Implications for controls on Upper Cambrian microbial build-ups across multiple-scales, Mason County, Central Texas, USA

Acoustic impedance to outcrop: Presenting near-surface seismic data as a virtual outcrop in carbonate analog studies

“…Step 5: We spatially registered artificial outcrop photos generated from step 4B using the trace header of the AI section and treated them as geospatially aware outcrop photos. We constructed the virtual outcrop model from these imageries using a similar method to construct the digital outcrop model (Menegoni et al 2019;Khanna et al 2020;Thomas et al 2020). We then exported the model as cloud points that contain the spatial location (x, y, z) and RGB channel of each point (Figure 7).…”

Three-dimensional morphometric analysis and statistical distribution of the Early Kimmeridgian Hanifa Formation stromatoporoid/coral buildups, central Saudi Arabia

“…Drone and measured sections are utilized for continuous outcrop facies mapping, while geophysics and core data extend the facies mapping into the three dimensions behind the outcrop. model (DOM) using Pix4D® software, following the method reported in Khanna et al (2020) and Menegoni et al (2019). For data interpretation and further analysis, we imported the DOM into VRGS software®.…”

“…Ripley's K analysis (Ripley, 1981;Dixon, 2002) is a spatial statistic method commonly applied to investigate the clustering tendencies of spatially distributed point features. The method examines how the distribution of points changes with distance by comparing points located inside the circles of variable radius (centered at each data point) with points from a completely random distribution (Khanna et al, 2020). This method was utilized in outcrop studies such as by Khanna et al (2020) and Jacquemyn et al (2018) to investigate the clustering tendencies of microbial buildups and rudstone-filled scoured channels.…”

“…The method examines how the distribution of points changes with distance by comparing points located inside the circles of variable radius (centered at each data point) with points from a completely random distribution (Khanna et al, 2020). This method was utilized in outcrop studies such as by Khanna et al (2020) and Jacquemyn et al (2018) to investigate the clustering tendencies of microbial buildups and rudstone-filled scoured channels. This study employs a similar approach to calculate Ripley's K-function of the mapped buildup centroids.…”

Three-Dimensional Morphometric Analysis and Statistical Distribution of the Early Kimmeridgian Hanifa Formation Stromatoporoid/Coral Buildups, Central Saudi Arabia

“…Ripley's K analysis (Ripley, 1981;Dixon, 2002) is a spatial statistic method commonly applied to investigate the clustering tendencies of spatially distributed point features. The method examines how the distribution of points changes with distance by comparing points located inside the circles of variable radius (centered at each data point) with points from a completely random distribution (Khanna et al, 2020). This method was utilized in outcrop studies such as by Khanna et al (2020) and Jacquemyn et al (2018) to investigate the clustering tendencies of microbial buildups and rudstone-filled scoured channels.…”