Carbon Dioxide Injection Research Articles

The Response Characteristics of Pore Volume and Specific Surface Area of Different Phases of Carbon Dioxide Injection into Anthracite Coal Pores

After the coal sample reacts with CO2, the porosity and pore volume change. Compared with dry raw coal sample, the porosity of coal after CO2 adsorption is increased. With the increase of CO2 injection pressure, the porosity of coal will gradually increase, especially when CO2 enters the supercritical phase. In terms of pore capacity of coal samples, CO2 adsorption time, CO2 adsorption pressure and CO2-H2O treatment do not show obvious regularity in the changes of pore capacity of coal samples, but in general, the increase of CO2 adsorption pressure and CO2-H2O treatment have a positive effect on the increase of pore capacity of coal samples, especially ScCO2-H2O. The mesoporous pore capacity increased by 137.1%. In terms of macro pore volume of coal sample, the change of macro pore volume after CO2 adsorption is more regular. Extending CO2 adsorption time, increasing CO2 adsorption pressure and CO2-H2O treatment all have positive effects on the increase of macro pore volume of coal sample. Under 8MPaScCO2-H2O, macro pore volume reaches a maximum of 0.016462ml/g. The increase also reached 130.4 percent. On the mesoporous specific surface area of coal sample, increasing CO2 adsorption pressure, prolongating CO2 adsorption time and CO2-H2O treatment can increase the mesoporous specific surface area of the sample. The mesoporous specific surface area of the sample at 8 MPa ScCO2-H2O is 0.631 m2/g, which reaches the maximum in this experiment, with an increase of 334.27%.

Brownfield modifications to convert existing gas production facilities for CCS operations

In recent years, traditional oil and gas operators have found novel means of extending the life of their assets and deferring onerous decommissioning costs by converting their facilities from gas production into carbon dioxide (CO2) injection. While the task of designing for CO2 may sound simple, CO2 injection works in counter-intuitive ways, with previously established heuristics derived from years of experience in gas condensate systems being quickly challenged as potentially dangerous. The world of designing CO2 systems is back-to-front compared with hydrocarbons; it isn’t simply a case of a change in flow direction. Some of the design challenges explored in this paper include: large density variability in CO2 systems where a small change in the ambient temperature can significantly impact the pressure of a shut-in system; optimal pressure ratings of the vents and drains systems and how previous safety margins may be unsafe; pipeline hydraulic modelling focussed on new areas outside of the traditional suite of analysis, such as assurance of the supercritical phase; understanding liquid water dropout being more of a concern than hydrate formation; injection wells counter-intuitively flowing from low pressure to high pressure; whether to vent CO2 above or below an offshore platform; and optimal liquefied CO2 storage vessel conditions and safeguarding.

Predicting ground surface deformation induced from CO2 plume movement using machine learning

Carbon capture and storage (CCS), which involves injecting carbon dioxide (CO2) into subsurface, is an increasingly popular process for mitigating human caused greenhouse gas emissions. In order to ensure the safety and efficacy of CCS implementation, it is necessary to possess a comprehensive understanding of the complex behaviour of CO2 plumes within geological formations and their potential impact on ground surface deformation. Therefore, conducting research and analysis on these critical aspects is of vital importance. This research provides a methodology to anticipate ground surface deformations, which result from the motion of CO2 plumes utilising an advanced machine learning (ML) technique. The ML surrogate model has been developed using conditional Generative Adversarial Networks (cGAN). The dataset used for the model training and testing comprises ground surface measurements (tiltmeters), reservoir properties, as well as pressure/volume data. The model has been trained and tested using a set of samples created using a forward finite element model. Results show that the surrogate model is capable of predicting reasonably accurate results while running much faster than the forward model.

Implementation of a novel EOR screening methodology to the oilfields in Türkiye

In response to growing energy demand of Türkiye, an enhanced oil recovery (EOR) applicability assessment was conducted through an improved screening methodology, calibrated with successful applications. The methodology incorporated some improvements in applicability ranges and a novel pointing system. 159 oilfields in Türkiye were characterized based on reservoir properties and categorized as heavy, weak and strong aquifer support. The characterization revealed how source rock type and regional paleo-tectonic events dictate primary recovery and need for EOR. The EOR assessment implemented promised 58 applicable cases out of 315. Carbon dioxide (CO2) injection is applicable for many fields, which could stimulate feasibility of carbon capture projects in the country. Immiscible nitrogen injection might be an alternative for many of the medium and light oil reservoirs in the absence of CO2. Polymer flooding is also promising mainly for fields having weak-aquifer support. However, our hands-on experience suggests that conformance control is required to control flow of EOR agent in densely fractured carbonates. Thermal methods do not seem applicable in heavy oil reservoirs due to depth limitations except in-situ combustion, which requires pilot test confirmation. Provided methodology in this study may be used as a guideline for other fields to assess EOR potential.

