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DOE OSTI2020

Vadose Zone Model for A Trenches Area for Composite Analysis

The objectives of the vadose modeling for the updated Hanford Site composite analysis (CA) are to simulate the flow and transport of water and radionuclide releases from the surface to the water table and to provide radionuclide transfer rates for the plateau to river (P2R) model, version 8.3. Water additions include natural recharge and water discharged to the ground as a result of industrial processes associated with Hanford Site operations. Contaminant sources include radionuclides in water discharged to the ground during operations and radionuclides disposed “dry” in solid waste burial grounds or other means. The parallel version of the Subsurface Transport Over Multiple Phases (STOMP) simulator, officially named the exascale Subsurface Transport Over Multiple Phases (eSTOMP), is used to simulate flow and transport for the vadose models. The scope of this ECF is to document the development and results of the A Trenches Area vadose zone model. The A Trenches Area model covers the region between the 200 East Area and southwest of the 216-B-3 Pond. The primary waste sites in this area are cribs associated with PUREX Plant (202-A).

12 MANAGEMENT OF RADIOACTIVE AND NON-RADIOACTIVE W↗

DOE OSTI2020

Modeling Efforts to Gain Insight into Historical Leak Events from the Single-Shell Tank A-105 in the Hanford 241-A Tank Farm - 20113

The 241-A Tank Farm is a single-shell tank (SST) farm constructed to store process waste from Hanford nuclear operations. Millions of gallons of nuclear waste were stored in the 241-A Tank Farm SSTs and some of the SSTs leaked in the past. In addition, spills and pipeline leaks during transfers and storage and intentional discharges to cribs and trenches resulted in releasing waste to the ground. Tank liner leaks are referred to as 'leaks' and all other discharges to the soil are referred to as 'releases.' Liquid waste that could be removed by pumping has been removed from all of the SSTs to reduce the potential for future leaks. The most significant historical leak event in 241-A Tank Farm occurred in 1965 when tank A-105 experienced a pressurized steam event. This event resulted in damage to the inner steel liner flooring of A-105, which was separated from the sidewalls over part of its circumference and buckled up to 2.5 m, vertically. During this event up to 7,570 L of contaminated liquid may have leaked to the adjacent soil. This leak occurred under extreme temperature and pressure conditions. Modeling efforts to better understand the nature and extent of historical leaks from subsurface SSTs that were used to store highly radioactive, self-boiling liquid wastes at 241-A Tank Farm have recently been undertaken. These efforts have compiled the available historical information to support a preliminary non-isothermal, multiphase flow and chemical transport modeling effort to re-create the conditions under which the leaks occurred and to formulate a conceptual model as to the extent and distribution of leaked radioactive contaminants in the adjacent soil material. The focus of this work was on developing an understanding of the key features, processes and bounding conditions related to tank A-105 leak events that occurred in the 1960's. The activities include estimation of leak composition, non-isothermal multiphase flow and transport modeling, and geochemical modeling. The STOMP{sup C} Water-Air-Energy modeling code was utilized to implement the three-dimensional representation of the subsurface tank and the surrounding flow field. Once constructed, the model was used to evaluate the conceptual understanding of leaks originating from different parts of the tank under the elevated temperature boundary conditions that were imposed by surrounding tanks at the time of the historical leaks. The chemical evolution of the liquid waste was also evaluated as it leaked from the tank under transient pressure and temperature gradients. The results of the preliminary evaluation suggested the presence of a heat-pipe effect beneath tank A-105 in which water vapor at an elevated temperature is driven away from the base of the tank to a position where water vapor cools, condenses and is then drawn back toward the tank by the strong capillary attraction of the dry soil. A non-sorbing contaminant (Tc-99) was introduced into this flow field to better understand the potential distribution patterns of leaked contaminants that may have occurred during the historical leak events. (authors)

12 MANAGEMENT OF RADIOACTIVE AND NON-RADIOACTIVE W↗

DOE OSTI2022

Coupling subsurface and above-surface models for optimizing the design of borefields and district heating and cooling systems in the presence of varying water-table depth. In: Proceedings, 46th Workshop on Geothermal Reservoir Engineering

