CO2 Reservoir Research Articles

Analysis of carbon dioxide reservoir performance and optimization strategies: a case study of a carbon dioxide plant

This study aimed at developing an empirical model for estimating and analyzing CO2 reservoir performance. This was achieved by using decline curve analysis (DCA) to determine an accurate empirical decline model for reservoir performance prediction and optimal producing, i.e., time at which the plant recovery build-up (RBU) efficiency has declined to an approximate value of 44.5%. MATLAB R2013b was used for calculating raw gas density whereas Ms Excel 2007 was used in plotting and performing all calculations. Through an examination of real production data, a harmonic decline model with an Arps’ decline constant (d) of 1.0 and a nominal decline rate of approximately 0.035572337/year was identified as the most suitable for characterizing reservoir performance. The study identifies the year 2048 as an optimal opportunity for implementing production optimization strategies to maximize returns while ensuring efficient resource recovery. Acknowledging the limitations of DCA, the study recommends exploring alternative forecasting models such as type curve analysis (TCA), material balance equation (MBE), and well simulation techniques to mitigate uncertainties in reservoir performance prediction. In addition, the study proposes a 5-year model verification and improvement program to refine reservoir descriptions and enhance data acquisition practices, aiming to optimize production efficiency and minimize uncertainties in CO2 reservoir operations.

Fluid effect on elastic properties of carbonate and implication for CO2 geologic sequestration monitoring

Laboratory measurement of the elastic properties of carbonates saturated with different fluids is crucial for characterizing reservoirs and monitoring CO2 sequestration. However, it is challenging to distinguish the effects of different fluids. We measure eight carbonate samples under varying pressure and fluid saturation conditions and conduct quantitative analysis. The measurements indicate that water saturation can increase P-wave velocity ([Formula: see text]), whereas oil and CO2 saturation may lead to an increase, decrease, or no change in [Formula: see text]. Meanwhile, all fluid saturation reduces the S-wave velocity ([Formula: see text]). The velocities of the dolomite samples are higher and less pressure sensitive than that of limestone samples. Four attributes are adopted to distinguish the fluid effect, including elastic moduli, impedance, [Formula: see text]/[Formula: see text] ratio, and a newly designed fluid discrimination factor F, which is obtained by multiplying P-wave modulus and square value of density change. Among the attributes, the F factor performs the best as it achieved evident and consistent results for all the samples. Rock-physics models are used to simulate elastic behaviors with the differential effective medium model predicting [Formula: see text] the best. The Gassmann’s equation correctly indicates positive or negative changes in rock velocity after fluid saturation even though its prediction does not exactly match the data. This study highlights the impact of various pore fluids on the carbonate elastic properties through laboratory measurement and theoretical modeling and introduces a novel fluid identification factor, providing insights for reservoir seismic characterization and CO2 sequestration monitoring.

Artificial neural network-based three-phase equilibria computation in compositional simulation of EOR and storage of CO2 in low-temperature reservoir

Artificial neural network-based three-phase equilibria computation in compositional simulation of EOR and storage of CO2 in low-temperature reservoir

A time-lapse multicomponent (9C 4D) seismic study at Vacuum Field, New Mexico, USA

In November and December 1995, the Reservoir Characterization Project (RCP) at the Colorado School of Mines acquired time-lapse multicomponent 3D surveys over the Central Vacuum Unit of Vacuum Field in Lea County, New Mexico. Two surveys were acquired — one before and one after the injection of 50 MMscf CO2 through a single wellbore into the San Andres Reservoir. The project determined that repeated multicomponent seismic surveys at the earth's surface can detect changes in bulk rock properties due to variations in reservoir pressures and fluid properties. Interpretation of the dynamic seismic response due to reservoir production processes over time provides an image of the relative permeability structure of the reservoir. Time-lapse multicomponent data were acquired using three-component geophones and vertically and horizontally actuated vibrator sources at the surface. A data processing flow was developed for time-lapse multicomponent 3D surveys. It uses surface-consistent processing algorithms and the source and receiver redundancy between initial and repeat surveys to derive surface-consistent corrections. Differences in S-wave polarization are measured between the initial and repeat surveys. S-wave data show sensitivity (through birefringence) to anisotropy caused by the orientation of fractures and low-aspect-ratio pore structure in a nonuniform stress field. The direction of fast S-wave polarization can be related to the direction of maximum horizontal stress and preferential permeability. Pore-pressure variations alter the effective stress. This varies the direction and intensity of open fractures and low-aspect-ratio pore structure within the current permeability structure of the reservoir, causing detectable changes in S-wave anisotropy. Anomalies in S-wave anisotropy, interpreted from time-lapse multicomponent 3D data, in conjunction with reservoir production data, are consistent with the fluid composition and pore-pressure changes associated with the CO2 injection program and reservoir processes in the survey area. Applications include monitoring hydrocarbon enhanced oil recovery; carbon capture, utilization, and storage; hydraulic stimulation; induced seismicity; and geothermal investigations.