Investigation on a mobile fire extinguishing approach using liquid carbon dioxide as inert medium for underground mine.

Injecting carbon dioxide is the most effective means of preventing and extinguishing fires in sealing hazardous areas, but the traditional method slowly and remotely injects carbon dioxide gas into the well after gasification on the ground, which is dependent on the complete mine pipe network without cooling effect. To inject liquid directly from the tank with vacuum interlayer and heat insulating powder for rapid inerting and cooling, a new approach using track mobile platform to go deep into the underground mine disaster area is proposed, so the liquid can be delivered to the nozzle at the end of DN40 large diameter pipe, and the continuous gasification jet can be realized. The experimental results show that: (1) The liquid volume in a tank of vacuum degree within 2.0 Pa and 200 mm interlayer reduced no more than 15.5% after 48 days; (2) Taking the pressure in the tank as the power source, because of environmental differences inside and outside the pipe after 100 m pressure holding delivery, the physical form of liquid and gas could be converted instantly; (3) The continuous discharge time without ice blocking for a tank full of 2 m3 liquid was about 10.5 min under 25 L dual mode nitrogen pressurization, which is 1/12 of injection time after ground gasification; (4) Based on the temperature decrease trend measured at different positions, the cooling characteristics on liquid gasification jet path are quantified, and the calculation formula of temperature changing with time on the center line of liquid gasification jet is obtained. Through this new approach, the integration of vacuum insulated storage, safe mobile transportation, and continuous and rapid release with large flow can be achieved for the liquid carbon dioxide.

A new approach to calculate CO2 displacement recovery considering near miscibility in tight oil reservoirs

Near miscibility widely exists in carbon dioxide (CO2) injection development projects. However, there is no existing approach to quantify the effect of near miscibility on oil recovery. In this paper, slim tube experiments were conducted to study near miscible region. The oil displacement efficiency curve is divided into immiscibility, near miscibility and miscibility. And three linear function is obtained, respectively. Then, the space between production well and CO2 injection well is discrete to characterize the effect of near miscibility on oil recovery. Then, a new approach is proposed to calculate oil recovery of CO2 displacement in tight oil reservoirs. This approach can calculate oil recovery considering near miscibility. It is found that minimum miscibility pressure (MMP) without considering near miscibility is 4 MPa lower than considering near miscibility. The near miscible pressure range is from 0.77 times to 1 time MMP considering near miscibility. Oil displacement efficiency difference reaches to be the maximum when the pressure is the minimum miscibility pressure without considering near miscibility. The maximum of the oil displacement efficiency difference is 3.4%. The optimal formation pressure considering near miscibility is 5 MPa larger than that without considering near miscibility. The oil recovery considering near miscibility is from 0.9 to 1.3% lower than that not considering near miscibility. It reaches to be the maximum when the pressure is the optimal formation pressure level without considering near miscibility. The maximum of the oil recovery difference is 1.3%.

Predicting asphaltene precipitation in CO2 flooding processes using artificial intelligence techniques

The removal of asphaltene depositions from crude oil wellbores and tubing is a very difficult and expensive process. Therefore, a very accurate predictor for the Asphaltene Precipitation (AP) is a very important tool for decision making. In this paper, the AP during the injection of carbon dioxide into crude oil reservoirs is forecasted using an artificial neural network (ANN). For this purpose, experimental data is collected from six different oil fields. 70% of the collected data is utilized for training and to develop the proposed ANN. Trainlm training algorithm was found to be the best ANN architecture for AP forecasting. In order to validate the capability of the designed ANN 30% of the unseen data is utilized for validation. The forecasting results show the Mean Square Error (MSE) of the forecasting is 0.0018 that confirms the high accuracy of the model. In order to evaluate the capability of the proposed methodology, the results of proposed ANN are compared with modified Hirschberg model. Comparison confirmed the proposed ANN has better capability and higher accuracy. In the final stage, the effects of various operating parameters on the AP during gas injection are examined. The results show that the most sensitive parameter is the reservoir temperature. In addition, there is a high correlation between an increase in the AP with an increase in carbon dioxide concentration in liquid phase.