Dynamic energy simulation is important for the design and sizing of district heating and cooling systems with geothermal heat exchange. Current modeling approaches in building and district energy simulation tools typically consider heat conduction through the ground between boreholes, without flow of groundwater. On the other hand, detailed simulation tools for subsurface heat and mass transfer exist, but these fall short in simulating above-surface energy systems. To support the design and operation of such systems, we have developed a coupled model including a software package for building and district energy simulation, and software for detailed heat and mass transfer in the ground. For the first, we use the open-source Modelica Buildings Library, which includes dynamic simulation models for building and district energy and control systems. For the heat and mass transfer in the soil, we use the TOUGH simulator. TOUGH can model heat and multi-phase, multi-component mass transport for a variety of fluid systems, as well as chemical reactions, in fractured porous media. In previous work, we described the coupling of these software packages, including how time-dependent boundary conditions for the borehole walls are synchronized for use in Modelica and TOUGH. We verified that the coupled Modelica/TOUGH code produced consistent results with the original Modelica code for an idealized problem in which heat transfer was purely by conduction in a uniform geologic medium. Here, we examine less idealized problems for which TOUGH’s advanced capabilities for modeling fluid flow are required. The first problem has a shallow vadose zone, and the second problem has a thicker vadose zone with a water-table depth that varies in time, which requires a fine vertical grid discretization for the TOUGH model.

Doughtry, Christine↗

DOE OSTI2018

Kinetics of D/H isotope fractionation between molecular hydrogen and water

At equilibrium, the D/H isotope fractionation factor between H 2 and H 2 O (α H 2 O-H 2 (eq) ) is a sensitive indicator of temperature, and has been used as a geothermometer for natural springs and gas discharges. However, δD H 2 measured in spring waters may underestimate subsurface temperatures of origin due to partial isotopic re-equilibration during ascent and cooling. In this work, we present new experimental data on the kinetics of D–H exchange for H 2 dissolved in liquid water at temperatures below 100 °C. Comparing these results with published exchange rates obtained from gas phase experiments (100–400 °C), we derive a consistent activation energy of 52 kJ/mol, and the following rate expressions; ln k =9.186 - 6298/ T and k 1 = 9764.61[H 2 O] e-6298/ T where T is absolute temperature (K), k is the universal rate constant ([L/mol]/hr), and k 1 is a pseudo-first-order constant (hr -1 ) applicable to water-dominated terrestrial systems by constraining [H 2 O] as the density of H 2 O (in mol/L) at the P-T of interest. The density-dependent rate constant accounts for the kinetic disparity of D–H exchange with H 2 when dissolved in liquid H 2 O relative to a gas/steam phase, exemplifed by 1/ k 1 at 100 °C of ~2 days in liquid, versus ~7 yrs in saturated steam. This difference may explain the high variability of δDH 2 observed in fumarolic gases. Fluids convecting in the crust frequently reach T > 225 °C, where isotopic equilibrium is rapidly attained (<1 hr). We compare fractionation factors measured in natural fluids (α OBS ) with values expected for equilibrium at the T of acquisition. Where these values differ, we use kinetic models to estimate cooling rates during upward advection that account for the observed disequilibrium. Models fit to fluids from Yellowstone Park and the Lost City (deep-sea) vent field, both recovered at ~90 °C, require respective transit times of ~7 hrs and ~11 days between higher temperature reaction zones and the surface. Using estimates of subsurface depths of origin, however, suggests similar mean fluid flow rates (10 s of meters/hr). Additional complications must be considered when interpreting the δDH 2 of lower-temperature effluent. When applied to data from deep-sea hydrothermal systems, our kinetic models indicate microbial catalysis accelerates D–H exchange once fluids cool below ~60 °C. The H 2 measured in both continental alkaline springs and fracture fluids from Precambrian shield rock is likely produced at T < 100 °C, through processes such as serpentinization. In these settings, δDH 2 values appear closer to equilibrium with H 2 O than those from geothermal systems. Considering kinetic isotope effects may yield H 2 that is out of equilibrium when generated at lower temperatures, we calculate maximum (isothermal) times to apparent isotopic equilibrium of 1.3 yrs at 50 °C, 9 yrs at 25 °C, and 35 yrs at 10 °C. A similar calculation applied to Antarctic brines (-13 °C), where measured δDH 2 is far from equilibrium, yields ~350 yrs. This time is shorter than the fluids have been isolated (2.8 ka), suggesting kinetic isotope effects associated with H 2 destruction or loss via diffusion may also be possible.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗

