DigiFract: A software and data model implementation for flexible acquisition and processing of fracture data from outcrops
This paper presents the development and use of our new DigiFract software designed for acquiring fracture data from outcrops more efficiently and more completely than done with other methods. Fracture surveys often aim at measuring spatial information (such as spacing) directly in the field. Instead, DigiFract focuses on collecting geometries and attributes and derives spatial information through subsequent analyses. Our primary development goal was to support field acquisition in a systematic digital format and optimized for a varied range of (spatial) analyses. DigiFract is developed using the programming interface of the Quantum Geographic Information System (GIS) with versatile functionality for spatial raster and vector data handling. Among other features, this includes spatial referencing of outcrop photos, and tools for digitizing geometries and assigning attribute information through a graphical user interface. While a GIS typically operates in map-view, DigiFract collects features on a surface of arbitrary orientation in 3D space. This surface is overlain with an outcrop photo and serves as reference frame for digitizing geologic features. Data is managed through a data model and stored in shapefiles or in a spatial database system. Fracture attributes, such as spacing or length, is intrinsic information of the digitized geometry and becomes explicit through follow-up data processing. Orientation statistics, scan-line or scan-window analyses can be performed from the graphical user interface or can be obtained through flexible Python scripts that directly access the fractdatamodel and analysisLib core modules of DigiFract. This workflow has been applied in various studies and enabled a faster collection of larger and more accurate fracture datasets. The studies delivered a better characterization of fractured reservoirs analogues in terms of fracture orientation and intensity distributions. Furthermore, the data organisation and analyses provided more independent constraints on the bed-confined or through-going nature of fractures relative to the stratigraphic layering.
geologic field acquisition natural fracture description customizing gis data model and spatial analyses