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Wettability plays a crucial role in multiphase fluid flow in porous media, impacting various geological applications such as hydrocarbon extraction, aquifer remediation, and carbon dioxide sequestration. Microfluidic methods have attracted interest for their capacity to explore and visualize essential multiphase flow dynamics at the pore level, mimicking actual rock pore structures. However, creating micromodels with representative mixed wettability is currently a challenge. Existing technology is limited to producing micromodels with a singular wettability, either water-wet or oil-wet, leaving a gap in representing mixed-wet scenarios. In this study, we introduce a novel method to fabricate microfluidic devices with controlled spatial distribution of wettability at the micro-scale, mimicking actual configurations of mixed-wet rocks arising from varied mineralogy and pore structures. The proposed method combines the soft lithography process with thin film deposition techniques. The micromodels were designed to mimic the pore network of actual reservoir rocks, and a silicon substrate served as the foundation for the photolithography process optimization and wettability alteration methodology. Perfluorodecyltrichlorosilane coating was applied using molecular vapor deposition technology for surface wettability modification. The coated parts of the microdevice substrate altered the localized wetting state of the silicon towards hydrophobic, while the wettability remained unchanged in the non-coated areas. We utilized surface measurements, including contact angle, X-ray photoelectron spectroscopy, transmission electron microscopy, scanning electron microscopy, and atomic force microscopy, to assess the wettability, composition, thickness, shape, roughness, and overall quality of the coating. Our fabrication process successfully produced a microfluidics device with tailored mixed-wet attributes at the micro-scale, which is, to our best knowledge, the first achievement in the field. This method enables the replication of mixed-wet characteristics commonly seen in various applications, such as carbonates and shales within underground rocks, providing a more accurate examination of fundamental multiphase fluid dynamics and rock interactions at the pore level.
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Significant amounts of hydrocarbon resources are left behind after primary and secondary recovery processes, necessitating the application of enhanced oil recovery (EOR) techniques for improving the recovery of trapped oil from subsurface formations. In this respect, the wettability of the rock is crucial in assessing the recovery and sweep efficiency of trapped oil. The subsurface reservoirs are inherently contaminated with organic acids, which renders them hydrophobic. Recent research has revealed the significant impacts of nanofluids, surfactants, and methyl orange on altering the wettability of organic-acid-contaminated subsurface formations into the water-wet state. This suggests that the toxic dye methylene blue (MB), which is presently disposed of in huge quantities and contaminates subsurface waters, could be used in EOR. However, the mechanisms behind hydrocarbon recovery using MB solution for attaining hydrophilic conditions are not fully understood. Therefore, the present work examines the impacts of MB on the wettability reversal of organic-acid-contaminated Khewra sandstone samples (obtained from the outcrop in the Potwar Basin, Pakistan) under the downhole temperature and pressure conditions. The sandstone samples are prepared by aging with 10-2 mol/L stearic acid and subsequently treated with various amounts of aqueous MB (10-100 mg/L) for 1 week. Contact angle measurements are then conducted under various physio-thermal conditions (0.1-20 MPa, 25-50 °C, and salinities of 0.1-0.3 M). The results indicate that the Khewra sandstone samples become hydrophobic in the presence of organic acid and under increased pressure, temperature, and salinity. However, the wettability changes from oil-wet to preferentially water-wet in the presence of various MB solutions, thus highlighting the favorable effects of MB on EOR from the Khewra sandstone formation. Moreover, the most significant change in wettability is observed for the Khewra sandstone sample that was aged using 100 mg/L MB. These results suggest that injecting MB into deep underground Khewra sandstone reservoirs may produce more residual hydrocarbons.
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Effectively storing carbon dioxide (CO2) in geological formations synergizes with algal-based removal technology, enhancing carbon capture efficiency, leveraging biological processes for sustainable, long-term sequestration while aiding ecosystem restoration. On the other hand, geological carbon storage effectiveness depends on the interactions and wettability of rock, CO2, and brine. Rock wettability during storage determines the CO2/brine distribution, maximum storage capacity, and trapping potential. Due to the high CO2 reactivity and damage risk, an experimental assessment of the CO2 wettability on storage/caprocks is challenging. Data-driven machine learning (ML) models provide an efficient and less strenuous alternative, enabling research at geological storage conditions that are impossible or hazardous to achieve in the laboratory. This study used robust ML models, including fully connected feedforward neural networks (FCFNNs), extreme gradient boosting, k-nearest neighbors, decision trees, adaptive boosting, and random forest, to model the wettability of the CO2/brine and rock minerals (quartz and mica) in a ternary system under varying conditions. Exploratory data analysis methods were used to examine the experimental data. The GridSearchCV and Kfold cross-validation approaches were implemented to augment the performance abilities of the ML models. In addition, sensitivity plots were generated to study the influence of individual parameters on the model performance. The results indicated that the applied ML models accurately predicted the wettability behavior of the mineral/CO2/brine system under various operating conditions, where FCFNN performed better than other ML techniques with an R2 above 0.98 and an error of less than 3%.
