SEARCH · Engineering Papers
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.
Research Hypothesis: The injection of a blend of rich hydrocarbon gas and CO2 into an oil reservoir will reduce molecular weight (MW) selectivity, lower minimum miscibility pressure (MMP) and viscosity of the oil, and improve gas solubility, resulting in an overall improvement in enhanced oil recovery (EOR) performance.
Controlled-ionic-composition waterflooding is an economic and effective method to improve oil recovery in carbonate oil reservoirs. Recent studies show controlling the salinity and ionic composition of injection water can alter the wettability of carbonate mineral surfaces. The pore-scale oil connectivity and displacement by controlled-ionic-composition waterflooding in heterogeneous carbonate reservoirs, especially at the early stage, is still unclear. The goal of this study is to examine the role of ion concentrations and types in the oil displacement efficiency and investigate the impact of the waterflooding on the pore-scale oil displacement using the national synchrotron facility. A carbonate rock sample was flooded with synthetic high-salinity water and other water solutions with different sulfate concentrations. The waterflooding processes were visualized with synchrotron X-ray microtomography to follow the evolution of pore-scale oil/brine interactions at typical field flow rates. Experimental results show that the water with lower sulfate concentration and higher salinity did not change the wettability of the pore surfaces. Higher sulfate ion concentrations in the water, in contrast, altered the wettability of carbonate pore surfaces from oil-wet to neutral-wet within the first few minutes of waterflooding. Finally, novel insight was gained on the ability of water with high-sulfate concentration to displace oil in the small pores and through abundant oil channels, which could consequently lead to higher oil recovery from the carbonate rock.
CO 2 storage through CO 2 enhanced oil recovery (EOR) is considered as one of the technologies to help promote larger scale deployment of CO 2 storage because of associated economic benefits through oil recovery, 45Q tax credits and the utilization of existing infrastructure. The objective of this study is to demonstrate how optimal reservoir management and operation strategies (including well completions and controls) can be used to optimize both CO 2 storage and oil recovery. The optimization problem was focused on jointly estimating the well completions (i.e., fraction of injection/production well perforations in each reservoir layer) and CO 2 injection/oil production controls that maximize the net present value (NPV) in a CO 2 EOR and storage operation. We utilized the newly developed StoSAG algorithm, one of the most efficient optimization algorithms in the reservoir management community, to solve the optimization problem. The performance of joint optimization approach was compared with the performance of well control only optimization approach. In addition, the performance of co-optimization of CO 2 storage and oil recovery approach was compared with the performances of maximization of only CO 2 storage and maximization of only oil recovery approaches. The optimization results showed that a joint optimization of well completions and well controls can achieve an 8.84% higher final NPV than the one obtained from the optimization of only well controls. It was observed that the NPV incremental for joint optimization is mainly due to the fact that the optimal well completions and controls approach results in efficient CO 2 storage and oil production from different reservoir layers depending on the differences in individual layer properties. Comparison of co-optimization (i.e., maximization of NPV) and maximization of only CO 2 storage or only oil recovery showed that the co-optimization and maximization of only oil recovery result in significantly higher final NPV than that obtained through maximization of only CO 2 storage approach while maximization of only CO 2 storage can achieve significantly higher CO 2 storage in the reservoir compared to the other two scenarios. The similar results for co-optimization and maximization of oil production are obtained because of the difference in oil revenue compared to CO 2 storage tax credit. To the best of our knowledge, this is the first study in oil/gas industry and CO 2 storage community to perform joint optimization of well completions and well controls in the fields. We expect that the proposed optimization framework will be a useful and efficient tool for field engineers to optimally manage CO 2 EOR projects to maximize revenue through oil recovery as well as CO 2 storage by taking advantage of the new 45Q tax law.