DOE OSTI2015

Surface and subsurface cracks characteristics of single crystal SiC wafer in surface machining

Different machining processes were used in the single crystal SiC wafer machining. SEM was used to observe the surface morphology and a cross-sectional cleavages microscopy method was used for subsurface cracks detection. Surface and subsurface cracks characteristics of single crystal SiC wafer in abrasive machining were analysed. The results show that the surface and subsurface cracks system of single crystal SiC wafer in abrasive machining including radial crack, lateral crack and the median crack. In lapping process, material removal is dominated by brittle removal. Lots of chipping pits were found on the lapping surface. With the particle size becomes smaller, the surface roughness and subsurface crack depth decreases. When the particle size was changed to 1.5µm, the surface roughness Ra was reduced to 24.0nm and the maximum subsurface crack was 1.2µm. The efficiency of grinding is higher than lapping. Plastic removal can be achieved by changing the process parameters. Material removal was mostly in brittle fracture when grinding with 325# diamond wheel. Plow scratches and chipping pits were found on the ground surface. The surface roughness Ra was 17.7nm and maximum subsurface crack depth was 5.8 µm. When grinding with 8000# diamond wheel, the material removal was in plastic flow. Plastic scratches were found on the surface. A smooth surface of roughness Ra 2.5nm without any subsurface cracks was obtained. Atomic scale removal was possible in cluster magnetorheological finishing with diamond abrasive size of 0.5 µm. A super smooth surface eventually obtained with a roughness of Ra 0.4nm without any subsurface crack.

36 MATERIALS SCIENCE↗

DOE OSTI2021

DVRFS Microbiome 2021 Manuscript Code

These scripts document the code used to analyze the Death Valley Regional Flow System (DVRFS) microbial community for a manuscript titled "Subsurface Planktonic Microbial Communities Reflect Regional-Scale Groundwater Hydraulic Connectivity".

Merino, NancyS.↗

DOE OSTI2017

Methane-Oxidizing Bacteria Shunt Carbon to Microbial Mats at a Marine Hydrocarbon Seep

The marine subsurface is a reservoir of the greenhouse gas methane. While microorganisms living in water column and seafloor ecosystems are known to be a major sink limiting net methane transport from the marine subsurface to the atmosphere, few studies have assessed the flow of methane-derived carbon through the benthic mat communities that line the seafloor on the continental shelf where methane is emitted. We analyzed the abundance and isotope composition of fatty acids in microbial mats grown in the shallow Coal Oil Point seep field off Santa Barbara, CA, USA, where seep gas is a mixture of methane and CO 2 . We further used stable isotope probing (SIP) to track methane incorporation into mat biomass. We found evidence that multiple allochthonous substrates supported the rich growth of these mats, with notable contributions from bacterial methanotrophs and sulfur-oxidizers as well as eukaryotic phototrophs. Fatty acids characteristic of methanotrophs were shown to be abundant and 13 C-enriched in SIP samples, and DNA-SIP identified members of the methanotrophic family Methylococcaceae as major 13 CH 4 consumers. Members of Sulfuricurvaceae, Sulfurospirillaceae, and Sulfurovumaceae are implicated in fixation of seep CO 2 . The mats’ autotrophs support a diverse assemblage of co-occurring bacteria and protozoa, with Methylophaga as key consumers of methane-derived organic matter. This study identifies the taxa contributing to the flow of seep-derived carbon through microbial mat biomass, revealing the bacterial and eukaryotic diversity of these remarkable ecosystems.