A novel conditional generative model for efficient ensemble forecasts of state variables in large-scale geological carbon storage

Integrating monitoring data to efficiently update reservoir pressure and CO2 plume distribution forecasts presents a significant challenge in geological carbon storage (GCS) applications. Inverse modeling techniques are commonly used to fuse observational data and refine reservoir model parameters, thereby improving state variable forecasts. However, these techniques often rely on linear or Gaussian assumptions, which can limit their effectiveness in accurately predicting state variables. Moreover, simulating large-scale three-dimensional (3D) GCS problems is computationally expensive, making iterative runs in inverse problems prohibitive. To address these challenges, we propose a conditional generative model utilizing the score-based diffusion method for real-time 3D pressure and saturation field distribution predictions. Our approach involves solving the score function with a mini-batch-based Monte Carlo estimator to generate labeled data. This data is subsequently employed to train a fully connected neural network, enabling it to learn the conditional sample generator within a supervised learning framework. This method enables the rapid generation of a large ensemble of predictions, facilitating comprehensive uncertainty quantification of state variables. We applied our method to forecast the dynamic 3D distributions of pressure and saturation fields over a 30-year injection period. The statistical assessment with low root mean square error (RMSE) values demonstrates that our method can accurately predict the spatiotemporal distributions of both pressure and saturation fields. Moreover, the developed conditional generative model shows high computational efficiency by generating 100 ensemble forecasts of 3D state variables in less than 10 min. The consistency between ensemble averages and ground truth values further illustrates the model’s capability to capture state variable dynamics during the CO2 plume injection process. Notably, the ground truth values fall within the ensemble forecasts, indicating that our uncertainty quantification effectively captures variability and potential noise in the observations. Thus, the developed conditional generative model proves to be a more efficient, accurate, and practical tool for GCS applications, facilitating timely risk analysis and informed decision-making.

Committee machine learning: A breakthrough in the precise prediction of CO2 storage mass and oil production volumes in unconventional reservoirs

Accurate prediction of CO2 storage mass and cumulative oil production is critical in the context of combining subsurface carbon capture with enhanced oil recovery (CCS-EOR). This study introduces a novel committee machine-learning Gaussian Process Regression (CML-GPR) model, which integrates three well-established machine-learning algorithms—Random Forest (RF), Multi-Layer Extreme Learning Machine (MELM), and Generalized Regression Neural Network (GRNN). The combination of these models leverages the strengths of each algorithm: RF captures nonlinear relationships, MELM enhances computational efficiency, and GRNN provides smooth, generalized predictions. By integrating these complementary techniques, the CML-GPR model demonstrates significant improvements in predictive accuracy over individual models, addressing limitations in their performance. The model predicts CO2 storage mass and cumulative oil production based on nine key reservoir input variables, including depth, porosity, and CO2 injection rate, among others. Utilizing a large dataset of 21,193 data points from reservoir simulations, a Mahalanobis distance-based outlier detection method further refines the input data quality. The CML-GPR model achieves root mean square error (RMSE) values of 0.49 million metric tons for CO2 storage mass and 13.68 million barrels for cumulative oil production, significantly outperforming individual models. The CML-GPR model provides a robust tool for optimizing CO2 storage capacity and oil recovery, with practical implications for real-world reservoir management, ensuring more efficient and reliable CCS-EOR operations. This study represents a pioneering advancement in predictive modeling, offering valuable insights for optimizing both CO2 storage and enhanced oil recovery in complex reservoirs.

