*Seismic Interpretation: ‘Computers Can’t Replace Geologists’ *
AAPG Explorer Issue March 2016
By *David Brown *

Computers have taken on more and more of the load in seismic interpretation.

But advances in computational seismology and the use of seismic attributes
won’t remove the geologist from the equation.

“Our task is to help the geologists do their interpretation,” said Sergey
Fomel. “We cannot always replace geological insight with what we extract
from the data.”

Fomel has a joint appointment at the University of Texas at Austin.

As a member of the faculty, he serves as Wallace E. Pratt professor of
geophysics in the university’s Jackson School of Geosciences.

He’s also a researcher in the school’s Bureau of Economic Geology (BEG) for
the Texas Consortium for Computational Seismology, a joint initiative of
BEG and the UT Center for Numerical Analysis at the Institute for
Computational Engineering and Science.

In the latter role, he sees the latest trends in computer-assisted seismic
interpretation and use of seismic attributes.
Current Trends Aren’t Necessarily New Trends

Not that he thinks all the trends are cutting-edge.

Some of those developments “are, in my opinion, not new developments,” he
said.

Progress sometimes involves perfecting approaches that were developed in
the past. Still, new advances in computer-assisted interpretation have
taken place in just the most recent two years.

Fomel sees these as some of the current trends:

   - Automating Seismic Interpretation: The interpretation process
   “typically involves a lot of manual activity, which is sometimes important
   activity because it requires geological insight. But it also can be
   tedious,” Fomel noted.
   - Advances in Picking Horizons and Identifying Features: “There are some
   new exciting algorithms where we can pick more than a human interpreter
   possibly could,” he said.
   - Better Implementation of Concepts: “Some of those involve highlighting
   discontinuities and measuring curvatures in the seismic horizon,” he said.

A Wide Umbrella

Fomel earned his doctorate in geophysics from Stanford University after
working at the Russian Institute of Geophysics and the Lawrence Berkeley
National Laboratory.

He received the J. Clarence Karcher Award from the Society of Exploration
Geophysicists in 2001 and the Conrad Schlumberger Award from the European
Association of Geoscientists and Engineers in 2011.

A quick review of the titles of some recent papers co-authored by Fomel
shows the wide-ranging nature of today’s research in computational
seismology and seismic attributes:

   - “Viscoacoustic modeling and imaging using low-rank approximation.”
   - “Seislet-based morphological component analysis using scale-dependent
   exponential shrinkage.”
   - “Random noise attenuation using local signal-and-noise
   orthogonalization.”
   - “A fast algorithm for 3-D azimuthally anisotropic velocity scan.”
   - “A robust approach to time-to-depth conversion and interval velocity
   estimation from time migration in the presence of lateral velocity
   variations.”
   - “Source-receiver two-way wave extrapolation for pre-stack
   exploding-reflector modeling and migration.”

Computational seismology adds the computer as a tool to assist
geoscientists who analyze and interpret seismic data. “We deal with
computation of various types. Traditionally in seismic, more of the
resources are spent on imaging,” Fomel said. “The other side of it is doing
seismic data analysis as it relates to interpretation.”

Current research challenges cited by the computing consortium include
estimating seismic velocities by using full waveform information,
identifying most-accurate and most-efficient imaging algorithms while
controlling the trade-off between accuracy and efficiency, and assisting
the seismic interpreter by automating common interpretation tasks.

Automating manual tasks is an especially meaningful problem, but it can be
a tricky one, according to Fomel. He said hand-work in seismic
interpretation can be so repetitive it becomes a health hazard.
The Human Factor

At the same time, hands-on interpretation allows geoscientists to bring
personal knowledge and experience to the task.

“We need to bridge the gap between manual interpretation, which brings in
the geological insight and computational seismology,” he said.

Fomel cited the example of 3-D seismic interpretation of salt bodies in the
Gulf of Mexico.

Computer programs and inexperienced interpreters faced with a choice can
easily pick a false bottom for salt, but geoscientists who have worked in
the Gulf will more often make the correct choice.

“They can tell from their experience which is more likely,” he said.

Another challenge for computer-assisted interpretation is combining seismic
data with information from well logs and other sources. That’s a
decades-old issue, but new developments in exploration and production make
it a timely problem, Fomel observed.

“It is especially true today because the scale that’s of interest in
unconventional resources and nonconventional reservoirs is smaller than
what we can detect in usual seismic,” he said.

Seismic interpreters use computers to help identify subtle features,
another important area of study. Fomel has conducted research into what he
calls “predictive painting,” or using a numerical algorithm for automatic
spreading of information in 3-D seismic volumes according to the local
structure of seismic events.

“In time-frequency analysis we also are developing new methods. This is
important, again, in recognizing subtle features,” he said.

Seismic attributes are extracted or derived from seismic data and commonly
used to enhance understanding, for a better geological or geophysical
interpretation. The most commonly used attribute is seismic amplitude.

Advances in identifying, quantifying and utilizing seismic attributes
continue, Fomel said, but the industry’s uptake of new developments can be
slow.

“A lot of interpreters still have some mistrust of attributes, so they
don’t understand how attributes can help them,” he noted.

Seismic imaging no doubt continues to receive the biggest share of
investment in seismic computing. But Fomel has noticed an increasing
interest in computational seismology, in tools for seismic data analysis.

“We see more companies putting money into computational tools,” he said. “I
see it as a new trend, but some companies are doing it.”
Salam,

Muhammad Arifai

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