Mechanical integrity of tubular elements based on strength and fracture criteria during transient CO2 injection

Geological carbon sequestration (GCS) is an essential technology for reducing carbon emissions. Wellbore integrity is crucial to ensure the safety of GCS. During low-temperature carbon dioxide (CO2) injection, the wellbore temperature decreases, causing the tubing and casing to contract, resulting in considerable axial tensile stresses, and making mechanical failure likely. This paper establishes a transient flow model for CO2 injection to predict the temperature and pressure distribution in the wellbore. Then, the strength safety factor of the tubing and casing is calculated using the material strength criteria. Fracture mechanics theory is employed to analyze the risk of crack propagation in defective tubing or casing during CO2 injection. The study indicates that the wellbore temperature near the wellhead is lower as CO2 is injected. Under typical injection conditions, the tubing and casing have high strength safety factors but small crack propagation factors. The stress intensity factor of cracks on the tubing and casing's outer surface is more significant than inner surface defects, posing a higher risk of crack propagation. When the tubing or casing exits a penetrating crack, its propagation safety factor is less than 1, necessitating the avoidance of through-wall cracks. The results guide maintaining wellbore integrity in carbon dioxide geological sequestration engineering.

Study on the Influence of Supercritical CO2 with High Temperature and Pressure on Pore-Throat Structure and Minerals of Shale.

Injection of carbon dioxide offers substantial social and economic advantages for reduction of carbon emission reduction. Utilizing CO2 in shale formations can significantly enhance the extraction of shale oil or gas. Conducting fundamental research on how CO2 affects shale rock's physical properties is crucial for enhancing its porosity and permeability. Particularly for deep shale layers, the effects of supercritical CO2 on shale physical properties should be investigated at a high temperature and pressure, differing from the standard conditions applied in shallower layers. A study examined the impact of supercritical CO2 under such conditions on the pore-throat structure and mineral composition of the shale. The experimental parameters included immersing shale rock in supercritical CO2 at pressures ranging from 10 to 70 MPa and temperatures between 55 and 95 °C. This study evaluated changes in mineral composition, pore-throat structure (using scanning electron microscopy and nitrogen adsorption tests), and the porosity and permeability of the shale rocks. Findings indicated that the dissolution of CO2 altered the relative content of certain minerals. The average quartz content rose and, potassium feldspar and the average contents of plagioclase declined conversely. When increasing the pressure, an increase in the relative content of I/S mixed layer and a decrease in illite content were observed and kaolinite content experienced minor changes. When increasing the temperature, kaolinite, I/S mixed layer, and chlorite all exhibited a decreasing trend with increasing temperature, while the relative contents of illite increased. Some of the pores become rounded in a high-magnification view under the impact of CO2 dissolution. Additionally, the Brunauer-Emmett-Teller specific surface area, pore volume, porosity, and permeability generally improved with increasing pressure and temperature. With the temperature and pressure of CO2 increased, the curves of nitrogen absorption had moved first upward and then downward. However, under specific CO2 conditions, the permeability enhancement effect could diminish or even negatively impact the shale's permeability. These findings underscore the need to optimize supercritical CO2 injection parameters under high-temperature and high-pressure conditions. This research aims to provide theoretical guidance for the efficient use of CO2 in deep shale applications to increase the shale gas output.

Compositional Simulation for Carbon Storage in Porous Media Using an Electrolyte Association Equation of State

