Today, I finished all calculations and comparisons.
Summary:
Good prediction:
porosity: r2=0.7685, nrmse=0.0909;
t2,gm: r2=0.8664, nrmse=0.0840;
t2,gm*porosity^2 (SDR model term): r2=0.7586, nrmse=0.0854.
Bad prediction: BVI, FFI/BVI*porosity (TC model term).
Main reason: when predicting 64 bins, the model consider them as a whole. So the parameter related to all 64 bins are accurate such as porosity and t2,gm, which use all 64 bins for calculation at the same time.
However, BVI and FFI divided T2 distribution into 2 parts, and calculating BVI focuses on just the first several bins. So BVI is not accurate, and FFI/BVI will even increase uncertainty.
As a result, I recommend to mention porosity, t2,gm and SDR model in our validation part instead of mentioning all of them. More research is needed to be done to predict BVI accurately through predicting T2 distribution.
Maybe predicting BVI directly is a good choice.
At the weekend, I will write the paper and finish it. I will send you the draft before Monday.
in the paper describe everything related to how you calculate porosity and tgmean
ReplyDeleteOk, I see.
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