CO2 Injection Research Articles

Study on CO2 Injection Enhanced Oil Recovery Method and Buried Mechanism in Low Permeability Gas Reservoir

Study on CO2 Injection Enhanced Oil Recovery Method and Buried Mechanism in Low Permeability Gas Reservoir

Improved Injection Schedules of CO2 for Pohang Basin, Yeongil Bay, South Korea: Regarding Field Security and Injection Effectiveness

Abstract Yeongil bay is a basin located in Pohang, South Korea. Numerous projects and researches have been conducted for carbon capture and storage in Yeongil bay. The objectives of most of studies were shifted from enhancing injection efficiency to ensuring safety of carbon dioxide (CO2) storage after the Pohang earthquake occurrence in 2017. In this research, we present a stepwise CO2 injection scenario, which gradually increases injection rate during early stage of CO2 injection period. Furthermore, we conduct sensitivity analyses on an optimal stepwise CO2 injection scenario, based on the variations of permeability, well skin factor, and boundary condition between the storage site and aquifer. In conclusion, we can reduce the duration of CO2 injection compared to other injection scenarios which have suggested by previous studies with the same safety conditions and total amount of CO2 injected.

Study on CO2-Enhanced Oil Recovery and Storage in Near-Depleted Edge–Bottom Water Reservoirs

The geological storage of carbon dioxide (CO2) is a crucial technology for mitigating global temperature rise. Near-depleted edge–bottom water reservoirs are attractive targets for CO2 storage, as they can not only enhance oil recovery (EOR) but also provide important potential candidates for geological storage. This study investigated CO2-enhanced oil recovery and storage for a typical near-depleted edge–bottom water reservoir that had been developed for a long time with a recovery factor of 51.93%. To improve the oil recovery and CO2 storage, new production scenarios were explored. At the near-depleted stage, by comparing the four different scenarios of water injection, gas injection, water-alternating-gas injection, and bi-directional injection, the highest additional recovery of 3.62% was achieved via the bi-directional injection scenario. Increasing the injection pressure led to a higher gas–oil ratio and liquid production rate. After shifting from the near-depleted to the depleted stage, the most effective approach to improving CO2 storage capacity was to increase reservoir pressure. At 1.4 times the initial reservoir pressure, the maximum storage capacity was 6.52 × 108 m3. However, excessive pressure boosting posed potential storage and leakage risks. Therefore, lower injection rates and longer intermittent injections were expected to achieve a larger amount of long-term CO2 storage. Through the numerical simulation study, a gas injection rate of 80,000 m3/day and a schedule of 4–6 years injection with 1 year shut-in were shown to be effective for the case considered. During 31 years of CO2 injection, the percentage of dissolved CO2 increased from 5.46% to 6.23% during the near-depleted period, and to 7.76% during the depleted period. This study acts as a guide for the CO2 geological storage of typical near-depleted edge–bottom water reservoirs.

Investigation into Enhancing Methane Recovery and Sequestration Mechanism in Deep Coal Seams by CO2 Injection

Injecting CO2 into coal seams to enhance coal bed methane (ECBM) recovery has been identified as a viable method for increasing methane extraction. This process also has significant potential for sequestering large volumes of CO2, thereby reducing the concentration of greenhouse gases in the atmosphere. However, for deep coal seams where formation pressure is relatively high, there is limited research on CO2 injection into systems with higher methane adsorption equilibrium pressure. Existing studies, mostly confined to the low-pressure stage, fail to effectively reveal the impact of factors such as temperature, high-pressure CO2 injection, and coal types on enhancing the recovery and sequestration of CO2-displaced methane. Thus, this study aims to investigate the influence of temperature, pressure, and coal types on ECBM recovery and CO2 sequestration in deep coal seams. A series of CO2 core flooding tests were conducted on various coal cores, with CO2 injection pressures ranging from 8 to 18 MPa. The CO2 and methane adsorption rates, as well as methane displacement efficiency, were calculated and recorded to facilitate result interpretation. Based on the results of these physical experiments, numerical simulation was conducted to study multi-component competitive adsorption, desorption, and seepage flow under high temperature and high pressure in a deep coal seam’s horizontal well. Finally, the optimization of the total injection amount (0.7 PV) and injection pressure (approximately 15.0 MPa) was carried out for the plan of CO2 displacement of methane in a single well in the later stage.

