Transcript Paige`s coherent noise primer

Paige’s coherent noise primer –
The reason coherent noise has gone un-noticed is that it is hard to see, Often stronger than the desired
events, it interleaves with them, creating a choppy combination usually mistaken as random noise. Each
type has its own arrival pattern and it is only when the system lines the data up by that pattern that it
becomes visible. I show some of these “lined up” displays later, but a perfectly valid way of proving it was
there is to remove it and then show the results.
On the example below, an initial look at the raw data at the left leaves the impression there is a serious
statics problem affecting the target zone. When the noise is detected and lifted off, that jaggedness
disappears and the reflection data is brought out. Pay close attention to the comparison in the target zone.
Because most are not aware how serious the noise
problem is world wide, illustrations like this are most
important. In particular, note that the signal that has
been brought out lies below an initial burst of noise.
There is no way the system could have invented the
good NMO pattern on the results. Again, proving the
noise is there, and showing how such interleaving
creates random like jaggedness is a major point. The
noise types removed were interbed multiples and
refractions (I watched them being detected).
What is in this presentation
History of my noise work and noise types.
Deep Gulf Coast shot format project.
Permian basin noise removal.
Scotland coal seam gasification preliminary.
The heavy energy cone seen below is omnipresent on land work.
The industry has generally called this “ground roll” (Rayleigh waves). While part of it may be, my work has shown that a goodly bit is
“shear wave” energy that is traveling vertically, generating refractions that affect inside traces.
If the waves were truly traveling horizontally, the problem could be easily solved by muting. My work has proven to me
that vertically traveling shear waves comprise the bulk of the noise we see here.
The problem is this energy spawns deeper refractions that move into the center of the spread. This is not
easy to show, but highly important.. The first detailed section is devoted to this explanation.
Point source refractions are the second and most insidious type of coherent noise. Caused by early critical angle crossovers they are very common (especially with the current emphasis on long spreads).
Inter-bed multiples are the third noise type. Their removal can be accomplished by first establishing expected velocity curves,
then iteratively scanning for events that have reflection type curvature, but whose apparent velocities exceed an acceptable range.
None of these noise types are easy to see, due to the steep arrival patterns. The next slide notes that the key to
finding and removing them is to use the system to iteratively adjust arrival times to fit their patterns, using the stack to detect their
presence. To repeat this important point. The system iterates through a broad range of angular assumptions. On each, it lines up
the traces by those offsets, then stacks them, selecting the maximum event amplitude to pick the best fit for this iterative pass.
Deep Refractions from vertical travel cutoffs
Are prevalent on both onshore and offshore work – and
few processors take this serious noise into account.
A
B
C
To the left you see the gathers I got to work with in my North Sea effort.
A is the
A North Sea Chalk.
B is the critical angle position, where the reflection begins cloning to a refraction.
Here vertical travel begins to be cut off.
C .is where no more energy gets through
The yellow line represents the deep mute I had to use to get any results.
Point source reflection theory has always been a mystery to me, but it is
one thing I have to buy into. In essence it says that when the reflection process hits
an abrupt end to either a reflecting interface or a break in the downwave, horizontal
refractions take place (thus proving nature abhors a vacuum). This means every
deeper event will be accompanied by fairly strong coherent noise that penetrates
into the spread.
A
B
C
This pre-stack migration was not able to handle refraction patterns. The exotic
explosion of energy we see at the upper right is the result. When I was on my way
out I was able to obtain some raw data that had no migration (or NMO). The set at
the lower left is from the same zone. The A,B and C markers apply in the same
way, and you can see there is no abrupt change in energy, proving the use of prestack migration to be at fault. Since that process mixes heavily in its attempt to
draw in energy that has wandered due to strong dip, it has to really murder the fine
detail on the fault breaks.
As a result of this phenomenon AVO on this data is virtually a joke. The
energy explosion would have triggered the searcher, but this would not have had
anything to do with the theory. Yet the major discussion theme when I came on the
scene was whether to use inside, middle or outside trace combos.
These refractions sometimes stack quite nicely, not looking like noise. Once
we know to expect them, we can search them out by their offset patterns. Once we
can detect them, lifting them off becomes simple. Improved results (all by
themselves) supply logical proof they were there. As you can see, the noise detail
here (with no migration) is beautiful compared to what I had to work with.
Here, from a Gulf Coast effort, is a
deep refraction that has been “lined
up” with a slope of 3256 samples
per spread total. It starts in the
shear wave high energy zone
pointed out on slide 2, but then
works its way well into the spread.
