CO2 Enhanced Oil Recovery Project Research Articles

An Experimental Investigation of Surfactant-Stabilized CO2 Foam Flooding in Carbonate Cores in Reservoir Conditions

Carbon dioxide (CO2) injection for enhanced oil recovery (EOR) has attracted great attention due to its potential to increase ultimate recovery from mature oil reservoirs. Despite the reported efficiency of CO2 in enhancing oil recovery, the high mobility of CO2 in porous media is one of the major issues faced during CO2 EOR projects. Foam injection is a proven approach to overcome CO2 mobility problems such as early gas breakthrough and low sweep efficiency. In this experimental study, we investigated the foam performance of a commercial anionic surfactant, alpha olefin sulfonate (AOS), in carbonate core samples for gas mobility control and oil recovery. Bulk foam screening tests demonstrated that varying surfactant concentrations above a threshold value had an insignificant effect on foam volume and half-life. Moreover, foam stability and capacity decreased with increasing temperature, while variations in salinity over the tested range had a negligible influence on foam properties. The pressure drop across a brine-saturated core sample increased with an increasing concentration of surfactant in the injected brine during foam flooding experiments. Co-injection of CO2 and AOS solution at an optimum concentration and gas fractional flow enhanced oil recovery by 6–10% of the original oil in place (OOIP).

A Comprehensive Summary of the Application of Machine Learning Techniques for CO2-Enhanced Oil Recovery Projects

This paper focuses on the current application of machine learning (ML) in enhanced oil recovery (EOR) through CO2 injection, which exhibits promising economic and environmental benefits for climate-change mitigation strategies. Our comprehensive review explores the diverse use cases of ML techniques in CO2-EOR, including aspects such as minimum miscible pressure (MMP) prediction, well location optimization, oil production and recovery factor prediction, multi-objective optimization, Pressure–Volume–Temperature (PVT) property estimation, Water Alternating Gas (WAG) analysis, and CO2-foam EOR, from 101 reviewed papers. We catalog relative information, including the input parameters, objectives, data sources, train/test/validate information, results, evaluation, and rating score for each area based on criteria such as data quality, ML-building process, and the analysis of results. We also briefly summarized the benefits and limitations of ML methods in petroleum industry applications. Our detailed and extensive study could serve as an invaluable reference for employing ML techniques in the petroleum industry. Based on the review, we found that ML techniques offer great potential in solving problems in the majority of CO2-EOR areas involving prediction and regression. With the generation of massive amounts of data in the everyday oil and gas industry, machine learning techniques can provide efficient and reliable preliminary results for the industry.

Adsorption Characteristics of CO2/CH4/H2S Mixtures in Calcite Nanopores with the Implications for CO2 Sequestration

Summary Injecting CO2 into reservoirs for storage and enhanced oil recovery (EOR) is a practical and cost-effective strategy for reducing carbon emissions. Commonly, CO2-rich industrial waste gas is used as the CO2 source, whereas contaminants such as H2S may severely impact carbon storage and EOR via competitive adsorption. Hence, the adsorption behavior of CH4, CO2, and H2S in calcite (CaCO3) micropores and the impact of H2S on CO2 sequestration and methane recovery are specifically investigated. The Grand Canonical Monte Carlo (GCMC) simulations were applied to study the adsorption characteristics of pure CO2, CH4, and H2S, and their multicomponent mixtures were also investigated in CaCO3 nanopores to reveal the impact of H2S on CO2 storage. The effects of pressure (0–20 MPa), temperature (293.15–383.15 K), pore width, buried depth, and gas mole fraction on the adsorption behaviors are simulated. Molecular dynamics (MD) simulations were performed to explore the diffusion characteristics of the three gases and their mixes. The amount of adsorbed CH4, CO2, and H2S enhances with rising pressure and declines with rising temperature. The order of adsorption quantity in CaCO3 nanopores is H2S > CO2 > CH4 based on the adsorption isotherm. At 10 MPa and 323.15 K, the interaction energies of CaCO3 with CO2, H2S, and CH4 are −2166.40 kcal/mol, −2076.93 kcal/mol, and −174.57 kcal/mol, respectively, which implies that the order of adsorption strength between the three gases and CaCO3 is CO2 > H2S > CH4. The CH4-CaCO3 and H2S-CaCO3 interaction energies are determined by van der Waals energy, whereas electrostatic energy predominates in the CO2-CaCO3 system. The adsorption loading of CH4 and CO2 are lowered by approximately 59.47% and 24.82% when the mole fraction of H2S is 20% at 323.15 K, reflecting the weakening of CH4 and CO2 adsorption by H2S due to competitive adsorption. The diffusivities of three pure gases in CaCO3 nanopore are listed in the following order: CH4 > H2S ≈ CO2. The presence of H2S in the ternary mixtures will limit diffusion and outflow of the system and each single gas, with CH4 being the gas most affected by H2S. Concerning carbon storage in CaCO3 nanopores, the CO2/CH4 binary mixture is suitable for burial in shallower formations (around 1000 m) to maximize the storage amount, while the CO2/CH4/H2S ternary mixture should be buried as deep as possible to minimize the adverse effects of H2S. The effects of H2S on CO2 sequestration and CH4 recovery in CaCO3 nanopores are clarified, which provides theoretical assistance for CO2 storage and EOR projects in carbonate formation.

