Geophysical Monitoring Technologies for the Entire Life Cycle of CO₂ Geological Sequestration

Abstract

Geophysical monitoring of CO₂ geological sequestration represents a critical technology for ensuring the long-term safe storage of CO₂ while verifying its characteristics and dynamic changes. Currently, the primary geophysical monitoring methods employed in CO₂ geological sequestration include seismic, fiber optic, and logging technologies. Among these methods, seismic monitoring techniques encompass high-resolution P-Cable three-dimensional seismic systems, delayed vertical seismic profiling technology, and four-dimensional distributed acoustic sensing (DAS). These methods are utilized to monitor interlayer strain induced by CO₂ injection, thereby indirectly determining the injection volume, distribution range, and potential diffusion pathways of the CO₂ plume. In contrast, fiber optic monitoring primarily involves distributed fiber optic sensing (DFOS), which can be further classified into distributed acoustic sensing (DAS) and distributed temperature sensing (DTS). This technology serves to complement seismic monitoring in observing interlayer strain resulting from CO₂ injection. The logging techniques utilized for monitoring CO₂ geological sequestration include neutron logging methods, such as thermal neutron imaging and pulsed neutron gamma-ray spectroscopy, which are primarily employed to assess the sequestration volume and state of CO₂ plumes within a reservoir. Seismic monitoring technology provides a broader monitoring scale (ranging from dozens of meters to kilometers), while logging techniques operate at centimeter to meter scales; however, their results can be significantly affected by the heterogeneity of a reservoir.

1. Introduction

China has established the objectives of achieving carbon peak and carbon neutrality, with a target to reach the peak of carbon emissions by 2030 and to strive for carbon neutrality by 2060. This initiative has garnered significant attention from both domestic and international communities [1]. As one of the critical technological means for attaining carbon neutrality, carbon capture, utilization, and storage (CCUS) technology is considered a pivotal approach in this endeavor [2]. In recent years, there have been notable shifts in global climate change dynamics and policies, leading to an emergence of new technologies within CCUS that exhibit increasing diversity, decreasing energy consumption costs, enhanced technical sophistication, and broader application scopes; its connotation and extension have also been further enriched and expanded [3]. Serving as a vital measure for reducing greenhouse gas emissions and addressing global climate change challenges, CO₂ geological sequestration represents China’s primary strategy for CO₂ emission reduction [4]. With the advancement of industrial policies coupled with favorable conditions, China is experiencing a surge in large-scale CCUS demonstration project development. These projects primarily focus on geological utilization and sequestration while being predominantly employed for enhanced oil recovery (CO₂-EOR) [5,6] and coalbed methane displacement (CO₂-ECBM), as well as brine layer sequestration [7].

While the prospects for CCUS are promising, the risk of leakage following geological sequestration of CO₂ and the associated monitoring methods remain significant challenges. Currently, it is believed that the primary causes of CO₂ leakage stem from compromised well integrity and seal integrity [8]. Monitoring CO₂ geological sequestration not only facilitates the assessment of leakage risks but also serves to verify and confirm dynamic changes post-CO₂ injection, as well as ensure consistency between injected volumes, actual sequestration volumes, and their respective locations relative to expected parameters. The geophysical monitoring techniques employed in CO₂ geological sequestration encompass time-lapse seismic imaging, fiber optic technology, thermal neutron logging, and nuclear magnetic resonance, among others. In terms of monitoring effectiveness for CO₂ geological sequestration, Zhang et al., Sun et al., and Massarweh et al. have provided comprehensive summaries on seismic logging technology [9], distributed fiber technology [10], and laboratory-scale studies [11]. By synthesizing recent advancements in seismic monitoring technologies, fiber optic monitoring technologies, and logging methodologies while analyzing their respective characteristics, various geophysical monitoring approaches can be integrated throughout the entire life cycle of CO₂ geological sequestration to address limitations inherent in individual detection methods, ultimately achieving a goal of comprehensive and continuous regulatory oversight regarding both the characteristics and dynamic changes associated with CO₂ geological sequestration.

2. Geophysical Monitoring Approaches for CO₂ Sequestration

2.1. Rock Physics Simulation Experiments

Rock physics simulation experiments play a crucial role in calibrating the rock properties of the target reservoir and developing a comprehensive reservoir property map. They hold significant importance throughout the entire life cycle of CO₂ geological sequestration monitoring. Currently, efforts in rock physics simulation primarily concentrate on replicating the geochemical indicators of the actual reservoir before and during CO₂ injection, utilizing core samples collected from the target reservoir to investigate the CO₂–water–rock interactions and capture corresponding dynamic changes in physical property parameters as well as variations in mineral composition. Consequently, these experiments can indirectly assess the actual volume of CO₂ sequestered within core samples during the mineralization phase using instruments such as scanning electron microscopes, X-ray computed tomography (CT), and mass spectrometers. The fundamental experimental principles and procedures are illustrated in Figure 1.