A Prediction Method for Calculating Fracturing Initiation Pressure Considering the Modification of Rock Mechanical Parameters After CO2 Treatment

The establishment of a more realistic CO2 fracturing model serves to elucidate the intricate mechanisms underlying CO2 fracturing transformation. Additionally, it furnishes a foundational framework for devising comprehensive fracturing construction plans. However, current research has neglected to consider the influence of CO2 on rock properties during CO2 fracturing, resulting in an inability to precisely replicate the alterations in the reservoir post-CO2 injection into the formation. This disparity from the actual conditions poses a substantial limitation to the application and advancement of CO2 fracturing technology. This work integrates variations in the physical parameters of rocks after complete contact and reaction with CO2 into the numerical model of crack propagation. This comprehensive approach fully acknowledges the impact of pre-CO2 exposure on the mechanical parameters of reservoir rocks. Consequently, it authentically restores the reservoir state following CO2 injection, ensuring a more accurate representation of the post-fracturing conditions. In comparison with conventional numerical simulation methods, the approach outlined in this paper yields a reduction in the error associated with predicting fracturing pressure by 9.8%.

A rock physics modelling approach for time‐lapse monitoring and characterization of fluid–rock interactions in hydrocarbon reservoirs

AbstractOne of the research gaps is to understand the development of seismic characteristics of gas‐saturated rock along with the change in rock properties because of chemical reactions. We suggest a method to explain the change in elastic properties brought on by CO2 injection in a rock by capturing the physico‐chemical interactions observed in the laboratory in a theory of rock physics. To explain the laboratory‐measured physical characteristics and velocity of a dynamic rock–fluid system, we include a time‐dependent component in the existing cemented‐sand model. We demonstrate theoretically the rate of change of elastic moduli of the dry frame by incorporating the measured rate of change of cement due to chemical dissolution. We adapt the theory such that it can be applied to the field data and calibrate the theory using water‐saturated well log data from the Ankleshwar field, an established oil field in the Cambay basin, western India. Theoretical time‐lapse logs of velocity and density are then produced using the theory over a range of CO2 saturations, assuming cementing material in grain contacts and geochemical interactions comparable to those observed in the laboratory rock. Then, using theoretical logs, corresponding time‐lapse synthetic seismic data are produced for different saturation. These data clearly demonstrate that, for a uniform model, velocity decreases by up to 18% as CO2 saturation increases from 0% to 20% (ignoring the chemical effect), and that, for a specific saturation, say 20%, chemical effects result in a 17% decrease in velocity from the present to the end of 60 years. However, for the patchy model, velocity decreases maximum by 14% and 16% due to varying saturation and chemical reaction. Moreover, for a particular saturation of CO2, say 20%, velocity differs by 16% for different types of models. This research contributes to making strategy for CO2‐sequestration in a designated field.

Predictive combination model for CH4 separation and CO2 sequestration with CO2 injection into coal seams: VMD-STA-BiLSTM-ELM hybrid neural network modeling

In the experimental process of separating coal seam gas using the CO2 displacement method, establishing a predictive model for key variables is essential to optimize displacement parameters, increase coal seam gas recovery, and improve CO2 sequestration efficiency. Traditional modeling methods often struggle with the complex nature of industrial data and are susceptible to overfitting due to multicollinearity caused by long-term datasets. This paper presents a hybrid predictive model based on variational mode decomposition (VMD), a spatiotemporal attention mechanism (STA), a bidirectional long short-term memory network (BiLSTM), and an extreme learning machine (ELM). During the offline phase, VMD is used to decompose raw data into intrinsic mode functions (IMFs). The hidden state from the last time step of the STA-BiLSTM is then added to the original data to enrich the features for ELM training. In the online prediction phase, the outputs from the VMD-STA-BiLSTM and VMD-STA-BiLSTM-ELM models are combined using an error reciprocal method to generate the final prediction. The proposed model is validated with experimental datasets from CO2 displacement for coal seam CH4 under various conditions, as well as with N2-ECBM and CO2-ECBM engineering datasets. The results show that the hybrid model surpasses VMD-ELM, STA-BiLSTM-ELM, BiLSTM, STA-BiLSTM, ELM, TCN, and Attention-TCN models in predictive accuracy. Even in multi-step and rolling predictions, the model exhibits minimal impact from cumulative errors, maintaining accurate forecasts with strong generalization and robustness. It effectively captures feature patterns across different datasets and accurately predicts unknown data. The model shows potential for application in diverse scenarios and complex environments, offering reliable support and decision-making for the field application of CO2 displacement in coal seam CH4 separation. It is an effective and promising predictive approach to enhance coal seam gas recovery and CO2 sequestration efficiency.