Molecular insights into mass transfer and adsorption behaviors of hydrocarbon and CO2 in quartz multiple-nanopore system

Exploitating liquid hydrocarbons from unconventional reservoirs is playing an ever-increasing role in addressing global energy supply issues. CO2 huff-and-puff is an environmental and effective method to enhance hydrocarbon recovery and achieve CO2 geo-sequestration simultaneously, playing an important role in carbon capture, utilization, and sequestration (CCUS) projects. The optimization of huff-n-puff operations requires clarifying the adsorption state and migration behaviors of hydrocarbons and CO2 in unconventional reservoirs dominated by nanopores. In this paper, we used molecular dynamics (MD) simulation to investigate adsorption behaviors and mass transfer of CO2and n-decane (nC10) molecules in multiple quartz nanopores by carefully considering pore size and structure effects. It shows that the adsorption behaviors and replacement efficiency of oil molecules are closely related to pore aperture. Interestingly, we found that the surface adsorption of nC10 demonstrates a non-monotonic trend of rising after falling as the pore size decreases from 5 nm to 0.7 nm. Specifically, when the pore size is reduced to ∼ 1 nm, nC10 molecules exhibit a pseudo-double layered distribution state. In such a nanopore, the surface adsorption of nC10 is significantly weakened but thesurface adsorption of CO2 is enhanced, leading to the maximum oil recovery efficiency. Although the reduction of pore width adversely affects the extraction speed of oil, it is generally favorable for improving final oil recovery. In a double-nanopore system, the exchange between nC10 and CO2presents a counter-current flow pattern. By contrast, in the triple-nanopore systems, nC10 and CO2form their respective dominant migration paths and the large pores dominates the equilibrium time. These observations provide a more in-depth understanding of CO2-enhanced oil recovery (CO2-EOR) mechanisms from the molecular level, and reveal new insights into CO2and oil adsorption and migration behaviors in complex nanopores, thus aiding in the efficient implementation of CO2-EOR project.

Effects of CO2 on creep deformation in sandstones at carbon sequestration reservoir conditions: An experimental study

We conducted four hydrostatic creep/flow-through experiments to investigate the evolution of rock hydraulic and mechanical properties due to fluid-rock interactions in the context of underground CO2 utilization and storage. The experiments were performed on the macroporosity-dominated lithofacies of the Morrow B sandstone. The Morrow B is an early Pennsylvanian fluvial/marine deposit, and the target reservoir of an ongoing CO2-enhanced oil recovery project at the Farnsworth Unit oilfield, Ochiltree County, Texas. Core samples were held at 38.5 MPa effective stress and 100 °C while flowing through reservoir brackish solution (control) or CO2-enriched reservoir brackish solution at different flow rates (0.01, 0.02, and 0.1 ml/min). We monitored the evolution of the outlet fluid chemistry, sample axial strain, permeability, and bulk modulus, and measured pre- and post-experiment porosities and ultrasonic wave velocities. Results showed mineral dissolution, but no enhanced creep deformation in the presence of CO2. Samples experienced fluctuations in the bulk modulus of elasticity with up to 18% and 3% increases for flow-through with reservoir brackish solution and CO2-enriched reservoir solution, respectively. Permeability decreased monotonically during flow-through with brackish solution, but fluctuated with CO2-rich brackish solution. All samples experienced a decrease in the post-test ultrasonic wave velocities, where the decrease was proportional to the test duration. Chemical reactions were not rate limited, and ion concentrations varied as the fluid volume through the core for all experiments irrespective of flow rate, duration, or experiment type. We believe that the observed fluctuation in sample bulk modulus was due to dissolution/microcracking leading to rock softening versus rock consolidation/pressure solution leading to rock stiffening, which is supported by petrographic observations. CO2-driven dissolution of disseminated ankerite cements did not cause enhanced compaction because of their low occurrence and the presence of the more abundant unreactive pre-compaction quartz cements forming long contacts with the framework grains. Porous sandstone reservoirs whose framework grains are supported by early diagenetic (pre-compaction) quartz cements make good targets for the long-term safe underground storage of CO2.