Again, all that was done to spot it
was to pull up the gather traces by
the calculated linear offsets for this
assumed refraction velocity.
During development the capability
to create these pictures on the fly
helped enormously. I put dozens of
these displays in an early show and
certainly convinced myself that the
system knew what it was doing. Up
to that point I was not aware of the
shear wave refraction problem, but I
am now. You will see the surprising
results later.
Before we leave here I want to emphasize the universal, “critical angle cutoff” problem.
To
the right is my inverted and integrated result on an in-line from the U.S. To the left in a gather approximately located by the arrow.
To get these results around 1/2 of the outside traces were thrown out by my optimized stack logic. The need for deep muting came
from the same type of critical angle wave trap we saw in the North Sea stuff. The stacked results without the mute were a mess in
the target zone.
From the many gather sets I have looked at, I predict that this problem exists on a large percentage of projects,
world wide. You might take a closer look at your gathers to see if you can spot the critical angle crossings.
This south gulf coast project is probably what I’m most proud of.
It broke entirely new ground and convinced me that deep seated noise is hiding significant stratigraphy all
over. By starting with data in the shot format, noise events that were surface oriented could be detected and
removed more efficiently. Ability to see and lift them gently off was developed here. Watching the system
remove event after event made me wonder if anything would be left. The results speak for themselves.
From shale play
To
Gulf coast prospects
There are timed topics
on many slides. An “end”
message will inform you
when the slide is done.
The show discusses:
A. Removal of strong coherent noise.
B. Dominating strike slip faults.
C. The evolution of a salt dome.
Shale play geology.
You are going to see a lot of events in the next slides. The main point of the show is that
removal of strong coherent noise has brought out a previously unseen geological reality. .
Conventional stack
Paige’s stack of traces de-noised at shot
This was a salt dome effort.. Conventional
processing had shown strong dips on what was
thought to be the flanks. It was the hope of the
geologist that my noise removal would enhance
the picture. Unfortunately, as we will see later, it
called those events noise, and nicely took them
out. For some reason he then lost interest, not
apparently sharing my excitement about the major
breakthrough I am seeing
For a before and after comparison. .In
your mind, pick up the left display and imagine it
between the yellow lines (to see the approximate
lineup). While you might think the events are the
same, closer examination will show that they are
not. Much more on this later.
This enhanced resolution leads to the next
major thrust of the presentation, which is to show
the complex set of strike slip faults (resulting from
deep plate movement) precipitated salt intrusions.
Strike slip faults are tough to track. They can
curve all over our two dimensional display. When I
first began to see them, suggesting their presence
to others met with some derision, since all were
used to the linear lineups of normal, down to the
sea lineups. As my pre-stack noise removal got
more effective, their presence became clear.
I show a major bounding fault. I’ll then
superimpose it on the conventional stack. I repeat
that for two more. The purpose is to provide you a
framework to examine the marked difference in
resolution between the two processing versions.
Whether you believe in the faults themselves is not
so important at this point. I will work that problem
later.
•...
Finishing up
.the
And here are two pairs of before and after’s. The outlines in yellow show the approximate comparison sections.
The ? Shows that
my resolution is still far
from perfect, and the
fault pattern eludes me.
?
The “before” is
at the far left.
And here are two pairs of before and after’s. The outlines in yellow show the approximate comparison sections.
You can see –
I did not draw in
any faults on the
right flank. I hope
by now you can
visualize where I
would put them.
we get serious
about this on the
next slide.
More on the role of strike slip faults in
the evolution of salt domes.
We back up here to a section that precedes
the dome. It is directly in line with the trend,
and we see that the faults are there. The salt
has just not intruded yet. We find the same
thing on the other end of the dome. Once
more we say we shouldn't be arguing about
whether strike slip faults exist, since common
sense tells us they have to (if we believe in
continental plate moves).
Whether I have tracked them accurately is
beyond the point. I have to warn you however
that I get cranky when some traditional fault
picker jumps in with old fashioned advice on
picking that does not take the nature of strike
slip faults into account. Establishing a pattern
is essential if one accepts that they trap and
this means you take some chances. Of
course I feel I am probably one of the very
few with this sort of experience, and when I
re-look at this display I am pleased. Not that I
wouldn’t make a few minor changes if I had
not frozen this into a picture. Several of these
changes would involve moving up through the
strong continuity at about 2.80. Again this
type of faulting may not exhibit any vertical
throw. In any case, just to get this far is a real
breakthrough.
At the bottom, on our deep target, we see a bright
spot that probably points to hydrocarbons. Again, the
faults have split the reservoirs so we’re forced into the
mode of searching for longer reservoir stretches.
