Search NASA⌕ Search

SEARCH · Search NASA

Results for “Geological Modeling”

Search indexed NASA NTRS and DOE OSTI research on propulsion, heat transfer, battery materials and energy systems. Follow report and document links to the original sources.

Quote a phrase for an exact phrase match. Source license links do not imply unrestricted reuse.

At least 451 records · Page 25

An Insight-Centric Paradigm for Data Reduction and Inference Speed Improvement at the Scurry Area Canyon Reef Operator’s Committee (SACROC) Unit

The poster presents the work conducted under SMART focusing on using insight-centric approach to design a meaningful proxy for machine learning. Domain insights are critical not just in understanding the prediction results but also in designing the model. This study demonstrated that a single meaningful scaler (as an extreme case) can effectively replace full-size 3D geologic properties. The model's accuracies are on par with other models, and it is the fastest model to predict all test cases, 5,000 times faster than traditional simulations.

Shih, Chung Yan↗

DECOVALEX-2019: An international collaboration for advancing the understanding and modeling of coupled thermo-hydro-mechanical-chemical (THMC) processes in geological systems

The DECOVALEX Project is an international research collaboration for advancing the understanding and modeling of coupled thermo-hydro-mechanical-chemical (THMC) processes in geological systems. DECOVALEX stands for “DEvelopment of COupled Models and VALidation against EXperiments”. The creation of this international initiative, now running for almost 30 years, was motivated by the recognition that prediction of these coupled effects is an essential part of the performance and safety assessment of geologic disposal systems for radioactive waste and spent nuclear fuel, and also for a range of other sub-surface engineering activities. DECOVALEX emphasizes joint analysis and comparative modeling of state-of-the-art field and laboratory experiments, across a range of host rock options and repository designs. Participating research teams are from radioactive waste management organizations, national research institutes, regulatory agencies, universities, and consulting groups, providing a wide range of perspectives and solutions to these complex problems. The most recent phase of the DECOVALEX Project, here referred to as DECOVALEX-2019, started in 2016 and ended in 2019. Modeling teams from 13 international partner organizations participated in the comparative evaluation of seven modeling tasks involving complex field and/or laboratory experiments. Furthermore, this Virtual Special Issue on DECOVALEX-2019 provides an in-depth overview of these collaborative research efforts and how these have advanced the state-of-the-art of understanding and modeling coupled THMC processes.

58 GEOSCIENCES↗

A simple thermal model of the earth's surface for geologic mapping by remote sensing

Thermal inertia of the earth's surface can be used in geologic mapping as a complement to surface reflectance data as provided by Landsat. Thermal inertia cannot be determined directly but must be inferred from radiation temperature measurements (by thermal IR sensors) made at various times in the diurnal cycle, combined with a model of the surface heating processes. A model is developed which differs from those created previously for this purpose, because it includes sensible and latent heating. Tests of this model using field data indicate that it accurately determines the surface heating. When the model is used with field measurements of meteorological variables and is combined with remotely sensed temperature data, a thermal inertia image can be produced.

Kahle, A. B.↗

Modeling-Based Assessment of Deep Seismic Potential Induced by Geologic Carbon Storage

Induced seismicity is an inherent risk associated with geologic carbon storage (GCS) in deep rock formations that could contain undetected faults prone to failure. Modeling-based risk assessment has been implemented to quantify the potential of injection-induced seismicity, but typically simplified multiscale geologic features or neglected multiphysics coupled mechanisms because of the uncertainty in field data and computational cost of field-scale simulations, which may limit the reliable prediction of seismic hazard caused by industrial-scale CO 2 storage. The degree of lateral continuity of the stratigraphic interbedding below the reservoir and depth-dependent fault permeability can enhance or inhibit pore-pressure diffusion and corresponding poroelastic stressing along a basement fault. In conclusion, this study presents a rigorous modeling scheme with optimal geological and operational parameters needed to be considered in seismic monitoring and mitigation strategies for safe GCS.