Innovative approaches are needed to improve the efficiency of oil recovery technologies to meet the growing demands of fossil-fuel based energy consumption. Enhanced oil recovery (EOR) methods such as low-salinity waterflooding and chemically tuned waterflooding aim to optimize the reservoir’s wetting properties, detaching oil globules from rock surfaces and allowing easier oil flow through pore throats. This wetting behavior is commonly quantified by contact angle measurements of the rock-oil-brine interface, which have been thoroughly investigated and theorized for many systems at ambient temperatures and pressures. However, few studies exist for extending contact angle theories away from ambient conditions. In this paper, we model the contact angles of a quartz-water-decane system at elevated temperatures using the surface tension component (STC) approach. Temperature-dependent van der Waals [Lifshitz-van der Waals (LW)] interactions and hydrogen-bonding (acid-base) interactions were calculated and are incorporated into the model for the quartz-water-decane interface. Additionally, the Hough and White procedure was used to create temperature-dependent dielectric functions of quartz, water, and normal decane for calculations of Hamaker coefficients. Hamaker coefficients calculated this way are highly linear with temperature and agree well with Israelachvili’s approximation. The acid-base interactions likely contribute the most to system wettability changes. Resulting contact angles of the quartz-water-decane system shift from water-wet (16°) to slightly water-wet (57.4°) as temperature increases. The model was also successfully verified for the quartz-air-water system. Our results can be used in future studies to determine optimal injected water compositions for specific rock-oil-brine and other systems with consideration of reservoir temperature.
Understanding and improving hydrocarbon yields during enhanced oil recovery (EOR) in unconventional reservoirs is complicated by the intrinsic mineralogical and geochemical heterogeneity of shale formations. Here, in this study, we utilized small-angle neutron scattering (SANS) and ultra-small-angle neutron scattering (USANS) to investigate the degree of oil retention and its location in the nanoporous shale matrix for two mineralogically distinct shale samples. The two samples, dubbed “dark” and “light” based on their color, were taken from adjacent strata in a Wolfcamp shale core. While both samples contained kerogen, the dark sample contained more kerogen and clay (43.7 wt %) while the light sample contained more calcite (54.9 wt %). Samples were presaturated with decane, a model hydrocarbon, prior to pressure cycling with methane. Results showed significantly more retention of decane in 1.5–10 nm radius pores of both, likely indicating that oil is retained within kerogen nanopores. Although the dark sample had a higher porosity of 8.7%, versus 3.3% for the light sample, more pores were accessible to decane and a higher percentage of the imbibed decane was removable from the light sample compared to the dark sample. The majority of decane was not recoverable for the dark sample, indicating that EOR with methane can be challenging. These new findings can help to model expected recoveries of in-place oil from heterogeneous shale formations, as well as inform improved EOR strategies.
GRACE and GRACE-FO gravimetry data are unique in its ability to observe global water mass variability and has frequently been applied for the determination of global mass rates to quantify the impacts of climate change and human activity on global freshwater availability and land ice evolution. However, its relatively coarse spatial resolution of ∼300-500 km at monthly intervals precludes its direct use to measure mass changes in smaller drainage basins and individual glacier systems. We present a new global high resolution mascon product that improves spatial resolution and signal recovery by estimating trends directly from more than 16 years of Level 1B GRACE and GRACE-FO data. We compare this product to independent gravimetry spherical harmonic trend estimates and to ice sheet mass rates derived from ICESat and ICESat-2 laser altimetry. We demonstrate enhanced global signal recovery and improved agreement with ICESat/ ICESat-2 and discuss likely causes for the remaining discrepancies between the gravimetry and laser altimetry solutions.
Carbonate reservoirs tend to be oil-wet/mixed-wet and heterogeneous because of mineralogy and diagenesis. The objective of this study is to improve oil recovery in low-temperature dolomite reservoirs using low-salinity and surfactant-aided spontaneous imbibition. The low-salinity brine composition was optimized using ζ-potential measurements, contact-angle (CA) experiments, and a novel wettability-alteration measure. Significant wettability alteration was observed on dolomite rocks at a salinity of 2,500 ppm. We evaluated 37 surfactants by performing CA, interfacial-tension (IFT), and spontaneous-imbibition experiments. Here, three (quaternary ammonium) cationic and one (sulfonate) anionic surfactants showed significant wettability alteration and produced 43–63% of original oil in place (OOIP) by spontaneous imbibition. At a low temperature (35°C), oil recovery by low-salinity effect is small compared with that by wettability-altering surfactants. Coreflood tests were performed with a selected low-salinity cationic surfactant solution. A novel coreflood was proposed that modeled heterogeneity and dynamic imbibition into low-permeability regions. The results of the “heterogeneous” coreflood were consistent with that of spontaneous-imbibition tests. These experiments demonstrated that a combination of low-salinity brine and surfactants can make originally oil-wet dolomite rocks more water-wet and improve oil recovery from regions bypassed by waterflood at a low temperature of 35°C.