16S rRNA gene↗

DOE OSTI2022

Modeling Flow and Transport in Fractured Rock using Machine Learning [Slides]

Fractured systems in the subsurface play a role in many natural and engineered applications such as geologic carbon sequestration, hydraulic fracturing and underground nuclear test detection. Structural information (fracture size, orientation, etc.) plays a key role in governing the dominant physics for these systems but can only be known statistically. Traditional modeling approaches either ignore or idealize structural information at these larger scales because we lack a computational framework that utilizes it in its entirety. The work presented here integrates computational physics, machine learning and graph theory to make a paradigm shift from computationally intensive high-fidelity models to coarse-scale graphs without loss of critical structural information. We exploit the underlying discrete structure of fracture networks in systems considering flow through fractures and fracture propagation. We demonstrate that compact graph representations require significantly fewer degrees of freedom (dof) to capture micro-fracture information and further accelerate these models with Machine Learning.

58 GEOSCIENCES↗

DOE OSTI2013

Modeling and Evaluation of Geophysical Methods for Monitoring and Tracking CO2 Migration

Geological sequestration has been proposed as a viable option for mitigating the vast amount of CO 2 being released into the atmosphere daily. Test sites for CO 2 injection have been appearing across the world to ascertain the feasibility of capturing and sequestering carbon dioxide. A major concern with full scale implementation is monitoring and verifying the permanence of injected CO 2 . Geophysical methods, an exploration industry standard, are non-invasive imaging techniques that can be implemented to address that concern. Geophysical methods, seismic and electromagnetic, play a crucial role in monitoring the subsurface pre- and post-injection. Seismic techniques have been the most popular but electromagnetic methods are gaining interest. The primary goal of this project was to develop a new geophysical tool, a software program called GphyzCO2, to investigate the implementation of geophysical monitoring for detecting injected CO 2 at test sites. The GphyzCO2 software consists of interconnected programs that encompass well logging, seismic, and electromagnetic methods. The software enables users to design and execute 3D surface-to-surface (conventional surface seismic) and borehole-to-borehole (cross-hole seismic and electromagnetic methods) numerical modeling surveys. The generalized flow of the program begins with building a complex 3D subsurface geological model, assigning properties to the models that mimic a potential CO 2 injection site, numerically forward model a geophysical survey, and analyze the results. A test site located in Warren County, Ohio was selected as the test site for the full implementation of GphyzCO2. Specific interest was placed on a potential reservoir target, the Mount Simon Sandstone, and cap rock, the Eau Claire Formation. Analysis of the test site included well log data, physical property measurements (porosity), core sample resistivity measurements, calculating electrical permittivity values, seismic data collection, and seismic interpretation. The data was input into GphyzCO2 to demonstrate a full implementation of the software capabilities. Part of the implementation investigated the limits of using geophysical methods to monitor CO 2 injection sites. The results show that cross-hole EM numerical surveys are limited to under 100 meter borehole separation. Those results were utilized in executing numerical EM surveys that contain hypothetical CO 2 injections. The outcome of the forward modeling shows that EM methods can detect the presence of CO 2 .

54 ENVIRONMENTAL SCIENCES↗

DOE OSTI2020

Flexible and Modular Simultaneous Modeling of Flow and Reactive Transport in Rivers and Hyporheic Zones

Investigations of coupled multiphysics processes in rivers and hyporheic zones have extensively used numerical models. Most existing models use a sequential, one-way coupling between the surface and subsurface domains. Such one-way coupling potentially introduces error. To overcome this, a fully coupled model, hyporheicFoam, was developed using the open-source computational platform OpenFOAM. It captures the coupled flow and multicomponent reactive transport processes within both surface and subsurface domains and across their interface. The coupling between two domains is implemented by mapping conservative flux boundary conditions at the interface through an iterative algorithm. Reactive transport is enabled by specifying a reaction network. To start, we have implemented reaction kinetics following the double Monod-type model with inhibition. The model capability is illustrated through modeling of both conservative and reactive hyporheic flow and transport through dune bedforms. With the novel coupled model, it is now possible to quantify reactions wherein the reactants and products are constantly exchanging between domains and have feedbacks. hyporheicFoam can simulate large, three-dimensional cases owing to the computational flexibility and power offered by the code structure and parallel design of OpenFOAM.