TECHNOLOGICAL COMPLICATIONS (FORMATION DAMAGE) DURING CO2 INJECTION FOR ENHANCED OIL RECOVERY. PART 3. PREVENTING AND REPAIRING FORMATION DAMAGE CAUSED BY CO2 INJECTION

The article considers technological complications arising during CO2 injection for enhanced oil recovery, with a focus on the formation of asphaltenes in the pore space and their negative impact on production efficiency. Formation of asphaltene solids in the reservoir leads to an increase in the skin factor, their removal to the wells, accumulation in the wellbore and on the surface of the equipment, which reduces oil flow to the well and requires expensive remedial work. Methods of identification and monitoring of asphaltene deposits are considered. Results of laboratory studies confirming the difficulty of quantitative assessment of asphaltene deposition are given, as well as practical examples of application of various technologies for their prevention and removal. Methods including the use of inhibitors and dispersants and the use of aromatic solvents to restore reservoir properties are reviewed. It also emphasises the need for continuous monitoring of field operations and the development of effective asphaltene management methods, which is critical to improving the economic feasibility of CO2 injection projects.

Carbon dioxide hydrate formation in porous media under dynamic conditions

AbstractInjecting carbon dioxide (CO2) into subsea water zones where the in situ temperatures are below the hydrate‐forming temperature of CO2 has been recently proposed to lock CO2 inside the water zones in solid hydrate form. It is a common concern that CO2 may form hydrates during the injection period that will reduce well injectivity. CO2 injection into sandstone cores under simulated subsea temperatures of 2°C and 3°C was investigated in this study. Experimental result shows that, at 2°C temperature, flowing CO2 at Darcy velocity 0.033 cm/s begins to form hydrate in the sandstone core at about 3.06 MPa (450 psi), which is much higher than the minimum required pressure of 1.5 MPa (220 psi) for CO2 to form hydrate in static condition. The pressure ratio is 450/220 = 2.05. At 3°C temperature, flowing CO2 at Darcy velocity 0.045 cm/s begins to form hydrate in sandstone core at about 3.67 MPa (540 psi), which is much higher than the minimum required pressure of 1.87 MPa (275 psi) for CO2 to form hydrate in static conditions. The pressure ratio is 540/275 = 1.96. The reason why the required minimum pressure for CO2 to form hydrates in dynamic conditions is about double the required hydrate‐forming pressure in static conditions is not fully understood. It is speculated that the shear rate effect of flowing fluids should slow down the growth of hydrate crystals or break down hydrate films, resulting in delayed formation of bulk CO2 hydrates. More investigations in this area are needed in the future.

Explicit and explainable artificial intelligent model for prediction of CO2 molecular diffusion coefficient in heavy crude oils and bitumen

Optimizing CO2 injection for enhanced oil recovery (EOR) requires a precise estimation of the CO2-diffusivity coefficient in porous media. This study developed a predictive model for the molecular diffusivity coefficient of CO2 in bitumen and heavy crude oils using a Bayesian regularized artificial neural network. The unique contributions of the developed model compared to existing models include: First, a simple and accurate mathematical correlation between inputs and CO2-diffusivity has been presented, making it easy to use particularly for individuals with limited understanding of machine learning. Secondly, the time it takes the model to make a prediction (its inference latency) has been established and the model has been physically validated using trend analysis. Fourthly, independent datasets were used to test for the model generalizability.The model was evaluated using 260 data points from the literature, with 70 % for training and 30 % for testing. Key performance metrics were calculated, including root mean square error (RMSE = 0.03), and coefficient of determination (R2 = 0.996). Furthermore, an outlier detection analysis using the statistical leverage approach demonstrated that the data used was of high quality. A relevancy factor analysis revealed that pressure had the greatest impact on CO2 diffusivity, followed by temperature, while CO2 mass fraction had the least impact. The developed model operates within a temperature range of 295 K – 363 K and a pressure range of 1 MPa – 8MPa. Overall, the outcomes of this study contribute to the efficient prediction of CO2 diffusivity in heavy crude oil and bitumen.

