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Conversion from shot to cmp #204
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Because I had issues with the same problem, I coded it myself in python. If
you want I can send you the script. It probably is not the most optimal
code but it works and it is accurate. It uses univariate spline to produce
your CMP projection curve. Then it is just some sorting.
Cheers
Julien
…On Mon, 15 Jun 2020, 12:49 nestorkid, ***@***.***> wrote:
Traces have been read and output as rsf file and header. However, the
various programs for conversion from shot to cmp gathers have not yielded
the expected cmp gathers. The data set is a 2D data set and regularly
spaced. The following modules were tried for sorting the data to cmp
gathers, shot2cmp, sfintbin, sftahsort.
A look at various reproducible papers and an effort to follow the steps in
such did not produce the desired result. Also, editing the header intervals
with the 'put' module did not help. Is there anything that might be the
issue or is a step missing? Also, observed that most data sets from most
reproducible were converted to cmp gathers prior to being run with
Madagascar.
- OS: WSL Ubuntu 20
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It will be really helpful if you can send me your code for shot to cmp trace sorting, I will really appreciate it. I have actually looked through many flows to appreciate that Madagascar is not optimized for shot to cmp sorting. Please, do let me know how best to run the code together with Madagascar. Chisom |
You can call the function in your Scon like this:
#########################Parameters ##################################
d1=0.004
d2=50
n1=12500
n2=120
CdP_Bin=100
Dir ='/path/to/your/files'
CoX, CoY = 15700000, 3000000 #Coordinate modifier usually 0,0
EPSG_in = 1234 # original projection
EPSG_Survey = 2345 # target projection
NSF = False #nearsurface velocity correction (static stretch file)
### concat your shot-receiver profiles. "All" is a list of names of
shot-receiver profiles
Filt_Line ='RSF/Filt_line'
Flow(Filt_Line, All, 'rcat ${SOURCES[1:-1]} axis=2')
Flow(Filt_Line+'_H', Heads, 'rcat ${SOURCES[1:-1]} axis=2')
### Prepare your data for CdP sorting
Prepare.Load(Dir, Filt_Line+'_H.rsf' , CoX, CoY, CdP_Bin, d2, NSF, EPSG_in,
EPSG_Survey)
###############Interpolate Missing Data and regularize ##################
##########################################################
Regularize.Cubize(Dir, Filt_Line+'.rsf', n1)
###load parameters
Params= np.genfromtxt(Dir+os.sep+'Utils/Parameters.txt', usecols=1, dtype=
np.int)
MinOff, MaxOff, Low_bound, High_bound = Params
################Import CdPs ##########################
Near= 1
Far = 62
N2 = Far-Near
N3 = High_bound-Low_bound #len(yi)
CdPw8 = []
for C in range(N3):
cdp= 'CDP_R_W8ted/CdP4_%s'%C
CdPw8.append(cdp)
Flow(cdp, 'CDP_R_W8ted/New_CDP_%s.dat'%C, 'sfcsv2rsf | put d1=%s
label1="Time", unit1="s" d2=%s label2="Offset" unit2="m"| window f2=%s
n2=%s | bandpass flo=10 | pow pow1=2'%(d1,d2, Near, N2))
You will probably need to adjust this a bit to make it work for yourself.
in python 2.7 you will need m8r pyproj, scipy, numpy and matplotlib. It is
probably easy to switch to 3 (it should!) but I didn't find the time. There
are multiple options you can activate and actual processing things you
could do but I would keep it as it is now as it is without much fuss. I
should get myself to integrate that properly into Madagascar but on my own
and without financial support I cannot.
If someone out there is interested they are most welcome as I believe the
3D approximation of the curve is the way to go, I have done it on several
projects and it is pretty accurate. The only parameter that you need to
tune and that is still hardcoded is the standard deviation of the CdP cloud
line 93 in Prepare.py. I have not found a satisfactory mathematical method
to automatically set it up, just bound it. It is pretty important for
controling the curvature of your crooked geometry. please read the
Scipy.Interpolate documentation. The code displays your future curve so
that's what you adjust to get a satisfactory trajectory. Please notice that
it interpolates only on 1/6 traces as I used to work on large point clouds
(line 95). Most lines are not shot in mountain passes so you probably can
forget about it. You can also setup surface velocities to better place your
points in 3D, you can extrapolate missing traces (experimental). I hope it
is understandable.
And the Regularyze is multithreading capable. Also shows your coverage in
CdP space
The folder should be organise like this (I hope I have it all)
scons
RSF/
Methods/
Utils/
CDP_R_W8ted/
Good luck!
Julien
…On Tue, Jun 16, 2020 at 9:51 AM nestorkid ***@***.***> wrote:
It will be really helpful if you can send me your code for shot to cmp
trace sorting, I will really appreciate it. I have actually looked through
many flows to appreciate that Madagascar is not optimized for shot to cmp
sorting. Please, do let me know how best to run the code together with
Madagascar.
Regards,
Chisom
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The NW-Edge <http://nw-edge.org>
Basin Analyst - Independent researcher in geology and applied geophysics
Co-Founder of Plastic@Bay <http://www.plasticatbay.org> - Strategic
development and research leader
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Mobile: +44 (0) 746 20 781 62
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Traces have been read and output as rsf file and header. However, the various programs for conversion from shot to cmp gathers have not yielded the expected cmp gathers. The data set is a 2D data set and regularly spaced. The following modules were tried for sorting the data to cmp gathers, shot2cmp, sfintbin, sftahsort.
A look at various reproducible papers and an effort to follow the steps in such did not produce the desired result. Also, editing the header intervals with the 'put' module did not help. Is there anything that might be the issue or is a step missing? Also, observed that most data sets from most reproducible were converted to cmp gathers prior to being run with Madagascar.
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