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All sources NASA NTRS DOE OSTI

DOE OSTI2022

Optimization of Water-Alternating-CO2 Injection Field Operations Using a Machine-Learning-Assisted Workflow

Summary This paper will present a robust workflow to address multiobjective optimization (MOO) of carbon dioxide (CO2)-enhanced oil recovery (EOR)-sequestration projects with a large number of operational control parameters. Farnsworth unit (FWU) field, a mature oil reservoir undergoing CO2 alternating water injection (CO2-WAG) EOR, will be used as a field case to validate the proposed optimization protocol. The expected outcome of this work would be a repository of Pareto-optimal solutions of multiple objective functions, including oil recovery, carbon storage volume, and project economics. FWU’s numerical model is used to demonstrate the proposed optimization workflow. Because using MOO requires computationally intensive procedures, machine-learning-based proxies are introduced to substitute for the high-fidelity model, thus reducing the total computation overhead. The vector machine regression combined with the Gaussian kernel (Gaussian-SVR) is used to construct proxies. An iterative self-adjusting process prepares the training knowledge base to develop robust proxies and minimizes computational time. The proxies’ hyperparameters will be optimally designed using Bayesian optimization to achieve better generalization performance. Trained proxies will be coupled with multiobjective particle swarm Optimization (MOPSO) protocol to construct the Pareto-front solution repository. The outcomes of this workflow will be a repository containing Pareto-optimal solutions of multiple objectives considered in the CO2-WAG project. The proposed optimization workflow will be compared with another established methodology using a multilayer neural network (MLNN) to validate its feasibility in handling MOO with a large number of parameters to control. Optimization parameters used include operational variables that might be used to control the CO2-WAG process, such as the duration of the water/gas injection period, producer bottomhole pressure (BHP) control, and water injection rate of each well included in the numerical model. It is proved that the workflow coupling Gaussian-SVR proxies and the iterative self-adjusting protocol is more computationally efficient. The MOO process is made more rapid by squeezing the size of the required training knowledge base while maintaining the high accuracy of the optimized results. The outcomes of the optimization study show promising results in successfully establishing the solution repository considering multiple objective functions. Results are also verified by validating the Pareto fronts with simulation results using obtained optimized control parameters. The outcome from this work could provide field operators an opportunity to design a CO2-WAG project using as many inputs as possible from the reservoir models. The proposed work introduces a novel concept that couples Gaussian-SVR proxies with a self-adjusting protocol to increase the computational efficiency of the proposed workflow and to guarantee the high accuracy of the obtained optimized results. More importantly, the workflow can optimize a large number of control parameters used in a complex CO2-WAG process, which greatly extends its utility in solving large-scale MOO problems in various projects with similar desired outcomes.

Energy & Fuels↗

DOE OSTI2020

Assessing mechanical response of CO 2 storage into a depleted carbonate reef using a site-scale geomechanical model calibrated with field tests and InSAR monitoring data

Geomechanical risks of injection have raised concerns regarding secure CO 2 storage. In this work, a combined monitoring and modeling approach is used to assess the stress changes and surface uplift associated with CO 2 injection into a depleted carbonate reef of the Michigan basin. A site-scale geomechanical model is built by assigning mechanical properties of formations using well-log and experimental data. Gravity load is applied to the model to estimate the vertical component of stress as well as different lateral boundary displacement scenarios to estimate horizontal stresses. We used a poroelastic pressure-dependent model (instead of a linear elastic mechanical earth model) to calibrate initial stresses using hydraulic fracture test data measured at depleted reservoir status. Multi-phase fluid flow-geomechanical simulations are performed to estimate the poroelastic response during (1) primary depletion (2) field-scale CO 2 injection phase (3) a hypothetical forecast scenario in which well bottom hole pressure (BHP) reach 45000 KPa. The predicted surface uplift is less than 1 mm at the end of the field-scale CO 2 injection phase which is in good agreement with Interferometric Synthetic Aperture Radar (InSAR) uplift measurement. Although the InSAR data shows an insignificant uplift, hydromechanical modeling of injection shows that CO 2 injection still causes reservoir deformation emphasizing the role of carbonate overburden and reservoir formation mechanical properties and limited size of reef on diminishing the surface deformation. Modeling indicates poroelastic response of caprock matters to estimate uplift. The lower permeability of the top two layers provides additional barrier to large uplift. Also, history of subsidence due to production should be accounted to predict uplift due to a follow up injection correctly. This report shows the significance of combining a calibrated geomechanical model with field measured stresses and monitoring data to be used as a tool to ensure the safety of CO 2 storage.

