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At least 235 records · Page 13

Techno-Economic Analysis and Market Potential of Geological Thermal Energy Storage (GeoTES) Charged With Solar Thermal and Heat Pumps into Depleted Oil/Gas Reservoirs and Shallow Reservoirs: A Technology Overview: Preprint

Depleted oil/gas reservoirs represent a waste of underground resources and investments of drilling, and also a potential risk to the earth's environment. Geologic thermal energy storage (GeoTES) is proposed as a solution to convert depleted oil/gas reservoirs into long-term seasonal energy storage. GeoTES can be hybridized with other techniques for viable commercial deployment, such as 1) concentrating solar power (CSP) collectors and 2) heat pumps with excess renewable energy. Here, a technology overview is given on the two GeoTES technologies, which includes system overview, techno-economic models, and case study. Both GeoTES technologies show great potential in the economics of individual project deployment and applicability across the US.

concentrating solar power↗

Historical Pattern Analysis of Global Geothermal Power Capacity Development

Between 1913 and 1958, Italy was the only country with an operational geothermal power plant until New Zealand installed its first plant in 1958. At present, 24 countries are involved in the geothermal power market, and they have a combined installed capacity of 16,127 GW. This study analyzes the historical patterns of geothermal power capacity in the world and in individual countries to investigate the ideal global geothermal development pattern by examining the annual cumulative capacity (ACC) and the annual capacity addition (ACA) graphs of the historical development of geothermal power capacity in 24 countries. First, the global patterns are analyzed using these graphs in five periods (1945-1957, 1958-1976, 1977-1991, 1992-2002, and 2003-2020) that are marked by a series of characteristics of ACA peaks separated by two major troughs. Then, five characteristic patterns are developed in five periods globally. These patterns correspond to the early-stage linear, the first acceleration, the first steady-state linear, the second acceleration, and the second steady-state linear developments. A positive relationship exists between global patterns and the 5-year shifted oil-price curve: two major factors influenced global development: 1) increasing oil prices and increasing awareness of global climate change, and 2) global development of geothermal power. Last, we investigate these patterns in each country. The top ten countries, which comprise 93.3% of the world's total installed capacity are separated into five groups based on the availability and characteristics of patterns globally developed in five periods. Group-1 (the United States) has an installed capacity of 3,794 MW, Group-2 (Mexico and Philippines) 963-1935 MW, Group-3 (New Zealand, Italy, Iceland, and Japan) 601-1,037 MW, and Group-4 (Indonesia, Kenya, and Turkiye) 944-2,356 MW. The remaining 14 countries (6.7%), which are called Group 5, are still in an immature stage and have installed capacities of 7-262 MW and are not involved in pattern analysis. Overall, geothermal power in the world is in its third stage of development, which had its peak development after 1977. A fourth development peak may be expected to occur after this through business-as-usual cases. The biggest barrier to the development of the global geothermal power market is the risk associated with exploration and drilling. If risk mitigation systems and funds are employed, the growth of geothermal power production projects could accelerate.

GEOTHERMAL ENERGY↗

Exploratory analysis of machine learning techniques in the Nevada geothermal play fairway analysis

Play fairway analysis (PFA) is commonly used to generate geothermal potential maps and guide exploration studies, with a particular focus on locating and characterizing blind geothermal systems. This study evaluates the application of machine learning techniques to PFA in the Great Basin region of Nevada. Following the evaluation of various techniques, we identified two approaches to PFA that produced promising results, 1) supervised Bayesian probabilistic neural networks to generate geothermal potential maps with confidence intervals, and 2) unsupervised principal component analysis paired with k-means clustering to generate both cluster maps to help identify spatial patterns, as well as new combined feature inputs. We applied these techniques to perform a comparative analysis between two principal sets of geological and geophysical features related to permeability and heat and a set of positive (known geothermal resources) and negative training sites (known drill sites with unsuitable geothermal conditions). We found that these methods constrain previously unrecognized feature controls on geothermal favorability, many of which are spatially organized within the extent of cluster groups and the major structural-hydrologic domains of the study area. Furthermore, we utilized exploratory unsupervised modeling to highlight spatial relationships between input data and predictive output results of our supervised modeling. As a result, we demonstrate how our models compare to the previous Nevada PFA and how the rapid insights these machine learning techniques offer may support future assessments of both known and undiscovered blind geothermal systems in the Great Basin region of Nevada and beyond.