58 GEOSCIENCES↗

DECOVALEX-2023: An international collaboration for advancing the understanding and modeling of coupled thermo-hydro-mechanical-chemical (THMC) processes in geological systems

The DECOVALEX initiative is an international research collaboration (www.decovalex.org), initiated in 1992, for advancing the understanding and modeling of coupled thermo-hydro-mechanical-chemical (THMC) processes in geological systems. DECOVALEX stands for “DEvelopment of COupled Models and VALidation against EXperiments”. The creation of this international initiative was motivated by the recognition that prediction of these coupled effects is an essential part of the performance and safety assessment of geologic disposal systems for radioactive waste and spent nuclear fuel. DECOVALEX emphasizes joint analysis and comparative modeling of the complex perturbations and coupled processes in geologic repositories and how these impact long-term performance predictions. The most recent phase of the DECOVALEX Project, here referred to as DECOVALEX-2023, started in early 2020 and ended in late 2023. More than fifty research teams associated with 17 international DECOVALEX partner organizations participated in the comparative evaluation of eight modeling tasks covering a wide range of spatial and temporal scales, geological formations, and coupled processes. This Virtual Special Issue on DECOVALEX-2023 provides an in-depth overview of these collaborative research efforts and how these have advanced the state-of-the-art of understanding and modeling coupled THMC processes. While primarily focused on radioactive waste, much of the work included here has wider application to many geoengineering topics.

Coupled processes↗

Optimizing Alabama’s CO 2 Storage in Shelby County (Project OASIS) Milestone 6.0: Evaluation of Class VI Readiness

Introduction. Project OASIS is approximately 30 miles southeast of Birmingham, Alabama, and approximately 5 miles north-northwest of Alabama Power Company's Plant Gaston. Geologically, the Project area is in the Alabama fold and thrust belt province. This work builds on the initiatives of the Southeast Regional Carbon Utilization and Storage Acceleration Partnership (SECARB-USA, DE-FE0031830) that identified nearly 500 million metric tonnes of CO 2 emitted on an annual basis that is not collocated with prospective storage geology (the Coastal Plain of the Southeastern US in this context). This observation suggests costly investments in connective infrastructure (e.g., pipelines) or exploratory well drilling campaigns to identify CO 2 storage opportunities in under explored areas. While not traditionally thought of for saline storage, these studies suggest that storage prospects in the Valley and Ridge Province occur in relatively flat lying structural panels between thrust faults. For the Project OASIS region, available geologic studies related to hydrocarbon exploration suggest that Cambro-Ordovician carbonates and Cambrian clastic units offer multiple potential storage intervals, and that regional confining systems are present, such as the tectonically thickened Floyd-Parkwood Shale. The Project OASIS surface property is owned by a timber and land stewardship company, The Westervelt Company, Inc., who worked with the Project Team to select and prepare adequate sites for geologic assessment. The purpose of drilling the Westover Stratigraphic Test Well #2 was to collect geologic data to model the feasibility of commercial scale CO 2 injection and storage in an under explored region. This initiative benefits the regions emitters as the data generated from this study can inform their own internal decision making. The field program included geological and geophysical evaluations, reservoir engineering analyses, and risk assessments. This report evaluates existing data, as well as a variety of modeling scenarios to evaluate project readiness. Importantly, the impact of this study is not limited to Alabama as there are numerous large emitters throughout Appalachia, in similar geologic settings, contemplating their decarbonization options.

20 FOSSIL-FUELED POWER PLANTS↗

Simulating the Formation of Lunar Floor-Fracture Craters Using Elastoviscoplastic Relaxation