Investment feasibilities of CCUS technology retrofitting China's coal chemical enterprises with different CO2 geological sequestration and utilization approaches

CO2 capture, utilization, and storage (CCUS) technology provides an efficient alternative for decarbonizing the coal chemical industry under China's carbon neutrality goal. However, uncertainties such as geological conditions, technology level, carbon markets, subsidy policies, etc., will greatly affect investor confidence in the CCUS applicability in this industry. This study develops a trinomial tree real options based CCUS investment decision model to explore CCUS investment feasibilities for China's coal chemical enterprises with different CO2 geological sequestration and utilization approaches, i.e., CO2 enhanced oil recovery (CO2-EOR) projects, CO2 enhanced coalbed methane (CO2-ECBM) projects, and deep saline aquifer (DSA) projects. The findings show that 1) CO2-ECBM projects have a larger investment benefit compared to CO2-EOR and DSA projects, with a critical coalbed methane (CBM) price for the immediate investment of 1.3 CNY/m³ under the current technology and carbon price level. 2) CO2-EOR projects are immediately investable at a critical oil price of 200 CNY/BBL; DSA projects require the execution of a delayed option with a critical carbon price of 361.8 CNY/t. 3) Provincial investment benefits vary substantially depending on CO2 transport distance and product revenue, particularly for CO2-ECBM projects in Henan and Guizhou, which have significant investment benefits due to high local CBM prices and short CO2 transport distances.

Prediction of Key Parameters in the Design of CO2 Miscible Injection via the Application of Machine Learning Algorithms

The accurate determination of key parameters, including the CO2-hydrocarbon solubility ratio (Rs), interfacial tension (IFT), and minimum miscibility pressure (MMP), is vital for the success of CO2-enhanced oil recovery (CO2-EOR) projects. This study presents a robust machine learning framework that leverages deep neural networks (MLP-Adam), support vector regression (SVR-RBF) and extreme gradient boosting (XGBoost) algorithms to obtained accurate predictions of these critical parameters. The models are developed and validated using a comprehensive database compiled from previously published studies. Additionally, an in-depth analysis of various factors influencing the Rs, IFT, and MMP is conducted to enhance our understanding of their impacts. Compared to existing correlations and alternative machine learning models, our proposed framework not only exhibits lower calculation errors but also provides enhanced insights into the relationships among the influencing factors. The performance evaluation of the models using statistical indicators revealed impressive coefficients of determination of unseen data (0.9807 for dead oil solubility, 0.9835 for live oil solubility, 0.9931 for CO2-n-Alkane interfacial tension, and 0.9648 for minimum miscibility pressure). One notable advantage of our models is their ability to predict values while accommodating a wide range of inputs swiftly and accurately beyond the limitations of common correlations. The dataset employed in our study encompasses diverse data, spanning from heptane (C7) to eicosane (C20) in the IFT dataset, and MMP values ranging from 870 psi to 5500 psi, covering the entire application range of CO2-EOR. This innovative and robust approach presents a powerful tool for predicting crucial parameters in CO2-EOR projects, delivering superior accuracy, speed, and data diversity compared to those of the existing methods.

Multi-objective optimization of CO2 enhanced oil recovery and storage processes in low permeability reservoirs

CO2 enhanced oil recovery (CO2-EOR) is a mature technology to improve production from low permeability reservoirs. The CO2-EOR process has the potential of both improving oil recovery and sequestering large volumes of injected CO2. The performance of CO2 flooding can be affected significantly by CO2 injection modes (continuous gas injection, CGI, or water alternating gas, WAG); types of optimizations (co-optimization or synergy optimization); and several operational parameters, e.g., injection rates, etc. This paper presented an integrated numerical framework for co-optimization and synergy-optimization of CO2-EOR performance and CO2 storage performance in low permeability reservoirs and provided a comparison of CGI and WAG injection modes. In co-optimization, we maximized cumulative oil production (COP) and CO2 storage capacity (CO2SC) simultaneously (i.e., bi-objective optimization) using multi-objective particle swarm optimization (MOPSO). In synergy-optimization, we maximized a weighted sum of COP and CO2SC (i.e., single objective optimization) using PSO. The optimization results provide significant insight to the decision-making process of coupled CO2-EOR and storage projects when multiple objective functions are considered. We also compared the influence of dimensionless objective functions on the optimization results for different types of optimizations, and the results proved dimensionless objective functions had no impact on the results of co-optimization, but had great influence on the results of synergy-optimization. Considering the tax credit of CO2 stored can obtain higher NPV due to balance out some of the operating cost. Synergy-optimization can approximately obtain partial optimization results of co-optimization when different weight of index is considered.