Numerical simulation of the coupled thermal-hydro-mechanical fields for evaluating CO2 geo-sequestration storage in deep saline aquifers of Hainan Fushan Sag, China

Geo-sequestration storage of CO2 in saline aquifers is an important technological option to reduce carbon emissions in China in the future. The theory of geo-sequestration storage of CO2 in saline aquifers involves complex physical operations and chemical phenomena among reservoir stress, seepage, and temperature fields, and the numerical simulation models coupling thermal-hydro-mechanical (THM) fields are widely applied to analyze the evolution of multiphysical processes in CO2 reservoirs. Based on the geo-sequestration storage project of saline aquifer CO2 in Fushan Sag, Hainan Province, under the premise of considering the change of permeability and porosity after the mineralization of CO2 in the rock reservoirs, this study simulates the evolution of temperature, stress, and seepage fields during the sequestration process of saline aquifer Continuous CO2 injection wells clarifies the range of influence of the temperature field, seepage field, and the boundary of its stress field of saline aquifer Continuous CO2 injection wells in different sequestration periods. It reveals the influence mechanism of the fault structure on the reservoir CO2 sequestration pressure and capacity, and evaluates and estimates the CO2 injection storage capacity of Fu 1# well in Fushan Sag and on this basis. The THM numerical simulation model proposed in this study plays a crucial role in guiding theoretical evaluations of the CO2 geo-sequestration potential in saline aquifers and determining its technical parameters, thereby offering significant value for engineering applications.

Studying the storage index systems and geological storage conditions of CO2 in typical coal basins

Abstract In China, the geological storage of CO2 in coal reservoirs started relatively late. There are still issues with the index mechanism for choosing storage sites. This study has identified eight types of basic engineering geologic indexes, ten types of basic storage potential indexes, and three types of basic socio-economic indexes at the regional scale for the type of coal reservoir in order to grasp the areas favorable for geological storage of carbon dioxide and the potential for storage in China. These categories are based on the results of current research and engineering practice both domestically and internationally.

Dynamics of impure CO2 and composite oil in mineral nanopores: Implications for shale oil recovery and gas storage performance

Evaluating the application effectiveness of impure CO2 in shale reservoirs is a prerequisite for reducing CO2 purification costs. Therefore, molecular dynamics simulations were applied to study the influential mechanisms of impurity gases, mineral types and oil components on impure CO2 enhanced oil recovery (impure CO2-EOR) and gas storage (GS). The orientation force between H2S and polar oil components and the strong adsorption of H2S on mineral walls improve the solubility and diffusivity of impure CO2 in shale oil. Moreover, the induction force between H2S and CO2 carry additional CO2 to walls, and the hydrogen bonds formed between H2S and walls further enhance oil–gas competitive adsorption, resulting in more adsorbed oil being stripped and more H2S/CO2 being sequestered. N2 hinders the dissolution of H2S/CO2 into shale oil and the diffusion of desorbed oil towards the center of nanopores. Therefore, the EOR and GS performances in nanopores are positively and negatively correlated with the proportion of H2S and N2 in impure CO2, respectively. Both EOR and GS performances of impure CO2 decrease sequentially in illite, quartz, and kerogen nanopores, because the strong adsorption of shale oil on kerogen walls causes oil molecules to arrange tightly and dissolve in kerogen. It weakens the solubility and diffusivity of impure CO2 in shale oil, and also increases the resistance of impure CO2 to displace adsorbed and dissolved oil. By contrast, illite walls have the weakest adsorption on shale oil and the largest number of hydrogen bonds formed with H2S. The increase of heavy component content further enhances the interaction between oil molecules and the adsorption of shale oil on wall, thereby weakening the effects of various impure CO2-EOR mechanisms.

Research Progress on CO2 as Geothermal Working Fluid: A Review

With the continuous increase in global greenhouse gas emissions, the impacts of climate change are becoming increasingly severe. In this context, geothermal energy has gained significant attention due to its numerous advantages. Alongside advancements in CO2 geological sequestration technology, the use of CO2 as a working fluid in geothermal systems has emerged as a key research focus. Compared to traditional water-based working fluids, CO2 possesses lower viscosity and higher thermal expansivity, enhancing its mobility in geothermal reservoirs and enabling more efficient heat transfer. Using CO2 as a working fluid not only improves geothermal energy extraction efficiency but also facilitates the long-term sequestration of CO2 within reservoirs. This paper reviews recent research progress on the use of CO2 as a working fluid in Enhanced Geothermal Systems (EGS), with a focus on its potential advantages in improving heat exchange efficiency and power generation capacity. Additionally, the study evaluates the mineralization and sequestration effects of CO2 in reservoirs, as well as its impact on reservoir properties. Finally, the paper discusses the technological developments and economic analyses of integrating CO2 as a working fluid with other technologies. By systematically reviewing the research on CO2 in EGS, this study provides a theoretical foundation for the future development of geothermal energy using CO2 as a working fluid.