Lunar floor-fracture craters formed during the height of mare basalt emplacement. Due to a general temporal and spatial relation with the maria, these craters, numbering some 200, may be diagnostic of the thermal structure of the crust during this time. As the name suggests, these craters exhibit brittle failure, generally limited to the central floor region. That, and a shallower depth than fresh lunar craters, has led to two main theories as to their formation: laccolith emplacement under the crater and viscous relaxation. The implications of each model for the state of the Moon's crust during this time are quite different, so the viability of each model must be checked. Laccolith emplacement has been treated elsewhere. However, previous attempts to study the relaxation of the craters have assumed only a uniform, Newtonian viscous response of the near surface to the topographic driving forces, and simply postulated that the fractures resulted from tensile stresses associated with floor uplift. Here, we use a more sophisticated rheological model that includes not only non-Newtonian viscous behavior (i.e., the viscosity is stress-dependent), but also incorporates elastic behavior and a plastic component to the rheology to directly simulate the formation of the floor fractures. The results of our simulations show that while elastoviscoplastic relaxation is potentially viable for larger floor-fracture craters, it is not viable for craters with diameters < or = 60 km, the size of the majority of floor-fracture craters. We employ the finite element method, a numerical technique well suited for boundary-value problems, via the commercially available MARC software package. To test the viability of topographic relaxation, our goal is to prepare the simulations as to maximize the amount of relaxation. We take advantage of the natural axisymmetry of craters, simulating one radial plane. Initial shapes are based on data for fresh craters from Pike. To simplify implementation, a fourth order polynomial is used for the basin, while a third order inverse function is used for the rim. This form closely approximates the long-wavelength behavior of complex craters, while ignoring higher-frequency topography, save the rim. This approximation is appropriate because crater relaxation is strongly controlled by long-wavelength topography. Loading is accomplished assuming a uniform gravity field (1.62 m/s-square) and a uniform density of 2900 kg/cubic m. The initial stress state is set to be hydrostatic, with an additional pressure term to account for any overlying topography. This additional pressure term is tapered exponentially with depth. While the simulations quickly settle on a preferred stress state, and while the final solution is fairly insensitive to the choice of the e-folding depth of the taper, selecting an e-folding depth close to the diameter of the crater sets the initial stress state near the preferred state. We assume a diuranally averaged surface temperature of -20 C, and allow temperature to increase with depth at a rate of 50 K//km. Assuming a thermal conductivity of 2 W/in/K, this gradient translates to a heat flow of 100mW/square m, an extremely high value for the Moon. Temperature, of course, will not increase without bound. To maximize relaxation, we allow our temperature profile to increase linearly until it reaches the solidus (assumed to be 1200C) at a depth of 24.4 km, at which point it is kept constant. The presence of melt will drop the bulk viscosity; however, we have no rheological control for partial melts. Therefore, we make no attempt to simulate this situation. Elastoviscoplastic rheological model. In general, geologic materials can behave in three main ways: elastically, viscously (via solid-state creep), and brittly (plasticity is a continuum approach to simulate this phenomenon). We combine these three deformation mechanisms in an extended Maxwell solid, where the total strain can be broken down into a simple summation of the elastic, creep, and plastic strains. In relaxation phenomena in general, the system takes advantage of any means possible to eliminate deviatoric stresses by relaxing away the topography. Previous analyses have only modeled the viscous response. Comparatively, the elastic response in our model can augment the relaxation, to a point. This effect decreases as the elastic response becomes stiffer; indeed, in the limit of infinite elastic Young's modulus (and with no plasticity), the solution converges on the purely viscous solution. Igneous rocks common to the lunar near-surface have Young's modulii in the range of 10-100 GPa. To maximize relaxation, we use a Young's modulus of 10 GPa. (There is negligible sensitivity to the other elastic modulus, the Poisson's ratio; we use 0.25.) For the viscous response, we use a flow law for steady-state creep in thoroughly dried Columbia diabase, because the high plagioclase (about 70 vol%) and orthopyroxene (about 17 vol%) content is similar to the composition of the lunar highland crust as described by remote sensing and sample studies: noritic anorthosite. This flow law is highly non-Newtonian, i.e., the viscosity is highly stress dependent. That, and the variability with temperature, stands in strong contrast to previous examinations of lunar floor-fracture crater relaxation. To model discrete, brittle faulting, we assume "Byerlee's rule," a standard geodynamical technique. We implement this "rule" with an-angle of internal friction of about 40 deg, and a higher-than-normal cohesion of about 3.2 MPa (to approximate the breaking of unfractured rock). The actual behavior of geologic materials is more complex than in our rheological model, so the uncertainties in the plasticity do not represent the state-of-the-art error. Additional information is contained in the original.

