Author: Mike Cline, T/X Resources
It’s pretty common knowledge that sunlight is composed of many different frequencies (colors) , and we perceive the color of an object by the color(s) that is/are reflected from the object—that is, an object is red because all of the other colors are absorbed (or filtered out) by the object.
We also know that seismic data contains many different frequencies, usually within a range from about 6-120 Hz (Hertz, or cycles per second). Have you ever considered that seismic data can be similarly filtered to reveal its “colors”? I know that this is probably pretty basic stuff for most of you, but bear with me for a minute so that I can better illustrate how you can eliminate most of the seismic frequencies, to reveal hidden features. Some might call it the “poor man’s” spectral decomposition.
Author: Mike Cline, T/X Resources
This was initially going to be the fourth posting in my seismic inversion-related series (see the 03/08/08, 03/12/08, and 03/16/08 postings), with the title “Seismic Inversion—Frequency Sensitivity Analysis”. However, after thinking about the subject for a while, I decided to expand the scope, and shorten the title a bit, to be more general in nature. After all, a study of frequency-related seismic responses can not only be applied to inversion, but can also be used to illustrate the complications of seismic correlations between different datasets, as well as why spectral decomposition can better highlight a variety of seismic features at different frequencies.
The image below is a series of synthetic seismograms which resulted from the convolution with four different zero-phase wavelets—the wavelets and frequencies are posted at the top of the display. Since they were going to be the input for inversion examples, the synthetics are all relative amplitude (ie. no AGC, or Automatic Gain Control amplitude equalization).
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Author: Mike Cline, T/X Resources
Do you ever need to use your SMT fault polygons for other applications? For example, I quite often convert them to an SMT culture layer, as a fault QC (quality control) tool, or use them in Surfer, when I need extended gridding capabilities.
The benefit of having an individual horizon’s fault polygons converted to an SMT culture layer is that you can easily keep the fault strikes consistent when working on an adjacent horizon, by overposting the culture layer onto your active horizon. I normally create fault planes on all of the faults that I see on multiple lines. However, some faults don’t extend far enough to be seen on more than one line, so it’s difficult to fault plane them with the lack of control points—a common occurrence in 2D projects, with widely-spaced lines (eg. regional projects).
Golden Software’s Surfer program has a wide array of gridding, and grid-manipulation capabilities, but it only uses the proprietary “bln” file format for faults. So, you will need to convert your SMT fault polygons to this format before you can use them in Surfer.
Author: Mike Cline, T/X Resources
At some point, you may find it necessary to create a seismic inversion from your existing seismic data, without having the benefit of reprocessing it. Depending on whether or not the relative amplitude processing (RAP) data is available, you may have to consider using data that has been previously gained. So that you can know the ramifications of using this non-relative amplitude data, this posting tests the sensitivity of seismic inversion to AGC (Automatic Gain Control) window lengths.
First, a little info about AGC for those who are unfamiliar with it. AGC is an ancient (technically speaking) seismic processing technique for equalizing energy absorption, but many processors still use it. Basically, it is a running-average process, and the number of samples that are averaged is controlled by the time window length. Common window lengths are 1000 ms (milli- seconds), and 500 ms, and occassionally, the processors will use different values, depending on what they are trying to do. Generally, the larger seismic amplitudes get smaller, and the smaller amplitudes get larger, with the AGC process—the amount of change depends largely on the window length.
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Author: Mike Cline, T/X Resources
As I mentioned in the previous post on seismic inversion, using zero-phase seismic data as an input for inversion, is one of the most critical elements for accurate results. However, this brought up the question of “how bad is bad”, when it comes to phase-matching errors? So, to answer this question, I had an idea to test the sensitivity of inversion results based on the phase of the input data.
Below, is a series of inversion images which were produced from the same initial synthetic seismogram. However, prior to generating the inversion, I rotated the phase of the input data in the amount indicated at the bottom of each image—that is: 0, 45, 90, 180, 270, and 315 degrees.
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Author: Mike Cline, T/X Resources
I recently wondered why I hardly ever see anyone using the Seismic Inversion tool, found in SMT’s TracePak module? Maybe you’ve thought about using it, but didn’t understand it well enough, or maybe tried it once, and the results didn’t match anything in the well(s). Like anything new, if you don’t under- stand it, it’s going to be difficult to use it properly. So, I thought that it would be helpful to explain some of the benefits and pitfalls of using inversion, for those interested.
First, for those unfamiliar with inversion, what is it, and how do we use it in our interpretation? You could think of seismic inversion as the reverse of a synthetic seismogram processing flow, and we use inversion to get some idea about rock properties. For an example, the portion of the seismic inversion in the image below, was generated from a synthetic seismogram in the well at the center of the line. Normally, you would generate the inversion from an actual seismic line, but I wanted an optimum response for this example. I’ve also posted three well logs from this well: the spontaneous potential (aka. SP log) in blue, the deep resistivity (RES log) log in magenta, and the acoustic impedance (AI log) in red.
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Author: Mike Cline, T/X Resources
This posting is another example of the power of shaded relief maps, and the details that they can provide.
The initial image below is a normal, color-filled elevation map of the world—the white color is the highest elevation (the Himalaya’s, of course), and the dark blue is the deepest depths of the oceans. The Digital Elevation Model (DEM) of the Earth was downloaded as a grid, and then loaded and displayed in Golden Software’s Surfer program.
Following the inital color image, is a series of gray-scale shaded relief maps. Starting with the second image, the illumination source is directly from the north, at a 45 degree angle above the horizon. In each successive image the illumination source is rotated counterclockwise 45 degrees. The light direc- tions therefore are from the: north, northwest, west, southwest, south, southeast, east, and finally, the northeast.