Wang et al. conducted an experimental analysis (Figure 1a) to investigate the changes in the mineral composition and chemical properties of rocks following CO₂ injection into coal seams. This experimental device is well-suited for experimental evaluation under standard temperature and pressure conditions to simulate the rock’s physical parameters during low-temperature and low-pressure phases in a CO₂ storage reservoir [12]. The results indicate that silicate minerals within the coal seam roof are transformed into smectite and illite due to dissolution processes, while carbonate minerals in calcareous shale primarily result from precipitation. Han et al. [13] and Cui et al. [14] used a high-temperature and high-pressure desorption adsorption device to determine the optimal CO₂ injection depth for each layer using the linear relationship between adsorption parameters and temperature, as well as a fixed drop method. They revealed that the adsorption capacity reached its peak at a depth of approximately 1000 m (Figure 1b). Additionally, researchers simulated alterations in saline water chemistry resulting from CO₂–water–rock interactions (Figure 1c) during continuous CO₂ injection, observing significant increases in concentrations of HCO₃⁻ and Ca²⁺ when utilizing sandstone reservoirs and shale caprocks as sequestration sites [15]. The CO₂–water–rock reaction significantly influences the wetting properties, microscopic pore structure, and mobile fluid saturation of the reservoir. Alkali feldspars, including potassium feldspar, calcite, and aluminum silicate minerals, undergo dissolution to create micron-sized dissolution pores and micro-fractures; concurrently, calcite experiences recrystallization [16,17]. The wetting characteristics of the reservoir shift from oil-wet/neutral wet to strong water-wet; newly formed precipitation particles lead to partial blockage of throat radii, consequently reducing the mobile fluid saturation governed by these throats. Furthermore, a higher concentration of alkali feldspars (e.g., potassium feldspars) within the core correlates with an intensified CO₂–water–rock reaction that enhances the microscopic heterogeneity of the reservoir while diminishing mobile fluid saturation [18,19]. Following their release into fractures, CO₂-rich fluids migrate into the overlying shale caprock, where calcite veins gradually precipitate within these fractures. This process augments both the cementation and sealing effects associated with calcite precipitation in fractures, thereby improving the sealing capacity of the overlying caprock [20].

Figure 1. Schematic diagram of a common CO₂ water rock reaction device. (a) Modified by Wang et al., 2016 [12]. (b) According to Cui et al.’s revision, 2024 [14]. (c) Modified by Liu et al., 2019 [15].

Figure 1. Schematic diagram of a common CO₂ water rock reaction device. (a) Modified by Wang et al., 2016 [12]. (b) According to Cui et al.’s revision, 2024 [14]. (c) Modified by Liu et al., 2019 [15].

CO₂–water–rock reactions can significantly modify the chemical composition, mineralogy, porosity, permeability, and wetting properties of both the reservoir and cap rock. Silicate minerals undergo dissolution processes, while carbonate minerals precipitate; this dissolution of silicate minerals generates clay minerals, such as illite and smectite, which further diminish the porosity of the cap rock and enhance the safety of CO₂ geological sequestration. Furthermore, CO₂–water–rock interactions can induce alterations in the composition and structure of carbonate rocks, increasing their hydrophilicity along with their porosity and permeability. Basalt reacts with CO₂ to form carbonate minerals that continue to interact with CO₂-saturated water solutions; this ongoing reaction increases both the porosity and permeability of the reservoir but may compromise sequestration safety. Consequently, a comprehensive study on seal integrity is essential, considering factors such as actual reservoir-cap rock combinations as well as lithology and post-diagenesis mechanisms associated with faults and fractures. In contrast, sandstone presents a more favorable choice for reservoirs in CO₂ geological sequestration; its integrity alongside mineralized sequestration can be effectively monitored through rock physics simulation experiments. Based on these findings, sites for CO₂ geological sequestration and geophysical monitoring primarily focus on sandstone and shale formations.

Rock physics simulation experiments can effectively monitor the integrity of wellbores at a laboratory scale, providing valuable references for assessing the integrity of existing wells and selecting materials for new constructions (Typical apparatus is illustrated in Figure 2). The study conducted by Condor et al. clearly demonstrates that under sulfate and CO₂ environments, both the permeability and compressive strength of the cement ring within the annulus will diminish, highlighting that the gap between the cement and casing may represent the most probable pathway for CO₂ leakage in wellbores [21].

