SMU Data Science Review

Automated Interactive 3D Geospatial Data Assimilation, Formatting and Visualization System for Development of Subsurface Conceptual Site Models

AARON CATTLEY, Southern Methodist UniversityFollow
Gavin HudgeonsFollow
Bruce LeeFollow

Abstract

The natural evolution of the collection and storage of sub- surface data in Texas has resulted in the current state where data for certain resources, such as water resources, have not been assimilated with state oil and gas and injection data in a meaningful way that allows for rapid understanding and data analysis for a physical land site. The consequences that result due to data from different spheres not being in sync are often duplication of work being performed but not in a consistent manner. However, the reality is that the infrastructure and impacts of these sectors are deeply intertwined. Lack of understanding of each sector can lead to massive revenue loss and damage to natural resources. Even the regulatory agencies who issue the permits designed to protect resources are not aware of what is going on. Additional consequences that result from not being on the same page are duplication of unnecessary expensive permits, failed groundwater protection and freshwater exploitation. What we propose to develop is a midstream product that assimilates these disparate data resources into an end-user centric data assimilation, visualization, and analysis service. This product would not only provide a one stop solution for customers, but also alleviate wasted costs and help preserve the environment.

Recommended Citation

CATTLEY, AARON; Hudgeons, Gavin; and Lee, Bruce (2020) "Automated Interactive 3D Geospatial Data Assimilation, Formatting and Visualization System for Development of Subsurface Conceptual Site Models," SMU Data Science Review: Vol. 3: No. 2, Article 14.
Available at: https://scholar.smu.edu/datasciencereview/vol3/iss2/14