Summary We present a new algorithm based on automatic differentiation that enables precise computation of the derivatives of the Z-factor, facilitating the utilization of Newton’s method or coupling with a robust flow solver. Leveraging a free open-source code [MATLAB Reservoir Simulation Toolbox (MRST)], we develop an electrolyte cubic plus association (e-CPA) equation of state (EoS) model to accurately represent the injection of carbon dioxide (CO2) in brine. By integrating flow and thermodynamics, we construct an advanced compositional simulator using MRST’s object-oriented, automatic differentiation framework and the newly developed e-CPA EoS model. This simulator offers flexibility through both overall-composition and natural-variable formulations, achieved by selecting different primary variables. The Péneloux volume translation technique is employed to modify the EoS model’s volume, ensuring accurate density calculation for the mixture. Additionally, we introduce a viscosity model, e-CPA-FV, which accurately predicts the viscosity of carbon capture and storage (CCS) fluids, surpassing the accuracy of the traditional Lohrenz-Bray-Clark (LBC) model. Our simulator demonstrates superior performance in predicting CO2-brine systems compared with the standard formulation based on the Peng-Robinson (PR) EoS and can handle brine with various salts. The self-contained source code necessary to reproduce all examples is available on the open-access Zenodo digital repository (doi: 10.5281/zenodo.10691505).

Exploring pore-scale production characteristics of oil shale after CO2 huff ‘n’ puff in fractured shale with varied permeability

Recent studies have indicated that the injection of carbon dioxide (CO2) can lead to increased oil recovery in fractured shale reservoirs following natural depletion. Despite advancements in understanding mass exchange processes in subsurface formations, there remains a knowledge gap concerning the disparities in these processes between the matrix and fractures at the pore scale in formations with varying permeability. This study aims to experimentally investigate the CO2 diffusion behaviors and in situ oil recovery through a CO2 huff ‘n’ puff process in the Jimsar shale oil reservoir. To achieve this, we designed three matrix-fracture models with different permeabilities (0.074 mD, 0.170 mD, and 0.466 mD) and experimented at 30 MPa and 91 °C. The oil concentration in both the matrix and fracture was monitored using a low-field nuclear magnetic resonance (LF-NMR) technique to quantify in situ oil recovery and elucidate mass-exchange behaviors. The results showed that after three cycles of CO2 huff ‘n’ puff, the total recovery degree increased from 30.28% to 34.95% as the matrix permeability of the core samples increased from 0.074 to 0.466 mD, indicating a positive correlation between CO2 extraction efficiency and matrix permeability. Under similar fracture conditions, the increase in matrix permeability further promoted CO2 extraction efficiency during CO2 huff ‘n’ puff. Specifically, the increase in matrix permeability of the core had the greatest effect on the extraction of the first-cycle injection in large pores, which increased from 16.42% to 36.64%. The findings from our research provide valuable insights into the CO2 huff ‘n’ puff effects in different pore sizes following fracturing under varying permeability conditions, shedding light on the mechanisms of CO2-enhanced oil recovery in fractured shale oil reservoirs.

Rock structural changes monitored by fibre Bragg Grating sensors and Nuclear magnetic Resonance during static and dynamic carbonated brine core flooding experiments

One proposed solution to reduce greenhouse gas emissions is the capture and storage of carbon dioxide (CCS) in geological formations such as depleted oil and gas reservoirs. Injected carbon dioxide (CO2) forms carbonic acid once dissolved in the formation water, which can lead to dissolution of certain types of rock minerals. This may weaken rock geomechanical properties that can jeopardize the safety of long-term storage. In this work, the use of Fibre Bragg Grating (FBG) sensors associated with Nuclear Magnetic Resonance (NMR) was investigated to measure the change in rock strain during core flooding experiments. Optical fibres were glued onto two synthetically calcite cemented sandstone rock samples (called CIPS). The samples were saturated with dead brine followed by live brine.The FBG sensors accurately monitored a change of approximately −30 µstrain during dead brine migration at a fast rate within 10–20 min, and then the FBG strain became constant when the sample reached 100% saturation. Exposing the CIPS to live brine induced up to −1000 µstrain in a dynamic injection exercise and – 250 µstrain in the static condition, these changes occurred after 5 h exposure, which was interpreted as the result of fluid-rock interactions occurred within the sample. Those changes continued to increase over the next 35 h, albeit at lower rate. The NMR T2, spatial T2 and FBG data confirmed structural changes within the rock samples. X-ray Computer Tomography (CT) imaging also supported the structural change at certain locations in the sample while featuring good agreement with FBG results.Overall, FBG sensing technology associated with NMR can accurately measure the changes in rock strain during core flooding experiments, while allowing it to monitor the reservoir’s geo-mechanical strength which is a key factor to ensure the long-term safety of CO2 storage.