42 ENGINEERING↗

DOE OSTI2025

Quantifying the Effect of Pore‐Size Dependent Wettability on Relative Permeabilities Using Lattice Boltzmann Simulation

Relative permeability is a crucial two-phase property in porous media that can be significantly impacted by wettability conditions. While traditional research has predominantly examined homogeneous wettability, this work explores the less studied pore-size dependent (PSD) wettability, featured by a pore-size dependent wettability distribution. Leveraging high-fidelity Lattice Boltzmann simulations on CT-scanned porous samples, we demonstrate how PSD wettability would impact relative permeability at the pore scale. Our findings reveal that the deviation of relative permeability from the homogeneous wettabilitity induced by PSD wettability can be 5%–20%. The deviation of relative permeability curves increases as the spanning range of the contact angle increases. We also find that this impact is less pronounced as the capillary number increases. By adopting a pore-size-dependent contact angle relationship, our approach provides a more accurate and nuanced understanding of how PSD wettability would impact two-phase flow. These findings discovered at the pore scale may also provide valuable insights on relative permeability at the core to reservoir scales.

25 ENERGY STORAGE↗

DOE OSTI2024

Multisectoral analysis of drought impacts and management responses to the 2008–2015 record drought in the Colorado Basin, Texas

Abstract. Drought has long posed an existential threat to society. Engineering and technological advancements have enabled the development of complex, interconnected water supply systems that buffer societies from the impacts of drought, enabling growth and prosperity. However, increasing water demand from population growth and economic development, combined with more extreme and prolonged droughts due to climate change, poses significant challenges for governments in the 21st century. Improved understanding of the cascading multisectoral impacts and adaptive responses resulting from extreme drought can aid in adaptive planning and highlight key processes in modeling drought impacts. The record drought spanning 2008 to 2015 in the Colorado Basin in the state of Texas, United States, serves as an outstanding illustration to assess multisectoral impacts and responses to severe, multi-year drought. The basin faces similar water security challenges to those across the western US, such as groundwater depletion and sustainability, resource competition between agriculture and growing urban populations, limited options for additional reservoir expansion, and the heightened risk of more severe and frequent droughts due to climate change. By analyzing rich, high-quality data sourced from nine different local, state, and federal sources, we demonstrate that characterizing regional multisector dynamics is crucial to predicting and understanding future vulnerability and possible approaches to reduce impacts to human and natural systems in the face of extreme drought conditions. This review reveals that, despite the severe hydrometeorological conditions of the drought, the region's advanced economy and existing water infrastructure effectively mitigated economic and societal impacts.

54 ENVIRONMENTAL SCIENCES↗

DOE OSTI2019

Experimental Realization of a Quantum Dot Energy Harvester

We demonstrate experimentally an autonomous nanoscale energy harvester that utilizes the physics of resonant tunneling quantum dots. Gate-defined quantum dots on GaAs/AlGaAs high-electron-mobility transistors are placed on either side of a hot-electron reservoir. The discrete energy levels of the quantum dots are tuned to be aligned with low energy electrons on one side and high energy electrons on the other side of the hot reservoir. Furthermore, the quantum dots thus act as energy filters and allow for the conversion of heat from the cavity into electrical power. Our energy harvester, measured at an estimated base temperature of 75 mK in a He 3 /He 4 dilution refrigerator, can generate a thermal power of 0.13 fW for a temperature difference across each dot of about 67 mK.