Here, we present a novel method for simulating unsteady, variable density, fluid flows in membrane desalination systems. By assuming the density varies only with concentration and temperature, the scheme decouples the solution of the governing equations into two sequential blocks. The first solves the governing equations for the temperature and concentration fields, which are used to compute all thermophysical properties. The second block solves the conservation of mass and momentum equations for the velocity and pressure. We show that this is computationally more efficient than schemes that iterate over the full coupled equations in one block. We verify that the method achieves second-order spatial-temporal accuracy, and we use the method to investigate buoyancy-driven convection in a desalination process called vacuum membrane distillation. Specifically, we show that with gravity properly oriented, variations in temperature and concentration can trigger a double-diffusive instability that enhances mixing and improves water recovery. We also show that the instability can be strengthened by providing external heating.
To maintain economic profit and improve the oil production efficiency after the primary and secondary production phase, advanced waterflooding techniques such as low salinity waterflooding in carbonate reservoirs have been investigated in numerical simulations, laboratory experiments, and field pilot tests. Multiple underlying mechanisms have been proposed based on these studies, and they are still under debate. Various numerical modeling approaches are introduced, but there exists a lack of a pore-scale comprehensive modeling scheme to fully understand the processes. Lattice-Boltzmann method (LBM) is a type of numerical fluid flow modeling technique that shows capabilities and flexibilities in modeling pore-scale fluid flow to integrate physical–chemical processes within complex structures. The intrinsic feature of LBM makes it a promising framework for simulating advanced waterflooding due to its flexibility, accuracy, and parallel efficiency. LBM works either by itself for solving reactive transport problems or by coupling with a third-party reaction solver. This review mainly introduces the LBM fluid flow and reactive transport capabilities and the concept and modeling approaches to simulate advanced waterflooding techniques. Meanwhile, an evaluation of the coupled LBM models for enhanced oil recovery (EOR) simulations is discussed with future research challenges and directions concluded.
Fibrillated cellulose derived from forestry feedstocks represents a renewable and high-strength materials platform for circular bioeconomies. However, its practical implementation is hindered by the irreversible aggregation of nanocellulose architectures, including cellulose nanofibers (CNFs). Solvent-based dispersion offers a simple and practical route to prevent CNF aggregation. Here, in this work, we integrate classical and enhanced sampling molecular dynamics (MD) simulations with experimental suspension rheology and atomic force microscopy (AFM) to elucidate how solvent environments tune CNF–CNF interactions and dispersion stability. CNF–CNF contact free energies computed from MD simulations reveal reduced aggregation in acetone/water, γ-valerolactone (GVL)/water, and tetrahydrofuran (THF)/water and pure acetone compared with pure water, reflecting stronger CNF-solvent relative to inter-CNF interactions. Correspondingly, CNF-solvent suspensions in these solvent systems exhibit stronger inter-fibril network structures and enhanced recovery compared to water, indicating improved CNF-solvent affinity. Liquid cell AFM imaging in acetone–water mixtures and in pure acetone further confirm the presence of well-dispersed CNFs. By combining multiscale computation with targeted experiments, this study establishes a rational framework for solvent design to achieve stable nanocellulose dispersions for high-strength biobased materials and efficient bioenergy conversion.