Uncertainty effect of CO2 molecular diffusion on oil recovery and gas storage in underground formations

CO2 molecular diffusion in underground reservoir fluids, quantified by diffusion (D) coefficient, is of great importance for CO2 storage and enhanced oil recovery (EOR) projects. The reported CO2 D coefficients values are uncertain due to difficulty of accurately measuring this parameter specifically at high pressure-high temperature conditions. Hence, this study aims to investigate the impact of the uncertainty in the value of CO2 D coefficient on both oil recovery and CO2 storage during intermittent CO2 assisted gravity drainage (CO2-GAGD) injection in oil reservoirs. The impact of the CO2 diffusion on oil compositional changes and fluid distribution in porous medium was also investigated here. To do so, using data from a Malaysian oil field, a tuned equation of state along with a composition simulation model were used to emphasis on the effect of diffusion during the intermittent CO2-GAGD process. The effects of reservoir permeability, reservoir porosity, injection rate, and soaking time on oil recovery and gas storage were tested across different values of CO2 D coefficient. Including the gas diffusion in the simulation resulted in enhancement of the gas penetration though the porous medium leading to the enhanced oil recovery especially at the final soaking-injection/production cycles of the intermitted CO2 injection. The lowest impact of the uncertainty in the CO2 D coefficient on the oil recovery and gas storage efficiency was found in the high permeability case. Additionally, decreasing the gas injection rate or increasing the soaking time magnified the impact of the uncertainty of the CO2 D coefficient. Furthermore, the CO2 storage efficiency was found to be highly sensitive to the changes in the D coefficient in the high porosity case. To verify the results, the obtained simulation results were compared and found to be consistent with previous findings reported in the literature. This study adds accuracy to predicting CO2 EOR and storage projects through understanding the uncertainty of molecular diffusivity.

Pegging input prices to output prices—A special price adjustment clause in long-term CO[formula omitted] sales contracts

Oil firms that apply the technique of CO2-enhanced oil recovery inject CO2 into oil reservoirs to increase oil production. The long-term CO2 sales contracts commonly used in the industry often include a special price adjustment clause—the CO2 price is pegged to the oil price faced by the buyer. This is quite different from typical price adjustment clauses in other long-term contracts, which peg the contract price to input costs faced by the supplier. Using a stylized model, we identify plausible conditions under which the pegging practice adopted in the CO2 market is optimal. Numerical simulations calibrated to an active CO2-enhanced oil recovery project suggest that the optimal pegging rate is sensitive to the anticipated oil price level, but not to the oil price variance around that level. The optimal pegging rate is sensitive also to a given oil project’s CO2 “utilization efficiency” – the amount of CO2 required to produce an additional barrel of oil – which is both highly variable across projects and uncertain up front.