15 GEOTHERMAL ENERGY↗

Space Station Habitability Recommendations Based on a Systematic Comparative Analysis of Analogous Conditions

Conditions analogous to the proposed NASA Space Station are systematically analyzed in order to extrapolate design guidelines and recommendations concerning habitability and crew productivity. Analogous environments studied included Skylab, Sealab, Tektite, submarines, Antarctic stations and oil drilling platforms, among others. These analogues were compared and rated for size and composition of group, social organization, preparedness for mission, duration of tour, types of tasks, physical and psychological isolation, personal motivation, perceived risk, and quality of habitat and life support conditions. One-hundred design recommendations concerning, sleep, clothing, exercise, medical support, personal hygiene, food preparation, group interaction, habitat aesthetics, outside communications, recreational opportunities, privacy and personal space, waste disposal, onboard training, simulation and task preparation, and behavioral and physiological requirements associated with a microgravity environment, are provided.

Stuster, Jack W.↗

Active sample acquisition system for micro-penetrators

This paper summarizes the design and development of a sub-surface sample acquisition system for use in micro-penetrators. The system was developed for flight use under NASA's New Millennium Program, Deep Space 2 project. The system goal is to acquire approximately 100 mg of Martian sub-surface soil and return it to the inside of the micro-penetrator for analysis to determine the presence of water. Various passive and active sampling techniques that were tested during the development cycle are described. After significant testing, a side bore drill mechanism was chosen to be developed for use in the flight penetrators. The design, development, and testing of mechanism element are outlined, with particular emphasis placed on actuator development, drill stem design, impact testing, and mechanism testing in various soil types. The other system elements, a pyrotechnically actuated door mechanism to seal the sample and an impact restraint mechanism, are also described.

Voorhees, Chris↗

Historical Pattern Analysis of Global Geothermal Power Capacity Development: Preprint

Between 1913 and 1958, Italy was the only country with an operational geothermal power plant until New Zealand installed its first plant in 1958. At present, 24 countries are involved in the geothermal power market, and they have a combined installed capacity of 16,127 GW. This study analyzes the historical patterns of geothermal power capacity in the world and in individual countries to investigate the ideal global geothermal development pattern by examining the annual cumulative capacity (ACC) and the annual capacity addition (ACA) graphs of the historical development of geothermal power capacity in 24 countries. First, the global patterns are analyzed using these graphs in five periods (1945-1957, 1958-1976, 1977-1991, 1992-2002, and 2003-2020) that are marked by a series of characteristics of ACA peaks separated by two major troughs. Then, five characteristic patterns are developed in five periods globally. These patterns correspond to the early-stage linear, the first acceleration, the first steady-state linear, the second acceleration, and the second steady-state linear developments. A positive relationship exists between global patterns and the 5-year shifted oil-price curve: two major factors influenced global development: 1) increasing oil prices and increasing awareness of global climate change, and 2) global development of geothermal power. Last, we investigate these patterns in each country. The top ten countries, which comprise 93.3% of the world's total installed capacity are separated into five groups based on the availability and characteristics of patterns globally developed in five periods. Group-1 (the United States) has an installed capacity of 3,794 MW, Group-2 (Mexico and Philippines) 963-1935 MW, Group-3 (New Zealand, Italy, Iceland, and Japan) 601-1,037 MW, and Group-4 (Indonesia, Kenya, and Turkiye) 944-2,356 MW. The remaining 14 countries (6.7%), which are called Group 5, are still in an immature stage and have installed capacities of 7-262 MW and are not involved in pattern analysis. Overall, geothermal power in the world is in its third stage of development, which had its peak development after 1977. A fourth development peak may be expected to occur after this through business-as-usual cases. The biggest barrier to the development of the global geothermal power market is the risk associated with exploration and drilling. If risk mitigation systems and funds are employed, the growth of geothermal power production projects could accelerate.