This report summarizes the work conducted on project DE-FE0031604 where University of Kentucky Center for Applied Energy (UK CAER) has validated its intensified CO 2 capture process through substantial enhancements to the kinetics of the absorption process and energy reductions by absorber temperature profile modification, dewatering and heat integration technologies for achieving significant capital and operating cost reductions. To address DOE’s objective of improving post-combustion CO 2 capture technology and reducing associated cost, UK CAER employed an intensified process which combined three key aspects targeted at overcoming inherent limitations or barriers in the conventional CO 2 capture and desorption process. The process designed to be independent of the type of solvent used, included (1) the use of 3-D printed two-channel structured packing material to control the temperature profile and increase the CO 2 absorption rate in the absorber, (2) a zeolite membrane dewatering unit for dewatering of the carbon-rich solvent to decouple solvent concentration needs for CO 2 absorption and desorption, and (3) a rich-split feed with two-phase flow heat transfer prior to the stripper that provided a secondary point of vapor generation to provide energy savings in steam extraction and solvent regeneration. The project was executed over two budget periods. This involved testing of individual process components which included the advanced heat transfer packing and the dewatering membrane on UK CAER’s 30 liter per minute (L/min) CO 2 (3” Column) capture bench unit with simulated flue gas in the first budget period. Subsequent scaled-up testing of these components together with the split-feed configuration were also tested in UK CAER’s 0.1 MWth CO 2 capture unit with coal-derived flue gas in the second-budget period. Long term studies were done during this period to assess process and solvent performance over extended duration. Project partners Lawrence Livermore National Laboratory (LLNL) and Media & Process Technology (MPT) led the development efforts for the advanced packing material and dewatering membrane respectively. Data from the long term testing was used as input for an environmental, health and safety (EH&S) assessment for the process and scaled technology performed by ALL4 LLC. Trimeric Corporation also completed a techno-economic analysis (TEA) for the UK CAER technology which was compared to the DOE reference Case B12B. Tests on the 3” column capture unit showed that the advanced heat transfer packing could be used to lower the bulge temperature in the absorber, and this was also proven in the scaled testing in the 0.1 MWth CO 2 capture unit. The bulge temperature could be lowered by >10 °C, changing the temperature profile in the absorber, and showed potential to enhance absorption with the ability to tailor the profile to provide conditions suitable for a solvent’s properties and kinetics. Conditions for short term evaluation of a 19” zeolite dewatering membrane on the 3” column capture unit yielded desirable fluxes and sustained rejection rates of >80%. However, for the scaled testing of six membrane modules consisting of 21 parts of 31-inch-long membrane tubes in each bundle (surface area 0.3 m 2 ), over a more extended duration, similar rejection rates could not be achieved. With the split-feed of the rich stream to the stripper, improved heat recovery minimized waste heat exiting the top of the stripper. The stripper exhaust temperatures could be reduced by >10 °C; reducing the amount of water vaporization contributed to lowering the regeneration energy by ~ 15%. The energy benefit could be sustained from the long term monitoring of the solvent performance. The solvent properties were not significantly impacted over the long-term operations. The benefits of the UK CAER process demonstrated experimentally were mostly validated from the TEA comparing a commercial scale application of the technology to DOE reference Case B12B. The cost of CO 2 capture for the UK CAER technology was estimated to be ~$34.97/tonne of CO 2 captured; a reduction of 23% compared to Case B12B. The increase in cost of electricity was also shown to be 16% lower than that of Case B12B. The total parasitic demand was also shown to be 11% lower. The key drivers for the benefits are a result of the process intensification approaches employed in the UK CAER technology for enhanced solvent performance, effective heat recovery and improved energy performance. The EH&S assessment did not find any major environmental concerns or barriers to the full scale implementation of the technology.
Numerical weather prediction (NWP) and climate models equipped with wind-farm parameterizations (WFPs) can simulate cluster wake effects affecting downstream wind farms in both onshore and offshore environments. This study evaluates wake recovery behind a wind farm represented by the NWP-WFP approach in the Weather Research and Forecasting (WRF) model using either the Fitch et al. (2012) or Ma et al. (2022a, b) WFPs. Results are benchmarked against large-eddy simulations (LES) of an idealized offshore wind farm with aligned and staggered layouts under neutral atmospheric stability. Near-farm wake recovery is underestimated in NWP-WFP simulations due to its representation on a coarse mesoscale grid. This limitation leads to slow wake recovery through two interconnected mechanisms: (i) spatial gradients in the wind velocity field are weaker compared to LES and (ii) turbulence kinetic energy (TKE) remains low not because of excessive dissipation but due to insufficient shear production caused by these weakened gradients. For the scenario considered here, a wind-speed bias develops in the near-farm wake and persists into the far wake. Differences between the NWP-WFP simulations and LES emerge within a short distance downstream of the farm exit, where the mesoscale simulations recover too slowly. This reduced recovery contributes approximately 0.15-0.50 m s-1 to the near-farm wind-speed bias. The bias established in this region is not subsequently compensated for downstream but instead propagates into the far wake, where wind-speed differences of approximately 0.4-0.6 m s-1 remain up to 50 km downstream. Higher-resolution mesoscale simulations partially reduce this bias. Increasing turbine-added TKE or including subgrid wake effects provides additional improvement, but neither fully addresses the underlying cause. The slow wake recovery is not caused by limitations of the WFPs themselves, as it also occurs outside their region of influence, and adding subgrid wake effects does not significantly impact recovery. Rather, the slow wake recovery is a consequence of mesoscale flow representation. This behavior is not limited to regions downstream of the wind farm but is less visible within the farm, where wake recovery occurs simultaneously with turbine-induced momentum extraction. These results highlight the need for improved representations of wake recovery both within and downstream of wind farms. While enhanced subgrid modeling, shear-driven TKE production, and refined WFP formulations may improve intra-farm dynamics, accurately capturing near-farm wake recovery downstream remains challenging, as WFPs do not act in this region.