Modeling Evaluates CO2 EOR, Storage Potential in Depleted Reservoirs

This article, written by JPT Technology Editor Judy Feder, contains highlights of paper SPE 200560, “CO2-EOR and Storage Potentials in Depleted Reservoirs in the Norwegian Continental Shelf,” by Elhans Imanovs, SPE, and Samuel Krevor, SPE, Imperial College London, and Ali Mojaddam Zadeh, Equinor, prepared for the 2020 SPE Europec featured at the 82nd EAGE Conference and Exhibition, originally scheduled to be held in Amsterdam, 8–11 June. The paper has not been peer reviewed. A combination of carbon dioxide (CO2) enhanced oil recovery (EOR) and storage schemes could offer an opportunity to produce additional oil from depleted reservoirs and permanently store CO2 in the subsurface in an economically efficient manner. The complete paper evaluates the effect of different injection methods on oil recovery and CO2 storage potential in a depleted sandstone reservoir in the Norwegian Continental Shelf (NCS). The methods include continuous gas injection (CGI), continuous water injection (CWI), water alternating gas (WAG), tapered WAG (TWAG), simultaneous water above gas coinjection (SWGCO), simultaneous water and gas injection (SWGI), and cyclic SWGI. CO2 EOR and Storage in the NCS In recent years, the number of newly explored fields in the NCS has decreased. Approximately 47% of total resources in the NCS have been produced, and approximately 20% of resources are estimated as recoverable reserves. To fill in the gap between energy demand and recoverable reserves, EOR methods could be employed. One of the most efficient EOR methods is CO2 injection, because complete microscopic sweep efficiency can be achieved, leading to a total depletion of the reservoir. The three major types of CO2 EOR processes—miscible, near-miscible, and immiscible—are described and discussed in the full paper. Four primary CO2-trapping mechanisms are used in the subsurface: structural/stratigraphic, solubility, residual, and mineral trapping. The main locations for underground geological storage are depleted oil and gas reservoirs, coal formations, and saline aquifers. Currently, underground CO2 storage is believed to be a major technology to dramatically reduce CO2 amounts in the atmosphere. According to the International Energy Agency, 54 major oil basins around the world have the potential to produce 75 Bsm3 of additional oil and store 140 Gt of CO2. CO2 EOR and storage projects in the NCS could have several benefits. First, surface and subsea facility availability in the NCS region reduces capital expenditures. Second, in addition to the revenue from extra oil production, carbon credits could be awarded for the CO2 storage. The main challenges of CO2 EOR and storage offshore projects are high operational and capital expenditures. In depleted reservoirs, these include modification of offshore platform materials; additional power supply for CO2 compression and recycling; and replacement of the tubing because wet CO2 is highly corrosive, resulting in scale, asphaltene, and hydrates formation. Contamination of a gas cap with injected CO2 might lead to loss of hydrocarbon gas market value. Only one CO2 EOR project has been implemented offshore—the Lula field in Brazil’s Santos Basin—meaning that industry has very limited experience in such projects.

A Comprehensive Techno-eco-assessment of CO2 Enhanced Oil Recovery Projects Using a Machine-learning Assisted Workflow

Injection of CO2 gas to partially depleted oil reservoirs not only enhances hydrocarbon production but also take advances of the underground porous media for carbon storage purposes. Therefore, carbon utilization to enhanced oil recovery (EOR) projects become more and more attractive in the petroleum industry. Notably, the use of anthropogenic CO2 in EOR project could be challenging due to the capital and operational costs of carbon capture, transportation, and recycling. In the meantime, the US government offers encouraging tax policies, Section 45 Q, to oil field operators who inject a large volume of CO2 to produce oil. Thus, the project economics of the CO2-EOR project could be even more complex, especially when the oil price is low at this time. In this article, a robust machine-learning assisted CO2-EOR project optimization and design protocol is presented. The workflow aims at simultaneously optimizing the hydrocarbon recovery, carbon storage volume and project economics using a Pareto-front-based multiple-objective optimization (MOO) scheme. A solution repository containing various optimized development strategies will be structured. Moreover, the proposed workflow will investigate the project economics of the solutions by systematically considering impactive factors such as tax credits, project capital costs, oil prices, etc., and provide comprehensive recommendations to the field operators for decision-making purposes. This work employs data collected from the Farnsworth unit (FWU) in west Texas, US, as a field case to demonstrate the workflow. FWU is characterized as partially depleted oil sands undergoing water-alternative-CO2 (CO2-WAG) injection processes. A compositional numerical reservoir simulation model is established to investigate the fluid transportations dynamic of FWU. The numerical model is validated via a rigorous history-matching study using 55-year of primary and secondary (water flooding) recovery data, and 8-year of ternary recovery (CO2-WAG) data. It is worth emphasizing that the history-matched model successfully incorporates eight relative permeability curves to various spatial regions of the field. Such relative permeability curves are measured via laboratory investigations using representative core samples collected from the fields (hydraulic flow units). The history matched numerical model can be used to forecast the hydrocarbon production and CO2 storage volume using different CO2-WAG designs. In order to obtain finer optimization solutions, the field operational parameters, such as water injection rate, gas injection period, water injection periods, production well specifications, etc. of each individual well are considered as control parameters. In this way, the field operators can get detailed guidance to operate each individual well. However, the imposing of MOO requires computationally intensive procedures by totally relying on the high-fidelity numerical simulator, which engages the motivation to employ machine-learning-based proxies in the workflow. In this work, supported vector machine regression (SVR) combined with the Gaussian kernel is utilized to mimic the high-fidelity numerical model. The hyper-parameters of the SVR are optimized using Bayesian Optimization to achieve a better generalization performance. The SVR couples with Multi-objective Particle Swarm Optimization (MOPSO) protocol to structure the Pareto-front solution repository. To further eliminate the uncertainties introduced by the proxy error margins, a self-adapting scheme is integrated into the workflow to justify the Pareto-front solutions. This scheme will automatically add new sampling data to the training dataset for surrogate model development, making the optimization results more correct. Furthermore, this paper will carry comprehensive techno-eco-assessments of the optimized solutions considering the vital economic factors including the carbon capture and transporting costs, field operational cost, tax credits, oil price, etc. With the help of the proxy models, fast uncertainty analysis can be conducted to obtain stochastic results of the project net present value, rate of return and payback period. Field operators can make their decisions to design CO2-WAG projects based on both technical and economical perspectives.