Investigation on the impact of CO2-Induced precipitation on microscopic pore structure of low-permeable reservoirs

CO2 injection into reservoirs might induce organic or inorganic precipitation in microscopic pores, and some of the pores are blocked by the precipitates, resulting in a decrease in the connectivity of pores and affecting oil recovery. In this paper, a set of experiments on CO2 displacement and CO2-water-oil-rock interaction are conducted to study the microscopic mechanisms of reservoir damage. In-situ Nuclear Magnetic Resonance (NMR) technology is applied to conduct the microscopic analysis of CO2-EOR and reservoir damage at real reservoir conditions. The results reveal that the particle size and the amount of inorganic precipitates formed in the formation water will increase with the rise of CO2 injection pressure, and the inorganic precipitates primarily consist of siderite and kaolinite. The change of NMR T2 spectra of the core samples reveals that the inorganic precipitates primarily block the small pores less than 0.89 μm. However, as a result of stronger mineral dissolution and solute transport, the pore volume of the large pores (greater than 0.89 μm) increases after the CO2-water-rock reaction. Ultimately, this interaction results in a 5.4% increment in pore volume. In addition, the displacement efficiency of water-saturated cores is improved after the first CO2 displacement, which indicates that CO2-water-rock interaction can effectively improve the seepage properties of reservoirs. Nevertheless, the reservoir damage caused by asphaltene precipitation during CO2 flooding is more significant. The asphaltene precipitation percentage in formation oil increases with the rise of CO2 injection pressure, reservoir temperature, and asphaltene content in virgin oil. CO2-induced asphaltene precipitation causes more severe blockage on small pores in comparison with large pores. After 2 h of CO2 injection to the oil-saturated core, permeability and oil recovery caused by CO2-induced precipitation decreased by 17.6% and 11.4%, respectively.

Unlocking Potential for Low-Carbon Hydrogen Production from U.S. Natural Gas Resources.

Hydrogen will potentially play a key role while transitioning to a net-zero economy. This study addresses resource, environmental, economic, policy, and societal issues related to low-carbon hydrogen production by steam methane reforming with carbon capture and storage in Wyoming and other natural-gas-rich states. For low-carbon hydrogen produced from natural gas and electricity supplies and which stores CO2 in saline reservoirs in Wyoming, the levelized cost of hydrogen (LCOH) ranges from $1.62-2.00/kg H2, and the life cycle emissions range from 3.85-5.74 kg CO2-eq/kg H2. If claimed, the 45Q tax credit decreases the LCOH by 19%. Although the supplies of renewable natural gas feedstock and zero- or low-carbon electricity can lower the carbon footprint to make hydrogen projects qualified for the 45V tax credit, the 45Q tax credit is still a stronger economic incentive. To reduce the supply cost, a hydrogen cluster can be developed in the state by leveraging the colocation and coavailability of multiple natural resources and transport infrastructure. Developing a hydrogen cluster can directly create several thousand construction jobs and several hundred permanent jobs in Wyoming. Low-carbon hydrogen production can also be scaled up in other states across the nation.

Influence of Heterogeneous Reservoir on Carbon Sequestration and Carbon Displacement

