Skip to main content
  • My Account
  • FAQ
  • About
  • Home
DigitalCommons@UTEP
Digital_Commons_UTEP
  • < Previous
  • Next >
  •  

Home > ENGINEERING > COMPUTER > CS_TECHREP > 640

Departmental Technical Reports (CS)

 

Title

Efficient Geophysical Technique of Vertical Line Elements as a Natural Consequence of General Constraints Techniques

Authors

Rolando Cardenas, University of Texas at El Paso
Martine Ceberio, University of Texas at El PasoFollow

Publication Date

8-2011

Comments

Technical Report: UTEP-CS-11-48

To appear in Journal of Uncertain Systems, 2012, Vol. 6, No. 2.

Abstract

One of the main objectives of geophysics is to find how density d and other physical characteristics depend on a 3-D location (x,y,z). In general, in numerical methods, a way to find the dependence d(x,y,z) is to discretize the space, and to consider, as unknown, e.g., values d(x,y,z) on a 3-D rectangular grid. In this case, the desired density distribution is represented as a combination of point-wise density distributions. In geophysics, it turns out that a more efficient way to find the desired distribution is to represent it as a combination of thin vertical line elements that start at some depth and go indefinitely down. In this paper, we show that the empirical success of such vertical line element techniques can be naturally explained if we recall that, in addition to the equations which relate the observations and the unknown density, we also take into account geophysics-motivated constraints.


Download
Find in your library

Included in

Computer Engineering Commons

Share

COinS
 
 
 

Follow

Advanced Search

 
  • Notify me via email or RSS

Links

  • Department of Computer Science Website

Browse

  • Collections
  • Subjects
  • Subjects
  • Authors
  • Years

Author Corner

  • Author FAQ
 

This collection is part of the
Digital Commons Network

Architecture • Arts and Humanities • Business • Education • Engineering • Law • Life Sciences
Medicine and Health Sciences • Physical Sciences and Mathematics • Social and Behavioral Sciences

Digital Commons

Home | About | FAQ | My Account | Accessibility Statement