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Dióxido de Carbono , Ecosistema , Humectabilidad , MineralesRESUMEN
Understanding the dynamic behavior of polymeric fluids in porous media is essential for vast geoscience applications, particularly enhanced oil recovery and polymer-enhanced soil washing, to clean up soil contamination. During the past decades, the behavior of polymeric fluids in microscopic space has only been investigated using ensemble-averaged experimental methods in which a bulk phase behavior of the fluids characterizes flow mechanisms. Multiple flow mechanisms have been proposed based on ensemble-averaged data; however, microscale characterization of the interactions between polymers and solid surfaces and the mechanisms governing polymer retention and permeability reduction as well as the reversibility of polymer retention are lacking, resulting in a limited understanding of the flow mechanisms. Here we report direct visualization and multi-scale characterization of the dynamic behavior of polymer molecules in a representative porous medium by integrating microfluidics with single-molecule imaging. We demonstrate that the polymers' adsorption, entrapment and hydrodynamic retention contribute to their overall retention in porous media. Our study illustrates how microfluidics can help in understanding the dynamic behavior of polymers, their interactions with the solid/fluid interface and their effects on flow properties. Additionally, it demonstrates the role of microfluidic platforms in providing a more representative and accurate model for polymer retention and permeability reduction in porous media. The obtained insights encourage the development of improved models that better capture the behavior of complex fluids in confined environments and have significant implications for a wide range of applications in geoscience, materials science, and rheology.
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A comprehensive workflow approach is necessary to link multiple experimental tasks and identify microemulsion (ME) formulations with 'optimal' stability, displacement behavior and technical feasibility in the petroleum industry. In this paper, a systematic approach is described with the aid of a case study which involves the formulation of an anionic sodium dodecyl sulfate-based microemulsion. The design of such ME systems requires a proper methodology, substantial laboratory work, and functional assessment from research/industrial viewpoints. The surfactant has been screened in terms of its micellization potential, followed by phase behavior analysis and Winsor classification of prepared microemulsions. The desired composition(s) are characterized via several tools to determine droplet size, morphology, oil/water solubilization potentials and salinity scan results. The suitability of the microemulsion system for conformance improvement technology (CIT) is proposed to be assessed via physicochemical evaluation studies encompassing two attributes: rheology and stability. For a favorable 'conforming' drive, the microemulsion must exhibit phase stability, sufficient injectivity, and moderate-to-high viscosity under shear. Technical assessment by the industry and research team must also include factors related to cost, availability of chemicals, environmental degradation, and reservoir considerations. The article demonstrates a comprehensive all-inclusive workflow methodology to design and formulate surfactant-stabilized microemulsions via case study analysis for application in CIT. This represents a sound approach to identifying efficient, cost-effective injection fluid systems and provides a framework to identify useful parameters for ME formulation design and employ the proposed (effective) strategy for conformance control.
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Mineralization reactions in basaltic formations have gained recent interest as an effective method for CO2 geo-storage in order to mitigate anthropogenic greenhouse gas emissions. The CO2/rock interactions, including interfacial tension and wettability, are crucial factors in determining the CO2 trapping capacity and the feasibility of CO2 geological storage in these formations. The Red Sea geological coast in Saudi Arabia has many basaltic formations, and their wetting characteristics are rarely reported in the literature. Moreover, organic acid contamination is inherent in geo-storage formations and significantly impacts their CO2 geo-storage capacities. Hence, to reverse the organic effect, the influence of various SiO2 nanofluid concentrations (0.05-0.75 wt%) on the CO2-wettability of organic-acid aged Saudi Arabian (SA) basalt is evaluated herein at 323 K and various pressures (0.1-20 MPa) via contact angle measurements. The SA basalt substrates are characterized via various techniques, including atomic force microscopy, energy dispersive spectroscopy, scanning electron microscopy, and others. In addition, the CO2 column heights that correspond to the capillary entry pressure before and after nanofluid treatment are calculated. The results show that the organic acid-aged SA basalt substrates become intermediate-wet to CO2-wet under reservoir pressure and temperature conditions. When treated with SiO2 nanofluids, however, the SA basalt substrates become weakly water-wet, and the optimum performance is observed at an SiO2 nanofluid concentration of 0.1 wt%. At 323 K and 20 MPa, the CO2 column height corresponding to the capillary entry pressure increases from -957 m for the organic-aged SA basalt to 6253 m for the 0.1 wt% nano-treated SA basalt. The results suggest that the CO2 containment security of organic-acid-contaminated SA basalt can be enhanced by SiO2 nanofluid treatment. Thus, the results of this study may play a significant role in assessing the trapping of CO2 in SA basaltic formations.