Mito et al. conducted an experiment to assess the impact of CO₂ alteration on wellbore integrity. By analyzing the reaction rates in experiments involving water vapor-saturated CO₂ and saturated CO₂ brine, the authors estimated that the corrosion depths of the steel casing would be 4.6 mm and 2.1 mm over a period of 30 years, respectively [22]. Vecchia et al. simulated the effects of injected CO₂ on the formation of corrosion layers on steel pipes using microscopy techniques and scanning electron energy-dispersive spectroscopy [23]. The results indicated that CO₂-rich brine initially interacted with the surface of the steel pipe, leading to the leaching of Fe²⁺ ions into solution and subsequent precipitation of FeCO₃ on its surface. As degradation progressed, Fe²⁺ began migrating into the cement structure, thereby impacting both the self-healing capabilities and pore-blocking characteristics of the material. Concurrently, Ca²⁺ started forming mixed carbonates (Fe_xCa_yCO₃), resulting in a corrosion film that further influenced the protective efficiency against corrosion layer deterioration. Ultimately, localized accumulation of Ca²⁺ and Fe²⁺; near materials may lead to CaCO₃ formation on corrosion layers as well as the precipitation of FeCO₃ within cement matrices.

Figure 2. Common wellbore integrity laboratory monitoring device (modified by Mamoudou et al., 2024 [24]).

Figure 2. Common wellbore integrity laboratory monitoring device (modified by Mamoudou et al., 2024 [24]).

Mamoudou et al. conducted an experimental (Figure 2) investigation into the reactivity of G-grade cement with supercritical CO₂, detailing the process of pore volume changes in cement subjected to a supercritical CO₂ environment [24]. The results indicated that after 2 weeks, the peak pore throat size decreased from 50 nm to 30 nm, signifying a reduction in pore throat dimensions and demonstrating that the carbonation process led to a decrease in the effective pore volume of the cement. However, after 5 weeks, there was a significant reduction in the number of pore throats averaging 30 nm in diameter, resulting in smaller pore throats forming within the range of 2–30 nm. This suggests that both dissolution and precipitation occur concurrently in larger pores, while dissolution is predominant solely within smaller pores.

The CO₂–water–cement/pipe experiment not only allows for the assessment of old wellbore integrity at a laboratory scale but also serves as an effective method for evaluating cement performance and facilitating timely improvements prior to the solidification of new wellbores, thereby significantly reducing the challenges associated with subsequent wellbore integrity monitoring. This experiment can effectively simulate real-world conditions and provide critical data on material interactions under varying circumstances. In terms of old wellbores, conducting a systematic analysis of existing structures and materials enables the identification of potential weaknesses and defects. Such preliminary assessments not only enhance safety but also offer a scientific basis for future maintenance efforts. For new wellbores, performing cement performance evaluations before solidification ensures that selected materials meet specific geological requirements, thus optimizing construction strategies.

In rock physics simulation experiments for CO₂ geological sequestration, several technical challenges must be addressed: A. Due to reservoir heterogeneity, the experimental environment cannot fully replicate the parameters found in actual formations, leading to discrepancies between experimental results and those observed in real reservoirs as a result of environmental parameter variations. B. Rock physics simulation experiments can only capture the CO₂ sequestration state and volume of core samples at specific time points. Therefore, it is essential to integrate geophysical monitoring technologies for multi-scale matching to facilitate effective scaling from laboratory conditions to field applications.

2.2. Seismic Techniques

Researchers are focused on developing seismic acquisition systems that offer higher resolution, enhanced deplorability, and superior imaging quality [25]. High-resolution seismic acquisition systems can be more effectively integrated with CO₂ fluid migration modeling studies. The prevalent seismic monitoring technologies include 3D and 4D seismic methods. Compared with 2D seismic technology, 3D seismic technology is more advantageous in capturing the three-dimensional characteristics of rock formations, but it has limitations in monitoring the spatial and temporal distribution of CO₂. In contrast, 4D seismic technology involves repeating the same 3D method multiple times at a fixed location over different time intervals, making it an essential tool for dynamic reservoir characterization and monitoring. Additionally, it serves as an effective physical monitoring approach for CO₂ geological sequestration due to its higher resolution compared to 3D techniques and its capability for real-time tracking of CO₂ variations over time. Nevertheless, the duration required for conducting 4D monitoring tends to be relatively longer.