Application of CO2 injection monitoring techniques for CO2 EOR and associated geologic storage

The Energy & Environmental Research Center (EERC), through its efforts leading the Plains CO2 Reduction (PCOR) Partnership, has successfully developed practices and technologies that can be used in future commercial-scale CO2 storage projects in different geologic formations, including both dedicated CO2 storage in saline formations and associated CO2 storage incidental to enhanced oil recovery (EOR). In this work, reservoir monitoring activities have been conducted in a large-scale CO2 EOR project to understand performance and associated storage. The activities include pulsed-neutron well logs (PNLs), 4D (time-lapse 3D) seismic surveys, and numerical simulation of injection and production. This enabled monitoring at different scales, from individual wells to field-scale reservoir assessments. The oil, water, and CO2 saturations were profiled to identify bypassed oil and high-conductivity CO2 migration pathways in the reservoir. These techniques provided actionable information, enabling better management of CO2 flooding, diagnosing performance and sweep efficiency while ensuring injected CO2 remained within the reservoir.

Explicit tracking of CO2-flow at the core scale using micro-Positron Emission Tomography (μPET)

Safe subsurface sequestration of carbon dioxide (CO2) is becoming increasingly important to meet climate goals and curb atmospheric CO2 concentrations. The world-wide CO2 storage capacity in carbonate formations is significant; within deep, saline aquifers and through several CO2-enhanced oil recovery projects, with associated CO2 storage. Carbonates are complex, both in terms of heterogeneity and reactivity, and improved core scale and sub core-scale analysis of CO2 flow phenomena is necessary input to simulators, aiming to establish large-scale behavior. This paper presents a recent advancement in in-situ imaging of CO2 flow, utilizing high-resolution micro-Positron Emission Tomography and radioactive tracer [11C]arbon dioxide to explicitly track CO2 during dynamic flow and subsequent trapping at the core scale. Unsteady state water injection (imbibition) and CO2 injection (drainage) were performed in a low-permeable chalk core at elevated pressure conditions. Short-lived radioisotopes were used to label water and CO2, respectively, and facilitated explicit tracking of each phase separately during single phase injection. Local flow patterns and dynamic spatial fluid saturations were determined from in-situ imaging during each experimental step. Initial miscible displacement revealed displacement heterogeneities in the chalk core, and dynamic image data was used to disclose and quantify local permeability variations. Radial permeability variations influenced subsequent flow patterns, where CO2 predominantly flooded the higher-permeability outer part of the core, leaving a higher water saturation in the inner core volume. Injection of water after CO2 flooding is proposed to be the most rapid and effective way to ensure safe storage, by promoting capillary trapping of CO2. PET imaging showed that presence of CO2 reduced the flow of water in higher-permeability areas, improving sweep efficiency and promoting a nearly ideal core-scale displacement. Alternate injections of water and gas is also expected to improve sweep efficiency and contribute to improved oil recovery and CO2 storage on larger scales. Sub-core analysis showed that residually trapped CO2 was evenly distributed in the chalk core, occupying 40% of the pore volume after ended water injection. Micro-Positron Emission Tomography yielded excellent small-scale resolution of both water and CO2 flow, and may contribute to unlocking fluid flow dynamics and determining mechanisms on the millimeter scale; presenting a unique opportunity in experimental core-scale evaluations of CO2 storage and security.

