoir Characterization of the Mississippian
15 Sep 2015 GSOC Annual Golf Tournament
14 Sep 2015 GSOC September Luncheon. SEG Honorary Lecturer, Dan Whitmore
19 May 2015 Spouse and Awards Night
28 Apr 2015 Continuing Education and Shrimp Boil
16 Apr 2015 SEG Distinguished Lecturer Dr. Jean Virieux
23 Mar 2015 March Technical Seminar and Luncheon
01 Jun 1990 1990 Annual Meeting

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Geophysical Society of Oklahoma City is a 501(c)3 non-profit organization. 

P.O. Box 1032  Oklahoma City, OK 73101

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