Huh et al. [26] and Luth et al. [27] employed four-dimensional seismic and two-dimensional/three-dimensional multi-channel reflection seismic techniques to investigate the storage capacity, spatial distribution, and migration pathways of CO₂. These studies utilized high-precision imaging technologies to effectively capture dynamic changes in subsurface structures, thereby providing critical insights for assessing CO₂ behavior across various reservoirs. Four-dimensional seismic monitoring is particularly well-suited for long-term tracking of fluid evolution within a reservoir post-injection, thus offering valuable data support for optimizing injection strategies. Wang et al. [28], Luo et al. [29], and Diao et al. [30] integrated the well log forward model with the Hertz–Mindlin equation and the Gassmann equation to predict the migration pathways and distribution areas of CO₂, as well as its sources and plume diffusion patterns. This comprehensive approach facilitates a more accurate simulation of how different rock types influence CO₂ migration characteristics while elucidating its behavior in complex geological environments. Furthermore, the model effectively identifies potential leakage points, thereby enhancing overall sequestration safety. Wang et al. employed the time-migrated seismic differential analysis method alongside the time-migrated amplitude versus offset (AVO) forward and inverse techniques to quantitatively predict gas saturation and reservoir pressure differentials resulting from CO₂ injection [31]. This approach effectively identifies changes in subsurface media induced by CO₂ injection through a comparative analysis of seismic data at various temporal intervals. Specifically, the time-migrated seismic differential analysis elucidates the heterogeneous distribution of fluids within the reservoir, while the time-migrated amplitude variation with offset (AVO) forward and inverse techniques yield additional insights into fluid properties, thereby providing a scientific basis for assessing sequestration efficacy. Waage et al. distinctly delineated the changes in saturation and leakage rates during the CO₂ injection and sequestration process through a comparative analysis of 3D P-Cable and conventional 3D seismic systems [32]. Leveraging its high-resolution imaging capabilities, the 3D P-Cable system allows researchers to monitor the dynamic behavior of CO₂ within the reservoir with enhanced precision across various stages. This comparison not only highlights the advantages of novel monitoring technologies in practical applications but also serves as an effective complement to traditional methods, thereby contributing to improved overall monitoring efficiency.

Seismic monitoring of CO₂ geological sequestration primarily focuses on geological strain induced by CO₂ injection, encompassing key aspects such as the distribution range and potential diffusion pathways of injected CO₂ plumes, along with indirect assessments of CO₂ saturation within pore spaces, thus addressing both structural sequestration and residual sequestration phases.

2.3. Fiber Optic Technology

The advantages of fiber optic technology for CO₂ geological sequestration monitoring include low loss, a wide dynamic range, non-electrical operation, compact size, lightweight design, flexibility in bending, and robust resistance to electromagnetic interference and radiation. Fiber optic technology has found extensive application in CO₂ geological sequestration monitoring. Currently, the predominant fiber optic technique employed for this purpose is distributed fiber optic sensing (DFOS). In comparison to traditional fiber optic sensing methods, DFOS offers benefits such as extended detection range, high pressure and temperature tolerance, multiplexing capabilities, and intelligent sensing features. Commercial DFOS systems primarily assess the effectiveness of CO₂ sequestration by monitoring formation strain through techniques, including distributed temperature sensing (DTS), distributed acoustic sensing (DAS), and distributed strain sensing (DFOSS). Among these technologies, DAS specifically targets vibrations induced by CO₂ injection; it is compact with strong networking capabilities but suffers from limited radial resolution and requires installation during drilling operations, rendering it unsuitable for existing well infrastructure. Conversely, DTS concentrates on measuring the depth and arrival of CO₂ entering the reservoir via injection well perforations; while it boasts a high resolution, its efficacy often necessitates integration with other fiber optic monitoring technologies. Distributed fiber optic strain sensing (DFOSS) is dedicated to monitoring the distribution of strain responses induced by CO₂ injection, facilitating the advancement of fiber optic monitoring technology from laboratory scale to carbon capture and storage (CCS) storage site applications. Nevertheless, it still faces challenges regarding resolution and accuracy.

It is evident that individual distributed temperature sensing (DTS), distributed acoustic sensing (DAS), and distributed fiber optic strain sensing (DFOSS), along with other fiber optic monitoring technologies, exhibit significant limitations in CO₂ geological sequestration monitoring, particularly regarding resolution and accuracy. Consequently, multiple fiber optic monitoring techniques are typically employed concurrently or integrated with seismic monitoring and logging methods, demonstrating widespread application across numerous CO₂ geological sequestration projects. Furthermore, due to the inherent characteristics of fiber optics, this technology cannot directly assess the dissolution saturation of CO₂ in brine; rather, it is primarily utilized for tracking the dynamic movement of CO₂ plumes. As such, fiber optic monitoring technology is predominantly applied to monitor structural and residual sequestration.

Distributed fiber optic sensing (DFOS) has found extensive application in the dynamic monitoring of oil and gas fields. In casing leakage detection, DTS or DAS data from the entire well section are collected during the pumping fluid state and following the cessation of injection recovery. The changes in temperature fields within the wellbore are analyzed based on axial and radial thermal dynamics principles. When anomalies in well temperature or abnormal recovery speeds are observed, it can be inferred that a leakage point exists within the well. Furthermore, the demodulation of vibration event signals allows the identification of abnormal points, which may also indicate potential leakage sites [33]. In CO₂ geological sequestration monitoring, insights gained from dynamic monitoring practices in oil and gas fields can be leveraged to assess the integrity of CO₂ injection wells using distributed fiber optic sensing technology.

