Electrokinetic Methods for Permeability Characterization.
Abstract not provided.
SEARCH · Search NASA
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.
Abstract not provided.
The main goal of this project was to create a state-of-the-art predictive capability that screens and identifies wellbores that are at the highest risk of catastrophic failure. This capability is critical to a host of subsurface applications, including gas storage, hydrocarbon extraction and storage, geothermal energy development, and waste disposal, which depend on seal integrity to meet U.S. energy demands in a safe and secure manner. In addition to the screening tool, this project also developed several other supporting capabilities to help understand fundamental processes involved in wellbore failure. This included novel experimental methods to characterize permeability and porosity evolution during compressive failure of cement, as well as methods and capabilities for understanding two-phase flow in damaged wellbore systems, and novel fracture-resistant cements made from recycled fibers.
Managing recharge of freshwater into saline aquifers requires accurate estimation of the heterogeneous permeability field for maximizing injection and recovery efficiency. Here we present a methodology for subsurface characterization in saline aquifers that takes advantage of the density difference between the injected freshwater and the ambient saline groundwater. We combine high-resolution forward modeling of density-driven flow with an efficient Bayesian geostatistical inversion algorithm. In the presence of a density difference between the injected and ambient fluids due to differences in salinity, the pressure field is coupled to the spatial distribution of salinity. This coupling renders the pressure field transient: the time evolution of the salinity distribution controls the density distribution which then leads to a time-evolving pressure distribution. We exploit this coupling between pressure and salinity to obtain an improved characterization of the permeability field without multiple pumping tests or additional salinity measurements. We show that the inversion performance improves with an increase in the mixed convection ratio—the relative importance between viscous forces from injection and buoyancy forces from density difference. Thus, our work shows that measuring transient pressure data at multiple sampling points during freshwater injection into saline aquifers can be an effective strategy for aquifer characterization, key to the successful management of aquifer recharge.
Abstract not provided.
The pore-scale flow of CO 2 and water in 2-D heterogeneous porous micromodels over a Ca range of nearly three orders of magnitude was explored experimentally. The porous geometry is a close reprint of real sandstone, and the experiments were performed under reservoir-relevant conditions (i.e., 8 MPa and 21°C), thus ensuring relevance to practical CO 2 operations. High-speed fluorescent microscopy and image processing were employed to achieve temporally and spatially resolved data, providing a unique view of the dynamics underlying this multiphase flow scenario. Under conditions relevant to CO 2 sequestration, final CO 2 saturation was found to decrease and increase logarithmically with Ca within the capillary and viscous-fingering regimes, respectively, with a minimum occurring during regime crossover. Specific interfacial length generally scales linearly with CO 2 saturation, with higher slopes noted at high Ca due to stronger viscous and inertial forces, as supported by direct pore-scale observations. Additionally, statistical analysis of the interfacial movements revealed that pore-scale events are controlled by their intrinsic dynamics at low Ca, but overrun by the bulk flow at high Ca. During postfront flow, while permeability is typically correlated with total CO 2 saturation in the porous domain (regardless of its mobility), the saturation of active CO 2 pathways in the current study correlated very well with permeability. This alternate approach to characterize relative permeability could serve to mitigate hysteresis in relative permeability curves. Taken together, these results provide unique insights that address inconsistent observations in the literature and previously unanswered questions about the underlying flow dynamics of this important multiphase flow scenario.
ASCII text files containing grid-block name, X-Y-Z location, and multiple parameters from TOUGH2 simulation output of CO2 injection into an idealized single fault representing a dipping normal fault at the Desert Peak geothermal field (readable by GMS). The fault is composed of a damage zone, a fault gouge and a slip plane. The runs are described in detail in the following: Borgia A., Oldenburg C.M., Zhang R., Jung Y., Lee K.J., Doughty C., Daley T.M., Chugunov N., Altundas B, Ramakrishnan T.S., 2017. Carbon Dioxide Injection for Enhanced Characterization of Faults and Fractures in Geothermal Systems. Proceedings of the 42st Workshop on Geothermal Reservoir Engineering, Stanford University, Stanford, California, February 13-17.