58 GEOSCIENCES↗

DOE OSTI2020

Hybrid geological modeling: Combining machine learning and multiple-point statistics

Accurately modeling and constructing a geologically realistic subsurface model remains an outstanding problem as the morphology controls the flow behaviors. Particularly, one of the pattern-based methods, namely cross-correlation based simulation, has been proved to be an effective way to reconstruct a realistic model, at both small and large scales. However, conditioning to point data in the large-scale problems is still a crucial issue in these algorithms, since there is always a trade-off between the quality of the realizations and the degree of point data reproduction. Specifically, it is not practical to build a training image (TI) which includes all the possibilities and variabilities. Therefore, finding a pattern that can represent the point data and, at the same time, preserving the connectivities is difficult. This leads to producing highly-connected realizations with a significant mismatch or poor models with a reasonable degree of point data reproduction. To accurately reproduce the densely distributed hard data, pixel-based methods can also produce some unrealistic artifacts around the hard data. In this paper, to overcome this challenge, however, we use pattern-based methods as they often produce more disconnected geobodies when dealing with dense hard data, and proposed a hybrid algorithm using the pattern-based methods and convolutional neural network (CNN). The trained CNN model is utilized to improve the quality of conditioning to point data for the original realizations generated by the pattern-based algorithm. As such, the mismatch locations are identified, and the same regions are used in the training of CNN to mimic the procedure through which a missing region can be filled. To evaluate the performance of the proposed hybrid algorithm, it is tested on cases with different dimensions and different numbers of facies. Then, the newly improved realizations are compared with the initial realizations generated by the pattern-based algorithm. The comparison is also conducted by the flow simulation test. And it indicates that the proposed hybrid algorithm can better reproduce the point data, while the connectivities are better preserved.

58 GEOSCIENCES↗

DOE OSTI2012

Three-Dimensional Bayesian Geostatistical Aquifer Characterization at the Hanford 300 Area using Tracer Test Data

Tracer testing under natural or forced gradient flow holds the potential to provide useful information for characterizing subsurface properties, through monitoring, modeling and interpretation of the tracer plume migration in an aquifer. Non-reactive tracer experiments were conducted at the Hanford 300 Area, along with constant-rate injection tests and electromagnetic borehole flowmeter (EBF) profiling. A Bayesian data assimilation technique, the method of anchored distributions (MAD) [Rubin et al., 2010], was applied to assimilate the experimental tracer test data with the other types of data and to infer the three-dimensional heterogeneous structure of the hydraulic conductivity in the saturated zone of the Hanford formation. In this study, the Bayesian prior information on the underlying random hydraulic conductivity field was obtained from previous field characterization efforts using the constant-rate injection tests and the EBF data. The posterior distribution of the conductivity field was obtained by further conditioning the field on the temporal moments of tracer breakthrough curves at various observation wells. MAD was implemented with the massively-parallel three-dimensional flow and transport code PFLOTRAN to cope with the highly transient flow boundary conditions at the site and to meet the computational demands of MAD. A synthetic study proved that the proposed method could effectively invert tracer test data to capture the essential spatial heterogeneity of the three-dimensional hydraulic conductivity field. Application of MAD to actual field data shows that the hydrogeological model, when conditioned on the tracer test data, can reproduce the tracer transport behavior better than the field characterized without the tracer test data. This study successfully demonstrates that MAD can sequentially assimilate multi-scale multi-type field data through a consistent Bayesian framework.

54 ENVIRONMENTAL SCIENCES↗

DOE OSTI2020

Analysis of Microseismicity and Reactivated Fault Size to Assess the Potential for Felt Events by CO 2 Injection in the Illinois Basin