Mawalkar et al. investigated the dynamics of CO₂ plume movement by integrating distributed temperature sensing (DTS) technology with formation pressure, gas saturation, and cable temperature logging. The findings indicated that this method effectively monitors the position of the CO₂ injection front, revealing that most injected CO₂ entered two target formations without vertically migrating to other formations along the casing [34]. Yao et al. introduced a Pareto-based multi-objective genetic algorithm (MOGA), which integrates an extended flowline inversion algorithm to establish local historical matches for achieving layered historical matching of CO₂ plumes during injection processes [35]. Pevzner et al. successfully combined distributed acoustic sensing (DAS) with four-dimensional vertical seismic profiling (4D VSP) monitoring technology to assess both the dynamic state and imaging of CO₂ plumes [36]. Additionally, by employing continuous seismic acquisition through multi-well DAS systems, they expanded the bandwidth required for data transmission, thereby mitigating delays between data acquisition and processing results in seismic monitoring applications. Li et al. employed distributed acoustic sensing (DAS), vertical seismic profiling (VSP), and an integrated approach utilizing synthetic aperture radar interferometry (InSAR) to investigate the dynamics of CO₂ gas plumes within coal seams. Subsequently, by leveraging InSAR technology from remote sensing satellites to monitor surface deformation, the direction of CO₂ migration was ascertained, with the results verified bidirectionally using a time-shifted DAS-VSP system [37]. Xu et al. utilized distributed fiber optic strain sensing (DFOSS) technology to assess the flow behavior of CO₂ in tight sandstone reservoirs [38]. The study revealed that the peak strain response consistently occurred at the CO₂ injection point, exhibiting gradient attenuation in alignment with fluid movement direction. Therefore, distributed fiber optic strain sensing technology can effectively monitor the position of the CO₂ front and evaluate its velocity based on the time difference between when CO₂ passes through monitoring points and when it flows into those points.

2.4. Well-Logging Technology

Among various logging techniques, neutron logging is extensively utilized for monitoring geological CO₂ sequestration. Research on the initial two monitoring methods indicates that most seismic and fiber optic monitoring technologies and equipment compare their results with neutron logging data throughout the monitoring process. Consequently, neutron logging assumes an indispensable role in CO₂ sequestration monitoring. Currently, the primary neutron logging techniques employed for CO₂ monitoring include delayed pulse neutron logging (PNL) and radioactive pulse neutron–gamma logging (PNG).

Baumann et al. applied the pulse neutron–gamma logging technique (PNG) to ascertain the saturation profiles of wells Ktzi201, Ktzi200, and Ktzi202 within Germany’s Ketzin project based on PNG data acquired during the CO₂ injection phase. The findings reveal that the CO₂ saturation at well Ktzi201 (SCO₂ > 68%) exceeds that of well Ktzi200 (SCO₂ > 60%) and well Ktzi202 (SCO₂ < 60%); furthermore, there is a gradual decrease in CO₂ saturation from Ktzi201 to both Ktzi200 and Ktzi202 [39]. Braunberger et al. employed delayed pulse neutron logging (PNL) and observed that the variation in CO₂ saturation within the reservoir’s middle section was significantly greater than that at the top and bottom sections. By integrating delayed pulse neutron logging with neutron capture cross-section logging (sigma logs) and carbon–oxygen ratio logging, a more accurate determination of CO₂ distribution after its entry into the reservoir can be achieved [40]. Song et al. validated the applicability of an approximate calculation formula for CO₂ saturation in reservoirs with low CH₄ saturation through simulation examples. The findings indicate that a precise calculation formula can limit the error in CO₂ saturation calculations to within 2%, excluding considerations for CH₄ saturation [41]. Conner et al. introduced a gamma ray capture ratio between short-interval detectors and ultra-long-interval detectors (RATO13), which, when combined with Sigma analysis, effectively identifies saturations of CO₂, water, and oil. The introduction of RATO13 addresses the limitation inherent in using Sigma analysis alone, which only allows for the identification of water and oil saturations [42]. Additionally, a non-elastic gamma ray count rate ratio (RIN13) was proposed; when salt plugs form within reservoir pores, RATO13 experiences a sharp increase, while RIN13 decreases; this characteristic serves as an indicator for identifying salt-cemented layers within target reservoirs.

Well-logging technology, particularly neutron logging, has been extensively utilized in CO₂ monitoring, serving not only to track the movement of CO₂ plumes but also to assess CO₂ saturation levels. It is evident that well logging primarily focuses on the monitoring of geological CO₂ sequestration, specifically addressing structural sequestration, residual sequestration, and dissolution sequestration. However, given the substantial influence of reservoir heterogeneity on well-logging accuracy, it is imperative to integrate other monitoring technologies to achieve a comprehensive life-cycle assessment of the characteristics and dynamic changes associated with geological CO₂ sequestration.

