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Three-Dimensional Modeling of Glacial Sediments Using Public Water-Well Data Records: an Integration of Interpretive and Geostatistical Approaches

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Three-Dimensional Modeling of Glacial Sediments Using Public Water-Well Data Records: an Integration of Interpretive and Geostatistical Approaches Three-dimensional modeling of glacial sediments using public water-well data records: An integration of interpretive and geostatistical approaches Erik R. Venteris Ohio Division of Geological Survey, 2045 Morse Road, Building C, Columbus, Ohio 43229, USA ABSTRACT and geophysics) are needed to parameterize Three-dimensional modeling techniques are facies simulations. essential for the mapping of surfi cial materi- Despite their importance to environmen- als due to the complexity of glacial sediments. tal issues and mineral resources, surfi cial Keywords: glacial sediments, geostatistics, hy- The glacial stratigraphy in Ohio is the result sediments are largely unmapped at depth drofacies, water wells, hydrogeology. of a lengthy depositional and erosional history in the United States. Full three-dimensional involving several oscillations of the Laurentide (3D) models of these materials are needed to INTRODUCTION ice sheet. This complexity is especially refl ected support hydrologic modeling, geotechnical in the sediments of the buried valleys, which engineering, and mineral-resource inven- Maps and models of surfi cial materials are typically contain alternating deposits of till, tory applications. The main source of infor- key to solving current problems in geology and lacustrine sediments, and >100-m-thick out- mation for such models in the Midwestern the environmental sciences. Hydrologic stud- wash. Such valleys are often a major source of United States is lithology logs from public ies that address issues such as water supply groundwater and the subject of numerical mod- water-well records. Three-dimensional mod- and non-point source pollution require accurate eling studies involving contaminant distribution eling of lithology was conducted to elucidate and realistic representations of unconsolidated and water supply. Three-dimensional geologic the nature and quality of spatial information sediments at depth. Surfi cial materials maps models are required to defi ne the physical char- sourced from water wells. The modeling was are also essential to engineering and geologic acteristics of this highly heterogeneous fl ow conducted on an ~130-km2 area near Lake hazard investigations such as risk assessments medium. In addition, 3D models reduce the Erie in northeast Ohio that contained an end for seismic damage and landslides. Despite abstraction inherent in traditional maps and moraine superimposed on a buried glacial the importance of surfi cial deposits, mapping cross sections, making such models invaluable valley. An integrated approach to 3D model- at depth is rare across the United States. When for describing and illustrating complex glacial ing was adopted where traditional interpre- available, surfi cial models are typically in the geology to the general public. tive techniques were used to defi ne glacial form of two-dimensional (2D) maps drawn at The quality and quantity of available data cre- stratigraphic units (glacial outwash, till, county and state scales. Such maps are common ates serious challenges to the mapping and mod- etc.) with geostatistical simulation of lithofa- for states with glacial deposits. An additional eling of surfi cial sediments. The main source of cies conducted within the stratigraphic lay- source, the digital soil survey (SSURGO, avail- data at depth for this and similar studies is lithol- ers. Despite the large amount of variability able from the United States Department of Agri- ogy logs from public water-well records (Ohio and noise inherent in water-well data, there culture, Natural Resource Conservation Service Department of Natural Resources Division of were statistical patterns in the lithology (Gabriel et al., 1992)), provides information at Water (ODOW), 2007). Well records contain records related to glacial stratigraphy. In the county scale to an average depth of ~1.5 m. lithologic information (sediment type, thick- contrast, the well data provided only mini- For most areas, the depth below the surveyed ness, and color) fi led by private water-well com- mal information on facies geometry within soil to the bedrock interface is unmapped. The panies. These wells have a typical spatial den- these units. The spatial structure of facies Ohio Division of Geological Survey is conduct- sity of four wells per square kilometer, which in the vertical direction was based on thick- ing three-dimensional (3D) mapping of surfi - has been found to be insuffi cient to characterize ness statistics from the water-well data and cial materials, 1:100,000-scale, as a fi rst step the lateral spatial structure of alluvial and bur- on