3D Seismic Attributes for Prospect Identification and Reservoir Characterization (5-day)
Kurt J. Marfurt
Professor of Geophysics
The University of Oklahoma
Abstract
A seismic attribute is any measure of seismic data that helps us better visualize or
quantify features of interpretation interest. Seismic attributes fall into two broad categories
– those that help us quantify the morphological component of seismic data and those that
help us quantify the reflectivity component of seismic data. The morphological attributes
help us extract information on reflector dip, azimuth, and terminations, which can in turn be
related to faults, channels, fractures, diapirs, and carbonate buildups. The reflectivity
attributes help us extract information on reflector amplitude, waveform, and variation with
illumination angle, which can in turn be related to lithology, reservoir thickness, and the
presence of hydrocarbons.
In the reconnaissance mode, 3D seismic attributes help us to rapidly identify
structural features and depositional environments. In the reservoir characterization mode,
3D seismic attributes are calibrated against real and simulated well data to identify
hydrocarbon accumulations and reservoir compartmentalization.
In this course, we will gain an intuitive understanding of the kinds of seismic features
that can be identified by 3D seismic attributes, the sensitivity of seismic attributes to seismic
acquisition and processing, and of how ‘independent’ seismic attributes can are coupled
through geology. We will also discuss alternative workflows using seismic attributes for
reservoir characterization as implemented by modern commercial software and practiced by
interpretation service companies. Participants are invited to bring case studies from their
workplace that demonstrate either the success or failure of seismic attributes to stimulate
class discussion.
Course Outline
Module name
Introduction
Topics addressed
An overview of how seismic attributes fit within modern interpretation
workflows.
Complex trace,
horizon, and
formation
attributes
Theory, definition, and limitations of attribute based on the analytic (or
complex trace) such as envelope and instantaneous frequency. Definition and
use of attributes computed from a horizon, such as dip magnitude and
horizon-based curvature as well as formation attributes computed between
horizons, such as RMS amplitude and thickness.
Multiattribute
display
Definition and interrelationship between RGB, CMY, and HLS color models.
Best practices for multiattribute display. Definition and use of horizon slices,
phantom horizon slices, stratal slices, and Wheeler slices.
Spectral
decomposition
Theory, workflows, and advantages of the three most commonly used
spectral decomposition algorithms (DFT, CWT, and matching pursuit). Their
use not only in mapping "tuned" lithologies but also as input to bandwidth
extension, Q estimation, and phase discontinuity mapping of unconformities.
Geometric
attributes
A summary of volumetric dip/azimuth, coherence, Sobel filter, amplitude and
structural curvature, reflector shapes, reflector rotation, reflector
convergence, and GLCM texture attributes.
Attribute
expression of
tectonic
deformation
Attribute expression of faulting and folding as seen on post stack volumes by
coherence, curvature, and reflector rotation.
Attribute
expression of clastic
depositional
environments
Attribute expression of fluvial/deltaic and deepwater systems as seen on post
stack volumes by spectral decomposition, coherence, curvature, and refector
convergence attributes. Attribute expression of differential compaction.
Attribute
expression of
carbonate
deposition
environments
Attribute
expression of
shallow
stratigraphy and
drilling hazards
Attribute
expression of
igneous extrusive
and intrusive rocks
Impact of
acquisition and
processing on
seismic attributes
Attribute expression of carbonate buildups and diagenesis as seen on post
stack volumes by coherence, curvature, and texture attributes. Attribute
expression of karst terrains.
Attribute expression of mass transport complexes, glide tracks, outrunner
blocks, pock marks, glacial keel marks,and shale "dewatering" (syneresis)
features, many of which when gas- or water-charged may become drilling
hazards.
Attribute expression of volcanic mounds, sills, fractured basement, and
lacoliths which can serve as or give rise to reservoirs. Impact of overlying
igneous rocks on seismic data quality.
Value of long-offset, wide-azimuth, and dense seismic surveys in seismic data
quality and attribute analysis.
Poststack seismic
data conditioning
Spectral balancing, structure-oriented filtering and footprint suppression of
poststack data volumes.
Prestack seismic
data conditioning
Prestack structure-oriented filtering, nonhyperbolic moveout, and correction
of NMO/migration stretch. Preconditioned least-squares migration and 5D
interpolation.
Attribute Prediction
of Fractures and
Stress
Use of curvature, impedance, and seismic anisotropy to map the orientation
and intensity of natural fractures and/or horizontal stress. Calibration with
lidar data and image logs.
Inversion for
acoustic and elastic
impedance
A hierarchal overview of inversion - emphasizing the assumptions and
interpreter input to each process.
Image
enhancement and
object detection
Algorithms that enhance faults and channels to generate computer "objects".
Lay-person's explanation of modren ant-tracking, skeletonization, and level
set algorithms that indicate the future of computer-assisted seismic
interpretation.
Interactive
multiattribute
analysis
Review of multiattribute display, crossplotting, and geobodies. Principal
component analysis.
Statistical
multiattribute
analysis
Fundamentals of geostatistics, including kriging, kriging with external drift,
colocated cokriging, sequential Gaussian simulation, and geostatistical
impedance inversion.
Unsupervised
multiattribute
classification
Clustering algorithms including k-means, self-organizing maps (e.g.
Stratimagic's "waveform classification") and generative topographic maps.
Supervised
multiattribute
classification
A simple overview and application of neural networks and support vector
machine algorithms.
Attributes and
hydraulic fracturing
of shale reservoirs
Review of the microseismic method and the relationship of microseismic
events to surface seismic measurements. The use of prestack impedance
inversion in predicting brittleness. Calibration using microseismic events and
production logs.
Attribute
applications to the
Mississippi Lime
Recent work in mapping the unconventional Mississippi Lime play in OK and
KS. Synthesizes previous sections on prestack impedance inversion,
curvature, texture analysis and Self-organizing maps.
Who should attend?
 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.
Advanced knowledge of seismic theory is not required; this course focuses on
understanding and practice.
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, structureoriented 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 SEG best paper (for coherence), SEG best presentation (for seismic
modeling) and as a coauthor with Satinder Chopra best SEG poster (for curvature) and best
AAPG technical presentation. 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.
Results of unsupervised multiattribute classification using generative topographic mapping, corendered with coherence, over a turbidite system, offshore New Zealand. Input attributes included
peak spectral frequency, peak spectral magnitude, curvedness, and GLCM entropy. (After Zhao et al.,
2015; data courtesy of New Zealand Petroleum Ministry).
N
Phantom horizon slices 20 ms above the top Viola limestone through amplitude
vs. azimuth (AVAz) anisotropy strike Ψ
modulated by its value B
. Mostazim
E
W
aniso
positive curvature is plotted against a gray scale and shows subtle faults. The
survey in the NW has been hydraulically fractured while that in the SE has not.
Note the compartmentalization of azimuth in the upper left survey, where
curvature acts as fracture barriers. Note the stronger anisotropy (brighter colors)
in the SE survey which had not yet been hydraulically fractured. (Image courtesy
of Shiguang Guo, OU).
S