71 CLASSICAL AND QUANTUM MECHANICS, GENERAL PHYSIC↗

DOE OSTI2021

Development of a Framework for Data Integration, Assimilation, and Learning for Geological Carbon Sequestration (DIAL-GCS) (Final Report)

This project aimed to develop and demonstrate a Data Integration, Assimilation, and Learning framework for geologic carbon sequestration projects (DIAL-GCS). DIAL-GCS is an intelligence monitoring system (IMS) for automating GCS closed-loop management by leveraging recent developments in machine learning technologies, complex event processing (CEP), and reduced-order modeling. The safe and efficient operation of GCS repositories requires integrated monitoring to track the injected CO¬2 as it moves within a storage reservoir. GCS projects are data intensive, as a result of proliferation of digital instrumentation and smart-sensing technologies. GCS projects are also resource intensive, often requiring multidisciplinary teams performing different monitoring, verification, accounting (MVA) tasks throughout the lifecycle of a project to ensure secure containment of injected CO2. The success of GCS thus depends in a large part on our ability to access, assimilate, and analyze heterogeneous data and information sources in a timely manner. This project included a number of meaningful and necessary tasks to transform the human domain knowledge into machine-interpretable rules for automating knowledge extraction and discovery in GCS. The specific technical objectives of the proposed DIAL-GCS project were to develop an ontology-driven GCS data management module for storing, querying, and exchanging GCS data (both historic and live sensor data) from multiple sources and in heterogeneous formats. Incorporate a CEP engine for detecting abnormal situations by seamlessly combining expert knowledge, rule-based reasoning, and machine learning. Enable uncertainty quantification and predictive analytics using a combination of coupled-process modeling, AI/ML methods, and reduced-order modeling, and integrate and demonstrate the system’s capabilities with both real and simulated data. As far as we know, this is one of the first projects aimed to develop intelligent monitoring systems (IMS) targeting the GCS. Under this project, the team had developed a large number of web applications and scientific algorithms that contribute the main theme of intelligent monitoring. The team has published more than a dozen peer reviewed papers and disseminated the research results at multiple technical meetings.

29 ENERGY PLANNING, POLICY, AND ECONOMY↗

DOE OSTI2021

Secondary porosity prediction in complex carbonate reefs using 3D CT scan image analysis and machine learning

Development and preservation of carbonate porosity and permeability are critical to characterizing reservoirs. However, secondary porosity, such as vugs and fractures, are difficult to identify and require collection of expensive wireline tools or core sampling. Wireline logs and cores have traditionally been used to identify the presence of secondary porosity but fail to quantify the contribution to total reservoir porosity. Additionally, advanced wireline logs and core are not readily available for most wells. Dual energy CT scans were collected on whole core from the A-1 Carbonate and Brown Niagaran formations drawn from six wells in northern Michigan. 3D analysis techniques were applied to identify and isolate secondary porosity features. A series of machine learning and data analytics techniques were applied to the dataset to predict secondary porosity features on basic wireline logs. The predictive model successfully predicted secondary porosity with high confidence.

