Predicting Collector Well Yields with MODFLOW

Abstract

Groundwater flow models are commonly used to design new wells and wellfields. As the spatial scale of the problem is large and much local-scale detail is not needed, modelers often utilize two-dimensional (2D) or quasi three-dimensional models based on the Dupuit-Forchheimer assumption. Dupuit models offer a robust set of tools for simulating regional groundwater flow including interactions with surface waters, the potential for well interference, and varying aquifer properties and recharge rates. However, given an assumed operating water level or drawdown at a well screen, Dupuit models systematically overpredict well yields. For design purposes, this discrepancy is unacceptable, and a method for predicting accurate well yields is needed. While published methods exist for vertical wells, little guidance is available for predicting yields in horizontal screens or collector wells. In plan view, a horizontal screen has a linear geometry, and will likely extend over several neighboring cells that may not align with rows or columns in a numerical model. Furthermore, the model must account for the effects of converging three-dimensional (3D) flow to the well screens and hydraulic interference among the well screens; these all depend on the design of a specific well. This paper presents a new method for simulating the yield of angled or horizontal well screens in numerical groundwater flow models, specifically using the USGS code MODFLOW. The new method is compared to a detailed, 3D analytic element model of a collector well in a field of uniform flow.

Review: Horizontal, directionally drilled and radial collector wells

“…Compared to the analytical models presented above, numerical models are more flexible with regard to the geometries of the HW and the types and locations of boundary conditions that can be treated. All types of grid discretization have been used for numerical modeling of RCW, finite difference (Eberts and Bair 1990;Cunningham et al 1995;Kawecki and Al-Subaikhy 2005;Mohamed and Rushton 2006;Su et al 2007;Patel et al 2010;Kelson 2012;Collins and Houben 2020;Božović et al 2020), polygon finite difference (Chen et al 2003), finite element (Ophori and Farvolden 1985;Birch et al 2007;Lee et al 2010Lee et al , 2012Dimkić et al 2013) and finite volume (Hayati-Jafarbeigi et al 2020). In rectangular finite difference (FD) grids, RCW laterals may not align with the rows and columns of the model grid, or in other words, are not at right angles to the grid cells.…”

“…In rectangular finite difference (FD) grids, RCW laterals may not align with the rows and columns of the model grid, or in other words, are not at right angles to the grid cells. This can be problematic, especially when modeling converging flow to a lateral and require additional grid refinement (Kelson 2012).…”

“…The effects of a skin layer was also addressed. Kelson (2012) proposed using a head-dependent flux boundary condition for the laterals within a Dupuit model. For his MODFLOW model he chose the DRN package.…”

Estudo experimental e de modelagem matemática do escoamento subterrâneo em uma vertente de zona ripária no bioma Cerrado

“…A modelagem matemática hidrogeológica abrange ainda a identificação de alternativas locacionais para perfuração de poços de abastecimento, avaliação de técnicas de recuperação de água subterrânea, delimitação de zonas de contribuição de poços e otimização no gerenciamento dos recursos hídricos (Cleary, 1989;Gao, 2011;Levy e Xu, 2012;Kelson, 2012;Ireson et al, 2013). As vantagens dos modelos matemáticos residem em sua versatilidade, quando comparados aos modelos físicos e analógicos, e estrutura lógica e de fácil alteração, fornecendo resultados para diferentes cenários num mesmo sistema.…”

“…Zheng (2011) afirma que a partir de 1990 a capacidade de aplicação dos modelos de fluxo e transporte foi ampliada em função da integração com interfaces de SIG, sofisticação e facilidade de uso das interfaces gráficas dos programas de modelagem; aumento dos modelos com acoplagem dos processos hidrológicos subterrâneos e superficiais e de transporte; aumento na acessibilidade de bancos dados; e intensificação no desenvolvimento de alternativas de solução das equações diferenciais parciais. Atualmente os modelos numéricos têm demonstrado ampla utilização em estudos de fluxo de água no solo (Rodriguez et al, 2008;Gao, 2011;Levy e Xu, 2012;Kelson, 2012;Ireson et al, 2013). Por fim, é importante evidenciar as colocações de Bronstert et al (1998).…”