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Dióxido de Carbono , Dióxido de Silicio , Arabia Saudita , Dióxido de Carbono/química , SilicatosRESUMEN
Polymers have been used effectively in the Oil & Gas Industry for a variety of field applications, such as enhanced oil recovery (EOR), well conformance, mobility control, and others. Polymer intermolecular interactions with the porous rock, in particular, formation clogging and the associated alterations to permeability, is a common problem in the industry. In this work, fluorescent polymers and single-molecule imaging are presented for the first time to assess the dynamic interaction and transport behavior of polymer molecules utilizing a microfluidic device. Pore-scale simulations are performed to replicate the experimental observations. The microfluidic chip, also known as a "Reservoir-on-a-Chip" functions as a 2D surrogate to evaluate the flow processes that take place at the pore-scale. The pore-throat sizes of an oil-bearing reservoir rock, which range from 2 to 10 nm, are taken into consideration while designing the microfluidic chip. Using soft lithography, we created the micromodel from polydimethylsiloxane (PDMS). The conventional use of tracers to monitor polymers has a restriction due to the tendency of polymer and tracer molecules to segregate. For the first time, we develop a novel microscopy method to observe the dynamic behavior of polymer pore-clogging and unclogging processes. We provide direct dynamic observations of polymer molecules during their transport within the aqueous phase and their clustering and accumulations. Pore-scale simulations were carried out to simulate the phenomena using a finite-element simulation tool. The simulations revealed a decline in flow conductivity over time within the flow channels that experienced polymer accumulation and retention, which is consistent with the experimental observation of polymer retention. The performed single-phase flow simulations allowed us to assess the flow behavior of the tagged polymer molecules within the aqueous phase. Additionally, both experimental observation and numerical simulations are used to evaluate the retention mechanisms that emerge during flow and how they affect apparent permeability. This work provides new insights to assessing the mechanisms of polymer retention in porous media.
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Reservoir stimulation is a widely used technique in the oil and gas industry for increasing the productivity of hydrocarbon reservoirs, most notably in carbonate formations. This work aims to develop an optimization workflow under uncertainty for matrix acidizing. A reactive transport model is implemented in a finite-element framework to simulate the initiation and propagation of dissolution channels in porous carbonate rock. The model is verified using an analytical solution. We utilize surrogate modeling based on polynomial chaos expansion (PCE) and Sobol indices to identify the most significant parameters. We investigate the effect of varying 12 identified parameters on the efficiency of the stimulation process using dimensionless groups, including the Damköhler, Peclet, and acid capacity numbers. Furthermore, the surrogate model reproduces the physics-based results accurately, including the dissolution channels, the pore volume to breakthrough, and the effective permeability of the stimulated rock. The developed workflow assesses how uncertainties propagate to the model's response, where the surrogate model is used to calculate the univariate effect. The global sensitivity analysis shows that the acid capacity number is the most significant parameter for the pore volume to breakthrough with the highest Sobol index. The marginal effect calculated for the individual parameter confirms the results from Sobol indices. This work provides a systematic workflow for uncertainty analysis and optimization applied to the processes of rock stimulation. Characterizing the impact of uncertainty provides physical insights and a better understanding of the matrix acidizing process.
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Carbon capture and storage projects need to be greatly accelerated to attenuate the rate and degree of global warming. Due to the large volume of carbon that will need to be stored, it is likely that the bulk of this storage will be in the subsurface via geologic storage. To be effective, subsurface carbon storage needs to limit the potential for CO2 leakage from the reservoir to a minimum. Water-dissolved CO2 injection can aid in this goal. Water-dissolved CO2 tends to be denser than CO2-free water, and its injection leads immediate solubility storage in the subsurface. To assess the feasibility and limits of water-dissolved CO2 injection coupled to subsurface solubility storage, a suite of geochemical modeling calculations based on the TOUGHREACT computer code were performed. The modelled system used in the calculations assumed the injection of 100,000 metric tons of water-dissolved CO2 annually for 100 years into a hydrostatically pressured unreactive porous rock, located at 800 to 2000 m below the surface without the presence of a caprock. This system is representative of an unconfined sedimentary aquifer. Most calculated scenarios suggest that the injection of CO2 charged water leads to the secure storage of injected CO2 so long as the water to CO2 ratio is no less than ~ 24 to 1. The identified exception is when the salinity of the original formation water substantially exceeds the salinity of the CO2-charged injection water. The results of this study indicate that unconfined aquifers, a generally overlooked potential carbon storage host, could provide for the subsurface storage of substantial quantities of CO2.
