Subsurface Characterization using Ensemble-based Approaches with Deep Generative Models

Estimating spatially distributed properties such as hydraulic conductivity (K) from available sparse measurements is a great challenge in subsurface characterization. However, the use of inverse modeling is limited for ill-posed, high-dimensional applications due to computational costs and poor prediction accuracy with sparse datasets. In this paper, we combine Wasserstein Generative Adversarial Network with Gradient Penalty (WGAN-GP), a deep generative model that can accurately capture complex subsurface structure, and Ensemble Smoother with Multiple Data Assimilation (ES-MDA), an ensemble-based inversion method, for accurate and accelerated subsurface characterization. WGAN-GP is trained to generate high-dimensional K fields from a low-dimensional latent space and ES-MDA then updates the latent variables by assimilating available measurements. Several subsurface examples are used to evaluate the accuracy and efficiency of the proposed method and the main features of the unknown K fields are characterized accurately with reliable uncertainty quantification. Furthermore, the estimation performance is compared with a widely-used variational, i.e., optimization-based, inversion approach, and the proposed approach outperforms the variational inversion method, especially for the channelized and fractured field examples. We explain such superior performance by visualizing the objective function in the latent space: because of nonlinear and aggressive dimension reduction via generative modeling, the objective function surface becomes extremely complex while the ensemble approximation can smooth out the multi-modal surface during the minimization. This suggests that the ensemble-based approach works well over the variational approach when combined with deep generative models at the cost of forward model runs unless convergence-ensuring modifications are implemented in the variational inversion

Progressive reduced order modeling: empowering data-driven modeling with selective knowledge transfer

Data-driven modeling can suffer from a constant demand for data, leading to reduced accuracy and impractical for engineering applications due to the high cost and scarcity of information. To address this challenge, we propose a progressive reduced order modeling framework that minimizes data cravings and enhances data-driven modeling's practicality. Our approach selectively transfers knowledge from previously trained models through gates, similar to how humans selectively use valuable knowledge while ignoring unuseful information. By filtering relevant information from previous models, we can create a surrogate model with minimal turnaround time and a smaller training set that can still achieve high accuracy. We have tested our framework in several cases, including transport in porous media, gravity-driven flow, and finite deformation in hyperelastic materials. Our results illustrate that retaining information from previous models and utilizing a valuable portion of that knowledge can significantly improve the accuracy of the current model. We have demonstrated the importance of progressive knowledge transfer and its impact on model accuracy with reduced training samples. For instance, our framework with four parent models outperforms the no-parent counterpart trained on data nine times larger. Our research unlocks data-driven modeling's potential for practical engineering applications by mitigating the data scarcity issue. Our proposed framework is a significant step toward more efficient and cost-effective data-driven modeling, fostering advancements across various fields

Effects of spatial heterogeneity and material anisotropy on the fracture pattern and macroscopic effective toughness of Mancos Shale in Brazilian tests

For assessing energy-related activities in the subsurface, it is important to investigate the impact of the spatial variability and anisotropy on the geomechanical behavior of shale. The Brazilian test, an indirect tensile-splitting method, is performed in this work, and the evolution of strain field is obtained using digital image correlation. Experimental results show the significant impact of local heterogeneity and lamination on the crack pattern characteristics. For numerical simulations, a phase field method is used to simulate the brittle fracture behavior under various Brazilian test conditions. In this study, shale is assumed to consist of two constituents including the stiff and soft layers to which the same toughness but different elastic moduli are assigned. Microstructural heterogeneity is simplified to represent mesoscale (e.g., millimeter scale) features such as layer orientation, thickness, volume fraction, and defects. The effect of these structural attributes on the onset, propagation, and coalescence of cracks is explored. The simulation results show that spatial heterogeneity and material anisotropy highly affect crack patterns and effective fracture toughness, and the elastic contrast of two constituents significantly alters the effective toughness. However, the complex crack patterns observed in the experiments cannot completely be accounted for by either an isotropic or transversely isotropic effective medium approach. This implies that cracks developed in the layered system may coalesce in complicated ways depending on the local heterogeneity, and the interaction mechanisms between the cracks using two-constituent systems may explain the wide range of effective toughness of shale reported in the literature

Computational thermal, chemical, fluid, and solid mechanics for geosystems management.

This document summarizes research performed under the SNL LDRD entitled - Computational Mechanics for Geosystems Management to Support the Energy and Natural Resources Mission. The main accomplishment was development of a foundational SNL capability for computational thermal, chemical, fluid, and solid mechanics analysis of geosystems. The code was developed within the SNL Sierra software system. This report summarizes the capabilities of the simulation code and the supporting research and development conducted under this LDRD. The main goal of this project was the development of a foundational capability for coupled thermal, hydrological, mechanical, chemical (THMC) simulation of heterogeneous geosystems utilizing massively parallel processing. To solve these complex issues, this project integrated research in numerical mathematics and algorithms for chemically reactive multiphase systems with computer science research in adaptive coupled solution control and framework architecture. This report summarizes and demonstrates the capabilities that were developed together with the supporting research underlying the models. Key accomplishments are: (1) General capability for modeling nonisothermal, multiphase, multicomponent flow in heterogeneous porous geologic materials; (2) General capability to model multiphase reactive transport of species in heterogeneous porous media; (3) Constitutive models for describing real, general geomaterials under multiphase conditions utilizing laboratory data; (4) General capability to couple nonisothermal reactive flow with geomechanics (THMC); (5) Phase behavior thermodynamics for the CO2-H2O-NaCl system. General implementation enables modeling of other fluid mixtures. Adaptive look-up tables enable thermodynamic capability to other simulators; (6) Capability for statistical modeling of heterogeneity in geologic materials; and (7) Simulator utilizes unstructured grids on parallel processing computers

