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.
This January 2020 monthly report is intended to communicate the status of North Slope Atmospheric Radiation Measurement (ARM) facilities managed by Sandia National Labs.
This report describes a comparison of the overlapping X1 and X3 Aerosol Observing Systems (AOS) at the North Slope of Alaska (NSA) observatory. Due to structural issues with the original observatory building, the National Oceanic and Atmospheric Administration (NOAA) funded the design and construction of a new observatory building. Construction began in 2019 and was completed in 2020. The now decommissioned old NOAA Barrow Observatory (BRW) housed the AOS referred to as an NSA external site X1 from October 1997 through August 2021. A new observatory building next door housed the AOS referred to as an NSA external site X3 starting in October 2020. In this document we will refer to the original observatory system measurements as 'OLD' and the measurements in the new building as 'NEW'.
The first ever polymer flood field pilot to enhance the recovery of heavy oils on the Alaska North Slope is ongoing. This study constructs and calibrates a reservoir simulation model to predict the oil recovery performance of the pilot through machine-assisted reservoir simulation techniques. To replicate the early water breakthrough observed during waterflooding, transmissibility contrasts are introduced into the simulation model, forcing viscous fingering effects. In the ensuing polymer flood, these transmissibility contrasts are reduced to replicate the restoration of injection conformance during polymer flooding, as indicated by a significant decrease in water cut. Later, transmissibility contrasts are reinstated to replicate a water surge event observed in one of the producing wells during polymer flooding. This event may represent decreased injection conformance from fracture overextension; its anticipated occurrence in the other production well is included in the final forecast. The definition of polymer retention in the simulator incorporates the tailing effect reported in laboratory studies; this tailing effect is useful to the simultaneous history match of producing water cut and produced polymer concentration. The top 24 best-matched simulation models produced at each stage of the history matching process are used to forecast oil recovery. The final forecast clearly demonstrates that polymer flooding significantly increases the heavy oil production for this field pilot compared to waterflooding alone. This exercise displays that a simulation model is only valid for prediction if flow behavior in the reservoir remains consistent with that observed during the history matched period. Critically, this means that a simulation model calibrated for waterflooding may not fully capture the benefits of an enhanced oil recovery process such as polymer flooding. Therefore, caution is recommended in using basic waterflood simulation models to scope potential enhanced oil recovery projects.
A polymer flood pilot has been ongoing in the Schrader Bluff viscous oil reservoir at Milne Point on the Alaska North Slope. The results from the pilot are encouraging. However, a major concern of the operator is the influence of polymer on the production system after breakthrough, especially the fouling in heat exchangers. This work applies a multiexperimental approach to study the severity of polymer-induced fouling in both dynamic and static states of produced fluids to determine safe operating conditions. Dynamic scale loop (DSL) tests were conducted to study fouling due to polymer at different skin temperatures (165–350°F) in a dynamic state of fluid flow where the fluids’ flow mimics the residence time of fluids in the heat exchanger of the field pilot. Static deposit tests were also conducted at similar skin temperatures of 165–250°F using a novel experimental apparatus designed and built in-house. It was found that at higher skin temperatures of 250–350°F, tube blocking was observed in the DSL tests, whereas the tests at 165–200°F did not show any tube blocking, even in a more extended test period. The deposit test showed that the deposit rate generally increases with skin temperature, and the presence of polymer aggravates the fouling. The copper tube performs best when the skin temperatures are 165–200°F, while the stainless steel tube performs best at a skin temperature of 250°F. These experiments also manifested the influence of the cloudpoint of the solution as the deposit rate increased significantly when the skin temperature was higher than the solution cloudpoint. The study provides a source of practical guidance to the field operations.
