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Title: Estimation of hydrologic properties of heterogeneous geologic media with an inverse method based on iterated function systems

Thesis/Dissertation ·
DOI:https://doi.org/10.2172/195663· OSTI ID:195663
 [1]
  1. Univ. of California, Berkeley, CA (United States). Dept. of Materials Science and Mineral Engineering

The highly heterogeneous nature of most geologic media, coupled with the restricted view of the subsurface available through boreholes, makes it difficult to determine the spatial distribution of subsurface hydrologic properties. Without such a description one cannot predict how fluid flow or solute transport will occur through permeable geologic media, and these predictions are critically needed to address many important environmental problems, including toxic chemical spills, leaking underground storage tanks, and long-term radioactive waste isolation. A common concern of these problems is the possible existence of high-permeability pathways connecting the problem to the biosphere. An understanding of flow and transport behavior is also necessary to optimize energy extraction from petroleum or geothermal reservoirs, where identifying low-permeability barriers that compartmentalize reservoirs and hamper efficient resource utilization is a key problem. The present work describes the development and application of a new inverse method for determining the spatial distribution of hydrologic properties (permeability and specific storage) in heterogeneous geologic media, using pressure transients from interference well tests. The method employs fractal concepts to improve efficiency and reliability. It is applicable to any sort of heterogeneous geologic medium in which wells communicate with each other, whether it be porous, fractured, or a combination thereof. Application to field data from a shallow aquifer at Kesterson Reservoir agrees well with an independent analysis using traditional well-test analysis methods. Application to a series of interference tests conducted at the Gypsy Pilot Site produces a detailed picture of the subsurface, which compares favorably with cross-well seismic imaging studies. 53 refs.

Research Organization:
Lawrence Berkeley National Lab. (LBNL), Berkeley, CA (United States)
Sponsoring Organization:
USDOE Office of Science (SC)
DOE Contract Number:
AC03-76SF00098
OSTI ID:
195663
Report Number(s):
LBL-38136; ON: DE96005819; TRN: AHC29605%%38
Resource Relation:
Other Information: TH: Thesis (Ph.D.); PBD: Dec 1995
Country of Publication:
United States
Language:
English