Abstract Carbon Capture, Utilization and Sequestration (CCUS) is a method of burying CO2 captured in various ways into the reservoir and extracting the remaining oil from the reservoir. It is one of the important methods to reduce carbon emissions and achieve carbon neutrality in the next few decades, and it is also considered to be the most economical and effective method to slow down the greenhouse effect. It is very important to study the influence of reservoir heterogeneity on CO2 storage and oil recovery in order to make CCUS scheme store more CO2 and recover more remaining oil. Firstly, the numerical simulation model of reservoir is established in this paper. Its injection-production mode is gas injection in vertical wells at the top of the reservoir at a fixed gas injection rate, and oil production in horizontal wells at the bottom of the reservoir at a fixed pressure. Secondly, the distribution of reservoir porosity and permeability is designed, and four reservoir models are established: homogeneous reservoir, heterogeneous reservoir, positive rhythm heterogeneous reservoir and reverse rhythm heterogeneous reservoir. Finally, the effects of four reservoir models on CO2 storage and oil recovery are studied, and the migration law of CO2 is comprehensively analyzed according to the characteristics of reservoir pressure distribution. The reverse rhythm reservoir has the best CO2 storage effect, and the positive rhythm reservoir has the highest oil recovery. That is, when burying is the main method, the reverse rhythm heterogeneous reservoir is preferred; When oil displacement is the main method, positive rhythm reservoir is preferred. Among the four homogeneous or heterogeneous reservoirs, the migration law of CO2 in reservoirs is quite different, mainly due to the influence of reservoir heterogeneity. CO2 preferentially migrates from the dominant channels in the reservoir, but regardless of the reservoir type, the molar fraction of CO2 at the top of the reservoir is the highest. In addition, the CO2 invasion of four kinds of reservoirs in different stages of caprock is analyzed and its safety is analyzed. This study provides an effective reference for the establishment of numerical simulation models of different types of heterogeneous reservoirs, the migration characteristics of carbon dioxide in reservoirs and the effective operation and evaluation of CCUS scheme.

Early extensional salt tectonics controls deep-water sediment dispersal

Predicting the distribution of sedimentary facies during the early stages of deformation of salt-detached continental margins is key to constraining the location and stratigraphic architecture of hydrocarbon and CO2 reservoirs, as well as to understanding the oceanic carbon cycle. Despite its importance, we still have a relatively poor understanding of salt-sediment interactions during the early phases of extensional salt tectonics, mainly because subsequent salt-related deformation and/or deep burial of the related stratigraphic succession means the related deposits are poorly imaged in seismic reflection data and/or not penetrated by borehole data. We investigated the interplay between early extension-related salt deformation and deep-water sediment dispersal using 3-D seismic reflection data from the northern Levant Basin offshore Lebanon. Our results indicate that salt tectonics has two contrasting impacts: Whereas slope-parallel faults favor early sediment transfer along downslope-oriented corridors to the abyssal plain, slope-normal faults and ramp-syncline basins trap land-derived sediments, hampering or delaying their transport to the abyssal plain. These results help refine source-to-sink models of turbidite systems developing in young salt basins, highlighting the crucial role of extensional tectonics in controlling sediment dispersal and the development of intra-slope depocenters and emphasizing the impact of fault strike, ramp-syncline basin evolution, and salt thinning. Our study has significant implications for predicting the location of deep-water coarse-grained sediment and the preservation of land-derived organic carbon in mature, more structurally complex, salt basins.

Three-Dimensional Coupled Temporal Geomechanical Model for Fault-Reactivation and Surface-Deformation Evaluation during Reservoir Depletion and CO2 Sequestration, Securing Long-Term Reservoir Sustainability

Assessing reservoir subsidence due to depletion involves understanding the geological and geophysical processes that lead to ground subsidence as a result of reservoir fluid extraction. Subsidence is a gradual sinking or settling of the Earth’s surface, and it can occur when hydrocarbons are extracted from underground reservoirs. In this study, a time-integrated 3D coupled geomechanical modeling incorporating the fourth dimension—time—into traditional 3D geomechanical models has been constructed utilizing seismic inversion volumes and a one-dimensional mechanical Earth model (1D MEM). The 3D geomechanical model was calibrated to the 1D MEM results. Geomechanical rock properties were derived from the density and sonic log data that was distributed with conditioning to the seismic inversion volumes obtained from running pre-stack inversion. The standard elastic parameter equations were used to generate estimates of the elastic moduli. These properties are dynamic but have been converted to static values using additional equations used in the 1D MEM study. This included estimating the Unconfined Compressive Strength. In situ stresses were matched using different minimum horizontal principal stress gradients and horizontal principal stress ratios. The match is good except where the weak carbonate faults are close to the wells, where the Shmin magnitudes tend to decrease. The SHmax orientations were assessed from image log data and indicated to be 110° in the reservoir section. A time-integrated 3D coupled simulation was created using the finite-element method (FEM). The effective stresses increase while there is depletion in all directions, especially in the Z direction. The predicted compaction in the reservoir and overburden was 350 mm. Most of the compaction occurs at the reservoir level and dissipates towards the surface (seabed). Furthermore, the case displayed no shear failure that might cause or fault reactivation in the reservoir interval (Kangan–Dalan Formations) located in the simulated area. In this study, we applied an integrated and comprehensive geomechanical approach to evaluate subsidence, fault reactivation and stress alteration, while reservoir depletion was assessed using seismic inversion, well logs, and experiment data. The deformation monitoring of geological reservoirs, whether for gas storage or hazardous gas disposal, is essential due to the economic value of the stored assets and the hazardous nature of the disposed materials. This monitoring is vital for ensuring the sustainability of the reservoir by maintaining operational success and detecting integrity issues.