We report that in a recent numerical study, it was demonstrated that characterizing reservoir permeability in terms of rock’s quality, as observed in lab and field, is the most important step before implementing an enhanced oil recovery operation or drilling a new well in a tight formation. In that study, it was shown that permeable features in shale-like organic matter (OM) and fractures were the only regions that allowed some reasonable movement of fluid, whereas inorganic matter (iOM) that occupies larger pore volume with significant saturation of hydrocarbons has extremely low permeability that did not allow any reasonable fluid movement to affect production. That study demonstrated the importance of characterizing reservoir heterogeneity in shale in order to economically exploit the shale resource. This study proposes a method to predict spatially heterogeneous field-scale permeability of shale in terms of natural fractures, and matrix (iOM and OM). The method developed in Part 1 is combined with a history-matching process that uses only readily available information from lab-scale and outcrop (information from geologists) to predict field-scale permeability. The method also ensures consistency between the underlying fracture distribution and optimally matched fracture lengths and their apertures, in addition to accounting for random distribution of fractures and their abundance. Optimized parameters of fracture distribution are used to generate multiple realizations of geological model, and the “best-fitting” (most-likely) permeability scenario is chosen by generating production response of each realization of the geological model and comparing them against the observed field production history. Finally, the novelty of the proposed to predict field-scale permeability is that it uses only readily available information while also ensuring consistency between the underlying fracture distribution and optimally matched fracture lengths and their apertures, in addition to accounting for random distribution of fractures and their abundance.
We link changes in crustal permeability to informative features of microearthquakes (MEQs) using two field hydraulic stimulation experiments where both MEQs and permeability evolution are recorded simultaneously. The Bidirectional Long Short-Term Memory (Bi-LSTM) model effectively predicts permeability evolution and ultimate permeability increase. Our findings confirm the form of key features linking the MEQs to permeability, offering mechanistically consistent interpretations of this association. Transfer learning correctly predicts permeability evolution of one experiment from a model trained on an alternate dataset and locale, which further reinforces the innate interdependency of permeability-to-seismicity. Models representing permeability evolution on reactivated fractures in both shear and tension suggest scaling relationships in which changes in permeability (Δk) are linearly related to the seismic moment (M) of individual MEQs as Δk ∝ M. This scaling relation rationalizes our observation of the permeability-to-seismicity linkage, contributes to its predictive robustness and accentuates its potential in characterizing crustal permeability evolution using MEQs.
Artificial water channels (AWCs) have emerged as a promising framework for stable water permeation, with water transport rates comparable to aquaporins (3.4–40.3 × 10 8 H 2 O/channel/s). In this study, we probe the influence of ring-size and side-chain length on the water permeability observed within a class of AWCs termed ligand-appended pillar[n]arenes (LAPs) that have an adjustable ring-size (m) and side-chain length (n). Through all-atom molecular dynamics simulations, we calculate the permeability of these channels using the collective diffusion model and find their permeabilities. We characterize the mechanistic influence of pillar[n]arene ring-size and side-chain length on the channel water permeability by analyzing the characteristics of the internal permeating water-wire and the surrounding channel structure. We observe that water permeability decreases as a function of increasing ring-size due to increases in hydrophilic contacts between the permeating water-wire and the oxygen groups on the channel wall. Further, we observe an increase in water permeability as a function of side-chain length due to increased partitioning of the channel terminal groups into the hydrophilic blocks of the surrounding bilayer. For the LAP6 channel, with increase in side-chain length, the distance between terminal groups increases and leads to an increase in pore size, thereby enhancing water permeability. In the case of LAP5, as side-chain length increases, the channel displays a compensatory effect between tilt and bend angle due to the flexible side-chains. Such flexibility leads to higher terminal group partitioning in the hydrophilic blocks of the bilayer and extends the permeating water-wire. Furthermore, this increase in water-wire length and hydrophilic block access overcomes the nonmonotonic pore size trend in pillar[5]arene channels.