02 PETROLEUM↗

NASA NTRS2015

Life in the Clouds of Venus? An Experimental Synthetic Biology Approach

The surface of Venus constitutes the most hellish and biologically inhospitable planetary surface in our solar system, boasting a pH of 0, blistering winds that can melt lead, and pressures of 60 atm. However, during the earlier years of the solar system, without the runaway greenhouse effect that has plagued the planet, Venus potentially housed oceans and perhaps even life. There is a possibility that microbes could have retreated into hospitable niches in the atmosphere, as suggested by Carl Sagan as early as 1967 [1]. For example, 50 km above the raging hell of the Venusian surface, exists a relatively temperate environment that might serve as reservoir for life. This astrobiology project seeks to explore life at the extremes and to theorize whether microbial communities could not only survive but also reproduce in the Venusian atmosphere. Specifically, we ask: are aerosols viable microbial environments? But before we can test for life in the clouds, we have to develop a proper reporter to visualize cell growth in situ. For this purpose, we aimed to develop cell-growth dependent reporters to serve as remote biosensors for cell growth. We developed two using the polA promoter, a DNA-replication dependent promoter, and nrd operon promoter, a cell-cycle dependent promoter. Using these cell-growth reporters, the next step is to aerosolize microbes expressing these reporters in a suspension chamber adapted from a Millikan Drop Apparatus to assay reproduction in an aerosolized environment. Better yet is to test the reproduction of microbes in a microgravity regime such as on ISS.Approach: We engineered two cell-cycle dependent genetic reporters. One was the polA promoter which codes for DNA Polymerase I, a gene active in DNA replication [2]. The other was the nrdP. The activation of ribonucleotide reductase reduces ribonucleotides into deoxyribonucleotides and is involved in the bacterial cell cycle [3]. This promoter began activation during the initiation of DNA replication and is cell-cycle dependent [4]. These promoters were fused to a GFP reporter, transformed into E. coli. The constructs were deposited in the iGEM registry as K847210: Escherichia coli DNA-replication dependent polA promoter K847211: Escherichia coli cell-division dependent nrd promoter Results: Our constructs displayed fluorescence when transformed into NEB-5alpha competent cells. While nrdP-E0840 displayed sufficient fluorescence as verified by fluorescent microscopy, the original polAP-E0840 construct (which uses mut3b GFP) exhibited low expression; while fluorescence was visible under the microscope, the signal was too weak for the camera to recognize. The polA promoter was therefore digest-ed with EcoRI and SpeI then ligated into plasmid pNCS containing a RBS, Clover, and a terminator. Clover is a highly engineered green fluorescent protein that exhibits extreme brightness [5] Fluoresence time course data demonsrated that the genes were induced in a cell cycle dependant manner [6]. Our assays via microscopy and the bulk assay shows that our promoters are functional as cell cycle reporters.Conclusions: The application of such tools are widespread and not limited to astrobiology; nrdP could be used to determine doubling times empirically and could possibly extrapolate DNA content from intensity of signals expressed by polAP. However, we are pri-marily interested in its use in astrobiology.

Escherichia↗

DOE OSTI2021

NRAP-Open-IAM: FutureGen2 Component Models

This report describes the development and testing of three component models for NRAP-Open-IAM, the National Risk Assessment Partnership’s open-source integrated assessment model. The FutureGen2 Lookup Table Reservoir component model is based on interpolation of data from a set of lookup tables. The lookup tables contain pressures and saturations predicted by multiphase flow simulations performed with a reservoir simulator. The FutureGen2 Above Zone Monitoring Interval (AZMI) component is a surrogate model that can be used to estimate the impact that carbon dioxide (CO 2 ) and brine leaks from the CO 2 storage reservoir at the FutureGen 2.0 site might have had on overlying aquifers or monitoring units were a leak to occur. The model estimates the size of “impact plumes” according to five metrics: pH, Total Dissolved Solids (TDS), pressure, dissolved CO 2 and temperature. The FutureGen2 Aquifer component is similar, but is limited to four metrics: pH, Total Dissolved Solids (TDS), pressure, and dissolved CO 2 . The input parameters for each model are the same, but the Aquifer component is applicable to depths between 100 m and 700 m and the AZMI component is applicable from depths between 700 m and 1050 m.

42 ENGINEERING↗

DOE OSTI2025

ZIPPER: Zonal isolation with plug and perf in enhanced reservoirs (Final Technical Report)

Modern multistage hydraulic stimulation treatments in cased wellbores require an effective method of isolating stages between treatments. A commonly used method in the oil and gas industry, plug and perf, is not currently viable for Enhanced Geothermal Systems (EGS) due to limitations of a critical component of the system – the ball drop (flow through) frac plug. Commercially available ball drop frac plugs do not meet the temperature or wellbore diameter requirements needed for use in EGS stimulations. For example, one particular drillable bridge and frac plug line from a large tool developer is only rated to 175 °C, while another is only available up to casing sizes of 5 ½” and rated up to 204 °C. We developed, prototyped, and field tested an upgraded ball drop frac plug to meet the requirements of EGS stimulations, including high-temperature (225+ °C), differential pressure (6000+ psi), and wellbore diameters ranging from 6 5/8” to 10 5/8”. We focused on designs and materials to optimize drillability, a key cost driver in plug and perf systems. The primary objective was to upgrade a drillable frac plug (currently rated to a temperature of 175°C and a pressure of 10,000 psi in 7” casing) to withstand temperatures of 225+°C. The upgraded frac plug was tested in the laboratory as well as in a field trial at a geothermal field. Engineering design and fabrication of the new plug was completed in 2019. Lab testing, validation, and qualification of the plug was completed in 2020. Ultimately the plug was successfully run during a multistage stimulation treatment in a fully horizontal EGS well in 2022. Prior to this project, a ball-drop, flow-through stimulation plug had never been used in a geothermal well. At the conclusion of this project, three different types of zonal isolation plugs were evaluated under full-scale operating conditions across 16 stimulation treatment stages in a first-of-a-kind EGS project called Project Red. This trial included the newly designed high-temperature, large-diameter plug. The plugs met all of 5 the technical requirements for commercial viability. Project Red has since been fully commissioned and is generating electricity on the Nevada grid - the first EGS project to successfully deliver power to the grid in the US.

