Abstract
Generating a realistic model of subsurface stratigraphy that fits data from multiple well locations is a well-established problem in the field of aquifer characterisation. This is particularly critical for the alluvial fan-hosted aquifers in northwestern India, as they have some of the highest rates of groundwater extraction in the world and spatially limited subsurface observations. The objective of this study is to develop a reduced-complexity model that generates probabilistic estimates of aquifer body occurrence within a sedimentary fan, based loosely on the northwestern Indian aquifer system. We propose a parsimonious, inverse-weighted random walk model that reconstructs potential channel belt pathways within a discrete depth range or slice by (i) connecting known aquifer locations with the fan apex, (ii) filling adjacent cells with non-aquifer material based on estimated channel-body dimensions, and (iii) random filling of the remaining cells until the model fraction of aquifer material is comparable to the bulk aquifer fraction observed from well data. Once filled, individual depth slices can be stacked to produce a three-dimensional representation of aquifer-body geometry, allowing informed inference and testable predictions about the configuration of aquifer units in the subsurface. A receiver operating characteristic (ROC) curve shows that the model performs better than fully random filling, both in matching the locations of aquifer material in the subsurface and in reconstructing the geometry of relict channel bodies preserved on the fan surface. The model differs from purely statistical-empirical approaches by incorporating some geomorphic knowledge of fluvial channel belt geometry within the fan system. In contrast to a fully process-based approach, the model is computationally fast and is easily refined as new subsurface data become available.
Highlights
Here we propose a physically-based heuristic model that predicts the potential aquifer body distribution through incorporating our best process understanding of how the aquifer system forms into a reduced-complexity model
We show how two-dimensional sediment routing assump125 tions in a given depth slice can be used to build a three-dimensional picture of the 126 subsurface stratigraphy
We have shown that the subsurface distribution of aquifer corridors across the Sutlej and Yamuna fans in northwestern India can be reconstructed by a reduced779 complexity probabilistic model that incorporates some degree of geological knowl780 edge of the depositional system
Summary
The paucity of subsurface data in many alluvial aquifer systems, and the predominance of elongate channel body aquifers, preclude simple lateral correlation between aquifer bodies recorded 21 in different wells, while the lack of detailed lithological data, including age con straints, may preclude the use of more sophisticated forward models that could simulate aquifer-system deposition and development. Previous approaches to this problem can be divided into structure-imitating, process-imitating, and descriptive methods (Koltermann and Gorelick, 1996; de Marsily et al, 2005). Statistical structure-imitating methods include traditional two-point kriging or conditional methods (e.g., Isaak and Sri vastava, 1990; Journel, 1988) and modern multi-point statistical (MPS) methods (e.g., Guardiano and Srivastava, 1993; Caers, 2001; Strebelle, 2002; Wu et al, 2008; Comunian et al, 2012; Rezaee et al, 2013; Mariethoz and Lefebvre, 2014)
Sign-in/Register to view highlights & summary Talk to us
Join us for a 30 min session where you can share your feedback and ask us any queries you have
Schedule a callDisclaimer: All third-party content on this website/platform is and will remain the property of their respective owners and is provided on "as is" basis without any warranties, express or implied. Use of third-party content does not indicate any affiliation, sponsorship with or endorsement by them. Any references to third-party content is to identify the corresponding services and shall be considered fair use under The CopyrightLaw.