Well-logging monitoring technology plays a crucial role in the dynamic assessment of wellbore integrity at the site scale and has been extensively utilized. Hawkes et al. [43], Nakajima et al. [44], and Duguid et al. [45] conducted evaluations of wellbore integrity using reservoir saturation logging (RST) and cement bond logging techniques. Specifically, Hawkes et al. employed acoustic and electromagnetic logging to assess the integrity of uncased wells, with monitoring results indicating that the overall condition of the casing was satisfactory. The findings from reservoir saturation logging (RST) revealed no presence of CO₂ outside the casing, thereby confirming that the annular space beneath the liner provided effective inter-layer isolation. Nakajima et al., through a combination of delayed ultrasonic logging and cement bond logging, demonstrated that there was no significant damage or deformation to the casing nor any notable changes in the cement state. Building on this foundation, Duguid et al. applied X-ray diffraction analysis to investigate the composition of cement samples collected from depths ranging from 2135.43 m to 3012.64 m and at 3026.51 m. They concluded that either a sufficiently low CO₂ concentration or slow migration rate along the well resulted in calcite formation within these cement samples, indicating complete carbonation of the cement phase.

In summary, the characteristics of CO₂ geological sequestration monitoring using seismic, fiber optic, and logging technologies are as follows:

A.

Seismic monitoring can simultaneously track CO₂ plume injection across multiple wells along with its distribution range and diffusion path. While it has extensive capabilities, it cannot accurately measure the CO₂ injection for individual wells;

B.

Logging technology covers the wellbore and surrounding area to detect CO₂ concentration and plume distribution in nearby formations around a single well. It is suitable for evaluating sequestration volumes—residual and dissolution—and wellbore integrity; however, its results may be affected by strong reservoir heterogeneity;

C.

Fiber optic monitoring also encompasses the wellbore and adjacent areas by tracking real-time temperature and pressure changes due to CO₂ injection to determine the injection volume and potential diffusion paths. This technology enhances the detection of wellbore integrity but is primarily used for assessing structural and residual sequestration volumes while being less effective for detecting dissolution or mineralization sequestration.

3. Integration of Geophysical Techniques and Machine Learning Algorithms

As CO₂ sequestration monitoring progresses, the volume of collected data is increasing, with seismic, fiber optic, and well-logging technologies yielding exponential growth in data. In this context, machine learning algorithms have shown unique advantages by processing large datasets quickly and significantly improving efficiency. After years of research, these algorithms are now widely applied in CO₂ geological sequestration.

Li et al. used a fully convolutional neural network (FCN) to predict carbon dioxide (CO₂) sequestration based on time-migrated differential seismic data, with its prediction accuracy increasing as the CO₂ injection rate varied [46]. Leong et al. predicted the location and saturation of the CO₂ plume during sequestration using seismic inversion data and compared SeisCO₂Net’s saturation map with physical model inversion results, revealing similar shapes, features, and saturation values for the CO₂ plume [47]. Sheng et al. achieved an accuracy of 95.8% in predicting the CO₂ plume location using 4D seismic monitoring data, with a precision of 0.8 mIoU (mIoU indicates the average overlap ratio between predicted and marked CO₂ areas) [48]. Nagao et al. employed two machine learning algorithms—a convolutional neural network (CNN) and a feedforward neural network (FFNN)—to predict the CO₂ plume location. By combining casing post-pressure with distributed temperature sensing (DTS), their average absolute percentage error (MAPE) was 2.75%, lower than errors of 3.04% when using DTS alone or 5.13% when relying solely on casing post-pressure [49,50].

The effectiveness of employing machine learning algorithms for processing CO₂ geological sequestration monitoring data hinges on parameter selection and model fitting [51]. Specifically, parameter selection involves identifying the most critical features influencing CO₂ behavior from a range of potential variables, utilizing domain knowledge and statistical analysis. This process is essential to ensure that the chosen parameters accurately reflect the physical and chemical characteristics of the underground reservoir. Furthermore, the quality of model fitting directly impacts the magnitude of prediction analysis errors. A high-quality model not only necessitates robust fitting but also demands strong generalization capabilities. To achieve this objective, researchers frequently employ cross-validation and other methodologies to assess model performance while optimizing the model structure through hyperparameter adjustment. Additionally, various types of machine learning algorithms (such as regression, decision trees, and neural networks) possess distinct advantages and disadvantages; thus, selecting the appropriate method is essential. In practical applications, data preprocessing, including steps such as noise reduction, normalization, and imputation of missing values, must also be considered to enhance data quality and improve the reliability of final prediction outcomes. Consequently, a comprehensive integration of diverse technical approaches is required throughout the process to ensure an accurate, efficient, and scientifically rigorous analysis of CO₂ geological sequestration monitoring data.

4. Discussion and Analysis

Following a comprehensive analysis of various monitoring technologies for CO₂ geological sequestration, it is necessary to fully consider the impact of spatial and temporal factors on the effectiveness of carbon dioxide geological sequestration. In the process of selecting appropriate monitoring technologies, it is crucial to emphasize the analysis of in-well fluid data to fulfill comprehensive life cycle monitoring objectives. Prior to CO₂ injection, it is essential to identify suitable reservoirs, assess their technical and economic feasibility, and recognize potential leakage risks to optimize the monitoring strategy. During the injection phase, real-time data analysis and frequency adjustments should be implemented, followed by regular evaluations of sequestration effectiveness post-injection. By leveraging domestic and international experiences in CO₂ sequestration monitoring—and acknowledging China’s current limited experience in this domain—a more systematic geophysical monitoring framework can facilitate successful project implementation. As future experiences accumulate from implementing comprehensive geophysical monitoring schemes for CO₂ geological sequestration in China, strategies can be tailored to local conditions, thereby developing more effective geophysical monitoring indicators.