Analysis of dynamic characteristics and influencing factors of CO2 low-permeability coal reservoir sequestration

ABSTRACT Abandoned coal seams can be an important carrier for CO2 geological storage. Considering the gas seepage-diffusion and physical adsorption coupling characteristics in the process of CO2 adsorption and storage in coal and rock, a two-dimensional model of coupled flow-solidity for geological storage of CO2 in low-permeability reservoir with double voids was established by introducing the Zhang Hongbin model algorithm and adding the Klinkenberg effect and the compression effect of the rock skeleton in coal reservoirs in the controlling equation for rock deformation. The coupled flow-solid model was solved by using the PDE equation of COMSOL Multiphics program, and the simulation results difference between the new model and the traditional model in terms of sequestration dynamics were compared. The dynamic characteristic of reservoir gas pressure, formation stress, permeability and sequestration density in the process of CO2 geologic sequestration and injection were analyzed, and the influences of injection pressure and injection well diameter on the amount of CO2 sequestration were explored. The results show that the new model is more reasonable for calculating reservoir gas pressure and permeability compared with the Palmer-Mansoori model (PM model), and can simulate the free-state seepage movement of CO2 in the fracture system as well as its physical adsorption process compared with the single-heavy pore medium model. With continuous CO2 injection, the maximum sequestration density was raised to a limit value of about 1000 kg/m3 after 1 year. The date of reaching the limit of the sequestration volume was advanced by about 45 d when the positive pressure of the injected gas was increased from 10 kPa to 50 kPa. This model can reproduce the main parameters including, when affecting the effect, and realize the calculation of parameters such as CO2 density reaching the limit value, sealing limit day, sealing limit amount, which can provide a theoretical basis for further deep understanding of CO2 geological sealing law and scientific development of gas injection scheme.

Predominance of aminated water interfaces on transition-metal nanoparticulate to enhance synergetic removal of carbonyls and inhibition of CO2 production

In the context of the air quality co-benefits of carbon neutrality, conventional strategies for the end-of-pipe control aimed at reducing volatile organic compounds (VOCs) to carbon dioxide (CO2) require a more realistic revision. This study explored the synergetic removal of carbonyls with low carbon emission by amine-functionalized manganese dioxide (MnO2), obtained through a method involving freezing-thawing cycles. Molecular-level characterization revealed that an ordered array of interfacial water dimers (H5O2+, a class of water-proton clusters) on the MnO2 surface enhanced the robust bonding of metal sites with amino groups. Amine-functionalized MnO2 can be negatively charged under environmental acidity to further interfacial proton-coupled electron transfers. This cooperativity in interfacial chemical processes promoted the selective conversion of carbonyl carbons to bicarbonated amides (NH3+HCO3−), serving as a reservoir of CO2. In comparison to a commercially used 2,4-dinitrophenylhydrazine (DNPH) control, this approach achieved nearly complete removal of a priority carbonyl mixture containing formaldehyde, acetaldehyde, and acetone synergically. The formation of secondary organic compounds in the gas phase and CO2 off-gas were suppressed.