GEOTHERMAL ENERGY↗

Integrating Machine Learning into a Methodology for Early Detection of Wellbore Failure [Slides]

Approximately 93% of US total energy supply is dependent on wellbores in some form. The industry will drill more wells in next ten years than in the last 100 years (King, 2014). Global well population is around 1.8 million of which approximately 35% has some signs of leakage (i.e. sustained casing pressure). Around 5% of offshore oil and gas wells “fail” early, more with age and most with maturity. 8.9% of “shale gas” wells in the Marcellus play have experienced failure (120 out of 1,346 wells drilled in 2012) (Ingraffea et al., 2014). Current methods for identifying wells that are at highest priority for increased monitoring and/or at highest risk for failure consists of “hand” analysis of multi-arm caliper (MAC) well logging data and geomechanical models. Machine learning (ML) methods are of interest to explore feasibility for increasing analysis efficiency and/or enhanced detection of precursors to failure (e.g. deformations). MAC datasets used to train ML algorithms and preliminary tests were run for “predicting” casing collar locations and performed above 90% in classification and identifying of casing collar locations.

54 ENVIRONMENTAL SCIENCES↗

Integrating Machine Learning into a Methodology for Early Detection of Wellbore Failure [Slides]

Approximately 93% of US total energy supply is dependent on wellbores in some form. The industry will drill more wells in next ten years than in the last 100 years (King, 2014). Global well population is around 1.8 million of which approximately 35% has some signs of leakage (i.e. sustained casing pressure). Around 5% of offshore oil and gas wells “fail” early, more with age and most with maturity. 8.9% of “shale gas” wells in the Marcellus play have experienced failure (120 out of 1,346 wells drilled in 2012) (Ingraffea et al., 2014). Current methods for identifying wells that are at highest priority for increased monitoring and/or at highest risk for failure consists of “hand” analysis of multi-arm caliper (MAC) well logging data and geomechanical models. Machine learning (ML) methods are of interest to explore feasibility for increasing analysis efficiency and/or enhanced detection of precursors to failure (e.g. deformations). MAC datasets used to train ML algorithms and preliminary tests were run for “predicting” casing collar locations and performed above 90% in classification and identifying of casing collar locations.

54 ENVIRONMENTAL SCIENCES↗

The Icebreaker Mission to Search for Life on Mars

The search for evidence of life on Mars is the ultimate motivation for its scientific exploration. The results from the Phoenix mission indicate that the high N. latitude ice-rich regolith at low elevations is likely to be a recently habitable place on Mars [Stoker et al., 2010]. The near-surface ice likely provided adequate water activity during periods of high obliquity, 3 to 10 Myr ago. Carbon dioxide and nitrogen are present in the atmosphere, and nitrates may be present in the soil. Together with iron in basaltic rocks and perchlorate in the soil they provide carbon and energy sources, and oxidative power to drive metabolism. Furthermore, the presence of organics is possible, as thermally reactive perchlorate would have prevented their detection by Viking and Phoenix. The Mars Icebreaker Life mission [McKay et al., 2013] focuses on the following science goals: (1) Search for biomolecular evidence of life; (2) Search for organic matter from either exogeneous or endogeneous sources using methods that are not effected by the presence of perchlorate; (3) Characterize oxidative species that produced reactivity of soils seen by Viking; and 4) Assess the habitability of the ice bearing soils. The Icebreaker Life payload (Figure 1) includes a 1-m rotary percussive drill that brings cuttings samples to the surface where they are delivered to three instruments (Fig. 1), the Signs of Life Detector (SOLID) [Parro et al., 2011] for biomolecular analysis, Laser Desorption Mass Spectrometer (LDMS) [??? 2015]) for broad spectrum organic analysis, and Wet Chemistry Laboratory (WCL) [Hecht et al., 2009] for detecting soluble species of nutrients and reactive oxidants. The Icebreaker payload fits on the Phoenix spacecraft and can land at the well-characterized Phoe-nix landing site in 2020 in a Discovery-class mission.