4.1. Rock Physics Simulation

The physical properties of rocks, including the modulus of elasticity and porosity, significantly influence CO₂ storage and its safety [52]. These two parameters are essential for assessing the physical characteristics of rocks, as they are directly linked to the safety and efficacy of CO₂ storage. The modulus of elasticity quantifies a rock’s resistance to deformation; thus, rocks with a high modulus can better withstand pressure and deformation, thereby mitigating the risk of rock failure during CO₂ storage. Conversely, porosity reflects the volume fraction of pore space within the rock, where increased porosity correlates with enhanced gas storage capacity but also elevates the potential for CO₂ leakage [53]. Specifically, while high-porosity rocks offer greater gas storage space, they may develop high-permeability pathways that facilitate CO₂ leakage and compromise storage safety. In contrast, low-porosity rocks exhibit limited gas storage capacity yet possess superior stability that aids in reducing leakage risks. Porosity represents the proportion of pore space within a rock, where increased porosity correlates with enhanced CO₂ storage capacity but also elevates the risk of leakage. Specifically, rocks with high porosity offer greater storage potential; however, they may develop high-permeability pathways that facilitate CO₂ leakage and compromise storage safety. Conversely, low-porosity rocks exhibit limited storage capacity yet provide superior stability, thereby aiding in the reduction of leakage risks [54].

Field outcrops and core samples from the target reservoir are collected for rock physics simulation experiments, during which the lithology and physical properties of the reservoir are determined and calibrated. Additionally, these simulations are employed to select injection wells that satisfy CO₂ injection requirements, with appropriate cement types and wellbore materials chosen accordingly. Furthermore, real-time monitoring of CO₂ mineralization sequestration progress in the target reservoir’s rock core is essential at the laboratory scale, particularly given the relatively rapid CO₂ mineralization rate in basalt; thus, continuous tracking of its sequestration degree within basalt is imperative.

4.2. CO₂ Geological Sequestration Monitoring at the Site Level

Based on the lithology and physical properties of both the study area and the target reservoir, appropriate geophysical monitoring technologies are selected.

A.

Structural and residual sequestration

Depending on the specific types of sequestration sites and geological characteristics, a combination of seismic monitoring, fiber optic monitoring, and logging technologies is employed to achieve optimal monitoring outcomes. For instance, in deep coal seams, depleted oil and gas reservoirs, and saline aquifers within sedimentary rocks, as well as basaltic formations, all three technologies can be utilized concurrently. Whereas for CO₂ sequestration in carbonate rocks, it is more prudent to select fiber optic and logging monitoring techniques;

• B. Dissolution sequestration

Given the inherent limitations of seismic and fiber optic monitoring methods during this phase, priority should be given to logging technology. Additionally, suitable detection methods must be chosen based on the type of target reservoir; for example, three-head pulse neutron logging and four-head pulse neutron logging are particularly effective for CO₂ sequestration in depleted oil and gas reservoirs;

• C. Mineralization sequestration

The mineralization process typically spans several decades; therefore, this stage necessitates employing time-lapse seismic monitoring technology alongside integrated fiber optic systems and other relevant methodologies for comprehensive oversight.

Basaltic extrusive rock, exemplified by basalt, is categorized as a dark, fine-grained, cryptocrystalline igneous rock with a magnesium–iron mineral content ranging from 45% to 85%. The distinctive gas bubbles and fractures formed during the cooling and tectonic processes significantly enhance the porosity and permeability of the rock matrix, thereby providing effective storage capacity for geological CO₂ sequestration [55].

When supercritical CO₂ is injected into basalt formations, it initially reacts with water to produce carbonic acid, which not only reduces the pH of the solution but also increases its reactivity with minerals. This process facilitates the dissolution of primary minerals within the basalt matrix and releases cations, such as Ca²⁺, Mg²⁺, and Fe³⁺, into the solution. The released divalent cations subsequently react with dissolved CO₂ to form stable carbonate minerals, including calcite, magnesite, and siderite [56,57]. The rapid dissolution of silicate rocks and the release of divalent cations from the matrix can effectively facilitate permanent carbonation. The selection of appropriate silicate rocks, enhancement of the mineral–fluid interface surface area, elevation in temperature, or injection of high-reactivity fluids can significantly expedite the dissolution process [58,59].