Dombard, A. J.↗

A simple model of clastic sediments on Mars

In preparation for the start of Mars Observer operations at Mars later this year, Viking Infrared Thermal Mapper (IRTM) observations were synthesized into a simple but geologically coherent conceptual model for use in establishing targets for coordinated Thermal Emission Spectrometer (TES) and Mars Observer Camera (MOC) observations. The model is based on three assumptions that are, at best, only partly true: that albedo is a measure of the presence or absence of dust; that thermal inertia is a measure of the weighted average particle size; and that rock abundance is a measure of the statistical thickness of fine sediment (i.e., that the observed areal abundance of rock reflects the whole or partial burial of rocks). Using this model, it is possible to show that, on the scale of 30 km, mantles of wind-transportable sediment (dust and sand) are at most about 1 m thick, and that on a global average such mantles are about 35 cm thick. It is shown that 3.8 x 10(exp 19) cu cm of such sediment covers Mars equatorward of +/- 60 deg latitude. Using the model, interpretation of digital maps of IRTM data focus attention not only on areas where dust is the primary sediment (e.g., Arabia Terra), but also on areas where sand is the primary sediment (e.g., eastern Valles Marineris) and where rocks and other coarse materials are abundant (e.g., eastern Kasei Vallis). Three IRTM data sets are used in the analysis: Viking 1 and 2 pre-dawn observations mosaiced into a global map of single-point thermal inertias at 0.5 deg/bin resolution; Pleskot and Miner's global albedo map using the best available, clear-period IRTM observations (1x/bin); and Christensen's 1 deg/bin rock abundance map. Uncertainty analyses indicate these data sets to be accurate to 5 percent, 2 percent, and 20 percent, respectively.

Christensen, Philip R.↗

Groundwater Volume Loss in Mexico City Constrained by InSAR and GRACE Observations and Mechanical Models

Abstract Groundwater withdrawal can cause localized and rapid poroelastic subsidence, spatially broad elastic uplift of low amplitude, and changes in the gravity field. Constraining groundwater loss in Mexico City, we analyze data from the Gravity Recovery and Climate Experiment and its follow‐on mission (GRACE/FO) and Synthetic Aperture Radar (SAR) Sentinel‐1A/B images between 2014 and 2021. GRACE/FO observations yield a groundwater loss of 0.85–3.87 km 3 /yr for a region of ∼300 × 600 km surrounding Mexico City. Using the high‐resolution interferometric SAR data set, we measure >35 cm/yr subsidence within the city and up to 2 cm/yr of uplift in nearby areas. Attributing the long‐term subsidence to poroelastic aquifer compaction and the long‐term uplift to elastic unloading, we apply respective models informed by local geology, yielding groundwater loss of 0.86–12.57 km 3 /yr. Our results suggest Mexico City aquifers have been depleting at faster rates since 2015, exacerbating the socioeconomic and health impacts of long‐term groundwater overdrafts.

58 GEOSCIENCES↗

Magsat: A satellite for measuring near earth magnetic fields

Magsat, designed for making measurements of the geomagnetic vector field, is evaluated. For accurate vector measurements the attitude of the fluxgate magnetometer will be determined to about 15 arc-seconds. Expected measurement accuracy will be 6 (gamma) in each component and 3 in magnitude. The Magsat data will be applied to solid earth studies including modeling of the Earth's main magnetic field, delineation of regional magnetic anomalies of crustal origin, and interpretation of those anomalies in terms of geologic and geophysical models. An opportunity will be presented to the scientific community to participate in data use investigations.

