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Identification of Subsurface Structure in United States Gulf Coast Using Remote-Sensing Imagery

D. A. Walker

Interpretation of remote-sensing imagery can identify surface indications of deep subsurface structures in the United States Gulf Coast. Structural growth can cause subtle changes in surface geology, topography, drainage patterns, vegetation, and soil moisture that are identifiable with Multispectral Scanner (MSS) Landsat and National High Altitude Photography Program (NHAP) images. Structural growth associated with salt diapirs, listric normal faults, and rollover anticlines has been identified in southeast Texas and southwest Louisiana with remote-sensing imagery.

Interactive computer manipulation effectively enhances such imagery. It enables the accurate integration of surface and subsurface data. By stacking geographically correlated data, explorationists can examine anomalous features from many different data, relating surface remote-sensing anomalies directly to subsurface structures. If an area lacks subsurface data, a remote-sensing lead can be used to guide subsurface data acquisition. MSS images are an effective reconnaissance tool enabling economical examination of the surface geology of entire basins. Their synoptic perspective makes them well suited for study of regional structural styles. NHAP images can give additional detailed geologic information about potential structures identified first from MSS images. Basins such as the Gulf Coast with unconsolidated surface units and dense vegetation can make remote-sensing analysis difficult. This problem can be overcome by integrating multiple image, surface, and subsurface data, to identify potential structures that previously had been overlooked.

AAPG Search and Discovery Article #91037©1987 AAPG Southwest Section, Dallas, Texas, March 22-24, 1987.