PATENT CLAIM ANALYSIS

Application Number: 16210192
Application Type: Utility
Filing Date: 2018-12
Publication Date: 2019-04
Patent Classification: ["702", "007000"]

Abstract:
In an embodiment a method of automatic adjustment of logging, processing, inversion, and visualization operations is disclosed. The method comprises gathering data about formation properties in a database, filtering the gathered data, generating rules based on the filtered data, and providing automatic adjustments to automatically adjust the logging, processing, inversion, and visualization operations. The gathered data includes a plurality of in-well measurement points and a plurality of wells in a given geological area. A quality factor is derived based on a difference between the automatic adjustments and parameters that an operator communicates as a best parameter. The quality factor is used to determine which of the gathered data is to be stored in the database. The rules are applied to a next iteration of data that is to be gathered. The method repeats until no further improvement is obtained.

Claim (Index 10):
The method of  claim 1  in which at least some of the rules that are to be applied to the next iteration of data that is to be gathered are applied to at least one of the group consisting of:\n noise filtering, \n temperature correction, \n software focusing, and \n borehole correction or calibration.

Metadata:
- Claim Count in Document: 29.0
- Percentile: 98.0
- Lexical Diversity: 2.01299
- Patent Class: 702.0
- Transitional Phrase Type: closed
- Component Type: 1
- Foreign Priority: False
- Related Applications: ['15021029', '14892558', '15565725', '15545750', '14787256']

Analysis Scores:
- 35 USC 101 Eligibility (BERT): 0.1876352343702073
- 35 USC 102 Novelty (BERT): 0.4916271239130467
- Combined Prediction Score: 0.2180344233244912
- Mean Citation Score: 132.33684200000002
- Max Citation Score: 179.78845
- Similarity Product: 119.9026602949858

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

Dataset: test