Langel, R. A.↗

Gravity and magnetic anomaly modeling and correlation using the SPHERE program and Magsat data

The spherical Earth inversion, modeling, and contouring software were tested and modified for processing data in the Southern Hemisphere. Preliminary geologic/tectonic maps and selected cross sections for South and Central America and the Caribbean region are being compiled and as well as gravity and magnetic models for the major geological features of the area. A preliminary gravity model of the Andeas Beniff Zone was constructed so that the density columns east and west of the subducted plates are in approximate isostatic equilibrium. The magnetic anomaly for the corresponding magnetic model of the zone is being computed with the SPHERE program. A test tape containing global magnetic measurements was converted to a tape compatible with Purdue's CDC system. NOO data were screened for periods of high diurnal activity and reduced to anomaly form using the IGS-75 model. Magnetic intensity anomaly profiles were plotted on the conterminous U.S. map using the track lines as the anomaly base level. The transcontinental magnetic high seen in POGO and MAGSAT data is also represented in the NOO data.

Braile, L. W.↗

NRAP-Open-IAM Analytical Reservoir Model: Development and Testing

Geological carbon sequestration (GCS) is a key technology for reducing global carbon dioxide (CO 2 ) emissions. Over the last decade, the U.S. Department of Energy has invested in understanding the science base, developing practical implementation methods, and demonstrating secure GCS technologies to mitigate the environmental impacts associated with the atmospheric release of CO 2 . As part of the National Risk Assessment Partnership, a systems-level risk assessment tool, called the NRAP-Open-IAM, has been developed to conduct risk assessment and enable safe operations at a GCS site. The current NRAP-Open-IAM contains a simple reservoir model component that calculates the evolution of CO 2 saturation and fluid pressure in a storage reservoir during CO 2 injection operations. This report presents the development and testing of a new analytical reservoir reduced-order model (ROM), which is extended from an existing semi-analytical model for estimation of CO 2 and brine leakage along legacy wells, and enhances the capability of the NRAP-Open-IAM to simulate more types of reservoir conditions. The developed model is validated against three reference studies, and the results indicate that the new ROM predicts the behavior of the two-phase fluids (brine and injected CO 2 ) well and is applicable to different reservoir simulation boundary conditions (i.e., constant pressure boundary and infinite-acting boundary) without a priori user specification of the boundary type. Sensitivity analysis for a set of model parameters is performed using 4,000 synthetic cases prepared via a fully automated process and using machine-learning-based feature selection. The stochastic analysis identifies gravitational number (i.e., ratio of gravitational forces to viscous force) and distance between the injection well and observation location as the most impactful parameters for matching the pressure and CO 2 saturation, respectively, between the numerical simulations and the ROM. This report details the possible ROM uncertainties and serves as a guide for users to understand the use and limitations of this ROM. The code implementation of the model will be released as a module within the NRAP-Open-IAM.

54 ENVIRONMENTAL SCIENCES↗

The geology of the Viking Lander 2 site

Models are discussed of several competitive geologic histories that can be hypothesized for the Viking Lander 2 site, none of which is uniquely persuasive. The craft landed on a flat plain of fine-grained sediment overlain by dispersed evenly distributed boulders. The fine-grain material appears to be part of a high-latitude mantle comprising material swept south of the pole regions. The boulders, which are covered by distinctive deep pits, or vesicles, may be the residue of an ejecta deposit from the crater Mie. Alternatively, they may be the remnants of lava flows which formerly covered the region. Polygonal sediment-filled cracks may have been formed by ice wedging, similar to the process that occurs in terrestrial permafrost regions. The possibility that they are desiccation polygons may not be excluded.