15 GEOTHERMAL ENERGY↗

DOE OSTI2025

Carbon Storage in Fold‐and‐Thrust Belts: An Overlooked Gigatonne Storage Opportunity

This study presents numerical investigations of the trapping characteristics of fold-and-thrust belt structures, defining three carbon capture and storage (CCS) play types that could be used to store commercial volumes (millions of tonnes) of CO 2 . Specifically, we present simulations of CO 2 storage in three fold-and-thrust belt models comprising a thrust-ramp, duplex, and thrust-fold geometry. To constrain these play types in realistic geology, each model is based on a study site, including a novel investigation of a greenfield saline reservoir in Virginia, USA, being considered for commercial carbon storage and two well-characterized petroleum fields: the Wilburton field in Oklahoma, USA, and the Incahuasi field in Bolivia. Our results provide insight into several key parameters, such as the long-term security of injected CO 2 in these geologies and injection strategies for maximizing storage efficiency while reducing pressure-related risk. These results improve the understanding of CCS in fold-and-thrust belt storage sites globally by describing general storage parameters that may be applied to site-specific projects. We find that thrust-ramp geometries may securely trap CO 2 through solubility and hydrodynamic trapping under suitable reservoir conditions, duplex structures may store some quantities of CO 2 but are pressure-constrained, and that thrust-ramp structures may store large quantities of CO 2 by maximizing fetch volume, which simultaneously lowers geomechanical risk by reducing pressure buildup along zones of weakness.

42 ENGINEERING↗

NASA NTRS2002

The Genesis Mission: Contamination Control and Curation

The Genesis mission, launched in August 2001, is collecting samples of the solar wind and will return to Earth in 2004. Genesis can be viewed as the most fundamental of NASA's sample return missions because it is expected to provide insight into the initial elemental and isotopic composition of the solar nebula from which all other planetary objects formed. The data from this mission will have a large impact on understanding the origins and diversity of planetary materials. The collectors consist of clean, pure materials into which the solar wind will imbed. Science and engineering issues such as bulk purity, cleanliness, retention of solar wind, and ability to withstand launch and entry drove material choices. Most of the collector materials are installed on array frames that are deployed from a clean science canister. Two of the arrays are continuously exposed for collecting the bulk solar wind; the other three are only exposed during specific solar wind regimes as measured by ion and electron monitors. Other materials are housed as targets at the focal point of an electrostatic mirror, or "concentrator", designed to enhance the flux of specific solar wind species. Johnson Space Center (JSC) has two principal responsibilities for the Genesis mission: contamination control and curation. Precise and accurate measurements of the composition of the solar atoms require that the collector materials be extremely clean and well characterized before launch and during the mission. Early involvement of JSC curation personnel in concept development resulted in a mission designed to minimize contaminants from the spacecraft and operations. A major goal of the Genesis mission is to provide a reservoir of materials for the 21 51 century. When the collector materials are returned to Earth, they must be handled in a clean manner and their condition well documented. Information gained in preliminary examination of the arrays and detailed surveys of each collector will be used to guide sample allocations to the scientific community. Samples allocated for analysis are likely to be small sections of individual collectors, therefore subdividing the materials must take place in a clean, well characterized way. A major focus of current research at JSC includes identifying and characterizing the contamination, waste, and alteration of the sample when using different subdividing, transport, and storage techniques and developing protocols for reducing their impact on the scientific integrity of the mission.