Accelerating Numerical Simulations of CO2 Geological Storage in Deep Saline Aquifers via Machine-Learning-Driven Grid Block Classification

The accurate prediction of pressure and saturation distribution during the simulation of CO2 injection into saline aquifers is essential for the successful implementation of carbon sequestration projects. Traditional numerical simulations, while reliable, are computationally expensive. Machine learning (ML) has emerged as a promising tool to accelerate these simulations; however, challenges remain in effectively capturing complex reservoir dynamics, particularly in regions experiencing rapid changes in pressure and saturation. This article addresses the challenges by introducing a fully automated, data-driven ML classifier that distinguishes between regions of fast and slow variation within the reservoir. Firstly, we demonstrate the variability in pressure across different reservoir grid blocks using a simple brine injection and production scenario, highlighting the limitations of conventional acceleration approaches. Subsequently, the proposed methodology leverages ML proxies to rapidly and accurately predict the behavior of slow-varying regions in CO2 injection simulations, while traditional iterative methods are reserved for fast-varying areas. The results show that this hybrid approach significantly reduces the computational load without compromising on accuracy. This provides a more efficient and scalable solution for modeling CO2 storage in saline aquifers.

Clinical experience of the carboxytherapy method in the treatment of patients with temporomandibular joint pain dysfunction syndrome (К07.60)

Objective. Improving the effectiveness of treatment of patients with TMJ PDS myogenic origin. Material and methods. According to the purpose of the study, a group of 10 patients (8 women and 2 men aged 14 to 60 years) was formed with the coincidence of a triad of signs: pain during movements of the lower jaw, a feeling of heaviness and tension in the chewing and facial muscles, restriction of mouth opening. A set of diagnostic measures has been implemented in the following scope: clinical and radiological examination methods, TMJ MRI, ultrasound and surface EMG of the chewing muscles, digital axiography. In the treatment of patients in the study group, the method of invasive carboxytherapy was used, based on dosed injections of CO2 in the projection of trigger points of the masticatory muscles. The research examines the therapeutic value of using of CO2 in the protocol of functional rehabilitation of patients with TMJ diseases of myogenic origin. Results. The analysis of the effectiveness of treatment of patients in the study group was carried out to assess the dynamics of key parameters: the severity of the pain syndrome according to VAS, the magnitude of the IMPACT index values and the magnitude of mouth opening. The severity of pain in patients in the study group, according to average values, decreased by 86% from the initial values, an increase in the amplitude of mouth opening by 28.5%, a decrease in the IMPACT index values by 42.5% from the initial values of hypertonicity of the masticatory muscles, an increase in blood flow speed of superficial temporal artery at 52.5%. Conclusion. The results of the clinical application of the carboxytherapy method in the treatment of patients with TMJ PDS allow us to recommend this method for implementation in the rehabilitation protocols of patients with TMJ PDS of myogenic origin, trismus and hypertonus of the masticatory muscles. Carboxytherapy as a method of etiopathogenetic rehabilitation contributes to the early relief of pain syndrome, normalization of the bioelectric activity of the chewing muscles and restoration the physiological kinematics of the lower jaw’s movements.

Effect of water on asphaltene-precipitation behavior of CO2-crude oil mixtures during CCUS processes

Water can extensively exist in reservoirs. Since the solubility of CO2 in water is not negligible under reservoir conditions, the aqueous phase should also be considered during the phase-behavior simulations of the CO2 flooding process. With the presence of an asphaltene phase and an aqueous phase, four phases (i.e., a vapor phase, a hydrocarbon phase, an asphaltene phase, and an aqueous phase) can coexist at a given thermodynamic equilibrium. In this study, a robust and efficient four-phase vapor–liquid-liquid-aqueous equilibrium calculation algorithm is applied to conduct four-phase vapor–liquid-asphaltene-aqueous equilibrium calculations by assuming asphaltene is a dense liquid phase. The algorithm is first validated by comparing the calculated asphaltene precipitation data with the presence of water against the experimental asphaltene precipitation data documented in the literature. The validation shows that the calculation results agree well with the experimental data, indicating that such algorithm can make reliable predictions of asphaltene precipitation with the presence of water. The validated algorithm is subsequently used to construct pressure–temperature (PT) and pressure-composition (Px) phase diagrams to study the effect of water on asphaltene precipitation under different pressure/temperature conditions and under the injection of CO2. We can conclude from the calculated results that although adding water to the reservoir fluid can cause obvious changes in the PT phase diagrams, it does not have a noticeable influence on the asphaltene precipitation onsets. However, it can be seen from the calculated Px phase diagrams that the presence of water during the CO2 flooding process can make asphaltene precipitated more easily. The maximum amount of asphaltene precipitation is decreased by the presence of water due to the fact that a considerable amount of CO2 is dissolved in the aqueous phase instead of the liquid hydrocarbon phase.