Abstract Background Acute high-risk abdominal surgery is common, as are the attendant risks of organ failure, need for intensive care, mortality, or long hospital stay. This study assessed the implementation of standardized management. Methods A prospective study of all adults undergoing emergency laparotomy over an interval of 42 months (2018–2021) was undertaken; outcomes were compared with those of a retrospective control group. A new standardized clinical protocol was activated for all patients including: prompt bedside physical assessment by the surgeon and anaesthetist, interprofessional communication regarding location of resuscitation, elimination of unnecessary factors that might delay surgery, improved operating theatre competence, regular epidural, enhanced recovery care, and frequent early warning scores. The primary endpoint was 30-day mortality. Secondary endpoints were duration of hospital stay, need for intensive care, and surgical complications. Results A total of 1344 patients were included, 663 in the control group and 681 in the intervention group. The use of antibiotics increased (81.4 versus 94.7 per cent), and the time from the decision to operate to the start of surgery was reduced (3.80 versus 3.22 h) with use of the new protocol. Fewer anastomoses were performed (22.5 versus 16.8 per cent). The 30-day mortality rate was 14.5 per cent in the historical control group and 10.7 per cent in the intervention group (P = 0.045). The mean duration of hospital (11.9 versus 10.2 days; P = 0.007) and ICU (5.40 versus 3.12 days; P = 0.007) stays was also reduced. The rate of serious surgical complications (grade IIIb–V) was lower (37.6 versus 27.3 per cent; P = <0.001). Conclusion Standardized management protocols improved outcomes after emergency laparotomy.
CO 2 injection is a promising method for enhanced oil recovery (EOR) in unconventional shale reservoirs. Here, in this work, we postulate that CO 2 EOR may be improved by the dissolution of surfactants into CO 2 . Although CO 2 is a relatively good solvent for oil, we show that CO 2 and Eagle Ford oil are immiscible at compositions above 70 wt % CO 2 , even at pressures as high as 62 MPa. The presence of a CO 2 –oil interface at reservoir conditions indicates that the addition of a surfactant has the potential to improve oil recovery–via wettability alteration from oil-wet to CO 2 -wet, CO 2 –oil interfacial tension (IFT) reduction, or both. Three nonionic surfactants (branched tridecyl ethoxylate Indorama SURFONIC TDA-9, branched nonylphenol ethoxylate Indorama SURFONIC N-100, and linear dodecyl ethoxylate Indorama SURFONIC L12-6) were evaluated for CO 2 -solubility, shale wettability alteration, effect on CO 2 –oil IFT, ability to generate CO 2 –oil foams, and ability to increase oil extraction from Eagle Ford, Mancos, and Bakken shale cores. Each surfactant dissolved in CO 2 up to 1 wt % at pressures and temperatures commensurate with CO 2 EOR. CO 2 -dissolved surfactants did not significantly affect CO 2 –oil IFT or generate CO2–oil foams, but they did induce a dramatic change in the contact angle of an oil droplet on an oil-aged shale chip in CO 2 from strongly oil-wet (11°) toward intermediate CO 2 –oil wettability (82°) (at 80 °C, 27.6 MPa). The branched tridecyl ethoxylated surfactant, SURFONIC TDA-9, afforded the highest oil recovery in core soaking experiments–75%, compared to 71% by pure CO 2 . Analysis of oil extracts by gas chromatography revealed that heavier oil components were produced when the surfactant was added to CO 2 . These results indicate that CO 2 -dissolved surfactants may increase oil recovery from shale by wettability alteration from oil-wet toward CO 2 -wet.
