PATENT CLAIM ANALYSIS

Application Number: 16162916
Application Type: Utility
Filing Date: 2018-10
Publication Date: 2019-04
Patent Classification: ["702", "014000"]

Abstract:
A method to classify one or more seismic surfaces or surface patches based on measurements from seismic data, including: obtaining, by a computer, a training set including a plurality of previously obtained and labeled seismic surfaces or surface patches and one or more training seismic attributes measured or calculated at, above, and/or below the seismic surfaces; obtaining, by the computer, one or more unclassified seismic surfaces or surface patches and one or more seismic attributes measured or calculated at, above, and/or below the unclassified seismic surfaces; learning, by the computer, a classification model from the previously obtained and labeled seismic surfaces or surface patches and the one or more training seismic attributes; and classifying, by the computer, the unclassified seismic surfaces or surface patches based on a comparison between the classification model and the unclassified seismic surfaces or surface patches.

Claim (Index 6):
The method of  claim 1 , wherein the learning includes learning the classification model implicitly from the plurality of previously obtained and labeled seismic surfaces or surface patches and the one or more training seismic attributes.

Metadata:
- Claim Count in Document: 41.0
- Percentile: 97.0
- Lexical Diversity: 3.29167
- Patent Class: 702.0
- Transitional Phrase Type: none
- Component Type: 0
- Foreign Priority: False
- Related Applications: ['15011135', '13378018', '12623130', '13695226', '12881789']

Analysis Scores:
- 35 USC 101 Eligibility (BERT): 0.1887644829014854
- 35 USC 102 Novelty (BERT): 0.6251150627776833
- Combined Prediction Score: 0.2323995408891052
- Mean Citation Score: 284.115684
- Max Citation Score: 548.4494
- Similarity Product: 544.2249850455522

Labels:
- Claim Label 101: 0
- Claim Label 102: 1
- Claim Label 103: 1
- Claim Label 112: 1
- Combined Label: 0
- Label 101 Adjusted: 0

Dataset: test