Stansbery, E. K.↗

DOE OSTI2024

A dynamic solvent chamber propagation estimation framework using RNN for warm solvent injection in heterogeneous reservoirs

Warm solvent injection (WSI), injecting low-temperature solvent into formations to reduce the viscosity of heavy oil, is a clean technology for heavy oil production through reducing greenhouse gas emissions and water usage. The success of WSI operation depends on the uniform development and propagation of solvent chambers in reservoirs. However, reservoir heterogeneity stemming from shale barriers plays a detrimental role in the conformance of solvent chamber development and oil production rate. In this work, we developed a novel recurrent neural network (RNN)-based framework with the capability of efficiently tracking and estimating the solvent chamber positions in heterogeneous reservoirs based on only production time-series data. The developed estimation model utilizes the “sequence-to-sequence" mapping methodology to correlate observed production time-series sequence and solvent chamber edge sequence via a long short-term memory (LSTM) algorithm. The trained RNN models exhibit high accuracy, evidenced by the predicted dynamic solvent chamber locations match the corresponding true locations from numerical simulation, with a high coefficient of determination (R 2 ) and a low mean squared error. Specifically, the achieved R 2 values exceed 0.98 on both the training and testing data. The developed RNN-based workflow was tested via several cases from both regularly- and irregularly-shaped shale barriers, and the results were promising. The predicted solvent chambers showed strong agreement with those obtained from numerical simulations. The major benefits of this workflow include reducing computational time and saving overall monitoring and tracking costs for conventional techniques. In conclusion, the present work would provide a good demonstration of the capability of practical integration of machine learning methods in solving engineering problems.

58 GEOSCIENCES↗

DOE OSTI2023

Hydropower Resilience Database for Assessing Microgrid Formation Capability and Enhancing Power Grid Resilience

In the face of increasing frequency of extreme events, enhancing resilience and reliability of energy infrastructure demands innovative solutions. Hydropower, with its inherent generation flexibility and grid-forming capability, offers significant potential for enhancing power grid resilience through the establishment of microgrids. To enable informed decision-making and strategic planning, we present the Hydropower Resilience Database (HRD) that integrates data from various sources such as Oakridge National Laboratory (ORNL) HydroSource, National Inventory of Dams, and US Western Grid database. By integrating relevant information on hydropower plant characteristics, including dams, reservoirs, and connected electrical grid, this resource enables hydropower plant owners, utilities, and community stakeholders to identify and evaluate the feasibility of using hydropower resources in microgrids to support nearby communities and critical infrastructure in various challenging scenarios. Using HRD, a set of metrics are evaluated to quantify the capability of hydropower plants to support essential microgrid functions. An interactive tool is developed using ArcGIS, enabling the visualization and analysis using HRD. Our research contributes to strategic planning efforts for fortifying energy infrastructure, ensuring reliable power supply during disruptions, and advancing the development of robust and resilient energy systems in regions susceptible to grid vulnerabilities.

13 HYDRO ENERGY↗

DOE OSTI2023

Hydropower Resilience Database for Assessing Microgrid Formation Capability and Enhancing Power Grid Resilience

13 HYDRO ENERGY↗

DOE OSTI2023

Evaluating Production Implications of Pressure Maintenance in Unconventional Oil and Gas Wells using a Machine Learning Modeling Approach: Case Study in the Permian Basin

This study implements the proprietary machine learning-based model (model) developed under the 2022 study titled “Evaluating the Impact of Proprietary Oil & Gas Data on Machine Learning Model Performance Using a Quasi-Experimental Analytical Approach” for forecasting unconventional oil and gas production using well data from the Permian Basin. The model, developed using an exclusive dataset that includes time series production data from an operator in the Permian Basin, is designed to jointly predict daily oil, gas, and water production for horizontal wells as a function of bottomhole pressure drawdown, spatial placement across the study domain, and well-completion attributes. In this study, the model was explicitly applied to explore its utility to evaluate the impact of varying drawdown strategies on the production forecast of a well in the Permian Basin dataset. Managing pressure drawdown has been identified as a way to improve estimated ultimate recovery (EUR) from unconventional shale wells due to the stress-dependent nature of fractures in shale reservoirs. Research has shown that applying a lower pressure drawdown helps to maintain the reservoir conductivity, resulting in higher productivity over the life of a well. Historic bottomhole pressure data from the well over time was used as a benchmark from which to set more and less aggressive pressure decline rates as bounding modeling cases. All pressure decline rates/strategies were forecasted over 5 years, and the model was used to generate oil, water, and gas prediction over the same timeframe. This report presents the results from the production forecast and discusses potential operational and economic implications, with contrasting perspectives between well productivity and profitability given typical oil and gas economics and the volatility in the oil and gas market.