This paper adds data to help the development of simulator motion cueing guidelines for stall recovery training by identifying time-varying manual control behavior in a stall recovery task under different simulator motion conditions. A study was conducted with seventeen general aviation pilots in the NASA Ames Vertical Motion Simulator. Pilots had to follow a flight director through four stages of a high-altitude stall task. A time-varying identification method was used to quantify how pilot manual control parameters change throughout different stages of the task in both roll and pitch. Four motion configurations were used: no motion, generic hexapod motion, enhanced hexapod motion and full motion. Pilot performance was highest for the enhanced hexapod and full motion configurations in both roll and pitch, and the lowest without motion. In the roll axis, the pilot position gain did not significantly change throughout the stall task, but was the lowest for the condition with no motion. The pilot roll velocity gain was significantly different between motion conditions, the largest difference being found close to the stall point. The enhanced hexapod motion condition had the highest pilot roll velocity gain. In the pitch axis, the pilot position gain was significantly different between time segments but not between motion conditions. The pilot pitch velocity gain was highest for the full motion condition and increased close to the stall point, but did not change significantly for the other motion conditions. Overall, pilot control behavior under enhanced hexapod motion was most similar to that under full aircraft motion. This indicates that motion cueing for stall recovery training on hexapod simulators might be improved by using the principles behind the enhanced hexapod motion configuration.
This presentation slide deck was presented at the SPE Improved Oil Recovery Conference, April 21 – 23, 2026. The major focus is a field oriented enhanced oil recovery use case demonstration with capacitance and resistance model and machine learning.
Increasing oil production from unconventional shale reservoirs is crucial to meet growing energy demands while achieving lower carbon emission than conventional crude oil. Enhanced oil recovery (EOR) has been proposed to improve hydrocarbon recovery rates through the injection of a fluid into the reservoir to facilitate residual oil release from the shale formation. However, economical and sustainable implementation of EOR requires advanced knowledge of fluid behavior in nano-sized pore spaces in shale. In this study, we utilize small-angle neutron scattering (SANS) and ultra-small-angle neutron scattering (USANS) as experimental probes to examine decane removal from a shale nano- to micro-porous matrix, utilizing methane as the injectant. The extent of decane saturation and recovery post-methane pressurization is quantified for clay-rich and carbonate-rich shale samples. A key finding is that extraction of decane by methane on depressurization is related to the methane-decane critical point. Furthermore, we found that although clay-rich shale had a much higher porosity of 5.6%, compared with 1.2% for carbonate-rich shale, decane was more easily removed from the carbonate-rich matrix, leading to similar hydrocarbon yields. These promising results demonstrate the ability of SANS and USANS to provide key insights into oil recovery from nano- to micron-sized pores in shale matrices. Combined with effects of various fractures on fluid behavior in shale, this experimental technique can be used to assess the viability of EOR injectants.
Instrumented experiments conducted at test reactors are essential to the deployment of new advanced reactor systems. Designing new experiments and generating data on specific reactor conditions require significant investments in terms of both time and cost. Finite element analysis software can be used to create high-fidelity models of experiment environments in order to support the actual experiments, but computation time remains a concern in terms of applying outcomes to real-time usage of data (e.g., a digital twin [DT]). Here, the present research proposes a machine-learning (ML) aided approach to making temperature and displacement predictions based on the thickness of the outer gas gap on the experimental capsule used for in-pile demonstration of a novel new thermal conductivity probe in the Advanced Test Reactor (ATR). This capsule consisted of U10Zr fuel, a rodlet, sodium, and inner and outer capsules. Gas gaps existed between the fuel and the rodlet, and between the inner and the outer capsule. The learning data pertained to an experimental capsule's radial distributions of temperature and displacement, as obtained based on Abaqus and the physical features. For the first step of ML sequence, the temperature was predicted using three positional parameters. Next, the displacement was predicted using seven additional parameters. Each physical feature was normalized in order to be both nondimensional and standardized. The temperature and displacement predictions showed good agreement with the simulation results in all cases involving interpolation and extrapolation. Furthermore, data similarity enhancement increased the similarity between the training and the target data, thereby increasing the predictive accuracy of the ML models. In certain extrapolation cases involving limited original ML model accuracy, data similarity enhancement and data recovery was able to somewhat improve this accuracy.