The results of monitoring of carbon dioxide (CO 2 ) injection at the Illinois Basin—Decatur Project (IBDP) and the companion Illinois Industrial Carbon Capture and Sequestration Sources (IL-ICCS) project—have shown that reservoir response to fluid pressure changes can vary significantly at different injection locations within the same reservoir. Predrill reservoir characterization is important to identify potentially seismogenic faults. However, interpretations of newly reprocessed 3D seismic reflection data illustrate the challenges related to their identification in a region dominated by faulting with small vertical offsets. Faults interpreted in the 3D seismic volume range from ~300 to 1200 m wide and are in the same size range as faults that could have been the source of historical events up to Mw 2.7 in central Illinois. The array of monitoring sensors that was installed for the IBDP continues to collect data, as injection operates in IL-ICCS, the second injection well. CO 2 injection rates for the IL-ICCS well are on average 1.7 times the rates injected in the IBDP well, but a significantly reduced rate of induced seismicity is observed. This article presents results of passive seismic monitoring for the duration of the project to date, integrating active and passive seismic data to develop a new interpretation of the subsurface structure at the Decatur site that explicitly identifies pathways for fluid flow into the basement leading to induced seismicity, and provides a geological explanation for the sharp reduction of induced seismicity during injection at higher rates into the second well. The use of seismic moment to estimate the length of seismogenic slip planes in the local subsurface suggests that faults large enough to produce felt seismicity are unlikely to be present at or near the Decatur site.

Geochemistry & Geophysics↗

DOE OSTI2018

Preferential flow systems amended with biogeochemical components: imaging of a two-dimensional study

The vadose zone is a highly interactive heterogeneous system through which water enters the subsurface system by infiltration. This paper details the effects of simulated plant exudate and soil component solutions upon unstable flow patterns in a porous medium (ASTM silica sand; US Silica, Ottawa, IL, USA) through the use of two-dimensional tank light transmission method (LTM). The contact angle (θ) and surface tension (γ) of two simulated plant exudate solutions (i.e., oxalate and citrate) and two soil component solutions (i.e., tannic acid and Suwannee River natural organic matter, SRNOM) were analyzed to determine the liquid–gas and liquid–solid interface characteristics of each. To determine if the unstable flow formations were dependent on the type and concentration of the simulated plant exudates and soil components, the analysis of the effects of the simulated plant exudate and soil component solutions were compared to a control solution (Hoagland nutrient solution with 0.01 M NaCl). Fingering flow patterns, vertical and horizontal water saturation profiles, water saturation at the fingertips, finger dimensions and velocity, and number of fingers were obtained using the light transmission method. Significant differences in the interface properties indicated a decrease between the control and the plant exudate and soil component solutions tested; specifically, the control (θ = 64.5° and γ = 75.75mNm -1 ) samples exhibited a higher contact angle and surface tension than the low concentration of citrate (θ = 52.6° and γ = 70.8mNm -1 ). Wetting front instability and fingering flow phenomena were reported in all infiltration experiments. The results showed that the plant exudates and soil components influenced the soil infiltration as differences in finger geometries, velocities, and water saturation profiles were detected when compared to the control. Among the tested solutions and concentrations of soil components, the largest finger width (10.19cm) was generated by the lowest tannic acid solution concentration (0.1mgL -1 ), and the lowest finger width (6.00cm) was induced by the highest SRNOM concentration (10mgL -1 ). Similarly, for the plant exudate solutions, the largest finger width (8.36cm) was generated by the lowest oxalate solution concentration (0.1mgL -1 ), and the lowest finger width (6.63cm) was induced by the lowest citrate concentration (0.1mgL -1 ). The control solution produced fingers with average width of 8.30cm. Additionally, the wettability of the medium for the citrate, oxalate, and SRNOM solutions increased with an increase in concentration. Our research demonstrates that the plant exudates and soil components which are biochemical compounds produced and released in soil are capable of influencing the process of infiltration in soils. The results of this research also indicate that soil wettability, expressed as cosθ 1/2 , should be included in the scaling of the finger dimension, i.e., finger width, when using the Miller and Miller (1956) scaling theory for the scaling of flow in porous media.

58 GEOSCIENCES↗

DOE OSTI2013

Effects of Pore Structure Change and Multi-Scale Heterogeneity on Contaminant Transport and Reaction Rate Upscaling

This project addressed the scaling of geochemical reactions to core and field scales, and the interrelationship between reaction rates and flow in porous media. We targeted reactive transport problems relevant to the Hanford site – specifically the reaction of highly caustic, radioactive waste solutions with subsurface sediments, and the immobilization of 90 Sr and 129 I through mineral incorporation and passive flow blockage, respectively. We addressed the correlation of results for pore-scale fluid-soil interaction with field-scale fluid flow, with the specific goals of (i) predicting attenuation of radionuclide concentration; (ii) estimating changes in flow rates through changes of soil permeabilities; and (iii) estimating effective reaction rates. In supplemental work, we also simulated reactive transport systems relevant to geologic carbon sequestration. As a whole, this research generated a better understanding of reactive transport in porous media, and resulted in more accurate methods for reaction rate upscaling and improved prediction of permeability evolution. These scientific advancements will ultimately lead to better tools for management and remediation of DOE legacy waste problems.

