Seismic Attributes as the Framework for Data Integration throughout the Oilfield Life Cycle

2018 Distinguished Instructor Short Course

Kurt J. Marfurt

University of Oklahoma
Norman, Oklahoma USA


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Course Duration

One day

Intended Audience

  • Seismic interpreters who want to extract more information from their data.
  • Seismic processors and imagers who want to learn how their efforts impact subtle stratigraphic and fracture plays.
  • Sedimentologists, stratigraphers, and structural geologists who use large 3D seismic volumes to interpret their plays within a regional, basin-wide context.
  • Reservoir engineers whose work is based on detailed 3D reservoir models and whose data are used to calibrate indirect measures of reservoir permeability.
  • Team leaders who wish to identify advances in machine learning technology that promise improved efficiency and accuracy in the integration of large data volumes.

Prerequisites (Knowledge/Experience/Education Required)

Participants should have a basic understanding of sedimentology and structural geology and familiarity, but not necessarily expertise in 3D seismic interpretation. The accompanying textbook will include mathematical details of volumetric attribute calculation, image processing, and machine learning algorithms. The lecture will focus on fundamental assumptions, algorithm application, and analysis of the results.

Course Outline

  • Introduction
  • Seismic attributes and what they measure
  • Post-migration data conditioning and image enhancement
  • The exploration stage of the oil field life cycle
  • The development stage of the oil field life cycle
  • The mature stage of the oil field life cycle
  • The rebirth stage of the oil field life cycle
  • Data integration and a profile of the future interpreter

Learner Outcomes

After completing this short course, the participant should be able to

  • use attributes to quantify geometric, dynamic, kinematic, statistical, and geomechanical properties of the 3D seismic data volume,
  • use 3D visualization and multiattribute crossplots to interactively enhance and isolate geologic features that otherwise might be overlooked,
  • use concepts of geomorphology, diagenesis, and tectonic deformation to integrate seismic and well-log data within an appropriate geologic framework,
  • use classical statistics and modern machine learning to establish correlations between 3D seismic data, rock properties, and engineering data that then can be employed to predict future rates of penetration, well-completion success, and well-fluid production, and
  • use seismic attributes computed from 3D seismic data as the framework for data integration throughout the lifespan of the oil field.



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 8 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). In addition to teaching and research duties at OU, Marfurt leads short courses on attributes for the SEG and AAPG, and currently serves as Editor in Chief of the AAPG/SEG Journal Interpretation.


Date Location Host
14 February Calgary, Canada CSEG
11 April Midland, TX USA Permian Basin Geophysical Society
26 April Houston, Texas GSH
25 May Dallas, Texas Dallas Geophysical Society
1 June Munich, Germany GeoNeurale
4 June Leoben, Austria Montanuniversitaet Leoban
7 June Milan, Italy ENI, SEG Italian section
15 June Copenhagen, Denmark SEG/EAGE
19 June Stavanger, Norway Schlumberger
11 July Perth, Australia ASEG
16 July Adelaide, Australia ASEG
18 July Melbourne, Australia ASEG
25 July Brisbane, Australia ASEG
9 August Buenos Aires, Argentina AAGGP
14 August Rio de Janeiro, Brazil SBGf
3 September Tokyo, Japan SEG Japan
6 September Qingdao, China China University of Petroleum (East China)
11-12 September Beijing, China BGP
18 September Seoul, South Korea KSEG
11 October Pittsburgh, PA USA AAPG- SPE 
18 October Anaheim, CA, USA SEG Annual Meeting
24 October Bogota, Colombia ACGGP
26 October St. Augustine, Trinidad and Tobago University of the West Indies
4 November Muscat, Oman Petroleum Development Oman
6 November Dhahran, Saudi Arabia Dhahran Geoscience Society (DGS)
8 November Ahmadi, Kuwait Kuwait Oil Company
12 November Kuala Lumpur, Malaysia Petronas

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