PATENT CLAIM ANALYSIS

Application Number: 15900679
Application Type: Utility
Filing Date: 2018-02
Publication Date: 2018-06
Patent Classification: ["703", "010000"]

Abstract:
A method includes obtaining a plurality of master sensor responses with a master sensor in a set of training fluids and obtaining node sensor responses in the set of training fluids. A linear correlation between a compensated master data set and a node data set is then found for a set of training fluids and generating node sensor responses in a tool parameter space from the compensated master data set on a set of application fluids. A reverse transformation is obtained based on the node sensor responses in a complete set of calibration fluids. The reverse transformation converts each node sensor response from a tool parameter space to the synthetic parameter space, and uses transformed data as inputs of various fluid predictive models to obtain fluid characteristics. The method includes modifying operation parameters of a drilling or a well testing and sampling system according to the fluid characteristics.

Claim (Index 33):
The method of  claim 24 , further comprising truncating a master data set to a same number of samples as the node data set, wherein each sample in the master data set comprises a measurement having a temperature setting and pressure setting similar to a temperature setting and a pressure setting of at least one measurement in the node data set.

Metadata:
- Claim Count in Document: 68.0
- Percentile: 88.0
- Lexical Diversity: 2.26471
- Patent Class: 703.0
- Transitional Phrase Type: open
- Component Type: 1
- Foreign Priority: False
- Related Applications: ['15514469', '15124282', '14436017', '14780780', '15035125']

Analysis Scores:
- 35 USC 101 Eligibility (BERT): 0.2186160175282025
- 35 USC 102 Novelty (BERT): 0.5109328969607754
- Combined Prediction Score: 0.2478477054714598
- Mean Citation Score: 205.730766
- Max Citation Score: 233.74742
- Similarity Product: 151.58596012867568

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