On the sustainability of CO2 storage through CO2 – Enhanced oil recovery

This work uses pilot examples of CO2 enhanced oil recovery to analyze whether and under which circumstances it is exergetically favorable to sequester CO2 through enhanced oil recovery. We find that the net storage efficiency (ratio between the stored and captured CO2) of the carbon capture and storage (CCS)-only projects is maximally 6–56% depending on the fuel used in the power plants. With the current state of technology, the CCS process will re-emit a minimum of 0.43–0.94 kg of CO2 per kg of CO2 stored. From thermodynamics point of view, CO2 enhanced oil recovery (EOR) with CCS option is not sustainable, i.e., during the life cycle of the process more energy is consumed than the energy produced from oil. For the CCS to be efficient in reducing CO2 levels (1) the exergetic cost of CO2 separation from flue gas should be reduced, and/or (2) the capture process should not lead to additional carbon emission. Furthermore, we find that the exergy recovery factor of CO2-EOR depends on the CO2 utilization factor, which is currently in the low range of 2–4 bbl/tCO2 based on the field data. Exergetically, CO2 EOR with storage option produces 30–40% less exergy compared to conventional CO2 enhanced oil recovery projects with CO2 supplied from natural sources; however, this leads to storage of >400 kg of extra CO2 per barrel of oil produced.

Phase behavior and fluid interactions of a CO2-Light oil system at high pressures and temperatures

This paper investigates the phase behavior and mutual interactions between a light crude oil and CO2 at high pressures and high temperatures (HPHT). To do so, we have measured PVT properties of the CO2-oil system at HPHT using a PVT setup. We have also tried to present a detailed methodology for measuring PVT properties of CO2-oil systems and highlight the difficulties such as oil vaporization by CO2 during the experiments. A crude oil sample, collected from a Malaysian oil field, was used here. Our experiments indicated that, CO2 solubility in the oil increased at higher pressures when measured at a fixed temperature. Our experiments also showed that increasing the test temperature would reduce CO2 solubility in the oil, while its effect is more significant at higher pressures. The swelling factor (SF) measurements showed an increasing trend with pressure up to a certain value so-called extraction pressure, at which, the SF started to be reduced even became less than one. The measurements of oil viscosity indicated that CO2 dissolution in the oil sample could reduce the mixture viscosity up to 61%. The interfacial tensions between CO2 and the crude oil at different pressures were also measured while the results were used to estimate the minimum miscibility pressure (MMP) and the first contact miscibility (FCM) pressure. The IFT measurements at various pressures displayed a reduction trend as a result of more CO2 dissolution in the oil but with two different slopes. That is, at lower pressure values, the measured IFTs were sharply reduced with pressure, while the reduction rate of the IFT became less when pressures exceeded the extraction pressure. This study helps with determining the optimum pressure and temperature conditions of CO2-oil systems to have a minimum IFT, a maximum CO2 solubility and SF, and a minimum oil viscosity that are favorable for CO2-enhanced oil recovery projects. Additionally, the methodology presented here gives guidelines on how to design PVT experiments of CO2-oil systems for petroleum and chemical engineering applications.

CO2 Sequestration-EOR in a Tight Oil Reservoir: Estimation of Dynamic CO2 Storage Capacity Using a Two-Stage Well Test

Evaluation of an accurate CO2 dynamic storage capacity, ultimate recycled CO2 and enhanced oil recovery (EOR) are key factors for a successful CO2 EOR project. The Yanchang Petroleum Company (YP)’s low permeability oil field is located at Ordos Basin - China with a very short and inefficient primary and secondary oil recovery and, therefore, YP proposed CO2 EOR as a potential tertiary oil recovery approach. In this work, the Wuqi reservoir in the Yanchang field is selected to evaluate the feasibility of full-field CO2 sequestration-EOR. The Wuqi reservoir has been in production for over a decade with historical data that can be used for a history matching process. To acquire essential dynamic data for evaluation of the CO2 injectivity/dynamic storage capacity, a specific two-stage pilot well test is proposed to inject first water and then CO2. It will provide relatively accurate calculated permeability for water (test phase 1) and CO2 (test phase 2) at the injection well. Also, the test will qualitatively estimate the location of water and CO2 fronts in the reservoir over time. Using two monitoring wells simultaneously, significantly increases the radius of investigation (ROI) that can be achieved for a given injection scenario and will also describe directional heterogeneity in the reservoir. When informed by the pilot test data, the model can be used to estimate the CO2 injection rate, ultimate cumulative CO2 injection and oil production and CO2 injection well numbers over 15 years of CO2 sequestration-EOR, which can be utilised for further techno-economic analysis of the project.