An improved prediction model for miscibility characterization and optimization of CO2 and associated gas co-injection

Insufficient reservoir pressure and gas source problems seriously limit effective applications of CO2 flooding in hydrocarbon reservoirs. An attractive strategy is to co-inject the produced associated hydrocarbon gas with CO2 to achieve miscible/near-miscible flooding to enhance oil recovery. However, the composition of the injected mixture and the in-situ spatio-temporal composition evolution of the displacing/displaced fluids significantly affect the CO2-oil miscibility and the overall hydrocarbon recovery performance. In this work, based on slim tube simulation results, a prediction model of minimum miscible pressure (MMP)/minimum near-miscible pressure (MNMP) is established. This model takes into account the effects of CO2 concentration distribution, oil composition and temperature changes to achieve accurate spatiotemporal characterization of miscibility in the reservoir. In addition, the distribution law of the phase and components front for the impure CO2 injection process was also investigated. The miscible volume factor and recovery efficiency were used as the basis for judging the minimum injection concentration limit of CO2. The simulation results of slim tube experiment indicate that the MMP and MNMP obtained are 16.74 MPa and 12.35 MPa, respectively. Furthermore, the error caused by the traditional slim tube experiment can be reduced by using the CO2 produced fraction. It is found that CO2 injection concentration and reservoir temperature are the main factors affecting miscibility, but injection rate has less effect. Moreover, the fast migration of CH4 front leads to the shrinkage of miscible/near-miscible zone, which is not conducive to CO2 flooding. Finally, the CO2 injection concentration of non-breakthrough stage, breakthrough stage and large-scale breakthrough stage was determined to be 78.3%, 61.5% and 29.2%, respectively. This work provides strong evidence for the treatment of associated gas reinjection, which is beneficial for optimization of carbon capture, EOR-utilization and storage (CCUS-EOR) projects.

Surface morphologic changes and mineral transformation mechanisms after CO2-brine-rock reaction in organic matter-rich ferroan shale

Sequestrating CO2 in shale reservoirs can not only reduce CO2 emission, and enhance oil and gas recovery. Nevertheless, shale reservoirs were normally formed in reducing environments, and are abundant in Fe2+ and organic matter. Fe2+ influence the dissolution and precipitation behavior of minerals within the reservoir. Simultaneously, organic matter occupies the pore spaces within the reservoir, thereby affecting the reservoir physical properties. The CO2-brine-rock reaction experiment was carried out using organic matter-rich ferroan shale in this study. The changes in surface morphology of minerals and organic matter utilizing X-ray Diffraction localization monitoring techniques. Based on the TOUGHREACT, a quantitative analysis was conducted on the dissolution and precipitation of individual components. The results suggest that the carbonates preferentially dissolved at the early stage, resulting in a rougher surface morphology andthe formation ofcracks. During the early stage, ankerite transformed into pyrite and chlorite. As the reaction progresses, an elevation in the solution’s acidity facilitates converts chlorite to pyrite and kaolinite. After the dissolution of dolomite, calcite is the primary secondary mineral. The formation of clay minerals consumes Mg2+, resulting in minimal magnesite. The dissolution of feldspar was weaker than carbonate minerals. Dissolution of plagioclase results in the formation of dawsonite in solution. The dissolution of K-feldspar induces the transformation of smectite to illite. In addition, as the reaction solution acid escalated, the soluble mineral components in the large-particle polymer dissolved and dispersed into small-particle organic matter. The small-particle organic matter absorbs secondary minerals generated to form a cake-like polymer.

Mechanism study on the influence of wettability on CO2 displacement of shale oil in nanopores

A four-phase model of an oil–gas-water-wall system was constructed using the molecular dynamics simulation method. On this basis, the effect of shale reservoir wettability on the mechanism of CO2 flooding of oil will be investigated. The study found that in hydrophilic and mixed wetting systems, the front of the CO2 molecules had a semilunar shape. In lipophilic systems, however, it advanced as a whole. In addition, water molecules in the mixed wet system will form a water bridge, preventing the forward movement of CO2 molecules. CO2 molecules can easily displace oil molecules in pores of different wettability, but cannot remove the water molecules adsorbed on hydrophilic and mixed wetting systems. Oil molecules interact weakly with the hydroxyl group on the wall, but strongly with the methyl group on the wall. CO2 molecules interact strongly with both the methyl and hydroxyl groups on the wall. The difficulty of CO2 in displacing shale oil in different wetting systems is ranked in the following order: mixed wetting system (41.90 %), lipophilic system (91.51 %), hydrophilic system (98.77 %). Additionally, the storage efficiency of the three nanopores for CO2 was 50.53 %, 77.53 %, and 74.24 %, respectively. The research results can provide theoretical support for the development of CO2 in shale reservoirs.