Pore network characterization is an important aspect in unconventional reservoir evaluation. While application of the technique of scanning electron microscope (SEM) brings substantial advances in pore characterization in shale, understanding the connected pore network that dominates flow in shale samples is limited by using SEM alone because of small fields of view and lack of views of connectivity in 3D. In this research, a technique integrating tracer imbibition, micro-computed tomography (CT) imaging, and SEM imaging was developed to provide a solution for multiscale imaging in shale. Tracer imbibition indicates pore connectivity; micro-CT imaging after tracer imbibition thus provides an overview of the connected pore network at the millimeter scale. With guidance from micro-CT images after tracer imbibition, a more accurate and detailed characterization of pore systems and related mineralogy can be conducted using higher-resolution SEM. The method was applied to five samples from Wolfcamp and Eagle Ford Formations. Results reveal the effectiveness of the integrated method by showing different patterns of distribution of the dominant pore network and different controlling mineralogy. Dominant porosity, estimated from grayscale analyses, displays a good correlation with permeability. This result indicates that dominant porosity is more relevant to permeability than is total porosity. Results from imbibition tests are also compared with that from contact angle measurement, and important implications on wettability can be obtained. The integrated method thus has the capacity to link the dominant pore network and wettability with microscale to submicroscale mineralogy, which can help better understand the pore systems and fluid flow in shale. Plain Language Summary Pore network characterization and wettability are two important aspects in unconventional reservoir evaluation and are crucial to understanding the nature of shale oil or gas storage and production. Here, a new technique integrating tracer imbibition, micro-computed tomography imaging, and scanning electron microscope imaging was developed for a more representative and effective pore characterization in shale. This integrated technique can provide a direct visualization of the dominant pore network in a millimeter-scale sample and, at the same time, can provide a guided pore network characterization under nanoscale resolution. This method thus can generate results that are more representative and more accurate in a more efficient way compared with the traditional scanning electron microscope method. The new technique can also reveal the local wettability in microscale. High-resolution analysis on the tracer imbibition or fluid displacement and mineralogy can shed light on the local wettability and the controlling mineralogy in shale.
Here this article demonstrates the process and characterization of additively manufactured polymer-matrix magnetic nanocomposites. These nanocomposites are composed of nickel-zinc ferrite (Ni 0.5 Zn 0.5 Fe 2 O 4 ) nanoparticles in a polyimide matrix. These materials are printed using multimaterial aerosol jet printing where aerosols of nickel-zinc ferrite and polyimide inks are mixed in place to fabricate structures with nonunity relative permeability. To characterize these materials, we use energy-dispersive X-ray spectroscopy to estimate the content of ferrite in the composite, fitted simulation models, and ring resonator measurements to estimate the permeability. In fully aerosol jet printed 1-mm 2 inductors, we demonstrate an increase in inductance density of 40% in a 4.5-turn microstrip spiral inductor using this printed composite. These fully printed inductors demonstrate an inductance density of 4.2-nH/mm 2 . EDS analysis shows films with 18 wt.% Ni 0.5 Zn 0.5 Fe 2 O 4 . Finally, we show microstrip transmission lines on printed composite compared to the same on polyimide subjected to a dc magnetic bias, displaying a magnetic resonance behavior.
A series of pentiptycene-containing disulfonated polysulfone copolymers (PENT-BP) were synthesized via condensation polymerization. Water and salt transport properties (solubility, diffusivity and permeability) were characterized for acid-form membranes (PENT-BP(H)) and compared with triptycene-based sulfonated polysulfones (TRP-BP(H)) and a non-iptycene-containing 4,4'-biphenol-based series (BPS(H)) of polysulfones to investigate the effect of pentiptycene on membrane performance. At comparable water content, the PENT-BP(H) exhibited increased water and salt permeability due to the additional free volume introduced by the pentiptycene units. Enhanced water/salt permeability selectivity of PENT-BP(H) series was also observed due to a significantly higher diffusivity selectivity. At comparable water permeance (P w D ~ 8 X 10 -6 cm 2 /s), the salt rejection of PENT-BP (H) copolymers obtained from dead-end filtration reached 91–93% at 400 psi, higher than that of a corresponding BPS(H) series. This study suggests that incorporation of iptycene moieties into polymer backbone is an effective strategy to enhance desalination membrane performance.
