Preprints
https://doi.org/10.5194/gmd-2021-66
https://doi.org/10.5194/gmd-2021-66

Submitted as: review and perspective paper 19 Apr 2021

Submitted as: review and perspective paper | 19 Apr 2021

Review status: a revised version of this preprint was accepted for the journal GMD and is expected to appear here in due course.

Spatial Agents for Geological Surface Modelling

Eric A. de Kemp Eric A. de Kemp
  • Geological Survey of Canada, Three-dimensional Earth Imaging and Modelling Lab 601 Booth Street, Ottawa, Canada, K0E 1E9

Abstract. Semi-autonomous software entities called spatial agents can be programmed to perform spatial and property interrogation functions, estimations and construction operations for simple graphical objects, that may be usable in building three-dimensional geological surfaces. These surfaces form the building blocks from which full topological models are built and may be useful in sparse data environments, where ancillary or a-priori information is available. Critical in developing natural domain models is the use of gradient information. Increasing the density of spatial gradient information (fabric dips, fold plunges, local or regional anisotropies) from geologic feature orientations (planar and linear) is key to more accurate geologic modelling, and core to the functions of spatial agents presented herein. This study, for the first time, examines the potential use of spatial agents to increase these types of gradient constraints in the context of the Loop 3D project (loop3d.org) in which new complementary methods are being developed for modelling complex geology for regional applications. The Spatial Agent codes presented may act to densify and supplement gradient and on contact control points used in LoopStructural (www.github.com/Loop3d/LoopStructural) and Map2Loop (https://doi.org/10.5281/zenodo.4288476). Spatial agents are used to represent common geological data constraints such as interface locations and gradient geometry, and simple but topologically consistent triangulated meshes. Spatial agents can potentially be used to develop surfaces that conform to reasonable geological patterns of interest, provided they are embedded with behaviors that are reflective of the knowledge of their geological environment. Initially this would involve detecting simple geological constraints; locations, trajectories and trends of geological interfaces. Local and global eigenvectors enable spatial continuity estimates which can reflect geological trends with rotational bias using a quaternion implementation. Spatial interpolation of structural geology orientation data with spatial agents employ a range of simple nearest neighbour to inverse distance weighted (IDW) and quaternion based spherical linear interpolation (SLERP) schemes. This simulation environment implemented in NetLogo is potentially useful for complex geology - sparse data environments where extension, projection and propagation functions are needed to create more realistic geological forms.

Eric A. de Kemp

Status: closed

Comment types: AC – author | RC – referee | CC – community | EC – editor | CEC – chief editor | : Report abuse
  • RC1: 'Comment on gmd-2021-66', Anonymous Referee #1, 15 Jul 2021
    • AC1: 'Reply on RC1', Eric de Kemp, 16 Aug 2021
  • RC2: 'Comment on gmd-2021-66', Guillaume Duclaux, 05 Aug 2021
    • AC2: 'Reply on RC2', Eric de Kemp, 16 Aug 2021

Status: closed

Comment types: AC – author | RC – referee | CC – community | EC – editor | CEC – chief editor | : Report abuse
  • RC1: 'Comment on gmd-2021-66', Anonymous Referee #1, 15 Jul 2021
    • AC1: 'Reply on RC1', Eric de Kemp, 16 Aug 2021
  • RC2: 'Comment on gmd-2021-66', Guillaume Duclaux, 05 Aug 2021
    • AC2: 'Reply on RC2', Eric de Kemp, 16 Aug 2021

Eric A. de Kemp

Eric A. de Kemp

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Short summary
This is a proof of concept and review paper of spatial agents with initial research focusing on geomodelling. The results may be of interest to others working on complex regional geological modelling with sparse data. Structural agent based swarming behaviour is key to advancing this field. The study provides groundwork for research in structural geology 3D modelling with spatial agents. This work was done with Netlogo a free agent modelling platform used mostly for teaching complex systems.