Combining low-salinity water (LSW) and polymer flooding was proposed to unlock the tremendous heavy oil resources (20–25 billion barrels) on the Alaska North Slope (ANS). The synergy effect of LSW and polymer flooding was demonstrated through coreflooding experiments carried out on representative rock and fluid systems. The results indicate that the high-salinity polymer solution (HSP, 2,300 ppm, salinity=27,500 ppm) requires nearly two thirds more polymer than the low-salinity polymer (LSP, 1,400 ppm, salinity=2,500 ppm) to achieve the same target viscosity of 45 cp measured from viscometer. Additional oil (5–9%) can be recovered from LSW flooding after extensive high-salinity water (HSW) flooding. LSW flooding performed in secondary mode can achieve higher recovery than in tertiary mode. Strikingly, LSP flooding can further improve the oil recovery by ~8% even after extensive HSP flooding with the same viscosity. LSP flooding performed directly after waterflooding can achieve ~10% more incremental oil recovery. The pH increase of the effluent during LSW/LSP flooding was significantly greater than that during HSW/HSP flooding, indicating the occurrence of ion exchange which might contribute to the improved oil recovery. Also, the water breakthrough was delayed in a low-salinity flood compared with a high-salinity flood. The idea of combining LSW and polymer flooding has been put into practice on a pattern-scale field pilot test in the target Milne Point field. Nearly two-year observation has shown impressive success: water cut reduction (70% to below 15%), increasing oil rate, and no polymer breakthrough so far. This work has demonstrated remarkable economical and technical benefits of combination of LSW and polymer flooding in enhancing heavy oil recovery.
This February 2020 monthly report is intended to communicate the status of North Slope ARM facilities managed by Sandia National Labs.
Abstract Cloud condensation nucleus control alter cloud solar albedo through cloud droplet size. Here, we leverage anthropogenic emissions at the North Slope of Alaska as a natural laboratory to study relationships between aerosols and Arctic liquid‐containing clouds. Averaging 14 years of MODIS observations, we found a reduction in temporally averaged cloud effective radius ( ) of up to 1.0 μm related to localized pollution. Pronounced regional gradients in cloud frequency of occurrence and liquid water path prohibit the detection of potential changes of these variables. Observed changes of alter radiative fluxes and increase cloud‐reflected shortwave radiation by up to 0.8 W m − 2 in the Prudhoe Bay area for the period covered by observations (April–September). Due to the frequent occurrence of liquid‐containing clouds, this implies that enhanced local emissions in Arctic regions can impact climate processes.
Here, artificial neural network-trained models were used to predict gas hydrate saturation distributions in permafrost-associated deposits in the Eileen Gas Hydrate Trend on the Alaska North Slope (ANS), USA and at the Mallik research site in the Beaufort-Mackenzie Basin, Northwest Territories, Canada. The database of Logging-While-Drilling (LWD) and wireline logs collected at five wells (Mount Elbert, Ignik Sikumi, and Kuparuk 7–11–12 wells at ANS, plus 2L-38 and 5L-38 wells at the Mallik research site) includes more than 10,000 depth points, which were used for training, validation, and testing the machine learning (ML) models. Data used in training the ML models include the well logs of density, porosity, electrical resistivity, gamma radiation, and acoustic wave velocity measurements. Combinations of two or three out of these five well logs were found to reliably predict the gas hydrate saturation with accuracy varying between 80 and 90% when compared to the gas hydrate saturations derived from Nuclear Magnetic Resonance (NMR)-based technique. The ML models trained on data from three ANS wells achieved high fidelity predictions of gas hydrate saturation at the Mallik site. The results obtained in this study indicate that ML models trained on data from one geological basin can successfully predict key reservoir parameters for permafrost-associated gas hydrate accumulations within another basin. A generalized approach for selecting a well log combination that can improve model accuracy is discussed. Overall, the study outcome supports earlier work demonstrating that ML models trained on non-NMR well logs are a viable alternative to physics-driven methods for predicting gas hydrate saturations.
The U.S. Department of Energy’s Atmospheric Radiation Measurement (ARM) User Facility operates an X-band Scanning ARM Precipitation Radar (XSAPR) at the North Slope of Alaska (NSA) atmospheric observatory in Utqiaġvik. This radar provides year-round dual-polarization measurements of snow and ice in an arctic environment. Over the past few years, there has been greater focus on the NSA XSAPR, and recent efforts by ARM staff have resulted in quality-controlled, b-level data (Rocque et al. 2026b). This report outlines the processing of the second set of b-level data released for this radar from May 2025 through April 2026 following similar methods from Rocque et al. (2026b).