To maximize the surface area for mineral–fluid interactions, it is essential to select appropriate porous fractured rocks that allow injected CO₂ to penetrate as deeply into the rock matrix as possible. Consequently, basalt may exhibit a higher reaction efficiency compared to other basaltic and ultramafic rocks. Notably, as the pH value increases downstream of the injection well, the precipitation of secondary minerals (such as calcite and magnesite) can diminish the available reaction surface area, ultimately resulting in blockages within migration channels [60]. Marini found that the interaction between carbon dioxide and basalt aquifer water leads to a reduction in porosity; therefore, it is essential to control the temperature and composition of the injected fluid to optimize the release rate of divalent cations [61]. The dissolution rate of basalt is a function influenced by pH, temperature, and other factors, while the solubility of carbon dioxide in water increases with pressure. Consequently, appropriately elevating the injection fluid to critical pressure levels will facilitate an acceleration in the dissolution rate [62,63];

• D. Well integrity

For site-level assessments of well integrity, a combined approach utilizing both fiber optic sensing and logging technologies is recommended. When implementing fiber optic monitoring techniques, one may draw upon advanced practices from oilfield development—such as distributed acoustic sensing or distributed temperature sensing—to facilitate real-time surveillance of well integrity. Furthermore, various assessment measures, including reservoir saturation testing, acoustic testing, cement bond evaluation, and delayed ultrasonic testing, can provide thorough evaluations.

4.3. Monitoring Data Processing:

Given the substantial volume of monitoring data and the multitude of parameters involved, it is essential to employ machine learning algorithms for processing geophysical monitoring data related to CO₂ geological sequestration and generating predictive outcomes. Among various machine learning techniques, deep learning methods should be prioritized, including convolutional neural networks, feedforward neural networks, and fully convolutional networks. Notably, when the injection speed of CO₂ exceeds 150 m/s, the predictive performance of fully convolutional networks (FCNs) demonstrates a distinct advantage. The primary benefit of utilizing machine learning algorithms for predicting CO₂ sequestration volumes lies in their ability to continuously adjust network parameters and autonomously identify complex patterns, thus producing high-quality predictions and classifications (Figure 3).

5. Conclusions

Based on the monitoring outcomes and technical insights of CO₂ geological sequestration, a systematic analysis was performed on the geophysical monitoring technologies applicable to CO₂ geological sequestration. A comprehensive set of multi-scale matching recommendations has been proposed for the entire process, spanning from laboratory scale to site level, with a focus on various sequestration sites and monitoring objectives. The recommended approach encompasses several critical stages, including initial screening of suitable reservoirs, conducting rock physics simulation experiments, and implementing field monitoring, as well as data processing and result evaluation. Additionally, a thorough compilation of multi-scale matching recommendations for geophysical monitoring in CO₂ geological sequestration—from laboratory scale to site level—targeting diverse sequestration sites and monitoring goals has been summarized.

(1) During the initial screening stage, a comprehensive geological survey should be conducted on potential reservoirs, integrating existing data to assess rock properties, hydrological conditions, and other pertinent factors in a holistic manner to identify the most promising sequestration sites. This process typically involves analyzing historical drilling data and current groundwater level information within the region while also considering the potential impacts of climate change on the subsurface environment. Subsequently, rock physical simulation experiments should be performed to obtain more precise parameters, thereby providing a scientific basis for subsequent monitoring efforts. These experiments facilitate researchers’ understanding of CO₂ behavior patterns across various reservoir types, ultimately optimizing injection strategies;

(2) During the on-site monitoring phase, advanced technological tools, such as fiber optic sensors, acoustic detection methods, and electromagnetic techniques, should be employed to capture real-time changes in the wellbore and surrounding environment, thereby facilitating an effective evaluation of the dynamic behavior associated with CO₂ injection. In monitoring CO₂ saturation, plume migration, and distribution, seismic monitoring techniques and logging methodologies can be utilized independently; however, fiber optic monitoring is typically integrated with seismic approaches. Most seismic and fiber optic monitoring technologies leverage neutron logging data for comparative analysis when assessing CO₂ saturation levels. Fiber optic sensors are capable of detecting variations in temperature and pressure, while acoustic detection methods can identify fractures or pore structures. Furthermore, data should be systematically collected at regular intervals across different time points to allow for timely adjustments to injection strategies and the optimization of overall sequestration effectiveness. By establishing a long-term monitoring framework, it ensures that all indicators consistently remain within safe limits;

(3) In the data processing and result evaluation phase, the integration of machine learning algorithms can significantly enhance the capability to identify complex patterns, thereby facilitating efficient data analysis. These algorithms are applicable for processing large, multi-dimensional datasets, thereby empowering the system to automatically identify potential issues and enhance decision-making efficiency. Furthermore, through iterative model refinement, prediction accuracy will progressively increase, rendering future projects more reliable. This series of measures will ensure that the entire CO₂ geological sequestration process is safer and more efficient while providing a reference methodology for analogous future projects, thus contributing significantly to global efforts in addressing climate change.