Most of Hawai'i's geothermal resources are blind—their manifestations, such as hot springs and steam vents, do not appear on the ground surface because the heated water flows far below. With the exception of $K\bar{i}lauea East Rift Zone$, in most areas of Hawai'i, high lateral permeability in the first kilometer below ground surface prevents surface thermal features from developing. As a methodology for discovering these blind resources, Play Fairway Analysis (PFA) involves finding potential locations of blind hydrothermal systems and describing potential geothermal sources in rift-zone settings. Using the PFA to find Hawai'i's geothermal resources, the University of Hawai'i (UH) conducted the Hawai‘i Play Fairway Project, Hawai'i's first statewide geothermal resource assessment since 1985. Sponsored by the U.S. Department of Energy, the Hawai'i Play Fairway Project provided an updated resource assessment, a roadmap for additional exploration activities, and the identification of areas for further exploration. Benefitting from UH's core competency in earth sciences and experienced geothermal researchers, the project comprised three phases. During the first phase, the team identified, compiled, and ranked existing geologic, groundwater, and geophysical datasets relevant to subsurface heat, fluid and permeability. Using a Bayesian statistical approach, the team developed a statistical methodology to integrate these data into a resource probability map. The team evaluated the confidence in the probability value and considered development viability of areas with geothermal resources. With these analyses, the team identified 10 locations in the Hawaiian Islands for exploration activities. For the second phase, the team collected new groundwater data in 10 locations across the state and new geophysical data on $L\bar{a}na‘i, Maui$, and central Hawai'i Island and modeled topographically induced stress to better characterize subsurface permeability. Analyzing the subsurface stresses, the team evaluated the potential for fracture-induced permeability. The team inverted the MT and gravity data to produce 3D models of resistivity and density, respectively, on $L\bar{a}na‘i$, across $Haleakal\bar{a}'s$ SW rift (Maui), and surrounding Mauna Kea (Hawai‘i Island). The team developed and applied a new method for incorporating depth information about resistivity, density, and potential for fracture-induced permeability into the statistical method for computing resource probability in these three focus areas. The team incorporated the new groundwater results with the new geophysical results and the calculations of potential for fracture-induced permeability to produce updated maps of resource probability and confidence. Through combining data from the first and second phases, the team determined locations for further exploration during the third phase. For MT and gravity surveys, the team recommended $Kaua'i's$ $L\bar{i}hu'e$ $Basin$, the east rift of $Maui's$ $Haleakal\bar{a}$ volcano, and the southwest rift of Hawai'i Island's Mauna Loa volcano. The MT and gravity surveys aimed to enable improved confidence in the resource potential in these locations. For drilling deep groundwater well(s), the team recommended Southeast Mauna Kea and $L\bar{a}na's$ $P\bar{a}l\bar{a}wai$ $Basin$. During the third phase, further exploration involved drilling a groundwater well in $L\bar{a}na's$ $P\bar{a}l\bar{a}wai$ $Basin$ and performing more geophysical surveys. We deepened an existing water well proximal to our target area on $L\bar{a}na'i$ due to funding constraints that precluded us from spudding a new well that would exceed 1km depth. Drilling was preceded by a number of substantial elements including: writing an Environmental Assessment and the subsequent legal process, performance of deviation logging, lowering a camera down the well, coordinating site preparation with $P\bar{u}lama$ $L\bar{a}na'i$, shipping the UH-owned rig interisland, procuring supplies, and leading 3 community meetings on $L\bar{a}na'i$. Drilling occurred 24/7 the entire month of June 2019 over which time $L\bar{a}na'i$ $Well$ 10 was deepened from 427 m to 1057 m, with continuous core collected. We measured a roughly linear temperature gradient averaging 42°C/km and a maximum bottom hole temperature of 66°C. This gradient is more than twice the background for Hawai'i and within a range of gradients measured in this depth range for some exploration wells within KERZ. We consider these results encouraging for $L\bar{a}na'i's$ resource potential and recommend following with a slim hole within $L\bar{a}na'i's$ caldera (our target zone) to ~ 2 km. Further, the positive implications such results have for the island of O‘ahu are substantial - the shield stage of O'ahu's volcanoes ended 1-2 My earlier. However, O'ahu uses more electricity than the rest of the islands combined, and the utility recently called for 500-700MW of firm, dispatchable renewable electricity on O'ahu by 2033. In Phase 3, we also collected limited new encouraging groundwater data, and updated our thoughts on the probabilities of fluid and permeability at resource depths (Pr F = 1; Pr P = mostly unconstrained). Ultimately, we advocate for using our final probability of heat, and confidence in this probability, to drive the next phase of exploration. We contend further development of geothermal in Hawai‘i will enable the state to achieve its 100% renewable policy objective and Hawai'i to transition off of fossil fuels through geothermal discovery and development. The project not only produced a large amount of data and expanded the existing knowledge of Hawai'i's geothermal resources, but also produced publications, theses, presentations, core photos, datasets, media reports, television interviews, community events, and a blog. Students and new professionals benefitted from the project's hands-on research experiences and educational opportunities and earned awards and recognition.