Time Lapse Measurement of Reservoir’s Parameters Change due to CO2 Injection in Parigi Carbonate West Java

CO2 injection is a process that involves injecting carbon dioxide gas into various substances or environments for different purposes. This technique, also called Carbon Capture and Storage (CCS) or Carbon Capture, Utilization, and Storage (CCUS), aims to prevent or reduce carbon dioxide emissions from reaching the atmosphere as they would affect climate change and also global warming. CCUS can also use the captured carbon dioxide for various purposes, such as enhancing oil recovery, producing fuels, chemicals, or building materials, or storing it underground or underwater. In this study, we investigated the phenomena of CO2 injection in Parigi carbonate rock from West Java. Our study involved various laboratory measurements of Parigi carbonate rock, focusing on changes in porosity due to CO2 injection. The porosity changes were observed using micro images analysis from microscope time-lapse analysis, CT-Scan, and laboratory helium porosity meter. The laboratory measurements of CO2 injection in brine water showed that the pH of the water can decrease to below 5, creating an acidic environment that induces dissolution of the pore structure. We measure the effect of CO2 injection to the Parigi carbonate samples by time lapse measurement strategy. Results of the laboratory measurements showed that the porosity increased during CO2 injection and the mass of the samples decreased during the CO2 injection process. These phenomena suggest that CO2 may induce dissolution of carbonate rock. Furthermore, the changes in porosity confirm that there is a chemical reaction during CO2 injection processes in Parigi carbonate.

Surface modified single-step nanofluid for improved CO2 absorption and storage Prospects at pore-scale in micromodels: CO2 utilization for saline porous media

The utilization (absorption and areal sweep) of injected carbon dioxide (CO2) can be enhanced if a viscous and agglomeration free nanofluid is used as most of the nanoparticles (NPs) prefer to stay in bulk phase rather than adsorbing on CO2 surface. NP adsorption can be improved if non-participating NPs are surface modified with a suitable surface modifying agent e.g., triethoxy (vinyl)silane (TVS). Thus, in this study, single-step approach was used to synthesize agglomeration free TiO2 nanofluid whose surface modification was carried out in varying proportion of TVS (1–5% v/v) followed by the discussion on comparative CO2 absorption and storage performance by different tools such as DLS, IFT, Rheology, Contact-angle, and Micromodel flow. The basic nanofluid (To) showed greater CO2 absorption after surface modification as demonstrated by molality results. However, surface modification also decreased dispersion stability of surface modified nanofluids (T1, T2, and T3) and T2 was regarded as the most stable nanofluid with −64.4 mV (ζ-potential) and 153 nm (NP size). After surface modification, increase in NP size and settlement was higher for surface modified nanofluids than To, which exhibited dispersion stability of 84 d with −53.4 mV and 15 nm. Contact angle results also showed that surface modified nanofluids possess greater affinity for CO2 absorption than basic nanofluid (To). Rheological analysis was also consistent with other tests where viscosity was found dependent on both storage period and temperature, and NP settlement was found to be the most influential parameter on flow properties of nanofluid. Finally, pore scale analysis was performed to understand areal sweep of injected CO2 in micromodel with and without nanofluid, where nanofluid imparted greater CO2 storage by diverting it in un-swept pore networks of micromodel which were untapped by CO2 without nanofluid.

Experimental study of carbonate samples dissolution using X-ray microcomputer-based tomography

Background: The study of the interaction of hydrochloric acid with carbonate materialsis important in the oil and gas industry. Carbonate rocks are common rock types, and half of all petroleum reserves worldwide are found in carbonate deposits. Understanding the mechanisms and characteristics of dissolution of carbonate rocks is of great practical importance in the production of hydrocarbons and the injection of carbon dioxide into formations.
 Aim: The purpose of this article is to study the dissolution processes of carbonate samples in laboratory conditions using X-ray microcomputer-based tomography.
 Materials and methods: The study used 5 cylindrical carbonate samples, which were tested during the injection of hydrochloric acid solutions. Additional experimental and digital data from 8 samples are also used. The three-dimensional pore space of the samples was obtained using specialized software based on tomographic images.
 Results: The results obtained demonstrate the significance of the use of X-ray computed tomography for a deeper understanding of dissolution processes in geological and engineering studies. The study highlighted the complexity of the rock dissolution process, which depends on many factors. The created three-dimensional models of the samples allowed us to visualize wormholes, including branched and dominant wormholes. 3D imaging provided valuable information about changes in the pore structure of the samples before and after acid exposure.
 Conclusion: The results of this study highlight the importance of considering physical and structural properties when analyzing dissolution processes in carbonate samples. These data can have practical applications in the oil and gas industry, contributing to a more accurate understanding and optimization of the processes of interaction of acid solutions with carbonate samples.

