Pumping tests in networks of multilevel sampling wells: Motivation and methodology

Citation
Jj. Butler et al., Pumping tests in networks of multilevel sampling wells: Motivation and methodology, WATER RES R, 35(11), 1999, pp. 3553-3560
Citations number
34
Categorie Soggetti
Environment/Ecology,"Civil Engineering
Journal title
WATER RESOURCES RESEARCH
ISSN journal
00431397 → ACNP
Volume
35
Issue
11
Year of publication
1999
Pages
3553 - 3560
Database
ISI
SICI code
0043-1397(199911)35:11<3553:PTINOM>2.0.ZU;2-A
Abstract
The identification of spatial variations in hydraulic conductivity (K) on a scale of relevance for transport investigations has proven to be a conside rable challenge. Recently, a new field method for the estimation of interwe ll variations in K has been proposed. This method, hydraulic tomography, es sentially consists of a series of short-term pumping tests performed in a t omographic-like arrangement. In order to fully realize the potential of thi s approach, information about lateral and vertical variations in pumping-in duced head changes (drawdown) is required with detail that has previously b een unobtainable in the field. Pumping tests performed in networks of multi level sampling (MLS) wells can provide data of the needed density if drawdo wn can accurately and rapidly be measured in the small-diameter tubing used in such wells. Field and laboratory experiments show that accurate transie nt drawdown data can be obtained in the small-diameter MLS tubing either di rectly with miniature fiber-optic pressure sensors or indirectly using air- pressure transducers. As with data from many types of hydraulic tests, the quality of drawdown measurements from MLS tubing is quite dependent on the effectiveness of well development activities. Since MLS ports of the standa rd design are prone to clogging and are difficult to develop, alternate des igns are necessary to ensure accurate drawdown measurements. Initial field experiments indicate that drawdown measurements obtained from pumping tests performed in MLS networks have considerable potential for providing valuab le information about spatial variations in hydraulic conductivity.