H41E-0827
Using geophysical logs and Coupled Markov-chain method to map hydraulic property zones
A numerical model was required to evaluate groundwater resources in the southern New Castle County, Delaware. The major deposits in Delaware Coastal Plain sediments are a seaward-dipping wedge of alternating layers of sand, silt and clay. The accurate distribution of these materials is very hard, if not impossible, to be obtained based on limited drilling boreholes. To simplify the model, we defined four hydraulic property zones based on sand percentage: Poor (<25%), Normal (25%-50%), Good (50%-75%) and Very good (>75%). The objective of this project is to map the distribution of the hydraulic property zones. Geophysical logs have been widely used for many years to interpret/predict subsurface lithology. In this study, we compiled various geophysical logs (normal gamma, spontaneous-potential and normal-resisitivity logs) recorded from 98 boreholes to determine the sand percentage. And then a coupled Markov-Chain method was applied to generate the distribution of the hydraulic property zones conditional on calculated sand percentages.
H41E-0828
A Method to Estimate Hydraulic Conductivity From Bulk Geochemical Compositions
A method has been developed to estimate hydraulic conductivity in fine-grained unconsolidated aquifers. The method uses bulk geochemical compositions correlated with hydraulic conductivities measured by field pumping tests. The concept is based on a general rule that hydraulic conductivity is principally controlled by grain size distribution and particle shape, which relate to mineralogical composition. After the conversion from bulk chemical compositions to normative mineralogical assemblages using MINLITH algorithm, the hydraulic conductivity (K in cm/s) can be expressed as a linear logarithmic equation to earthy mineral content (E in weight percent): logK=-1.292-0.0581E. This equation should not be applied to aquifers composed of medium and coarser grain sizes due to interference from lithic fragments. In addition, this equation tends to overestimate hydraulic conductivity possibly because the effect of compaction is ignored in this study. To correlate more data from high-resolution profiling tests with sediment geochemical compositions may overcome the difficulty in overestimation.
H41E-0829
A Comparison of Groundwater Fluxes Computed with MODFLOW and a Stable Isotope Mixing Model: Application to the Eastern Nevada Test Site and Vicinity
The primary objective of this study was to compare groundwater flows in the vicinity of the eastern Nevada Test Site (NTS) computed with a hydraulically defined groundwater flow model against those predicted with an isotopically based mixing model. The US Geological Survey (USGS) Death Valley Regional Flow Model (DVRFM) is a transient, three-dimensional, groundwater model that uses the public domain, finite difference code MODFLOW. The second model (Discrete-State Compartment Model-Shuffled Complex Evolution; DSCM-SCE) is a recently developed code that auto-calibrates groundwater flows (both magnitude and direction) using a steady- state mixing algorithm to best match observed conservative tracer concentrations in groundwater. The model can be calibrated based on data for multiple tracers with tracer concentrations considered either independent or fully covariant. To compare modeling approaches, DVRFM boundary conditions and cell-to-cell interactions were used in the DSCM-SCE's 15-cell eastern NTS model. Analysis of δD and δ18O data conducted throughout the model domain suggests recharge and mixing may be the dominant mechanisms for groundwater isotopic enrichment in the down gradient direction. Model results show that DVRFM boundary fluxes and cell outflows match representative groundwater isotopic values relatively well. However, optimization on data for an individual isotope lowered the objective function, while combining δD and δ18O independently produced the least error. Large uncertainty in the estimated covariant relationships between δD and δ18O prohibited development of a unique DSCM-SCE solution. Results suggest error exists in estimated DVRFM boundary conditions associated with three of the fifteen modeled basins, while the lack of isotopic data in several basins defining the eastern edge of the model prevents certitude of results pertaining to fluxes in this portion of the model. Future work will look at the uncertainty associated with boundary conditions and what data will better constrain the model for improved fit.