Carbon dioxide and nitrogen↗

Fixed Bit Rotary Drilling Failure Criteria Effect on Drilling Vibration

Polycrystalline diamond compact (PDC) bit use has been expanded to geothermal drilling applications due to their improved performance in drilling compared to roller cone bits. Multiple vibration models have been developed yet and there are limited use of field data to study the ability of numerical vibration model to predict recorded vibration in the field. The objective of this paper is to evaluate the capabilities of two different rock-bit interaction models with two different ROP formulations for predicting the actual behavior seen in the field. The first model (Model-I) considers the rock-bit interaction, incorporating the effect of subsurface formation characteristics. The second model (Model-II) is a PDC bit model that uses calculated threshold weight-on-cutter (WOCt) to study the interaction of the bit with the rock surface. The models, which couple the drill stem axial and torsional motions, are solved numerically using the fourth-order Runge-Kutta method and compared with recorded downhole drilling data from the Chocolate Mountain Aerial Gunnery Range (CMAGR) geothermal well located in California. An 8–½" PDC bit with 8 blades was modeled and vibration simulation was performed to investigate stick-slip vibrations at 1400 ft. depth. Simulation results using field data indicate that Model-II encounters a low range of stick-slip severity (SSV) as compared to Model-I, which is in the moderate range. Comparison with the field value for SSV shows Model-II is the best representative of the field case for this depth. The sensitivity analysis shows that results are sensitive to model constants making prediction of SSV from models uncertain.

15 GEOTHERMAL ENERGY↗

Characterizing the Phyllosilicate Component of the Sheepbed Mudstone in Gale Crater, Mars Using Laboratory XRD and EGA

The Curiosity rover investigated the mineralogy of the Sheepbed mudstone member of the Yellowknife Bay formation in Gale crater. Data from the Chemistry and Mineralogy (CheMin) X-ray diffractometer (XRD) helped identify phyllosilicates in the two drilled samples, John Klein and Cumberland. These patterns showed peaks at low angles, consistent with (001) peaks in 2:1 swelling phyllosilicates [1]. Evolved gas analyses (EGA) by the Sample Analysis at Mars (SAM) instrument of these samples confirmed the presence of phyllosilicates through the release of H2O at high temperatures, consistent with dehydroxylation of octahedral OH in phyllosilicates [2]. CheMin data for the phyllosilicates at John Klein and Cumberland show that they are structurally similar in that their (02l) peaks are near 22.5 deg 2theta, suggesting both samples contain trioctahedral 2:1 phyllosilicates [1]. However, the positions of the (001) peaks differ: the phyllosilicate at John Klein has its (001) peak at 10 Angstroms, whereas the phyllosilicate at Cumberland has an (001) peak at 14 Angstroms. Such differences in (001) dspacings can be ascribed to the type of cation in the interlayer site [3]. For example, large monovalent cations (e.g., K(+)) have low hydration energies and readily lose their H2O of hydration, whereas small divalent cations (e.g., Mg(2+)) have high energies of hydration and retain H2O in the phyllosilicate interlayers [3,4]. The goal of this study is to determine whether differences in the interlayer cation composition can explain the CheMin data from John Klein and Cumberland and to use this knowledge to better understand phyllosilicate formation mechanisms.

Rampe, E. B.↗

Analysis of Selected Publicly Available Geothermal Exploration Data Gaps

As part of a United States Department of Energy (DOE) supported retrospective analysis of DOE's Play Fairway Analysis (PFA) projects, the National Renewable Energy Laboratory (NREL) compiled and analyzed publicly available geothermal exploration datasets to identify and highlight data gaps in areas prospective for hosting geothermal resources. The analysis was intended to understand the existing geographic coverage of selected datasets commonly utilized both by the PFA projects and geothermal developers during resource assessments including geologic mapping, temperature gradient drilling, and aeromagnetic, gravimetric, and lidar surveys. Results indicate that broad areas of the western United States estimated to have geothermal potential lack sufficient geologic and geophysical coverage necessary for even regional resource exploration. The study directly informed the recent Geoscience Data Acquisition for Western Nevada, or GeoDAWN - which united DOE's Geothermal Technologies Office (GTO) with the U.S. Geological Survey (USGS) of the U.S. Department of the Interior to assist U.S. needs for energy and critical minerals. The study also has the potential to inform public investment in further data acquisition for characterization of the Earth both for geothermal and other natural resource assessments.

