Using a Graph Database Tree and Data Analytics to Model an Ancient River System
summary
Digitized junctions of the Cretaceous J Sandstone river network become nodes in a Neo4j graph exported as GraphML and visualized in Gephi, with flow directions encoded as directed edges. Applying PageRank to ~hundreds of junctions ranks channel segments by inferred flow strength; high PageRank areas align with published channel maps, greater channel widths and higher porosity/permeability values across the mapped ~150 by 300 mile region, supporting Neo4j Gephi PageRank as a practical workflow.
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chapters (8)
- 0:00Introduction to the talk
- 3:19What is a tree structure
- 7:55Can rivers be modeled as trees
- 12:19Modeling river systems in graphs
- 16:37Building the graph database model
- 22:20Why use PageRank algorithm
- 28:52Comparing PageRank to published data
- 30:39Results and oil exploration implications
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