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TagsReflection Seismology Attenuation Anisotropy Geology Physics & Mathematics
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Table of Contents
Anisotropy is not going away
Vladimir Grechka
Beware the interpretation-to-data trap
Evan Bianco
Calibrate your intuition
Taras Gerya
Don’t ignore seismic attenuation
Carl Reine
Don’t neglect your math
Brian Russell
Don’t rely on preconceived notions
Eric Andersen
Evolutionary understanding is the key to interpretation
Clare Bond
Explore the azimuths
David Gray
Five things I wish I’d known
Matt Hall
Geology comes first
Geophysics is all around
José M Carcione
How to assess a colourmap
Matteo Niccoli
Know your processing flow
Duncan Emsley
Learn to program
Leonardo was a geophysicist
Mind the quality gap
Pavlo Cholach
My geophysical toolbox, circa 1973
Dave Mackidd
No more innovation at a snail’s pace
Paul de Groot
Old physics for new images
One cannot live on geophysics alone
Marian Hanna
Pick the right key surfaces
Mihaela Ryer
Practise pair picking
Practise smart autotracking
Don Herron
Pre-stack is the way to go
Marc Sbar
Prove it
Publish or perish, industrial style
Sven Treitel
Recognize conceptual uncertainty and bias
Remember the bootstrap
Tooney Fink
Document Text Contents
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porosity, cementation, pore fluid, and lithology. They are not all independent or unique, so it is important to apply other
geologic constraints to make the problem tractable.
Your software should enable you to calculate the amplitude of zero offset (intercept) and the change in amplitude with
offset (gradient) on a target reflector. If there are measurable changes in intercept and gradient that can be related to
something of interest, then create an AVO class volume from the angle stacks and use it to scan the data for the
character change you desire. Use a program that links the class volume to the gathers, then inspect the gathers to verify
the anomaly. Does it make geologic sense if you map it? Are there other ways to explain this observation? This is where
experience in many different geologic settings is valuable.
Once the data quality has been verified and you have done some of the quick tests above, it makes sense to create pre-
stack inversion volumes to obtain a better measure of uncertainty. Rock property volumes can then be computed based
on relationships from the well data and rock property databases. These can more clearly define the lead, prospect, or area
for development and help you determine the volume and assess the risk of drilling. You’ll wonder why you ever drilled a well
without it.

Prove it
Matt Hall

How many times have you heard these?

The signal:noise is lower (or higher/improved/reduced)
It’s too thin to see (interpret/detect) on seismic
You can’t shoot seismic in the summer (winter/snow/wind)
More fold (bandwidth/signal:noise/data) is too expensive
That won’t (will/can/can’t) work
It looks geological (ungeological/right/wrong)

I say these sorts of things all the time. We all do. We feel like we’re bringing our judgment to bear, we’re exercising our
professional insight and experience. It’s part of the specialist advisor role, which many of us play, at least from time to
time. Sometimes, when time is short or consequences are slight, this is good enough and we can all move on to more
important things.
Often though, we do have some time, or the consequences are substantial, and we need a more considered approach. In
those situations, at least for most of us, it is not enough to trust our intuition. Our intuition is not a convincing enough
reason for a decision. Our intuition is unreliable (Hall 2010).
Science is reliable. So challenge your intuition with a simple task: prove it. The bed is sub-resolution? Prove it. More fold
costs too much? Prove it. This attribute is better than that? Prove it.
First, gather the evidence. Find data, draw pictures, make spreadsheets, talk to people. What were the acquisition
parameters? What actually happened? Who was there? Where are the reports? Very often, this exercise turns up
something that nobody knew, or that everyone had forgotten. You may even find new data.
Next, read up. Unless you’re working on the most conventional play in the oldest basin, there has almost certainly been
recent work on the matter. Check sources outside your usual scope — don’t forget sources like the Society of Petroleum
Engineers ( and the Society of Petrophysicists and Well Log Analysts (, for example. Talk to people,
especially people outside your organization: what do other companies do?
Then, model and test. If you’re measuring signal:noise, seismic resolution, or the critical angle, you’re in luck: there are
well-known methods and equations estimating those things. If you want to shoot cheaper data, or operate out of season,
or convince your chief that vibroseis is better than dynamite, you’ll have to get creative. But only experiments and models
— spreadsheets, computer programs, or even just mind-maps — can help you explore the solution space and really
understand the problem. You need to understand why shots cost more than receivers (if they do), why you can mobilize
in June but not July, and why those air-guns in the swamp were a waste of time and money. Modelling and testing take