CO2–Water–Rock Interaction and Its Influence on the Physical Properties of Continental Shale Oil Reservoirs

Shale oil resources are abundant, but reservoirs exhibit strong heterogeneity with extremely low porosity and permeability, and their development is challenging. Carbon dioxide (CO2) injection technology is crucial for efficient shale oil development. When CO2 is dissolved in reservoir formation water, it undergoes a series of physical and chemical reactions with various rock minerals present in the reservoir. These reactions not only modify the reservoir environment but also lead to precipitation that impacts the development of the oil reservoir. In this paper, the effects of water–rock interaction on core porosity and permeability during CO2 displacement are investigated by combining static and dynamic tests. The results reveal that the injection of CO2 into the core leads to reactions between CO2 and rock minerals upon dissolution in formation water. These reactions result in the formation of new minerals and the obstruction of clastic particles, thereby reducing core permeability. However, the generation of fine fractures through carbonic acid corrosion yields an increase in core permeability. The CO2–water–rock reaction is significantly influenced by the PV number, pressure, and temperature. As the injected PV number increases, the degree of pore throat plugging gradually increases. As the pressure increases, the volume of larger pore spaces gradually decreases, resulting in an increase in the degree of pore blockage. However, when the pressure exceeds 20 MPa, the degree of carbonic acid dissolution will be enhanced, resulting in the formation of small cracks and an increase in the volume of small pores. As the temperature reaches the critical point, the degree of blockage of macropores gradually increases, and the blockage of small pores also occurs, which eventually leads to a decrease in core porosity.

Experimental Study on Carbon Dioxide Flooding Technology in the Lunnan Oilfield, Tarim Basin

The Lunnan Oilfield in the Tarim Basin is known for its abundant oil and gas resources. However, the marine clastic reservoir in this oilfield poses challenges due to its tightness and difficulty in development using conventional water drive methods. To improve the recovery rate, this study focuses on the application of carbon dioxide flooding after a water drive. Indoor experiments were conducted on the formation fluids of the Lunnan Oil Formation, specifically investigating gas injection expansion, thin tube, long core displacement, oil and gas phase permeability, and solubility. By injecting carbon dioxide under the current formation pressure, the study explores the impact of varying amounts of carbon dioxide on crude oil extraction capacity, high-pressure physical parameters of crude oil, and phase characteristics of formation fluids. Additionally, the maximum dissolution capacity of carbon dioxide in formation water is analyzed under different formation temperatures and pressures. The research findings indicate that the crude oil extracted from the Lunnan Oilfield exhibits specific characteristics such as low viscosity, low freezing point, low-medium sulfur content, high wax content, and medium colloid asphaltene. The measured density of carbon dioxide under the conditions of the oil group is 0.74 g/cm3, which closely matches the density of crude oil. Additionally, the viscosity of carbon dioxide is 0.0681 mPa·s, making it well-suited for carbon dioxide flooding. With an increase in the amount of injected carbon dioxide, the saturation pressure and gas-oil ratio of the crude oil also increase. As the pressure rises, carbon dioxide dissolves rapidly into the crude oil, resulting in a gradual increase in the gas-oil ratio, expansion coefficient, and saturation pressure. As the displacement pressure decreases, the degree of carbon dioxide displacement initially decreases slowly, followed by a rapid decrease. Moreover, an increase in the injection rate of carbon dioxide pore volume leads to a rapid initial improvement in oil-displacement efficiency, followed by a slower increase. Simultaneously, the gas-oil ratio exhibits a slow increase initially, followed by a rapid rise. Furthermore, as the displacement pressure increases, the solubility of carbon dioxide in water demonstrates a linear increase. These research findings provide valuable theoretical data to support the use of carbon dioxide flooding techniques for enhancing oil recovery.