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We present a novel approach to model hydro-chemo-mechanical responses in rock formations subject to fracture propagation within chemically active rock formations. The framework developed integrates the mechanisms of reactive transport, fluid flow and transport in porous media, and phase-field modelling of fracture propagation in poroelastic media. The solution approach integrates the geochemical package PHREEQC with a finite-element open-source platform, FEniCs. The PHREEQC solver is used to calculate the localized chemical reaction, including solid dissolution/precipitation. The resulting solid weakening by chemical damage is estimated from the reaction-induced porosity change. The proposed coupled model was verified with previous numerical results and applied to a synthetic case exhibiting hydraulic fracturing enhanced with chemical damage. Simulation results suggest that mechanical failure could be accelerated in the presence of ongoing chemical processes due to rock weakening and porosity changes, allowing the nucleation, growth, and development of fractures.
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Reactive transport models are useful tools in the development of cement-based materials. The output of cement-related reactive transport models is primarily regarded as qualitative and not quantitative, mainly due to limited or missing experimental validation. This paper presents an approach to optimize the calibration process of reactive transport models for cement-based materials, using the results of several short-term experiments. A quantitative comparison of changes in the hydrate phases (measured using TGA and XRD) and exposure solution (measured using ICP-OES) was used to (1) establish a representative chemical model, limiting the number of hydrate phases and dissolved species, and (2) calibrate the transport processes by only modeling the initial tortuosity. A case study comprising the early age carbonation of cement is presented to demonstrate the approach. The results demonstrate that the inclusion of a microstructure model in our framework minimizes the impact of the initial tortuosity factor as a fitting parameter for the transport processes. The proposed approach increases the accuracy of reactive transport models and, thus, allowing for more realistic modeling of long-term exposure.
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HYPOTHESIS: Actualization of the hydrogen (H2) economy and decarbonization goals can be achieved with feasible large-scale H2 geo-storage. Geological formations are heterogeneous, and their wetting characteristics play a crucial role in the presence of H2, which controls the pore-scale distribution of the fluids and sealing capacities of caprocks. Organic acids are readily available in geo-storage formations in minute quantities, but they highly tend to increase the hydrophobicity of storage formations. However, there is a paucity of data on the effects of organic acid concentrations and types on the H2-wettability of caprock-representative minerals and their attendant structural trapping capacities. EXPERIMENT: Geological formations contain organic acids in minute concentrations, with the alkyl chain length ranging from C4 to C26. To fully understand the wetting characteristics of H2 in a natural geological picture, we aged mica mineral surfaces as a representative of the caprock in varying concentrations of organic molecules (with varying numbers of carbon atoms, lignoceric acid C24, lauric acid C12, and hexanoic acid C6) for 7 days. To comprehend the wettability of the mica/H2/brine system, we employed a contact-angle procedure similar to that in natural geo-storage environments (25, 15, and 0.1 MPa and 323 K). FINDINGS: At the highest investigated pressure (25 MPa) and the highest concentration of lignoceric acid (10-2 mol/L), the mica surface became completely H2 wet with advancing (θa= 106.2°) and receding (θr=97.3°) contact angles. The order of increasing θa and θr with increasing organic acid contaminations is as follows: lignoceric acid > lauric acid > hexanoic acid. The results suggest that H2 gas leakage through the caprock is possible in the presence of organic acids at higher physio-thermal conditions. The influence of organic contamination inherent at realistic geo-storage conditions should be considered to avoid the overprediction of structural trapping capacities and H2 containment security.
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Hidrógeno , Silicatos de Aluminio , Sales (Química) , HumectabilidadRESUMEN
Results are presented for real-time seismic imaging of subsurface fluid flow by parsimonious refraction and surface-wave interferometry. Each subsurface velocity image inverted from time-lapse seismic data only requires several minutes of recording time, which is less than the time-scale of the fluid-induced changes in the rock properties. In this sense this is real-time imaging. The images are P-velocity tomograms inverted from the first-arrival times and the S-velocity tomograms inverted from dispersion curves. Compared to conventional seismic imaging, parsimonious interferometry reduces the recording time and increases the temporal resolution of time-lapse seismic images by more than an order-of-magnitude. In our seismic experiment, we recorded 90 sparse data sets over 4.5 h while injecting 12-tons of water into a sand dune. Results show that the percolation of water is mostly along layered boundaries down to a depth of a few meters, which is consistent with our 3D computational fluid flow simulations and laboratory experiments. The significance of parsimonious interferometry is that it provides more than an order-of-magnitude increase of temporal resolution in time-lapse seismic imaging. We believe that real-time seismic imaging will have important applications for non-destructive characterization in environmental, biomedical, and subsurface imaging.