data↗

Simulating Vibrations in a Complex Loaded Structure

The Dynamic Response Computation (DIRECT) computer program simulates vibrations induced in a complex structure by applied dynamic loads. Developed to enable rapid analysis of launch- and landing- induced vibrations and stresses in a space shuttle, DIRECT also can be used to analyze dynamic responses of other structures - for example, the response of a building to an earthquake, or the response of an oil-drilling platform and attached tanks to large ocean waves. For a space-shuttle simulation, the required input to DIRECT includes mathematical models of the space shuttle and its payloads, and a set of forcing functions that simulates launch and landing loads. DIRECT can accommodate multiple levels of payload attachment and substructure as well as nonlinear dynamic responses of structural interfaces. DIRECT combines the shuttle and payload models into a single structural model, to which the forcing functions are then applied. The resulting equations of motion are reduced to an optimum set and decoupled into a unique format for simulating dynamics. During the simulation, maximum vibrations, loads, and stresses are monitored and recorded for subsequent analysis to identify structural deficiencies in the shuttle and/or payloads.

Cao, Tim T.↗

Modeling the Risk of U.S. Offshore Oil & Gas Exploration-Well Drilling, Commercial Nuclear Plants, and Human Spaceflight

Nuclear power, offshore oil & gas exploration, and human spaceflight all have high consequence potential if something goes wrong. Each has had at least one major incident that pointed to a need for improved risk assessment. Careful risk analysis is very important for technologies having complexity, uncertainty, and high consequence potential. All rely on multiple barriers/controls/redundancy to minimize risk. NRC (Nuclear Regulatory Commission) has moved towards risk informed regulation with Probabilistic Risk Assessment (PRA) as a major input.

PRA↗

An Ultrasonic Sampler and Sensor Platform for In-Situ Astrobiological Exploration

The search for existing or past life in the Universe is one of the most important objectives of NASA's mission. In support of this objective, ultrasonic based mechanisms are currently being developed at JPL to allow probing and sampling rocks as well as perform as a sensor platform for in-situ astrobiological analysis. The technology is based on the novel Ultrasonic/Sonic Driller/Corer (USDC), which requires low axial force, thereby overcoming one of the major limitations of planetary sampling in low gravity using conventional drills. The USDC was demonstrated to: 1) drill ice and various rocks including granite, diorite, basalt and limestone, 2) not require bit sharpening, and 3) operate at high and low temperatures. The capabilities that are being investigated including probing the ground to select sampling sites, collecting various forms of samples, and hosting sensors for measuring chemical/physical properties. A series of modifications of the USDC basic configuration were implemented leading an ultrasonic abrasion tool (URAT), Ultrasonic Gopher for deep Drilling, and the lab-on-a-drill.

robotics↗

Slip Tendency Analysis of Fracture Networks to Determine Suitability of Candidate Testbeds for the EGS Collab Hydroshear Experiment

Experiment 2 of the EGS Collab project is aimed at testing stimulation by hydro-shearing of existing natural fractures, versus Experiment 1, which is focused on hydraulic fracturing a rock mass to enhance permeability. The main criterion for the testbed selection in Experiment 2 is the presence of an interconnected network of fractures, at least 10 meters in extent, and with orientations such that shear slip can be induced at injection pressures less than the minimum horizontal stress (Shmin). The feasibility analysis for this experiment requires a well-constrained stress state along with well-characterized fracture networks. The fracture systems at two candidate locations in the Sanford Underground Research Facility (SURF), the 4850 Level (number refers to depth below ground surface in feet) and the 4100 Level, have been characterized to different extents. The 4850 Level has a well-characterized Discrete Fracture Network (DFN) from borehole (drilled for an experimental test bed) and drift observations. In contrast, the 4100 level has a fracture network characterized only by observations from the drift wall, which provides little constraint on fracture extents. This paper will present assessments for the interpreted slip potential for the natural fractures at the two locations. Data uncertainties are addressed by performing a probabilistic analysis that takes into account the uncertainty in the stress state, uncertainty in the fracture properties, and preliminary borehole locations. There is strong evidence of shear stimulation of some natural fractures in Experiment 1 on the 4850 level. We use examples of natural fractures strongly linked to shear stimulation in Experiment 1 from multiple monitoring indicators to test the consistency of the stress model and guide the uncertainty interpretation. This analysis is intended to guide the site selection process for Experiment 2 by highlighting the fracture orientations that are likely to be shear-stimulated in a majority of modeled realizations.