Mutch, T. A.↗

Deep Learning for Modeling Enhanced Geothermal Systems

Enhanced Geothermal Systems (EGS) offer a vast potential to expand the use of geothermal energy. Heat is extracted from this engineered system by injecting cold water into a subsurface fractures, which are in contact with the hot dry rock, and pulled through the production wells. Creating EGS requires improving the natural permeability of hot crystalline rocks. To develop economically viable EGS reservoirs, significant technical barriers (e.g., better stimulation technologies without adequate water and/or permeability) and non-technical barriers (e.g., land access and permitting) must be overcome. In this short conference paper, we present a workflow to address a part of this challenge – “How to develop economically viable EGS using existing technologies?”. Our workflow called the GeoThermalCloud (GTC) for EGS, leverages recent advances in machine learning, deep learning, and cloud computing. This GTC framework is open-source and available at https://github.com/SmartTensors/GeoThermalCloud.jl. The GTC framework provides trained deep learning (DL) models to estimate the net present value of a given EGS design scenario. The Geothermal Design Tool (https://github.com/GeoDesignTool/GeoDT.git), a fast and simplified multi-physics solver, is used to develop a database for training DL models. The database consists of EGS design parameters (inputs to DL model) and their net present value (output of DL model) in uncertain geologic systems. The EGS design parameters for constructing this training database are based on Utah FORGE but include the options of more wells and deeper depths. The DL models are trained by ingesting the EGS design parameters and estimating the corresponding net present value. Such an emulation allows us to screen various EGS designs quickly and identify good development strategies by coupling them with optimization techniques. Our preliminary results show promise in DL emulation of net present value. However, a lot more work is needed to improve the predictive capability of DL models (i.e., extensive hyperparameter tuning is necessary). This will be the primary focus of our future work.

artificial neural networks, geothermal↗

Geophysical and Environmental Monitoring Data, and Subsurface Flow Modelling Results for Chicken Bone Meadow, Mt. Snodgrass, Crested Butte, CO

This dataset includes geoelectrical monitoring data acquired between October 2021 and November 2022, soil moisture and temperature data, groundwater data obtained from borehole SNIB covering the period from June 2021 to September 2022, and hydrological modelling results. The data were acquired to investigate how variations in bedrock type and topography, and vegetation cover control subsurface flow dynamics. To provide insights into the subsurface flow dynamics and their controls, a monitoring transect was installed at the Chicken Bone Meadow, Mt. Snodgrass, Crested Butte, CO, measuring the spatio-temporal variations of soil moisture, soil and snow temperature, subsurface electrical resistivity variations, and groundwater dynamics. Field data are organized in a folder structure, with Electrical Resistivity Tomography (ERT) data being provided as one file per measurement, and data of the soil moisture and temperature sensors being provided as text files covering the entire monitoring period. The ‘Locations.csv’ file contains the location of all sensors, given in NAD83 – UTM Zone 13N. ERT monitoring data has been processed to filter data based on reciprocal errors (data with errors > 30% were removed), a linear error model was fitted to each survey, and to ensure a constant set of measurements for time-lapse inversion, filtered data were interpolated and assigned a 100% measurement error. Soil moisture and temperature data were acquired at 15 min intervals, and averaged to provide 1h data. Weather data and borehole data (groundwater depth, conductivity and temperature) were acquired at 30 min intervals, and are provided as daily measurements; all measurements are averaged, except of precipitation values, which are given as daily accumulation. The hydrological model was set up along the ERT monitoring transect, and net infiltration was used as surface boundary condition and derived from the weather data. Four different results are provided, (1) results for a parameterization using hydraulic permeability and porosity as derived from the ERT data through petrophysical relationships, and (2) three simplified model results, using 1 to 3 geological layers above the bedrock. Modelling was performed using PFLOTRAN, and for each model the PFLOTRAN input files are provided. The result files include weekly hydrological modelling results (e.g., saturation, velocities, pressures), as well as the model parameterization. The dataset additionally includes a file-level metadata (flmd.csv) file that lists each file contained in the dataset with associated metadata; and a data dictionary (dd.csv) file that contains column/row headers used throughout the files along with a definition, units, and data type.