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Author: Mike Cline, T/X Resources
No, the title isn’t about those difficult teenage years, it is related to the subtle details of seismic phase determination. Sorry if you thought that I was going to solve one of life’s little mysteries. 
How many times have you correlated two different sets of intersecting seis- mic data, and had difficulty trying to decide which phase rotations produce the best character match? For example, when you were trying to tie a syn- thetic seismogram with a seismic line, or correlate two seismic lines of various vintages. I have (many times), and until I figured this out, I sometimes had nagging doubts about my selections.
Here’s how I do it now. The four columns of traces below were taken from a larger synthetic in a singe wellbore, and they represent four different phase rotations. From left-to-right: zero degrees, 90 degrees, 180 degrees, and 270 degrees. Note that the synthetic time interval that I chose for this example has no particular significance, other than it was relatively compact, and had many of the phase details that I wanted to illustrate.
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Author: Mike Cline, T/X Resources
For those who read my previous posting, “Making the Case for Synthetic Seismograms“, but didn’t currently have a program to generate your own synthetics, I thought that I would include a few links to the programs that I knew about. All of the programs listed below, except SMT’s SynPak, are stand-alone programs, or part of a group of software related to synthetics (log editing, AVO modeling, etc.)—at least that I could determine from their websites.
Please note that I have only used the first two programs in the list, and cannot recommend any of the remaining software, relative to how accurate they are, how well they perform, etc. The list is provided for your informa- tion, and convenience only.
Author: Mike Cline, T/X Resources
Why bother using synthetic seismograms (aka. synthetics) to calibrate well info to our seismic data? Simple answer, TO REDUCE DRILLING RISK !
For example, I’ve seen prospects “evaporate” because the originator was mapping the wrong event—or just as bad, started mapping on the correct event, but ended up on the wrong event due to a character, or response change in the seismic data. This only became evident after a couple of synthetic correlations!
I also continue to see prospects that are being sold on the strength of an amplitude, or avo response, that is somehow related to a key wellbore. However, often a synthetic hasn’t been used to tie (correlate) the well to the seismic data. How could they even know for sure what was causing the anomaly, without a synthetic tie?
So, with these recent real-life examples in mind, I thought that it would be a good idea to cite some reasons why we should use synthetics, with a blog posting.
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Author: Mike Cline, T/X Resources
I was just notified that the instructions in the info page of the Culture Symbol Spreadsheet (posted on 02/08/08) were in error.
I had copied-and-pasted the intial text, for the info page, from another spreadsheet, and thought that I had made the appropriate changes. However, I may have uploaded the wrong version when I finished.
Sorry for any confusion, previously. I have corrected the version in the original posting, but here is the corrected Culture Symbol Spreadsheet, along with the ascii file that goes with it.
Copyright © T/X RESOURCES, 1995-2008. All Rights Reserved.
Author: Mike Cline, T/X Resources
One of the limitations of seismic visualization that I often encounter, prior to interpreting the data, is being able to effectively isolate a geobody without including too much of the surrounding data.
For those new to visualization, the two common methods for displaying geo- bodies are: (1) Amplitude Restriction within a window (requires no previous interpretation), and (2) Data Extraction adjacent to an interpreted feature (ie. a fault, or horizon). Method 1 is usually faster, but can leave in a lot of extraneous data, as I’ve already mentioned. Method 2 is usually better at eliminating extraneous data, but most of the time it can’t be done until after a detailed interpretation—not much help if you’re in a hurry to see something.
So, I’m mainly looking for a method that can be used prior to a detailed inter- pretation, but is much better than Method 1 (and hopefully quicker than Method 2). The idea that I had is similar to the erase function in many raster image editing programs. Why can’t we erase the seismic data that we don’t want, just like we erase pixels in an image, using a combination of polygons for larger areas, and an adjustable “eraser” tool, for detailed, manual deletions.
See the larger Adobe Reader pdf file (four pages).
Note: The avi file is fairly large, so it will take some time before the animation starts.
Author: Mike Cline, T/X Resources
Synthetic seismograms are a very important part of seismic interpretation (in my opinion, but that’s a future post), but sonic logs are often not available. This is where our trusty friend, the pseudo-sonic log, comes in handy.
Since I use synthetics on every one of my interpretation projects, pseudo-sonic log generation has been a long-time interest of mine. I even published an article in the Oil & Gas Journal (Cline, 1989), comparing sonic and density logs to pseudo-sonic and pseudo-density logs computed from Deep Induction Resistivity logs, using the Faust equation.
Since then, I have developed a technique to generate pseudo-sonic logs from Neutron Porosity logs, that shows promise as an alternative method. I have also included three other common techniques for comparison, in this posting.
See the larger Adobe Reader pdf file (six pages).
Author: Mike Cline, T/X Resources
Imagine a wall of water, with a flow rate of over one million cubic meters (35.31 million cubic feet) per second, rushing towards you—an amount that is 100 times the average flow rate of the Mississippi River today!
If you were crossing the broad chalk ridge (indicated by the thin, red line in the gray-shaded image below) that connected Britain with mainland Europe sometime between 200,000 and 450,000 years ago, you could have witnessed this ridge-busting torrent that ultimately separated the two countries.
See the larger Adobe Reader pdf file (two pages).
You can also watch a video report from the BBC News.
Author: Mike Cline, T/X Resources
Here’s the latest in the series of T/X Resources spreadsheets designed to help when you need to create symbols to import as an SMT culture layer.
In the image below, a variety of symbols have been created to highlight certain wellbore attributes. For example, they could represent producing formations, hydrocarbon shows, well log types, or test results. You can also vary the symbol sizes, and colors, to represent a ranking order, such as production volumes, etc. It doesn’t really matter what you want to show on your map—this is an easy way to do it.
See the larger Adobe Reader pdf file.