6/29/2017

Follow the instructions

Today, I follow the instructions as the meeting.

Summary:

First, I predict 4 real con and 4 imaginary con together with 19 inputs. The results of 4 imaginary con are still not good, which are converted from real permittivity.
The reason may be that the conversion is just multiplying some parameters. So there will be little help to improve the prediction.
The first figure is 4 real con prediction performance. The R2 of the testing data are 0.76, 0.83, 0.63, 0.77, which are as good as before.
 The second figure is 4 imaginary con prediction performance. The R2 of the testing data are 0.14, 0.17, 0.29, 0.54, which are as bad as before.
In conclusion, the conversion from real permittivity to imaginary conductivity may be little help for improving the prediction performance.

Second is to predict them with just 11 inputs.
The first figure is 4 real con prediction performance. The R2 of the testing data are 0.75, 0.74, 0.73, 0.74.
  The second figure is 4 imaginary con prediction performance. The R2 of the testing data are 0.05, 0.16, 0.42, 0.52.
In conclusion, the deletion of 8 inputs make the prediction of 4 real con more stable and increase the prediction of 4 imaginary con a little. Generally, 11 inputs are similar to 19 inputs in prediction performance. Actually, more inputs will not decrease the prediction performance. However, we can use just 11 inputs to predict 8 con since 19 inputs do not perform much better.

Third, I check different lithologies step by step. For now, there are 10 different lithologies before division, category from 2 to 11.

1. I check the performance by selecting category from 4 to 10.
The first  is 4 real con prediction performance. The R2 of the testing data are 0.68, 0.58, 0.62, 0.66.
The second  is 4 imaginary con prediction performance. The R2 of the testing data are 0.13, 0.15, 0.32, 0.39.
So the performance is worse.

Tomorrow, I will continue to check lithologies. After that I will continue the instructions with magnitude and tan and NMR. Also, the change of training function may be a choice.


21 comments:

  1. good work..

    what will happen when you bring in NMR?

    ReplyDelete
    Replies
    1. I have not bring in NMR since you said it is the last choice.

      Delete
  2. Replies
    1. finish checking lithologies, continue instructions with magnitude, tan and NMR
      change training function

      Delete
  3. following are few reasons for poor performance of perm...

    1. input data is not related to perm
    2. perm is not calculated correctly by SLB

    what are other reasons for poor performance? Why will a prediction be so bad??

    ReplyDelete
    Replies
    1. I have no idea. One guy in SPWLA said that in low frequency, permittivity data themselves may be not right. But I doubt that conclusion.

      Delete
  4. there are various types of perm and cond data... use another set of perm and cond and see what happens... may be XO XD XS which is better for prediction??

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  5. PERM sees electrical storage in the system... electrical storage happens due to water, clays, conductive minerals, grain texture...

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  6. Replies
    1. Yes, but there is no change. I think that is because 10 20 30 60 90 are all similar to each other and they provide very similar information. So using 10 and 90 are enough.

      Delete
  7. follow the format for blog entry.. it helps me help you

    ReplyDelete
  8. how can you use the fact that there is a relationship between perm and cond at each freq....

    how can you use the fact that there is a relationship between perms at different frequecnies


    how can you use the fact that there is a relationship between conds at different frequencies

    ReplyDelete
    Replies
    1. 1. predict 8 of them together.
      2&3. calculate magnitude and tan values and predict them, I will do it later tomorrow.

      Delete
  9. One thing you can try is... first predict cond... then use predicted cond to predict perm...

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  10. in your prediction of perm you need to give higher weightage to Res (water) , GR (clay), Neu (clay), Den (pyrite),

    ReplyDelete
  11. first predict cond... then use predicted cond along with other inputs to predict the perm...

    ReplyDelete