Arrays of instruments for monitoring winter precipitation (snowfall) and snow cover on the ground installed in 2017 at the U.S. Department of Energy Atmospheric Radiation Measurement (ARM) user facility’s North Slope of Alaska (NSA) C1 and at Oliktok Point sites became operational in 2018. In 2022, the instruments from Oliktok Point were moved to NSA E12, about 5.4 km south of NSA C1, where two arrays now operate. The instrument arrays monitor wind speed and direction, snow depth at multiple locations, the horizontal flux of blowing snow, and the number and fall speed of hydrometeors. The arrays are monitored using digital cameras. Collectively, the instruments produce a wealth of data on falling and accumulated snow, but, as with any instrument array, some data are more reliable and accurate than others. In this document, we present our findings on the efficacy, accuracy, and reliability of each type of instrument. Overall, a key finding is that no single instrument provides sufficient information to determine the source of falling snow particles nor the cause of changes in snow depth. However, if used in concert, the instruments produce a reliable understanding of the processes affecting the snow cover depth distribution and the true winter precipitation.
Gas hydrate, a solid combination of gas (mostly methane in nature) and water molecules stable at low temperatures and elevated pressures, occurs naturally in marine and permafrost-associated environments. Gas hydrate reservoirs, such as those in the Alaska North Slope, have been considered potential energy resources for gas production. To understand the petrophysical and geo-mechanical characteristics of the reservoir, core samples retrieved from the site of the JOGMEC-DOE-USGS collaborative gas hydrate R&D project have been analyzed in the laboratory for their hydraulic and mechanical properties. This paper focuses on both seal and reservoir samples associated with the B1 and D1 sands, which are evaluated for index properties (including porosity, grain size distribution, liquid and plastic limits, specific surface area, and specific gravity), consolidation, permeability, and water retention. Furthermore, the reservoir core samples were tested with pore-filling, laboratory-grown tetrahydrofuran hydrate, in order to assess reservoir behavior during gas production from hydrates. Under simulated in situ stress conditions, the seal and hydrate-free reservoir cores had a permeability anisotropy ratio of k h /k v = 3.0−5.0, and k h /k v = 2.4−3.0 for the reservoir tetrahydrofuran hydrate-bearing cores. The data suggest that depressurizing the reservoir to induce hydrate dissociation alters the reservoir effective permeability in three ways: permeabilities decrease due to porosity lost (e.g., the initial reservoir thickness can decrease by up to 5% upon 7 MPa depressurization), permeability increases due to the loss of solid hydrate in the pore space, and permeability anisotropy k h /k v decreases in response to the evolving pore-space geometry. We show that given the simulated in situ gas hydrate saturations (i.e., S h = 32% in core 7P-2E and S h = 21% in core 20P-4), gas production from the dissociation of tetrahydrofuran hydrate in the two tested cores results in a net increase in effective permeability and a decrease in k h /k v . This study highlights the importance of investigating seal and reservoir sediments and the impacts of depressurization on the porosity and permeability responses during production.
Polymer flooding has become globally established as a potential enhanced oil recovery method for heavy oils. To determine whether this technology may be useful in developing the substantial heavy oil resources on the Alaska North Slope, a polymer flood field pilot commenced at the Milne Point Unit in August 2018. This study seeks to evaluate the results of the field pilot on a technical and economic basis. A reservoir simulation model is constructed and calibrated to predict the oil recovery performance of the pilot through machine-assisted reservoir simulation techniques. To replicate the early water breakthrough observed during waterflooding, transmissibility contrasts are introduced into the simulation model, forcing viscous fingering effects. In the ensuing polymer flood, these transmissibility contrasts are reduced to replicate the restoration of injection conformance during polymer flooding. Transmissibility contrasts are later reinstated to replicate fracture overextension interpreted in one of the producing wells. The calibrated simulation models produced at each stage of the history matching process are used to forecast oil recovery. These forecasts are used as input for economic analysis, incremental to waterflooding expectations. The simulation forecasts indicate that polymer flooding significantly increases the heavy oil production for this field pilot compared to waterflooding alone, yielding attractive project economics. However, meaningful variations between simulation scenarios demonstrate that a simulation model is only valid for prediction if flow behavior in the reservoir remains consistent with that observed during the history matched period. Critically, this means that a simulation model calibrated for waterflooding may not fully capture the technical and economic benefits of an enhanced oil recovery process such as polymer flooding. Subsequently, the simulation model and economic model are used in conjunction to conduct a sensitivity analysis for polymer flood design parameters, from which recommendations are provided for both the continued operation of the current field pilot and future polymer flood designs. The results demonstrate that a higher polymer concentration can be injected due to the development of fractures in the reservoir. The throughput rate should remain high without exceeding operating constraints. A calculated point-forward polymer utilization parameter demonstrates the decreasing efficiency of the polymer flood at later times in the pattern life. Future projects will benefit from starting polymer injection earlier in the pattern life. A pattern with tighter horizontal well spacing will observe a greater incremental benefit from polymer flooding.