DDR-type zeolite membrane: A novel CO2 separation technology for enhanced oil recovery

JGC Corporation (JGC) and NGK Insulators, Ltd. (NGK) have been developing the world’s largest DDR-type zeolite membrane to meet the practical needs of CO2/hydrocarbon separation in the natural gas and CO2 Enhanced Oil Recovery (CO2-EOR) industries.DDR-type zeolite has desirable nano-size pores for CO2/hydrocarbon separation. NGK has developed a thin, defect-free DDR-type zeolite membrane with a monolithic structure. This membrane is prepared onto the inner surface of a cylindrical monolithic alumina substrate having 30 channels with a diameter and length of 30 mm and 160 mm, respectively. CO2 permselectivity over CH4 of the monolithic membrane was investigated using the binary gas mixture of 61–67 mol% CO2 and 33–39 mol% CH4 at 44–46 °C with up to 8.0 MPa G as the feed pressure. The CO2 permeability reached 1973 Barrer (6.6 × 10−13 mol m m−2 s−1 Pa−1) while the separation factor of CO2/CH4 exceeded 140 at the transmembrane pressure difference of 2.5 MPa. This CO2 permeability decreased to 1154 Barrer (3.9 × 10−13 mol m m−2 s−1 Pa−1) at the transmembrane pressure difference of 7.0 MPa; however, the separation factor of CO2/CH4 was still as high as 90. In order to understand the stability of the monolithic membrane, the change in the permeability of CO2 and CH4 with time was measured at 58–60 °C with transmembrane pressure difference of 7.4–7.7 MPa using the binary gas mixture of 65–71 mol% CO2 and 29–35 mol% CH4 for 140 h. During the gas permeation test, the CO2 permeability was almost constant while CH4 permeability slightly decreased. As a result, the separation factor of CO2/CH4 was maintained at the initial value.Based on the experimental results, we evaluated the potential applicability of the DDR-type zeolite membrane compared to the conventional polymer membrane for a CO2 recovery process in a CO2-EOR project where CO2 is often separated from the associated gas for re-use. We assumed that the associated gas contains 70 mol% CO2 and 30 mol% CH4 at a pressure of 4.0 MPa G while the specification of CO2 purity in the permeate gas was 95 mol% at a pressure of 0.3 MPa G. When this associated gas is treated using a single-stage membrane process, only 49% of CO2 was recovered by a membrane having a CO2/CH4 separation factor of 12.5 like a typical polymer membrane. On the other hand, membranes having CO2/CH4 separation factors of 80–100 could recover 98–99% of CO2 while more than 96 mol% purity of CH4 was obtained at the retentate side. This simulation study indicated that the highly selective membrane like the DDR-type zeolite membrane can recover not only high purity CO2 for CO2-EOR projects, but also make available CH4 for use or sale. This high purity CH4 brings additional benefit to the CO2-EOR operators.

Revival of mature onshore oil field in U.S.

During planning stage of CO2 EOR （enhanced oil recovery）, evaluation of remaining oil volume is one of the most important works because of its significant impact on field performance and project economics. However, the evaluation becomes very challenging when the concerned field is a legacy field where historical data are insufficient unless reliable data were later supplemented. We describe how to evaluate CO2 EOR project for a legacy field with insufficient historical data.

Soil gas investigation of an alleged gas migration issue on a residential farm located above the Weyburn-Midale CO2 enhanced oil recovery project

Stable (13C) and radiogenic (14C) carbon isotope tracers are recognized approaches to identify gas sources using soil gas monitoring techniques; however, definitive characterization from a subsurface injection/storage reservoir can be complicated by processes that produce and consume CO2. Few studies assess the combined use of compositional (fixed gases, hydrocarbons, and sulphurous compounds) and isotopic (13C, 18O and 14C) indicators from soil gases as tools to evaluate CO2 storage reservoir leaks. Compositional and isotopic indicators from soil gases were compared at an investigation site (IS) alleged to be impacted by CO2 leaking from an underlying injection reservoir with a baseline control site (BCS) outside of the injection area. Soil gas δ13CCO2 values collected from the IS (−23.4‰to −22.6‰) were comparable with the range observed at the BCS (−22.8‰ and −23.3‰), falling within the range anticipated for both biogenic and injected CO2. 14C values were also comparable between IS (98.0 pMC to 107.0 pMC) and BCS (102.8 pMC to 105.3 pMC) sites, representing a modern carbon source that was distinct from the CO2 injection gas (0.34 pMC). The results provide several lines of evidence that CO2 fluxes in soil gases at the IS were related to naturally occurring processes and were not caused by a gas migration issue from a geological CO2 storage reservoir.