AAPG Bulletin, V. 84, No. 6 (June 2000), P. 727-740.

Quantitative Structural Analysis with Stereoscopic Remote Sensing Imagery¹

Frank Bilotti,² John H. Shaw,³ and Peter A. Brennan⁴

©Copyright 2000. The American Association of Petroleum Geologists. All rights reserved.
¹Manuscript received June 18, 1998; revised manuscript received September 22, 1999; final acceptance November 15, 1999.
²Texaco Upstream Technology, 4800 Fournace Place, Bellaire, Texas 77401; e-mail: [email protected]
³Department of Earth and Planetary Sciences, Harvard University, 20 Oxford Street, Cambridge, Massachusetts 02138.
⁴Consultant, 5003 Plantation Colony Court, Sugar Land, Texas 77478.
We thank Alfredo Prelat and Jack Carnes for their support and encouragement in this project. Steve McDougall, Kristi Keller, and Glenn Winters introduced us to the study areas, and Chris Connors gave valuable guidance in merging remote sensing and subsurface structural inter pretations. Dave Schunk provided insight into stereo data and reviewed an early manuscript. Also, Jimmy Wang helped with image processing, and Steve Hook provided helpful comments on the manuscript. Landsat and NAPP data are available from the U.S. Geological Survey, EROS Data Center, Sioux Falls, South Dakota. SPOT data published with permission of SPOT Image Corp.

ABSTRACT

We employ powerful stereoscopic methods with satellite imagery to obtain surface bedding attitude measurements. These data are used to constrain geologic structures in three dimensions using quantitative structural models. We document a numerical method for measuring the strike and dip of bedding using stereoscopic pairs of air photos, as well as Landsat Thematic Mapper™ and SPOT™ images. In examples from the North American and Andean cordilleras, these remote measurements prove consistent with direct surface control and subsurface structures imaged in seismic reflection profiles. Remotely derived measurements are combined with subsurface data to generate balanced structural interpretations that define complex structural traps using fault-related folding theory. These remote sensing methods can provide a low-cost and rapid means of delineating prospects and leads.