geologic interpretation for the horizontal toward fi lling this knowledge gap (Venteris, ied valley sediments by traditional geostatisti- direction. Several sequential indicator simu- 2007; Schumacher, G.A., Venteris, E.R., and cal structural analysis (Weissmann et al., 1999; lation models were conducted to investigate Swinford, E.M., unpublished data, 2007). In Ritzi et al., 2000). The depths of these wells the effect of grid-cell thickness, stratigraphic addition to this work, quantitative techniques vary widely, but rarely extend beyond 50 m, trimming, and length-to-thickness ratios on for mapping are being investigated to better often leaving large intervals of buried valleys the reproduction of thickness statistics. This understand the spatial variability of glacial with little or no data upon which to constrain case study confi rms that water wells are a sediments and the quality of geologic informa- models. In addition, the lithologic information viable data source for stratigraphic model- tion available from lithology logs sourced from contained in individual water wells ranges in ing, but better data sources (e.g., outcrops public water-well databases. quality, from highly detailed borings that can Geosphere; December 2007; v. 3; no. 6; p. 456–468; doi: 10.1130/GES00090.1; 8 fi gures; 5 tables. 456 For permission to copy, contact [email protected] © 2007 Geological Society of America Downloaded from http://pubs.geoscienceworld.org/gsa/geosphere/article-pdf/3/6/456/854355/i1553-040X-3-6-456.pdf by guest on 25 September 2021 3D modeling of glacial sediments using water wells provide reliable information on both strati- water wells and current geophysical techniques area, a major north-south bedrock valley. The graphic units and facies, to clearly erroneous typically do not provide information of suffi - feature is approximately four miles wide and records. Careful evaluation and interpretation of cient quantity or quality to allow explicit map- contains up to 100 m of glacial sediments. The the water-well data set is required before their ping at facies scales. The multiple realizations valley is fi lled with till (overlying) and sand use. Water-well data can occasionally be sup- generated by geostatistical simulation provide and gravel deposits interbedded with lacustrine plemented from detailed borings (from private a method of accounting for facies heterogene- and probably remnant till facies (Venteris, sector studies, the Ohio Environmental Protec- ity that directly incorporates the considerable 2007). The area has been mapped at the surface tion Agency, or the Ohio Department of Trans- uncertainty into the workfl ow. Finally, simulat- many times (White and Totten, 1979; Pavey et portation), which contain penetration tests and ing lithology types rather than fl ow parameters al., 1999), but studies at depth have not been full laboratory analysis of texture. Such detailed allows the direct comparison of modeling results published. records were not available for the immediate to traditional geological maps and models (Ven- study area. teris, 2007). METHODOLOGY This work seeks to create 3D models based This work seeks to better understand the on water-well data using a combination of potential uses and limitations of water-well data Preprocessing of Well Data stratigraphic interpretation and geostatistical for the creation of 3D models at the stratigraphic simulation. Geologic interpretation, confi rmed and facies scales. It is critical to obtain a bet- The fi rst step in modeling was to convert the by statistical analysis of the well data, is used ter understanding of the information contained water-well data to a format appropriate for geo- to defi ne regions where the assumption of sta- within this data set. For much of the state of statistical modeling. The water-well database tionarity is reasonable (Carle et al., 1998, Weiss- Ohio, and most of the industrialized world, sim- from ODOW consisted of lithologies described mann and Fogg, 1999; Ritzi et al., 2000; Proce ilar well databases represent the main source of using three-letter codes (for example, CLA for et al., 2004). Facies heterogeneity is then mod- information about the shallow subsurface. clay and DRF for drift). For this study area, there eled within the defi ned stratigraphic units using were sixty-fi ve different codes describing sedi- sequential indicator simulation (SISIM). Study Area ment, rock, and anthropogenic material such as Spatial variability in lithology and hydrologic fi ll. These descriptions required simplifi cation parameters at the facies scale is usually mod- A buried valley near Lake Erie was the focus for modeling, a process that included interpre- eled using indicator geostatistics (Journel, 1983; of this modeling exercise, which was initially tation and generalization. A lookup table was Carle and Fogg, 1996; Ritzi et al., 2000). In this conducted to support qualitative mapping of created to reclassify
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