Study on the effect of morphology of anthracite coal containing through-fracture on CO2 enhanced coalbed methane recovery

When CO2 is injected into the coal seam, different forms of fractures within the coal have different effective diffusion areas and distribution characteristics for the gas, affecting methane's adsorption-desorption-diffusion and seepage behavior. In this study, based on the control experiments of the intact coal sample, CO2 injection experiments were carried out on three groups of coals containing through-fracture to investigate the influence of fracture morphology on CO2-enhanced coalbed methane recovery behaviors and to discuss and analyze the changes in the volume of the coal samples, the composition of the tailing gas, and the changes in the permeability during the gas injection process. The results show that: the existence of fractures has an inhibitory effect on the volume expansion after gas adsorption of the coal, and the larger the surface area of fractures, the more obvious inhibitory effect, and at the same time, the faster the strain rate; the breakthrough time of CO2 in the fractured coal samples is much shorter than that in the intact samples; the increase in the surface area of the fractures and uniformity of distribution can enhance the concentration of CH4 in the tail gas, and in the pre-injection stage, uniformity of the distribution of the fractures is more important than the surface area of the fractures in increasing the output CH4 concentration; the magnitude of permeability change and the change rate of the coal samples during CO2 injection increased with the increase in the fracture surface area of the coal samples.

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.

Experimental investigation on fracture propagation in shale fractured by high-temperature carbon dioxide

The productivity of shale reservoirs was significantly enhanced by the high-temperature CO2 fracturing technique. The injection of high-temperature CO2 into the formation induced rock fracture propagation, creating advantageous pathways for fluid flow. In this research, a self-developed in situ high-temperature convective heat simulation experimental apparatus was employed to systematically conduct simulated experiments on high-temperature CO2 fractured shale under different influencing factors. The experimental results demonstrated that the permeability of CO2 increased as the injection temperature increased. The rock fracture pressure was effectively reduced by high-temperature CO2 fractured shale. Higher complexity was observed in fracture propagation, accompanied by a substantial increase in microcracks and branching fractures. The shale fracture pressure increased with increasing triaxial stress and CO2 injection rate. The confining pressure restricted the further propagation of fractures under relatively high stress conditions, thereby reducing the width and density of fractures, lowering the fracture complexity. Nevertheless, the thermal shock effect of the fluid was exacerbated as the injection rate of high-temperature CO2 increased. The initiation of microcracks was facilitated by the intensification of local thermal stress in shale, inducing multiple curved fractures and forming a more complex fracture network. Compared to horizontal bedding shale, the fracture pressure of vertical bedding shale was relatively higher during high-temperature CO2 fracturing. In addition, the geometric morphology of fracture propagation was more complex, characterized by rougher fracture surfaces, leading to a greater improvement in reservoir reconstruction volume. This research contributed to the optimization of CO2 resource utilization, provided experimental evidence for the application of high-temperature convection fracturing technology in in situ shale conversion projects.

Mathematical model of permeability evolution of liquid CO2 pressurized coal

To examine the permeability alterations in coal seams induced by liquid CO2 injection, we employed COMSOL simulations to recreate the flow, force, and temperature fields, along with the corresponding physical parameters of the geological formation. We established a mathematical model to track the evolution of the coal body’s permeability, enabling us to capture the phase distribution of CO2, the dynamics of fluid transportation, and the coal body’s mechanical responses during the liquid CO2 injection process. Our findings revealed that the coal seam undergoes significant changes due to low-temperature freezing and shrinkage, gas-liquid phase transitions, and expansion impacts from solid-liquid phase changes. These factors collectively modify the pore structure, subsequently influencing the coal seam’s permeability. Notably, the coal body’s permeability, influenced by the pore structure and the Klinkenberg effect, increases logarithmically with rising injection pressure and falling temperatures. The structural changes in the coal body are markedly impacted by seepage and phase change pressures, with the permeability enhancement from secondary phase changes being 2.28 times greater than that from primary phase changes, and five times greater than in scenarios without phase change.

