AV整氈窒

 

Carlos Wong

2018_WONG_MSc

B.Sc. (Honours) Thesis


(PDF - 7.5Mb)

The Carboniferous Joggins Formation outcrops along the shoreline of Chignecto Bay (Nova Scotia, Canada). The area of the Joggins Fossil Cliffs (UNESCO World Heritage Site) presents an outstanding set of channel and floodplain deposits, and fossilized tree trunks. This study focuses on the Coal Mine Point reference section, which comprises interbedded sandstone, shale and coal seams, and where accommodation was created by halokinetic activity (salt withdrawal). This study uses lidar to interpret the outcrop, augmented with gamma-ray and permeability data. Currently Joggins Fossil Cliffs records fossilized trees with a measured section log. With the use of lidar and spatially-calibrated Differential Global Positioning System (DGPS) to capture high-resolution images of meanderbelt channel architecture and fossils of upright lycopsids and calamitaleans. This imaging technique is an innovative approach and utilizes new technologies to provide a high-resolution 3D survey of the cliff (4 mm resolution at 100 m) detailing of channels and fossil tree trunks. Using the 3D survey coupled with other tools including scintillometer and permeameter, we can supplement data from the lidar scan and increase confidence of interpretations. Scintillometer measurements recorded at outcrop are used to generate a pseudo-gamma log and permeameter measurements were recorded to understand permeability of the corresponding lithologies. Lidar provided important information for rock properties and high detail of the outcrop that can used in the assessment of the reservoir characteristics of the Joggins Formation in Cole Mine Point section. Annual lidar surveys with scintillometer and permeameter will provide an informative data set to continue analysis and interpretations of the Joggins Fossil Cliffs.

Keywords: Bay of Fundy, Cumberland Basin, Joggins Fossil Cliffs, Joggins Formation, Carboniferous, Reservoir Characterization, Digital Outcrop Models, Permeability, Gamma-Ray, Lidar
Pages: 68
Supervisor: Grant Wach