PATENT CLAIM ANALYSIS

Application Number: 16037864
Application Type: Utility
Filing Date: 2018-07
Publication Date: 2019-05
Patent Classification: ["702", "011000"]

Abstract:
Techniques for determining geometries of hydraulic fractures include identifying a data structure that includes data associated with hydraulic fracture identifiers and observed fluid pressures, at least one of the hydraulic fracture identifiers representing a first hydraulic fracture formed from a monitor wellbore into a subsurface rock formation and at least another of the hydraulic fracture identifiers representing a second hydraulic fracture formed from a treatment wellbore into the subsurface rock formation, at least one of the observed fluid pressures includes a pressure change in a fluid in the first hydraulic fracture that is induced by formation of the second hydraulic fracture; performing a single- or multi-objective, non-linear constrained optimization analysis to minimize at least one objective function associated with the observed fluid pressures; and based on minimizing the at least one objective function, determining respective sets of hydraulic fracture geometries associated with at least one of the first hydraulic fracture or the second hydraulic fracture.

Claim (Index 15):
The structured data processing system of  claim 1 , wherein the data structure comprises an observation graph that comprises a plurality of nodes and a plurality of edges, each edge connecting two nodes, and each node represents one of the plurality of hydraulic fractures and each edge represents one of the observed poromechanically induced pressures.

Metadata:
- Claim Count in Document: 80.0
- Percentile: 95.0
- Lexical Diversity: 2.49231
- Patent Class: 702.0
- Transitional Phrase Type: none
- Component Type: 0
- Foreign Priority: False
- Related Applications: ['15915303', '15201470', '14133687', '15192218', '14896685']

Analysis Scores:
- 35 USC 101 Eligibility (BERT): 0.2198846621654399
- 35 USC 102 Novelty (BERT): 0.5816873382810712
- Combined Prediction Score: 0.256064929777003
- Mean Citation Score: 316.522896
- Max Citation Score: 498.54507
- Similarity Product: 380.9005270167589

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