Dynamic Visualization and Interpretation of 3.5 Million Geospatial Data Points
*Courtesy U.S. Energy Information Administration (EIA)
- Jul 17, 2019 9:14 pm GMT
- 342 views
GIS and other computer scientists at Wood MacKenzie have come up with a way to visualize and interpret 3.5 million geospatial data points on a single, dynamic, digital map, something that had not been possible before.
The work was undertaken on behalf of Wood MacKenzie's clients in the oil and gas industry, but it seems it could be adapted and applied to the power and utility sector, particularly given development and growth of distributed energy resources, smart grids and customer-interactive power networks.
Wood MacKenzie's oil and gas industry clients "want to know just one thing— where to drill their next well. To answer that question, explorers need to be able to see the big picture— hot spots and trends— as well as being able to zoom in on the details of specific sites and wells," Wood MacKenzie relates in a Lens R&D news brief.
The market research and management consultancy outlined the GIS data visualization and interpretation challenge as follows:
Explorers want to be able to visualise 3.5 million wells in real time
A standard oil and gas map tops out at 30,000 to 50,000 data points
Processing, shipping and rendering 3.5 million data points was not possible using the industry-standard approach to natural resources mapping
The R&D then broke the challenge down into three facets:
Processing: How to process oil and gas well data quickly and efficiently
Shipping: How to group or cluster data points to make shipping easier
Rendering: How to visualise data in a granular way to answer customer need
Referring to Uber's real-time fleet maps and conferring with the company's GIS and computing specialists provided the key that enabled the Wood MacKenzie team to achieve the breakthrough. Doing so led the R&D team to Mapbox and Nico Belmonte, Uber's former head of data visualization.
Wood MacKenzie's R&D team tapped into Mapbox's GIS and data visualization tools, many of which were developed in open source settings. "The collaboration between Mapbox and Uber on Kepler and Deck.gl provided a jumping off point for the team's work," according to the R&D update.
They came up with a solution in just a few months. "The ultimate solution is an innovative combination of techniques and technologies: GPU-based parallel calculations, web graphics libraries and open-source streaming platforms," the team explains.
Looking forward, the Wood MacKenzie Lens team aims to enable end users to cross reference data in real time to answer just about any question regarding natural resources use, such as "How is the availability of gas and renewable energy going to impact coal demand?," according to the feature report.