Evaluation Results - Version 1

We compute quality measures with respect to the four ground truth seismic cubes depending on their discrete or continuous amplitude values. The metrics are summarized below, for more precise mathematical details, please refer to our paper [1].

Discrete group:

  • precision: Percentage of true positives of extracted edges/faults in attributes to all extracted edges/faults.
  • recall: Percentage of true positives of extracted edges/faults in attributes to all ground truth edges/faults.
  • rmseDistance: Root mean square error weighted by the nonlinear distance (sigmf([1:1:30],[0.5 10])) between edges/faults in attributes and their closest edges/faults in ground truth. Extracted edges/faults using the seismic attributes are treated differently depending on their distance to the closest object in the ground truth.

Continuous group:

  • recall: Percentage of true positives of extracted attributes to ground truth.
  • rmse: Root mean square error between attributes and ground truth.
  • rmseDiscontinuity: Root mean square error between attributes and ground truth without including the edges/faults area. This originates from the fact that most structural attributes (except edge attributes) are undefined at (or very near) edges or discontinuities. This is because derivatives are undefined at discontinuities.

The threshold for a true positive is different for each ground truth category. For each continuous group, the threshold D is 20% of the difference between the maximum and minimum of its ground truth. If the submitted seismic attribute for edge/fault is continuous, not discrete, they will be discretized according to the top 20% rule.

We have computed their varieties, both in 3D and 2D, as well as in different dip regions [0°, 90°] and [0°, 45°]. In the 3D version, the quality measures are computed over the entire seismic cube, whereas in 2D they are first computed on every inline, crossline, and time section of the cube, followed by a mean operation. A caveat of the above metrics is that they do not discriminate between attributes at different dip angle ranges. However, in practice, it is very hard to image structural dips beyond 45 degrees for most types of seismic data. Therefore, more quality metrics (named *_LowDip), which account only for the dip in the 0-45 degrees range, are developed.

Submit and evaluate your own attributes.

