Gravity prospecting

James Conder
Southern Illinois University Carbondale,
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Students are given a set of gravity data with the aim of finding high density anomalies in the subsurface.
Keywords: Data analysis; inverse modeling

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Learning Goals

Students are expected to create a script that will objectively evaluate models of density against a data set.
Students are to create a visualization of their "best" answer.
Students must apply some critical thinking in that the "best" answer uses both objective (i.e., misfit to data) and subjective (e.g., how realistic) criteria.

Context for Use

The assignment was designed for first or second year grad students. It is to be done outside the classroom. I typically give the students one week to complete it. Students should be grasping the basics of scripting in MatLab and make use of vectorization. It draws from a geophysics backdrop, but can be straightforwardly used for any Data Analysis type class.

Description and Teaching Materials

As this is a data analysis exercise to be done outside class, only access to MatLab or other computing software is necessary. MatLab is preferred for its vectorization programming and ease of visualization, although there is no inherent reason other computing software couldn't be used.
Student handout for Gravity Prospecting assignment (Microsoft Word 2007 (.docx) 139kB Sep29 17)

instructor script (Matlab File 4kB Sep29 17)

Teaching Notes and Tips

Students tend to struggle with discretization. To get them started, it helps to draw a diagram of the target area broken into 12-16 boxes as a way to set up the problem. The attached solution uses inverse theory, but depending on their understanding of inverse theory, a grid search may be easier for some to tackle.


Students meet the goals of this assignment with a working script that gives a "reasonable" model of the subsurface and can explain how they came up with that particular solution - I.e., what subjective criteria did they include with the objective criteria?

References and Resources