[OpendTect_Users] [Support-Americas] RE: fault detection by attributes

[Friso Brouwer]

Hello Taizhong,

On the dip steering cube:

   - The dip-steering volume is a two component volume, containing the
   inline dip and crossline dip of the seismic reflectors.
   - The amount of filtering applied to the dip-steering cube determines if
   the dip are the exact local dips (detailed steering cube) or smoothed, more
   (sub) regional dips (background steering cube).
   - In many attributes and filters (such as similarity and the dip-steered
   median filter), the dip steering volume acts as a guide. It ensures that the
   data extractions in the step-out traces that are used in the multi-trace
   calculations are corrected of the dip of the reflector. In other words the
   correction applied to the step-out traces ensures that with one calculation
   only seismic data from the same stratigraphic interval is considered.
   - Just for completeness, in some attributes (e.g curvature) the dip
   steering volume acts (indirectly) as an attribute.

Here are some links that may help you further:
On steering<http://opendtect.org/rel/doc/User/dgb/chapter2_steering.htm#LINK-STEERING.HEADCHAPTER>
Dip Steered Similarity<http://opendtect.org/rel/doc/User/dgb/chapter2.3_attributes_with_steering.htm#LINK-STEERING.ATTRIBUTES.SIMILARITY>
Steering Webinar<http://www.opendtect.org/tutorials/Webinar_Optimal_Steering>

I hope this helps your forward, cheers, Friso

-- 
Friso Brouwer
Support Americas
dGB Earth Sciences

+1 281 240 3939 (o)
support-americas at dgbes.com


On Thu, Jun 2, 2011 at 7:05 AM, Duan, Taizhong (MRO)
<tduan at marathonoil.com>wrote:

>  Friso,
>
>
>
> Thanks for your help. I will try some your ideas. I have another question.
> In OD algorithms, how is the steering cube used? as a constraint? Or
> something else. In which OD documents, I can find the detailed explanation?
> For example, how is the dip steering cube applied in calculating the
> similarity?
>
> Regards,
>
> Taizhong
>
>
>
> *From:* Friso Brouwer [mailto:support-americas at dgbes.com]
> *Sent:* Tuesday, May 31, 2011 10:26 AM
> *To:* Duan, Taizhong (MRO)
> *Cc:* users at opendtect.org
> *Subject:* Re: [OpendTect_Users] fault detection by attributes
>
>
>
> Dear Taizhong,
>
> That is a non-trivial issue and it may be impossible achieve a complete
> removal of stratigraphic features. I do not think the filtering of the
> steering cube will make much of a difference, I advise to use the background
> steering cube a defined in our standard workflow<http://www.dgbes.com/images/stories/PDF/effectivedipsteeringworkflowusingbgsteering_primerodata.pdf>.
>
>
> What could help, or at least mitigate your problem are the following
> solutions, in order of complexity (try them in order) :
>
>    1. Increase the time window of the similarity attribute, this will tune
>    out vertical small features, which are often the stratigraphic features, not
>    the faults.
>    2. Do post-attribute filtering on the similarity volume, using the
>    volume statistics.
>    3. Use an completely other attribute for fault detection, curvature is
>    a good candidate, here an article<http://www.dgbes.com/images/stories/PDF/fault_attributes_niger_delta_aapg.pdf>
>    .
>    4. If the fault system and stratigraphic features have different
>    directions in the horizontal plane, one can separate them using directional
>    decomposition of the attribute. This is not trivial, and if this is an
>    option for you, let me know, so I can explain you the details.
>    5. Use a second attribute that detects the stratigraphic features, but
>    not faults (e.g. a small window energy). Then use a cross-plotting approach
>    to identify the domain in the crossplot where the faults are "clean" and use
>    the mathematics attribute (conditional statements) to pass only attribute
>    combinations within this domain.
>    6. Extending on point 5 one can choose an user-driven multi-attribute
>    neural network approach. This relies on there being a multiple attributes
>    that each can partially separate faults and stratigraphic features. Based on
>    user picked examples the neural network will then "learn" how to combine the
>    different attributes to arrive at a more complete separation of faults and
>    stratigraphic features. Here is an article<http://www.dgbes.com/images/stories/PDF/eage_2000_meldahl_obj.pdf>and product
>    information <http://www.dgbes.com/index.php/neural-networks.html>.
>
> All in all it remains a difficult problem as faults and stratigraphic
> features often have there main characteristic/attributes, such as
> discontinuity (similarity) and curvature, in common. Still with the above
> methods you should be able to at least achieve an improvement. I gladly help
> you with the further details if you choose to experiment with one of the
> methods.
>
> Kind regards,
>
> Friso
>
> --
> Friso Brouwer
> Support Americas
> dGB Earth Sciences
>
> +1 281 240 3939 (o)
> support-americas at dgbes.com
>
> On Thu, May 26, 2011 at 9:30 PM, Duan, Taizhong (MRO) <
> tduan at marathonoil.com> wrote:
>
> Hi all,
>
>
>
> What is the way to filter out all stratigraphic discontinuities in
> similarity calculation? The dip cube steering is supposed to do so? (bkg: I
> tried with dip steering cubes filtered with i-j stepout from 3-9, but it
> seems make not much difference, i.e., there is still significant
> stratigraphic discontinuities left on the volume. Of course I want to keep
> all non-vertical faults/fractures).
>
>
>
>  Anyone gets a better workflow?
>
> Thanks.
>
>
>
> Taizhong Duan
>
>
>
> Marathon Oil
>
>
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