Comprehensive parametric study of CO2 sequestration in deep saline aquifers

Carbon dioxide injection in deep saline aquifers is a key method for permanently sequestering anthropogenic CO2. This study employs a reactive transport model to explore mineral precipitation/dissolution and its impact on reservoir properties in deep saline aquifers. We also assess capillary pressure and relative permeability hysteresis on various CO2 trapping mechanisms. Results from this study reveal the significant influence of initial brine composition on mineral precipitation/dissolution. The dissolution and precipitation of minerals have different effects around the wellbores compared to the overall reservoir. Additionally, salt concentration (Ca++ and Mg++) and quartz surface area affect CO2 mineralization, while Na+ impacts halite precipitation, altering reservoir flow properties. The effect of capillary pressure is significant, as including the capillary pressure in the simulation case resulted in significantly improved CO2 trapping, achieving almost total dissolution of the injected CO2 in around 300 years. This study offers novel insights into the interactions of reservoir minerals, brine properties, and the injected CO2.

On the Evaluation of Coal Strength Alteration Induced by CO2 Injection Using Advanced Black-Box and White-Box Machine Learning Algorithms

Summary The injection of carbon dioxide (CO2) into coal seams is a prominent technique that can provide carbon sequestration in addition to enhancing coalbed methane extraction. However, CO2 injection into the coal seams can alter the coal strength properties and their long-term integrity. In this work, the strength alteration of coals induced by CO2 exposure was modeled using 147 laboratory-measured unconfined compressive strength (UCS) data points and considering CO2 saturation pressure, CO2 interaction temperature, CO2 interaction time, and coal rank as input variables. Advanced white-box and black-box machine learning algorithms including Gaussian process regression (GPR) with rational quadratic kernel, extreme gradient boosting (XGBoost), categorical boosting (CatBoost), adaptive boosting decision tree (AdaBoost-DT), multivariate adaptive regression splines (MARS), K-nearest neighbor (KNN), gene expression programming (GEP), and group method of data handling (GMDH) were used in the modeling process. The results demonstrated that GPR-Rational Quadratic provided the most accurate estimates of UCS of coals having 3.53%, 3.62%, and 3.55% for the average absolute percent relative error (AAPRE) values of the train, test, and total data sets, respectively. Also, the overall determination coefficient (R2) value of 0.9979 was additional proof of the excellent accuracy of this model compared with other models. Moreover, the first mathematical correlations to estimate the change in coal strength induced by CO2 exposure were established in this work by the GMDH and GEP algorithms with acceptable accuracy. Sensitivity analysis revealed that the Spearman correlation coefficient shows the relative importance of the input parameters on the coal strength better than the Pearson correlation coefficient. Among the inputs, coal rank had the greatest influence on the coal strength (strong nonlinear relationship) based on the Spearman correlation coefficient. After that, CO2 interaction time and CO2 saturation pressure have shown relatively strong nonlinear relationships with model output, respectively. The CO2 interaction temperature had the smallest impact on coal strength alteration induced by CO2 exposure based on both Pearson and Spearman correlation coefficients. Finally, the leverage technique revealed that the laboratory database used for modeling CO2-induced strength alteration of coals was highly reliable, and the suggested GPR-Rational Quadratic model and GMDH correlation could be applied for predicting the UCS of coals exposed to CO2 with high statistical accuracy and reliability.

A One-Dimensional Convolutional Neural Network for Fast Predictions of the Oil-CO2 Minimum Miscibility Pressure in Unconventional Reservoirs

Summary Miscible carbon dioxide (CO2) injection has proven to be an effective method of recovering oil from unconventional reservoirs. An accurate and efficient procedure to calculate the oil-CO2 minimum miscibility pressure (MMP) is a crucial subroutine in the successful design of a miscible CO2 injection. However, current numerical methods for the unconventional MMP prediction are very demanding in terms of time and computational costs which result in long runtime with a reservoir simulator. This work proposes to employ a one-dimensional convolutional neural network (1D CNN) to accelerate the unconventional MMP determination process. Over 1,200 unconventional MMP data points are generated using the multiple-mixing-cell (MMC) method coupled with capillarity and confinement effects for training purposes. The data set is first standardized and then processed with principal component analysis (PCA) to avoid overfitting. The performance of the proposed model is evaluated with testing data. By applying the trained model, the unconventional MMP results are almost instantly produced and a coefficient of determination of 0.9862 is achieved with the testing data. Notably, 98.58% of predicting data points lie within 5% absolute relative error. This work demonstrates that the prediction of unconventional MMP can be significantly accelerated, compared with the numerical simulations, by the proposed well-trained deep learning model with a slight impact on the accuracy.