02 PETROLEUM↗

NASA NTRS1998

Subsurface Structure in the Martian Polar Layered Deposits: The Deep Space 2 Impact Accelerometry Experiment

While primarily a technology demonstration mission, the New Millenium Mars Microprobes (also known as Deep Space 2, or simply DS2)will also provide the first in situ science measurements of the martian subsurface. The DS2 impact accelerometry experiment will provide both engineering data about the depth of probe emplacement and science data about the physical nature of the subsurface at the probes' landing sites. Little is known about the detailed physical properties or small-scale vertical structure of the subsurface at the DS2 landing site in the southern martian polar layered deposits. Imaging data from the Viking Orbiters and Mars Global Surveyor reveal alternating bands of light and dark material in this region with thicknesses at least as small as the limit of resolution, about 10 m. The overall composition of these layers is poorly constrained, but generally thought to be a mixture of dust and ice with the layers being caused by variations in the dust/ice ratio, or perhaps by dust deposits of different densities. Low thermal inertias in the region suggest that the top few centimeters of the surface are composed of a mantling of fine-grained dust. However, 3.5-cm radar returns indicate that the maximum depth of this dust is not greater than a few tens of centimeters. Thermal models generally agree that, while the layered deposits do provide a potential near-surface reservoir for ice, the uppermost few centimeters to meters in these regions are likely to be ice-free because of sublimation losses. Finally, while it is generally agreed that the layered deposits are the product of variations in the martian climate, no direct correlation has been made between band sequences and specific climate changes. Our intention is to shed light on some of these questions about the martian polar layered deposits by using the DS2 accelerometry experiment to determine the physical nature of the layered deposits, and to detect the presence of any subsurface layering of dust, ice, and/or rock. In the process, we will also determine the final resting depth of the two microprobes, an important parameter in the interpretation of other DS2 experiments.

Moersch, J. E.↗

DOE OSTI2022

Maximizing the Proppant Carrying and Viscoelastic Properties of the Bakken Hypersaline-Produced Water with High-Viscosity Friction Reducers for Sustainable Applications

Summary The development and production of unconventional reservoirs, such as the Bakken Formation, have become a resolved mystery for operators in North America since the arrival and advancement of horizontal drilling and hydraulic fracturing technologies. As a result, unconventional reservoir assets became the central focus of the oil and gas industry at the state, national, and global levels. The produced water from these activities in the Bakken Formation have high salt contents (110,000–350,000 ppm) total dissolve solids (TDS) and can pose significant challenges to the environment if not treated. Deep injection into disposal wells is the routine method used to get rid of the Bakken produced water. However, there have been some concerns that unrestrained injections, in addition to polluting the groundwater, could potentially lead to seismic activities either at the time of injection or in the near future. To diminish the environmental impacts that may be associated with induced seismicity, including the reduction of the costs of water acquisition, the produced water can be treated and reused in the hydraulic fracturing processes. Also, the treated water could be used for irrigation purposes, for power generation, and coal mining operations. The issues of waste water and residual oil high in TDS are challenges yet to be effectively addressed despite preceding research and studies on advancing produced water technologies. The goal of this study is to explore all applicable ways by which the produced water from the Bakken Formation can serve as a replacement base fluid for use with polymers like the high-viscosity friction reducers (HVFRs) to create hydraulic fracturing fluids that can be stable with reservoir conditions and also be able to minimize environmental impacts and cost of operations. Experimental investigations using the high-salinity produced water from the Bakken Formation with HVFRs were carried out. The studies included a base case that served as a bench mark for comparing the effectiveness of the other scenarios. The results indicate that the Bakken hyper-saline produced water can withstand effect of heavy metals, salinity, hardness and remain stable through different shear rates (66–330 s−1) when treated with higher dosages [4–8 gal/1,000 gal (gpt)] of HVFRs. Filtration and dilution were the only methods used on the Bakken Formation produced wate for this research

Engineering↗