H41E-0830
Study on Potential Changes in Geological and Disposal Environment Caused by 'Natural Phenomena' on a HLW Disposal System
We have developed a formal evaluation method to assess the potential impact of natural phenomena (earthquakes and faulting; volcanism; uplift, subsidence, denudation and sedimentation; climatic and sea-level changes) on a High Level Radioactive Waste (HLW) Disposal System. In 2000, we had developed perturbation scenarios in a generic and conservative sense and illustrated the potential impact on a HLW disposal system. As results of the development of perturbation scenarios, two points were highlighted for consideration in subsequent work: improvement of the scenarios from the viewpoints of reality, transparency, traceability and consistency and avoiding extreme conservatism. Subsequently, we have thus developed a new procedure for describing such perturbation scenarios based on further studies of the characteristics of these natural perturbation phenomena in Japan. The approach to describing the perturbation scenario is effectively developed in five steps: Step 1: Description of potential process of phenomena and their impacts on the geological environment. Step 2: Characterization of potential changes of geological environment in terms of T-H-M-C (Thermal - Hydrological - Mechanical - Chemical) processes. The focus is on specific T-H-M-C parameters that influence geological barrier performance, utilizing the input from Step 1. Step 3: Classification of potential influences, based on similarity of T-H-M-C perturbations. This leads to development of perturbation scenarios to serve as a basis for consequence analysis. Step 4: Establishing models and parameters for performance assessment. Step 5: Calculation and assessment. This study focuses on identifying key T-H-M-C process associated with perturbations at Step 2. This framework has two advantages. First one is assuring maintenance of traceability during the scenario construction processes, facilitating the production and structuring of suitable records. The second is providing effective elicitation and organization of information from a wide range of investigations of earth sciences within a performance assessment context. In this framework, scenario development work proceeds in a stepwise manner, to ensure clear identification of the impact of processes associated with these phenomena on a HLW disposal system. Output is organized to create credible scenarios with required transparency, consistency, traceability and adequate conservatism. In this presentation, the potential impact of natural phenomena in the viewpoint of performance assessment for HLW disposal will be discussed and modeled using the approach. http://www.jaea.go.jp/
H41E-0831
Coupled inverse geochemical and microbial reactive transport models in porous media
Microbial processes play a major role in controlling geochemical conditions in subsurface systems. Various laboratory and in situ experiments have been performed to evaluate the relevance of microbial processes and derive key microbial parameters. Such experiments are often interpreted by suboptimal trial-and-error curve fitting. Here we present an inverse model for coupled flow, reactive solute transport, geochemical and microbial processes which overcomes the limitations of trial-and-error methods by making data interpretation in a systematic, objective, and efficient manner. It extends the capabilities of existing inverse models which deal mostly with flow and chemically-reactive solute transport. Our inverse model relies on the microbial reactive transport code BIOCORE of Samper et al. (2006a) and improves the inverse reactive transport model INVERSE- CORE of Dai and Samper (2004) by allowing the simultaneous estimation of geochemical and microbial parameters. The inverse model has been implemented in a finite element code, INVERSE-BIOCORE2D and its capabilities have been verified and tested with a synthetic experiment involving equilibrium speciation, kinetic sorption/desorption and kinetic biodegradation reactions. Model results indicate that both chemical and microbial parameters can be estimated accurately for error-free data. Estimation errors of microbial parameters are larger than those of kinetic sorption parameters and generally increase with increasing standard deviation of data noise. Estimation error of yield coefficient is the smallest among all microbial parameter and which does not depend on data noise. The inverse model has been used also to estimate microbial parameters of a laboratory experiment involving sucrose fermentation by yeast. Inverse estimation improves significantly the fit to measured data.
H41E-0832
GEOPHYSICS IN HYDROGEOLOGICAL INVERSE PROBLEM: HERO OR VILLAIN?
Geostatistical inverse problem is a powerful tool to aid decision-makers in aquifer management. During the last few years, existing inverse problem codes have been updated in order to accommodate "non- traditional" types of observations (i.e. heads or concentrations). The potential of exhaustive geophysical data has been shown to be well-suited for aquifer characterization. However, limited attention has been devoted to the use of this information in real field hydrogeological inverse problems. In this work, we present an application of inverse problem to the management of coastal aquifers including different types of data (heads, resistivities and prior information on transmissivity and storage coefficient). Spatial variability is characterized using the regularized pilot points method. The procedure is as follows. First, we obtain a characterization of the transmissivity and storage coefficient fields from calibration data. Second, this characterization is used to design a pumping network by means of a genetic algorithm. Several constraints apply, such as operational costs or environmental side effects. Three cases are presented, depending on the calibration data sets: (1) only resistivities (no calibration is performed), (2) heads and prior information of model parameters, and (3) all of them altogether (resistivities are used as external drift). Results show that, by themselves, resistivity or head data sets (and prior information) do not suffice to obtain a reliable characterization of the system. However, the consideration of all data at the same time leads to the best characterization of the system among the ones tested.