Dip_Azimuth_Polar
Attribute Name Updated Average Train
N/F
Train
N/R
Train
N/C
Test 1
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Test 1
N/R
Test 1
N/C
Test 2
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Test 2
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Test 2
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SLB_Petrel_Consistent dip azimuth_Xing 2016/12/11 0.7164 0.8203 0.6175 0.7310 0.8135 0.6156 0.7249 0.8033 0.6060 0.7151
SLB_Petrel_Local structural azimuth_Xing 2016/12/11 0.2772 0.4078 0.4039 0.3708 0.3012 0.2979 0.2876 0.1419 0.1411 0.1424
Attribute Name Updated Average Train
N/F
Train
N/R
Train
N/C
Test 1
N/F
Test 1
N/R
Test 1
N/C
Test 2
N/F
Test 2
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Test 2
N/C
SLB_Petrel_Consistent dip azimuth_Xing 2016/12/11 15.7835 12.0850 16.8442 18.0028 12.3538 17.3029 17.9281 12.1733 17.3834 17.9778
SLB_Petrel_Local structural azimuth_Xing 2016/12/11 16.8037 10.8663 17.6011 16.1429 13.3520 18.8710 17.6130 16.2856 20.7911 19.7103
Attribute Name Updated Average Train
N/F
Train
N/R
Train
N/C
Test 1
N/F
Test 1
N/R
Test 1
N/C
Test 2
N/F
Test 2
N/R
Test 2
N/C
SLB_Petrel_Consistent dip azimuth_Xing 2016/12/11 15.5727 12.2273 17.1103 18.3798 11.9232 16.4852 17.7210 11.7499 16.6173 17.9404
SLB_Petrel_Local structural azimuth_Xing 2016/12/11 15.2005 9.8024 17.5481 15.8729 10.1681 17.3333 15.5669 13.4490 19.3168 17.7473
Attribute Name Updated Average Train
N/F
Train
N/R
Train
N/C
Test 1
N/F
Test 1
N/R
Test 1
N/C
Test 2
N/F
Test 2
N/R
Test 2
N/C
SLB_Petrel_Consistent dip azimuth_Xing 2016/12/11 11.2497 8.5941 12.3038 12.3460 8.8688 12.6197 12.3791 8.8983 12.7443 12.4930
SLB_Petrel_Local structural azimuth_Xing 2016/12/11 14.6162 10.2775 14.2500 13.4068 12.2231 15.4881 14.7307 15.4762 18.1780 17.5157
Attribute Name Updated Average Train
N/F
Train
N/R
Train
N/C
Test 1
N/F
Test 1
N/R
Test 1
N/C
Test 2
N/F
Test 2
N/R
Test 2
N/C
SLB_Petrel_Consistent dip azimuth_Xing 2016/12/11 10.5203 7.9058 12.0238 11.9521 7.8238 11.7540 11.6723 7.8078 11.9151 11.8278
SLB_Petrel_Local structural azimuth_Xing 2016/12/11 13.2706 9.3693 13.7684 12.8595 9.9385 14.0619 13.0961 13.4075 16.9225 16.0116
Attribute Name Updated Average Train
N/F
Train
N/R
Train
N/C
Test 1
N/F
Test 1
N/R
Test 1
N/C
Test 2
N/F
Test 2
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Test 2
N/C
SLB_Petrel_Consistent dip azimuth_Xing 2016/12/11 0.8700 0.9472 0.9349 0.7712 0.9323 0.9204 0.7570 0.9163 0.9066 0.7444
SLB_Petrel_Local structural azimuth_Xing 2016/12/11 0.3747 0.6103 0.6061 0.5551 0.4471 0.4428 0.4071 0.1001 0.1014 0.1026
Attribute Name Updated Average Train
N/F
Train
N/R
Train
N/C
Test 1
N/F
Test 1
N/R
Test 1
N/C
Test 2
N/F
Test 2
N/R
Test 2
N/C
SLB_Petrel_Consistent dip azimuth_Xing 2016/12/11 4.1670 3.3302 3.5388 4.5910 3.7710 3.9213 4.9201 4.0744 4.2093 5.1473
SLB_Petrel_Local structural azimuth_Xing 2016/12/11 9.1200 6.9658 7.0419 7.1798 8.1069 8.1736 8.4081 11.9395 11.9700 12.2944
Attribute Name Updated Average Train
N/F
Train
N/R
Train
N/C
Test 1
N/F
Test 1
N/R
Test 1
N/C
Test 2
N/F
Test 2
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Test 2
N/C
SLB_Petrel_Consistent dip azimuth_Xing 2016/12/11 1.8328 0.7335 1.5089 3.2543 0.7427 1.5042 3.2869 0.7057 1.4743 3.2847
SLB_Petrel_Local structural azimuth_Xing 2016/12/11 6.8599 4.4719 4.5127 4.8012 5.5016 5.5299 5.7647 10.3132 10.3230 10.5213
Attribute Name Updated Average Train
N/F
Train
N/R
Train
N/C
Test 1
N/F
Test 1
N/R
Test 1
N/C
Test 2
N/F
Test 2
N/R
Test 2
N/C
SLB_Petrel_Consistent dip azimuth_Xing 2016/12/11 4.7243 4.3054 4.2023 5.9133 4.6863 4.5457 6.0215 3.8329 4.0654 4.9459
SLB_Petrel_Local structural azimuth_Xing 2016/12/11 10.4066 8.5871 8.4236 9.2347 9.6080 9.4382 9.9530 12.5444 12.6161 13.2545
Attribute Name Updated Average Train
N/F
Train
N/R
Train
N/C
Test 1
N/F
Test 1
N/R
Test 1
N/C
Test 2
N/F
Test 2
N/R
Test 2
N/C
SLB_Petrel_Consistent dip azimuth_Xing 2016/12/11 1.6199 0.4356 1.4675 2.8162 0.4646 1.4805 2.8678 0.5271 1.5552 2.9646
SLB_Petrel_Local structural azimuth_Xing 2016/12/11 7.0120 4.5013 4.5483 4.9545 5.5390 5.5735 5.9624 10.5055 10.5288 10.9949
Ground Truth vs Attribute Result (Snapshots from different view angles. Please single click the table cell above.)