Characterizing the properties of groundwater aquifers is essential for predicting aquifer response and managing groundwater resources. In this work, we develop a high-dimensional scalable Bayesian inversion framework governed by a three-dimensional quasi-static linear poroelastic model to characterize lateral permeability variations in groundwater aquifers. In this work, we determine the maximum a posteriori (MAP) point of the posterior permeability distribution from centimeter-level surface deformation measurements obtained from Interferometric Synthetic Aperture Radar (InSAR). The scalability of our method to high parameter dimension is achieved through the use of adjoint-based derivatives, inexact Newton methods to determine the MAP point, and a Mat´ern class sparse prior precision operator. Together, these guarantee that the MAP point is found at a cost, measured in number of forward/adjoint poroelasticity solves, that is independent of the parameter dimension. We apply our methodology to a test case for a municipal well in Mesquite, Nevada, in which InSAR and GPS surface deformation data are available. We solve problems with up to 320,824 state variable degrees of freedom (DOFs) and 16,896 parameter DOFs. A consistent treatment of noise level is employed so that the aquifer characterization result does not depend on the pixel spacing of surface deformation data. Our results show that the use of InSAR data significantly improves characterization of lateral aquifer heterogeneity, and the InSAR-based aquifer characterization recovers complex lateral displacement trends observed by independent daily GPS measurements.
This final report on Laboratory Directed Research and Development (LDRD) project 209234 presents background material for electrokinetics at the pore and porous media scales. We present some theoretical developments related to uncoupling electrokinetic flow solutions, from a manuscript recently accepted into Mathematical Geosciences for publication. We present a summary of two pore-scale modeling efforts undertaken as part of the academic alliance with University of Illinois, resulting in one already submitted journal publication to Transport in Porous Media and another in preparation for submission to a journal. We finally show the laboratory apparatus built in Laboratory B59 in Building 823 and discuss some of the issues that occurred with it.
Abstract not provided.
Abstract not provided.
Abstract Quantification of heterogeneous multiscale permeability in geologic porous media is key for understanding and predicting flow and transport processes in the subsurface. Recent utilization of in situ imaging, specifically positron emission tomography (PET), enables the measurement of three‐dimensional (3‐D) time‐lapse radiotracer solute transport in geologic media. However, accurate and computationally efficient characterization of the permeability distribution that controls the solute transport process remains challenging. Leveraging the relationship between local permeability variation and solute advection behavior, an encoder‐decoder based convolutional neural network (CNN) is implemented as a permeability inversion scheme using a single PET scan of a radiotracer pulse injection experiment as input. The CNN can accurately capture the 3‐D spatial correlation between the permeability and the radiotracer solute arrival time difference maps in geologic cores. We first test the inversion accuracy using synthetic test datasets and then test the accuracy on a suite of experimental PET imaging datasets acquired on four different geologic cores. The network‐predicted permeability maps from the geologic cores are used to parameterize forward numerical models that are directly compared with the experimental PET imaging data. The results indicate that a single trained network can generate robust 3‐D permeability inversion maps in seconds. Numerical models parameterized with these permeability maps closely capture the experimentally observed solute arrival time behavior. This work provides an unprecedented approach for efficiently characterizing multiscale permeability heterogeneity in complex geologic samples.