54 ENVIRONMENTAL SCIENCES↗

Groundwater and Surface Water Flow (GSFLOW) model files to explore bedrock circulation depth and porosity in Copper Creek, Colorado

This data package contains integrated hydrological model input and output files for Copper Creek, Colorado (24 km2), a tributary of the East River located in the headwaters of the Upper Colorado River Basin. The model code is the U.S. Geological Survey (USGS) Groundwater and Surface Water Flow (GSFLOW) model. The model contains a 100-m grid resolution and a daily timestep. The land surface model is dynamically linked to a three-dimensional groundwater flow model that allows for streamflow gaining and losing conditions. The groundwater model contains 12 model layers and extends 400 m below land surface. The original Copper Creek model was modified to contain geologic layers representing saprolite, shallow bedrock, and deep bedrock. Endmember depth versus hydraulic conductivity relationships and porosity values for fractured crystalline rock are simulated. For the shallow case, median flow depths occur in the shallow saprolite at depths <8 m, while the deep case promotes a median groundwater flow depth of 100 m. With this modeling framework we compare streamflow response to a plausible worst-case drought lasting up to five years. Streamflow metrics of analysis include average streamflow, fraction of stream network that is dry, no-flow duration, average groundwater flow to streams and time to recovery following the drought. Results and implications are presented in a paper submitted to Geophysical Research Letters titled, "The role of bedrock circulation depth and porosity in mountain streamflow response to prolonged drought" by Rosemary WH. Carroll, Andrew H. Manning and Kenneth H Williams. A Readme.txt file provides instructions on how to download all model files and execute each model scenario. In addition to the GSFLOW output/prms/copper_drought.csv file containing daily basin water stores and fluxes (refer to GSFLOW manual) and the output/prms/copper_drought_statvar.dat file with output defined in the gsflow3.control file (refer to GSFLOW Manual), output files also include spatially distributed daily values of total evapotranspiration, canopy evaporation, precipitation, snowfall, infiltration, snow water equivalent, potential evapotranspiration, recharge, sublimation, soil moisture, contributing interflow, water table elevations, changes in groundwater storage, groundwater evapotranspiration, interbasin groundwater flow (limited to the alluvium below the stream outlet), and surface-groundwater exchanges within the river system.

54 ENVIRONMENTAL SCIENCES↗

A deep learning-based workflow for fast prediction of 3D state variables in geological carbon storage: A dimension reduction approach

Deep learning (DL) models are extensively used as surrogate models for high-fidelity simulations of multiphase fluid flow in porous media at large scales, enabling fast forecasts of the spatial–temporal evolution of three-dimensional (3D) state variables in geological carbon storage (GCS). However, training these models in high-dimensional space remains computationally demanding and prone to overfitting because of limited training data. This paper presents a novel workflow to address these challenges by integrating dimension reduction (DR) methods. Here, the proposed workflow employed pre-trained DR models to extract the latent variables of geological models and state variables and utilized the multi-layer perceptron (MLP) for constructing mapping functions between the input and output variables in latent spaces. Subsequently, the pre-trained reconstruction models converted the MLP-predicted latent state variables to their original high-dimensional form. Furthermore, we proposed a novel strategy for the DR and reconstruction of 3D saturation fields to account for the unique data characteristics of sparsity, nonuniformity, and discontinuity. The proposed strategy applied PCA and inverse PCA for 2D average saturation fields and developed a DL-based 3D reconstruction model, leveraging three 2D average saturation fields as input to produce a 3D saturation field as output. The pre-training of DR and reconstruction models and training of MLP models were conducted on 84 Gulf of Mexico (GoM) simulations and evaluated on 12 testing simulations. Each simulation contained 720 monthly time steps, with the first 360 months as the injection period and the rest as the post-injection period. The proposed workflow, incorporating DR and DL models, accurately predicts the normalized 3D pressure fields, achieving mean square error (MSE) of 2.92 × 10 -7 compared to the ground truth obtained from a full-physics simulator. Furthermore, the proposed strategy outperformed PCA and convolutional autoencoder (CAE) models on 3D saturation fields, resulting in minor workflow prediction errors with an MSE of 2.93 × 10 -5 . The results suggest the proposed workflow provides sufficient predictive fidelity across temporal and spatial scales, and enables a speedup of 160 times compared to the full-physics simulator, facilitating improved decision-making and risk assessment for large-scale GCS management in real-time scenarios.

3D reconstruction model↗