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time, but the time is an investment. Most projects are multi-year, sometimes multi-decade, initiatives. The effort you
spend may change how you operate for many years. It’s almost always worth doing. If your boss disagrees, do it
anyway. You will amaze everyone later.
Finally, document everything. Better yet, do this as you go. But do wrap up and summarize. You aren’t just doing this
for the geoscientist picking up your project in five years, you’re also doing it for your future self. Since most interpretation
tools don’t have built-in documentation capabilities, you’ll have to find your own tools — look for ones that let you add links
and comments for a rich report you can easily share. Wikis are perfect.
At each step, either find or pretend to be the most skeptical person in the world. Ask the tough questions. Doubt
everything. Then prove it.

Hall, M (2010). The rational geoscientist. The Leading Edge 29 (5), 596 ff, DOI 10.1190/1.3422460

Publish or perish, industrial style
Sven Treitel
The old saw ‘publish or perish’ is often derogatively used to account for the flood of publications coming from certain
members of the academic community. A different, and less humorous, interpretation of this term applies, I believe, to
some of those doing industrial research in private corporations.
While academics are under ongoing pressure to publish to obtain promotions and research grants, industrial scientists often
face the opposite problem: they are discouraged from publication by management fearing that release of significant
technical know-how must invariably benefit the competition. This can happen when a manager, not sufficiently familiar with
the subject of a paper requested for release, finds that the simplest way out is to say no. It is true that such restrictions
are sometimes justified, but my experience over several decades in industrial R&D suggests that these concerns are
usually unfounded. My own professional experience has been with a major oil company, but I venture to guess that the
observations I make here are hardly unique to this industry.
What happens to a scientist working in this kind of an industrial environment? As the years roll by, he writes technical
reports, which are read by a few of his coworkers, but the research never faces the scrutiny of peers on the outside. A
successful scientist needs to interact with his professional colleagues through the vehicle of written as well as oral
publication: those who do not do this tend to become professionally ossified over time. Of course the employer loses as
well: an unmotivated and insular R&D staff is unlikely, even unable, to come up with cutting edge results.
There is an additional and equally nefarious consequence of a restrictive industrial publication policy: a scientist’s worth in
the job market is in large measure his publication record. Layoffs in industry have become an increasingly popular means
to cut costs under the unrelenting pressure from investors. R&D often seems to be an early item to go on the block, and
now the unknown, terminated industrial research scientist is left to fend for himself. He or she must compete with those
better-known in their field by virtue of their publication record, and thus faces an uncertain and increasingly grim
professional future. Clearly the best way for an industrial scientist to avoid falling into this trap is to make certain that the
prospective employer’s practices include a reasonably open publication policy.
From the employer’s viewpoint, a reasonable publication policy makes even more sense: a company staffed by aggressive
and creative scientists continuously interacting with their peers outside their own organization is much more likely to be
successful over time than one which is obsessively secretive. A scientist remaining in such a restrictive environment is
bound to perish professionally over time and lose marketability outside the company. As Matt Hall put it so aptly to me
when I proposed this essay to him: ‘It’s ironic that preparing yourself to be laid off would probably lead to you not being
laid off!’

Recognize conceptual uncertainty and bias
Clare Bond
How many different interpretations could be made of the same seismic image? This is a question that few interpreters
consider when faced with a seismic image to interpret. That’s because we try and match the image to something familiar
and hone in on those qualities of the image that are most similar to those we expect. When we determine the concept

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Brian Romans is a sedimentary geologist and assistant professor in the Department of Geosciences at Virginia Tech. He graduated from SUNY Buffalo with a geology degree in 1997 and then worked as a geotech
for small oil and gas companies in Buffalo, New York and Denver, Colorado for a few years. Brian received an MS in geology from Colorado School of Mines in 2003 and then headed to California where he earned a PhD in
geological and environmental sciences from Stanford University in 2008. He worked as a research geologist for Chevron Energy Technology from 2008 to 2011 before joining the faculty at Virginia Tech. Brian’s research on the
patterns and controls of clastic sedimentation during and since graduate school have resulted in numerous papers, which you can access at Brian is @clasticdetritus on Twitter and writes the blog Clastic
Detritus where he shares thoughts and photos about earth science.