Hydrate management strategies for CO2 injection into depleted gas reservoirs

Sequestering CO2 in depleted gas reservoirs using carbon capture, utilization, and storage technologies has emerged as a viable strategy for mitigating global carbon emissions. However, CO2 hydrate formation during injection processes is challenging and poses a risk to the operational integrity and efficiency of sequestration projects. This study investigated CO2 hydrate formation dynamics within silica gel environments that closely mimicked the median pore size of natural sandstone reservoirs, particularly targeting depleted gas fields in the East Sea of Korea. Integrating kinetic insights into experimental hydrate formation assessments and molecular dynamics simulations provided a comprehensive understanding of the CO2 hydrate formation mechanisms, as well as the formation dynamics and stability of the CO2 hydrates. For example, the hydrate formation kinetics were significantly reduced in the small pores, suggesting the feasibility of implementing more economical hydrate inhibitor injection strategies during CO2 injection. Moreover, this study evaluated the inhibitory effects of NaCl and methanol on CO2 hydrate stability by accurately measuring the three-phase (H-Lw-V) equilibria and employing silica gels (6 nm pore size). The presence of methanol and amorphous silica significantly impacted hydrate formation, with methanol potentially influencing the local structure around the hydrate phase and silica hindering hydrate growth through dynamic interactions with CO2 molecules. In addition, we elucidated the complex interplay between CO2, water, and methanol (hydrate inhibitor) within the constrained environments of porous media, offering strategic insights for the development of effective CO2 injection and sequestration strategies. Integrating molecular-level observations with real-world geological modeling presents a novel methodology for enhancing the safety, efficiency, and environmental sustainability of carbon capture and storage operations. The findings of this study provide critical insights into hydrate phase behavior, highlighting the importance of precise equilibrium determination under simulated reservoir conditions to effectively anticipate and mitigate hydrate formation challenges.

Study of recovery factor and CO(2) storage behavior in a reservoir using numerical simulation

In this study, the behavior of the recovery factor during the displacement and storage phases of carbon dioxide (CO2) in an Ecuadorian reservoir was investigated by numerical simulation. Continuous injection and CO2 WAG methods were used. The methodology included field data collection, creation of a static reservoir model, configuration of the PVT model with CMG software, construction of a dynamic model in GEM-CMG based on rock-fluid properties, and evaluation of CO2 injection scenarios. After a screening analysis, the optimal scenario was identified and the performance of the recovery factor over time was studied. The results indicated that, during the 8 years of simulation, the recovery factor with continuous injection was 28%, while with the WAG method it reached 31%. It was concluded that WAG was the most efficient method. Regarding storage, it was observed that continuous injection was able to store 83% of the CO2 in the reservoir.

Supervised Deep Learning for Detecting and Locating Passive Seismic Events Recorded with DAS: A Case Study.

Exploring shallow mineral resources requires acquiring denser seismic data, for which Distributed Acoustic Sensing is an effective enabler and relevant to mining operations monitoring. Passive seismic can be of interest in characterizing the subsurface; however, dealing with large amounts of data pushes against the limits of existing computational systems and algorithms, especially for continuous monitoring. Hence, more than ever, novel data analysis methods are needed. In this article, we investigate using synthetic seismic data, paired with real noise recordings, as part of a supervised deep-learning neural network methodology to detect and locate induced seismic sources and explore their potential use to reconstruct subsurface properties. Challenges of this methodology were identified and addressed in the context of induced seismicity applications. Data acquisition and modelling were discussed, preparation workflows were implemented, and the method was demonstrated on synthetic data and tested on relevant seismic monitoring field dataset from the Otway CO2 injection site. Conducted tests confirmed the effects of time shifts, signal-to-noise ratios, and geometry mismatches on the performance of trained models. Those promising results showed the method's applicability and paved the way for potential application to more field data, such as seismic while drilling.