H41E-0833
Screening Models of Aquifer Heterogeneity Using the Flow Dimension
Despite advances in test interpretation and modeling, typical groundwater modeling studies only indirectly use the parameters and information inferred from hydraulic tests. In particular, the Generalized Radial Flow approach to test interpretation infers the flow dimension, a parameter describing the geometry of the flow field during a hydraulic test. Noninteger values of the flow dimension often are inferred for tests in highly heterogeneous aquifers, yet subsequent modeling studies typically ignore the flow dimension. Monte Carlo analyses of detailed numerical models of aquifer tests examine the flow dimension for several stochastic models of heterogeneous transmissivity, T(x). These include multivariate lognormal, fractional Brownian motion, a site percolation network, and discrete linear features with lengths distributed as power-law. The behavior of the simulated flow dimensions are compared to the flow dimensions observed for multiple aquifer tests in a fractured dolomite aquifer in the Great Lakes region of North America. The combination of multiple hydraulic tests, observed fracture patterns, and the Monte Carlo results are used to screen models of heterogeneity and their parameters for subsequent groundwater flow modeling.
H41E-0834
Fast vertical movement of groundwater at the borehole in volcanic confined aquifer detected from point-dilution test with multi-level observations
A point-dilution tracer test was performed at a Seokwang well field, one of the pulbic water supply system for southwestern part of Jeju island, South Korea. Seokwang well field is located at the elevation of about 180 m above mean sea level with gentle tilted surface topography to southwest direction. Based on the geological columnar section of supply well no. 3, Seokwang well field area is consisted of Basalt, tuff, clinker, and soil layer. various types of basalt such as trachy basalt, feldspar augite basalt, feldspar basalt and soil layers occurred overlapping each other and clinker zone act as permeable aquifer whereas tuff act as impermeable confining layer. 20 cubic meter's tracer solution as NaCl is injected through pipe at the depth of 170 m below top of the casing using pump and the EC breakthroughs at 18 different depths in the borehole BH3 are monitored using 5 CTD Divers and 13 series of EC sensors. The injected tracer solution transported vertically upward from the injection depth with slight downward movement of about 1 meter from the mouth of the injection pipe due to the force of inertia and gravity. The estimated vertical velocity of groundwater is 1.33 x 10-2 m/s (\ 0.424 L/s )\) , which was too fast to be detected by borehole logging using heat pulse type flowmeter.
H41E-0835
Subsurface Characterization using Sensitivity based Pilot Point Methods
A large number of contaminated groundwater sites suffer from insufficient hydraulic property information leading to inefficient cleanup strategies and inaccurate prediction of contaminant fate and transport. Thus, significant researches have focused on developing efficient parameter estimation methods to obtain accurate subsurface hydraulic properties (i.e., hydraulic conductivity or permeability) from secondary measurements such as hydraulic head and/or tracer/contaminant concentrations. Due to the limited amount of information and their associated uncertainty, these problems are often ill posed and non-unique. To minimize these shortcomings, many methods have been developed including a class of methods called the pilot point methods (PPMs). The physical meaning of pilot points is that they are not direct measurement points; rather these are strategically selected points in the domain and are added to the parameter searching procedure to reduce ill-posedness. In the context of subsurface characterization, this method can provide improved estimates of hydraulic conductivity distribution by combining direct measurements of hydraulic conductivity with secondary measurements. In this study, an evolutionary algorithm based PPM using the D-Optimality sensitivity criterion is developed. This method is based on searching for a collection of pilot points that have the greatest influence on secondary information with slight perturbation of hydraulic conductivities. Thus, this criterion maximizes the dataworth of the secondary measurement (e.g., hydraulic head) while minimizing the impact to the original covariance structure of measured hydraulic conductivities. Four different synthetic scenarios were built and used to explore the effectiveness of this method in finding suitable pilot points for hydraulic conductivity estimation. Results show that pilot point selection using the D-optimality criterion can lead to improved hydraulic conductivity characterization than either a random pilot point selection method or a sequential sensitivity based PPM developed previously. Final hydraulic conductivity distributions obtained using our method are shown to be very close to the synthetically generated unknown reality.