The scale of a wavelet

Brian Russell started his career as an exploration geophysicist with Chevron in 1976, and worked for Chevron affiliates in both Calgary and Houston. He then worked for Teknica and Veritas in Calgary before co-
founding Hampson-Russell in 1987 with Dan Hampson. Hampson-Russell develops and markets seismic inversion software which is used by oil and gas companies throughout the world. Since 2002, Hampson-Russell has been a
fully owned subsidiary of Veritas and Brian is currently Vice President of Veritas Hampson-Russell. He is also an Adjunct Professor in the Department of Geology and Geophysics at the University of Calgary. Brian was
President of the CSEG in 1991, received the CSEG Meritorious Service Award in 1995, the CSEG medal in 1999, and CSEG Honorary Membership in 2001. He served as chair of The Leading Edge editorial board in 1995, technical
co-chair of the 1996 SEG annual meeting in Denver, and as President of SEG in 1998. In 1996, Brian and Dan Hampson were jointly awarded the SEG Enterprise Award, and in 2005 Brian received Life Membership from SEG. Brian
holds a BSc in geophysics from the University of Saskatchewan, an MSc in geophysics from Durham University, UK, and a PhD in geophysics from the University of Calgary. He is a registered Professional Geophysicist in

Don’t neglect your math
See the big picture

Sweat the small stuff

Mihaela Ryer has more than 17 years of experience in the oil and gas industry. She has worked for Marathon Oil, the ARIES Group, Prospectiuni (in Romania), and ConocoPhillips. Mihaela’s research interests have
been in the fields of seismic, sequence stratigraphy, depositional systems analysis and prediction. Most recently, she has employed a process-based approach to the prediction of lithofacies distribution and three-dimensional
architecture of clastic systems through time and space, by using data-constrained stratigraphic forward-modelling technologies and tools. She is @mihaela4021 on Twitter.

Pick the right key surfaces

Marc Sbar got his PhD in earthquake seismology from Columbia University in 1972, and enjoyed a research and teaching career at Lamont-Doherty Earth Observatory and the University of Arizona until 1983. He
then changed gears and spent 18 years as a geophysical specialist at BP, before moving to Phillips Petroleum in 2000, staying on at ConocoPhillips until 2009. Returning to academia, Marc recently moved to Tuscon, Arizona,
impressing the next generation of University of Arizona geoscientists with the wonders of geophysics.

Pre-stack is the way to go

Rob Simm is a seismic interpreter with a special interest in rock physics, AVO, and seismic inversion technologies. Rob’s early career (1985–1999) was spent with British independent oil and gas exploration
companies Britoil, Tricentrol, and Enterprise Oil, working in both exploration and production. An interest in applying rock physics in prospect generation and field development led him to set up his own consultancy, Rock Physics
Associates. His training course The Essentials of Rock Physics for Seismic Amplitude Interpretation is recognized worldwide. Rob is the author of numerous papers as well as co-author of 3-D Seismic Interpretation
(Cambridge University Press, 2007). Since May 2010, Rob has had a staff position as Senior Geophysical Advisor at Agora Oil and Gas, a North Sea exploration company.

Resolution on maps and sections
The unified AVO equation

Sven Treitel grew up in Argentina and was educated at MIT where he graduated with a PhD in geophysics in 1958, before enjoying a long career at Amoco. Sven has published over 40 papers and is the recipient
of numerous learned society awards, including the 1969 SEG Reginald Fessenden award, and in 1983 was awarded Honorary Membership of SEG. While his interests have been broad and varied, his main contribution to the field
of geophysics has been to bridge the gap between signal processing theory and its application in exploration geophysics. He is the co-author of the definitive volumes Geophysical Signal Analysis (Prentice-Hall, 1980 & SEG,
2000) and Digital Imaging and Deconvolution (SEG, 2008). Although officially retired, Sven still lectures and consults widely.

Publish or perish, industrial style

Fereidoon Vasheghani received his PhD in geophysics in 2011, and MEng in petroleum engineering in 2006, both from the University of Calgary, Alberta. He is currently working as a geophysicist at ConocoPhillips.
He is a member of SEG and SPE.

The subtle effect of attenuation

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There’s new writing about geoscience from Matt and Evan every week on the Agile Geoscience blog

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