40 EE - Geothermal Technologies Office (EE-4G)↗

Chemical and Reactive Transport Processes Associated with Hydraulic Fracturing of Unconventional Oil/Gas Shales

Hydraulic fracturing of unconventional oil/gas shales has changed the energy landscape of the U.S.. Recovery of hydrocarbons from tight, hydraulically fractured shales is a highly inefficient process, with estimated recoveries of < 25% for natural gas and < 5% for oil. This review focuses on the complex chemical interactions of additives in hydraulic fracturing fluid (HFF) with minerals and organic matter in oil/gas shales. These interactions are intended to increase hydrocarbon recovery by increasing porosities and permeabilities of tight shales. However, fluid-shale interactions result in the dissolution of shale minerals and the release and transport of chemical components. They also result in mineral precipitation in the shale matrix, which can reduce permeability, porosity, and hydrocarbon recovery. Competition between mineral dissolution and mineral precipitation processes influences the amounts of oil and gas recovered. We review the temporal/spatial origins and distribution of unconventional oil/gas shales from mudstones and shales, followed by discussion of their global and U.S. distributions and compositional differences from different U.S. sedimentary basins. We discuss the major types of chemical additives in HFF with their intended purposes, including drilling muds. Fracture distribution, porosity, permeability, and the identity and molecular-level speciation of minerals and organic matter in oil/gas shales throughout the hydraulic fracturing process are discussed. Also discussed are analysis methods used in characterizing oil/gas shales before and after hydraulic fracturing, including permeametry and porosimetry measurements, X-ray diffraction/Rietveld refinement, X-ray computed tomography, scanning/transmission electron microscopy, and laboratory- and synchrotron-based imaging/spectroscopic methods. Reactive transport and spatial scaling are discussed in some detail in order to relate fundamental molecular-scale processes to fluid transport. Furthermore, our review concludes with a discussion of potential environmental impacts of hydraulic fracturing and important knowledge gaps that must be bridged to achieve improved mechanistic understanding of fluid transport in oil/gas shales.

04 OIL SHALES AND TAR SANDS↗

The Subsurface Ice Probe (SIPR): A Low-Power Thermal Probe for the Martian Polar Layered Deposits

The distinctive layering visible in images from Mars Global Surveyor of the Martian polar caps, and particularly in the north polar cap, indicates that the stratigraphy of these polar layered deposits may hold a record of Martian climate history covering millions of years. On Earth, ice sheets are cored to retrieve a pristine record of the physical and chemical properties of the ice at depth, and then studied in exacting detail in the laboratory. On the Martian north polar cap, coring is probably not a practical method for implementation in an autonomous lander. As an alternative, thermal probes that drill by melting into the ice are feasible for autonomous operation, and are capable of reasonable approximations to the scientific investigations performed on terrestrial cores, while removing meltwater to the surface for analysis. The Subsurface Ice Probe (SIPR) is such a probe under development at JPL. To explore the dominant climate cycles, it is postulated that tens of meters of depth should be profiled, as this corresponds to the vertical separation of the major layers visible in the MOC images [1]. Optical and spectroscopic analysis of the layers, presumably demarcated by embedded dust and possibly by changes in the ice properties, would contribute to the construction of a chronology. Meltwater analysis may be used to determine the soluble chemistry of the embedded dust, and to monitor gradients of atmospheric gases, particularly hydrogen and oxygen, and isotopic variations that reflect atmospheric conditions at the time the layer was deposited. Thermal measurements can be used to determine the geothermal gradient and the bulk mechanical properties of the ice.

Cardell, G.↗