Now we look at a Permian basin noise removal project. The interesting story here is that the enterprising
geophysicist (who got permission for me to look at the data) thought his major problem was caused by an AVO
type “polarity reversal in midspread”. He now agrees enthusiastically that interbed multiples were the culprit.
Unfortunately he got hit by the spending cuts so this turned out to be another pro-bono effort.
Before
A tutorial
on the effect
of seismic
noise.
(Requires lots
of toggling to
really see how
noise interacts
with signal).
I start with two sets of before
& after gathers to emphasize
the fairly amazing success of
the noise removal algorithm.
after showing some results I
take you on to a discussion of
the noise itself, using more of
the examples as prompts.
So toggle back and
forth with one finger
on the left arrow and
another on the right.
Toggle guide
After
A tutorial
on the effect
of seismic
noise.
(Requires lots
of toggling to
really see how
noise interacts
with signal).
The noise has
been removed
by Paige’s non
linear logic.
I start with two sets of before
& after gathers to emphasize
the fairly amazing success of
the noise removal algorithm.
after showing some results I
take you on to a discussion of
the noise itself, using more of
the examples as prompts.
So toggle back and
forth with one finger
on the left arrow and
another on the right.
Toggle guide
Before
I am putting these 2
before and afters
up front to get you
used to toggling. I’ll
then show some of
my inverted and
integrated results
before continuing
with a long series of
further examples.
Toggle guide
After
Some results
I am putting these 2
before and afters
up front to get you
used to toggling. I’ll
then show some of
my inverted and
integrated results
before continuing
with a long series of
further examples.
While you can see
the logic got rid of a
lot of multiples and
refractions, the data
are still noisy, so be
kind in judging the
results.
And remember you
are looking at the
simulation of sonic
logs.
Toggle guide
In case you missed it,
some words on my
inversion/integration module –
It’s purpose is to simulate sonic logs from
seismic data. Since reflections are primarily
caused by abrupt changes in velocity, this is
our best hope to actually model lithology. The
ability to do this is vital to long range seismic
correlations.
At the left is an in-line with a superimposed
sonic log. Because the stratigraphy is quite
regular in this study zone, the sonic log is
almost generic, and no great care was taken to
place it exactly (although the location is close).
The purpose was to make sure my logic knew
what it was doing when it indicated the
presence of thick beds. As you can see, there
is no problem with the well match here.
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And finally the pre-study on Scottish coal seam gasification.
About Paige -
MS in geology,spent 7 years in Venezuela for Mobil,& then Phillips Maracaibo interpretation found
Phillips’ major field there.
Back to states, joined Phillips computing, became project manager for exploration. Hired by Western Geo. To start digital operations in Shreveport.
Wrote first predictive deconvolution program that put Western on the map in digital processing (and formed the non-linear basis for later ADAPS software),
After brief sojourn in commercial processing (where he wrote a table driven programming system), joined Dresser Olympic as both manager of processing
and of research. Went on his own to start non=linear development.
Consulting package
consists of Paige’s personal time, his open-ended software and use of his processing hardware.
Unless full segy detail is requested (segy output), the product is a series of PowerPoint studies.
He can be reached at [email protected]
De-noising Vibroseis
The contention
is that the
correlated Vibroseis field record (to the far left)
is a mess of overlapping coherent noise and
signal, the noise being strong enough to control
the stack.
Lifting off vs filtering
is a major key to the success of my non-linear
logic in uncovering the target events! The noise
itself can be several times as strong and
frequency sensitive filtering does little good.
The operative target is below the red line. The
goal is delineation of a series of coal beds.
On first glance, one would think there is a
serious statics problem, but once the non-linear
process lifts off most of the noise (to the right) ,
we see that statics are not involved. No event
shifting was used, so removing this jaggedness
proves the overlapped thesis. I just show this
first processing stage to prove the presence of
the coherent noise as well as the logic’s ability
to detect and gently lift it off.
As you will see when you continue through the
14 adjacent points, the logic was consistent on
its very selective event selection. Note here how
it took out the leading lobes just below the red
line and then emphasized the ones just below.
Once again, the initial jaggedness was the result
of the intricate overlay of noise and signal, and
eliminating that phenomenon is the essential
proof of the logic. The fact that what comes out
exhibits the proper event shape is the final
verification, since we are not smart enough to
force that result.
This is a timed show, so relax and pay
attention to the detail. Click anywhere to start.
(Clicking later will speed it of course).
Click to continue with a
newer inter-bed multiple
treatment with caustic
comments.
Or click here to return to
base.