The Global Electric Circuit (GEC) of the atmosphere provides a unique perspective on Earth’s changing climate. Monitoring this global electrical signature provides details of the global nature of electrified clouds and thunderstorms. The North Slope of Alaska (NSA) is a unique location for collecting these electric field measurements. Besides being at the opposite pole from many previous electric field measurements taken at Russia’s Vostok station in Antarctica, this site provides a rare opportunity to use other instruments at the U.S. Department of Energy Atmospheric Radiation Measurement (ARM) User Facility’s NSA observatory at Utqiaġvik (formerly known as Barrow), such as the Ka-band ARM Zenith Radar (KAZR), upward-facing micropulse lidar (MPL), vertical profile of meteorological measures, and other aerosol measurements. Since 2017, Texas A&M University at Corpus Christi (TAMUCC) has established an observational instrument package, including CS110 electric fields and anemometer, at ARM’s NSA observatory at Utqiaġvik. This enabled the unique opportunity to not only provide information about the global signature of the GEC, but also the physical inputs to the local electric field, by analyzing the physical properties of the simultaneous cloud, wind, and aerosol properties occurring with the vertical electric field.
The Global Electric Circuit (GEC) of the atmosphere provides a unique perspective on Earth’s changing climate. Monitoring this global electrical signature provides details of the global nature of electrified clouds and thunderstorms. The North Slope of Alaska (NSA) is a unique location for collecting these electric field measurements. Besides being at the opposite pole from many previous electric field measurements taken at Russia’s Vostok station in Antarctica, this site provides a rare opportunity to use other instruments at the U.S. Department of Energy Atmospheric Radiation Measurement (ARM) User Facility’s NSA observatory at Utqiaġvik (formerly known as Barrow), such as the Ka-band ARM Zenith Radar (KAZR), upward-facing micropulse lidar (MPL), vertical profile of meteorological measures, and other aerosol measurements. Since 2017, Texas A&M University at Corpus Christi (TAMUCC) has established an observational instrument package, including CS110 electric fields and anemometer, at ARM’s NSA observatory at Utqiaġvik. This enabled the unique opportunity to not only provide information about the global signature of the GEC, but also the physical inputs to the local electric field, by analyzing the physical properties of the simultaneous cloud, wind, and aerosol properties occurring with the vertical electric field.
In this work, we investigate by means of numerical simulation a planned year-long field test of depressurization-induced production from a permafrost-associated hydrate reservoir on the Alaska North Slope at the site of the recently drilled Hydrate-01 Stratigraphic Test Well. The main objective of this study is to assess quantitatively the impact of temporary interruptions (well shut-ins) on the expected fluid production performance from the B1 Sand of the stratigraphic Unit B during controlled depressurization over different time scales, as well as on other relevant aspects of the system response that have the potential to significantly affect the design of the field test. We consider eight different cases of depressurization, including (a) rapid depressurization over a 60-day period to a terminal bottomhole pressure P W of 2.8 MPa and (b) a slower depressurization rate to a final P W of 0.6 MPa at the end of the year-long production test, in addition to (c) a multi-step depressurization regime and (d) a quasi-linear continuous depressurization strategy. The results of the study indicate that shut-ins obviously reduce gas release and production during and immediately after their occurrence, but their longer-term effects are strongly dependent on the depressurization regime and on the time of observation, covering the entire range of potential outcomes. Shut-ins (a) have a universally strong negative effect when quasi-linear depressurization is involved regardless of the length of the production period, and (b) have a strong positive effect in multi-step depressurization schemes that becomes apparent earlier for large initial pressure drops, but (c) can also appear to have practically no effect for slow stepwise depressurization at the end of the year-long production test. Shut-ins lead to a rapid reformation of hydrates, even to the point of disappearance of a free gas phase in the reservoir. Rapid depressurization regimes lead to early maximum rates of hydrate dissociation and gas production, while the maximum rates occur at the end of the production test for the cases of slower depressurization. Shut-ins do not appear to have a significant impact on water production, as the cessation of production is followed by higher rates production when depressurization resumes. Similarly, (a) the fraction of produced CH 4 originating from exsolution from the water, (b) the water-to-gas ratio, and (c) the rate of replenishment of produced water by boundary inflows do not appear significantly affected by shut-ins, the effects of which seem to be temporary in the majority of the cases. The study confirmed the superiority of multi-step depressurization methods as the most effective strategies for hydrate dissociation and gas production and showed that two observation wells (located at distances of 30 and 50 m from the production well) are appropriately positioned and both able to capture the P, T, and S G behavior during the fluid production and shut-ins in any of the eight cases we investigated.