EMSL Pore Scale Modeling Challenge/Workshop

Report covers the background for the workshop, objectives, important research directions, necessary capabilities and overall recommendations

Influence of Soil Moisture Dynamics on DNAPL Spill Zone Architecture and Its Impact on Mass Removal Mechanisms During Soil Vapor Extraction in Heterogeneous Porous Media

153 p.Thesis (Ph.D.)--University of Illinois at Urbana-Champaign, 2005.The spatial distribution of DNAPL saturation, water saturation, and soil permeability (i.e., spill zone architecture) determines the pore-scale processes that control soil vapor extraction (SVE). To test this hypothesis, a fully coupled multiphase flow and transport simulator, STOMP was chosen. STOMP was first used to develop a new conceptual model for the migration and distribution of DNAPL in heterogeneous porous media for different NAPL and water loading histories (i.e., soil moisture dynamics). A 2-D vertical cross-section with layered heterogeneity mimicking the Hanford Site was assumed. In cases of co-disposal of NAPL with large volumes of wastewater, the form and location of NAPL were most strongly influenced by high water recharge rates. The effect of NAPL evaporation on NAPL migration was dramatic just after the spill event when the NAPL was present near the ground surface, resulting in a high diffusive mass flux into the atmosphere. For low water infiltration rate scenarios, the distribution of water content prior to a NAPL spill event had a significant impact on NAPL migration and distribution. Mass transfer processes for slow desorption and rate-limited dissolution from trapped NAPL were incorporated into the STOMP simulator. The modified STOMP was used to determine the effects of heterogeneity, slow desorption, and rate-limited NAPL mass transfer on mass removal mechanisms during SVE. Gas flow by-passing of low permeability zones was one of the dominant factors for diminished SVE effectiveness at late time. Rate-limited mass transfer from trapped NAPL led to a longer tailing when most remaining NAPL in the low permeability layer was trapped NAPL. These simulations indicate that NAPL-water spill-driven gas advection, vapor diffusion, and NAPL vertical movement enhanced by water flow must be considered in order to predict NAPL distribution and migration in the vadose zone. In addition, if trapped NAPL is expected in heterogeneous porous media, an improved mass transfer rate can be achieved not only by delivering gas directly to zones where trapped NAPL exists, but by changing the NAPL form from trapped NAPL to free NAPL.U of I OnlyRestricted to the U of I community idenfinitely during batch ingest of legacy ETD

Influence of Soil Moisture Dynamics on DNAPL Spill Zone Architecture and Its Impact on Mass Removal Mechanisms During Soil Vapor Extraction in Heterogeneous Porous Media

153 p.Thesis (Ph.D.)--University of Illinois at Urbana-Champaign, 2005.The spatial distribution of DNAPL saturation, water saturation, and soil permeability (i.e., spill zone architecture) determines the pore-scale processes that control soil vapor extraction (SVE). To test this hypothesis, a fully coupled multiphase flow and transport simulator, STOMP was chosen. STOMP was first used to develop a new conceptual model for the migration and distribution of DNAPL in heterogeneous porous media for different NAPL and water loading histories (i.e., soil moisture dynamics). A 2-D vertical cross-section with layered heterogeneity mimicking the Hanford Site was assumed. In cases of co-disposal of NAPL with large volumes of wastewater, the form and location of NAPL were most strongly influenced by high water recharge rates. The effect of NAPL evaporation on NAPL migration was dramatic just after the spill event when the NAPL was present near the ground surface, resulting in a high diffusive mass flux into the atmosphere. For low water infiltration rate scenarios, the distribution of water content prior to a NAPL spill event had a significant impact on NAPL migration and distribution. Mass transfer processes for slow desorption and rate-limited dissolution from trapped NAPL were incorporated into the STOMP simulator. The modified STOMP was used to determine the effects of heterogeneity, slow desorption, and rate-limited NAPL mass transfer on mass removal mechanisms during SVE. Gas flow by-passing of low permeability zones was one of the dominant factors for diminished SVE effectiveness at late time. Rate-limited mass transfer from trapped NAPL led to a longer tailing when most remaining NAPL in the low permeability layer was trapped NAPL. These simulations indicate that NAPL-water spill-driven gas advection, vapor diffusion, and NAPL vertical movement enhanced by water flow must be considered in order to predict NAPL distribution and migration in the vadose zone. In addition, if trapped NAPL is expected in heterogeneous porous media, an improved mass transfer rate can be achieved not only by delivering gas directly to zones where trapped NAPL exists, but by changing the NAPL form from trapped NAPL to free NAPL.U of I OnlyRestricted to the U of I community idenfinitely during batch ingest of legacy ETD