54 ENVIRONMENTAL SCIENCES↗

DOE OSTI2013

Effects of Pore Structure Change and Multi-Scale Heterogeneity on Contaminant Transport and Reaction Rate Upscaling

58 GEOSCIENCES↗

DOE OSTI2022

A gradient-based deep neural network model for simulating multiphase flow in porous media

We report simulation of multiphase flow in porous media is crucial for the effective management of subsurface energy and environment-related activities. The numerical simulators used for modeling such processes rely on spatial and temporal discretization of the governing mass and energy balance partial-differential equations (PDEs) into algebraic systems via finite-difference/volume/element methods. These simulators usually require dedicated software development and maintenance, and suffer low efficiency from a runtime and memory standpoint for problems with multi-scale heterogeneity, coupled-physics processes or fluids with complex phase behavior. Therefore, developing cost-effective, data-driven models can become a practical choice, and in this work, we choose deep learning approaches as they can handle high dimensional data and accurately predict state variables with strong nonlinearity. In this paper, we describe a gradient-based deep neural network (GDNN) constrained by the physics related to multiphase flow in porous media. We tackle the nonlinearity of flow in porous media induced by rock heterogeneity, fluid properties, and fluid-rock interactions by decomposing the nonlinear PDEs into a dictionary of elementary differential operators. We use a combination of operators to handle rock spatial heterogeneity and fluid flow by advection. Since the augmented differential operators are inherently related to the physics of fluid flow, we treat them as first principles prior knowledge to regularize the GDNN training. We use the example of pressure management at geologic CO 2 storage sites, where CO 2 is injected in saline aquifers and brine is produced, and apply GDNN to construct a predictive model that is trained with physics-based simulation data and emulates the physics process. We demonstrate that GDNN can effectively predict the nonlinear patterns of subsurface responses, including the temporal and spatial evolution of the pressure and saturation plumes. We also successfully extend the GDNN to convolutional neural network (CNN), namely gradient-based CNN (GCNN), and validate its capability to improve the prediction accuracy. GDNN has great potential to tackle challenging problems that are governed by highly nonlinear physics and enable the development of data-driven models with higher fidelity.

42 ENGINEERING↗

DOE OSTI2018

The Importance of Capturing Topographic Features for Modeling Groundwater Flow and Transport in Mountainous Watersheds

Abstract Physics‐based distributed hydrological models that include groundwater are widely used to understand and predict physical and biogeochemical processes within watersheds. Typically, due to computational limitations, watershed modelers minimize the number of elements used in domain discretization, smoothing or even ignoring critical topographic features. We use an idealized model to investigate the implications of mesh refinement along streams and ridges for modeling three‐dimensional groundwater flow and transport in mountainous watersheds. For varying degrees of topographic complexity level (TCL), which increases with the level of mesh refinement, and geological heterogeneity, we estimate and compare steady state baseflow discharge, mean age, and concentration of subsurface weathering products. Results show that ignoring lower‐order streams or ridges diminishes flow through local flow paths and biases higher the contribution of intermediate and regional flow paths, and biases baseflow older. The magnitude of the bias increases for systems where permeability rapidly decreases with depth and is dominated by shallow flow paths. Based on a simple geochemical model, the concentration of weathering products is less sensitive to the TCL, partially due to the thermodynamic constraints on chemical reactions. Our idealized model also reproduces the observed emergent scaling relationship between the groundwater contribution to streamflow and drainage area, and finds that this scaling relationship is not sensitive to mesh TCL. The bias effects have important implications for the use of hydrological models in the interpretation of environmental tracer data and the prediction of biogeochemical evolution of stream water in mountainous watersheds.

Wang, Chao↗