Accurate reservoir evaluation requires reliable three-dimensional (3-D) geological models. Here, this study conducted 3-D geological modeling for numerical flow simulation of the B1 sand gas hydrate reservoir at the Kuparuk State 7-11-12 pad, Prudhoe Bay Unit, Alaska North Slope. The model integrates well logs, core, and seismic data to address spatial heterogeneity in geological structures and reservoir properties. Two modeling types were performed: structural framework modeling and petrophysical property modeling. For structural framework modeling, seismic data and well log markers were used to reproduce subsurface structures characterized by a normal fault system. A volume-based modeling algorithm and stair-stepping grid were applied. The resulting 3-D model comprised 2,640,000 grid cells across 264 layers, including seven fault grids. For petrophysical property modeling, total porosity was initially modeled using sequential Gaussian simulation with collocated cokriging. To reproduce the upward coarsening of the B1 sand, upscaled log-derived total porosity and a three-dimensional (3-D) trend depicting total porosity variation were used as primary and secondary data, respectively. Gas hydrate saturation distribution was modeled similarly, with secondary data from estimated porosity distribution and seismic-derived acoustic impedance map enhancing accuracy. Results indicate higher gas hydrate saturation in the upper part of the B1 sand and areas with higher acoustic impedance. Intrinsic permeability was modeled from the total porosity and clay-bound water volume, and effective permeability was derived from the gas hydrate saturation and intrinsic permeability distributions based on the “Tokyo model”. Effective permeability distributions were influenced by the total porosity, gas hydrate saturation, and intrinsic permeability. Within the same layer, higher gas hydrate saturation leads to decreased effective permeability. In total, 100 sets of multiple scenarios were prepared, providing input data for dynamic flow simulations to evaluate the effects of lateral heterogeneity in reservoir properties and the hydraulic characteristics of faults on production behavior for preassessment before the long-term production test.
In December 2018, a partnership between the U.S. Department of Energy National Energy Technology Laboratory (DOE NETL), the Japan Oil, Gas and Metals National Corporation (JOGMEC), and the U.S. Geological Survey (USGS) successfully drilled and logged the Hydrate-01 Stratigraphic Test Well (STW) in the greater Prudhoe Bay oil field on Alaska North Slope. The logging-while-drilling (LWD) data confirmed the presence of gas hydrate-bearing reservoirs within two sand reservoirs (Unit B and Unit D) that are suitable targets for future testing. The interpreted log data and core sample measurements were used to create reservoir models for the Prudhoe Bay Unit (PBU) Kuparuk 7-11-12 Site. The models combine both gas hydrate-bearing sections in Unit B and Unit D together with the intermediate Unit C and over- and underburden sands and shales. The vertical heterogeneity in porosity, gas hydrate saturation, and permeability distributions for reservoir and non-reservoir units was implemented using fine mesh discretization. The depressurization method was applied to Unit B to induce gas hydrate destabilization at constant bottom hole pressure (BHP) values. The results of the numerical simulations support the development of production scenarios, well design, surface facilities, and field test procedures with the main goal to perform efficient and safe scientific production testing. Project results contribute to the knowledge base of permafrost-associated gas hydrate accumulations as a future energy source.
Climate in the Arctic is changing at a rapid pace. When vegetation reacts to these changes, chemicals called biogenic volatile organic compounds (BVOCs) can be released into the atmosphere in new ways. This project seeks to investigate how climate change affects the quantity and type of BVOCs released into the atmosphere on the North Slope of Alaska (NSA). In addition, we are interested in the chemical reactions these BVOCs undergo in the arctic atmosphere. Project goals will be accomplished through field work on the NSA at the U.S. Department of Energy Atmospheric Radiation Measurement (ARM) user facility’s observatory in Utqiagvik, real-time measurements, and collection and laboratory analysis of atmospheric aerosol samples.