Geologic Carbon Storage Research Articles

A framework to simulate the blowout of CO2 through wells in geologic carbon storage

It is important to evaluate the risks associated with CO2 leakage in large scale carbon capture and storage (CCS) projects. Leaky wells are considered a major concern for potential CO2 leakage in geologic carbon storage. The most rapid and spectacular mode of CO2 leakage is the blowout of a CO2 storage well. The Sheep Mountain CO2 blowout in March 1982 is an example of this type of catastrophe wherein several thousand tons of CO2 were released into the atmosphere every day. The blowout was stopped only in early April. In the current work we present a numerical framework to simulate blowouts of CO2 wells accounting for the supercritical-liquid–gas–solid phase transitions of CO2 during the process. It is an in-house finite volume method based code for CO2 transport in open wells, relying on a hybrid Span–Wagner equations of state. We present extensive verification and validation of the code against numerical and experimental data in the literature. When applied to well blowouts, our numerical method is able to identify the locations along the well where CO2 transitions between its different phases. Our simulations show that while the heat transfer between CO2 and the casing has a significant impact on the transient characteristics of the blowout, it does not affect the steady-state leakage rate significantly. We also find that the CO2 leakage rate increases as the total depth of the well increases, with an average leakage rate of 2.09×104 tons per day across all the well depths simulated ranging between 1 km and 3.5 km. Our simulations show that when the temperature and pressure at the well bottom are appreciably lower than the geothermal temperature and hydrostatic pressure at the given depth, CO2 is released as dry ice at the wellhead. The dry ice modeled here has a significant time-averaged mass fraction of 30% at quasi-steady state, and causes rapid fluctuations in the CO2 leakage rate.

Shallow Geologic Storage of Carbon to Remove Atmospheric CO2 and Reduce Flood Risk.

Geologic carbon storage currently implies that CO2 is injected into reservoirs more than 1 km deep, but this concept of geologic storage can be expanded to include the injection of solid, carbon-bearing particles into geologic formations that are one to two orders of magnitude shallower than conventional storage reservoirs. Wood is half carbon, available in large quantities at a modest cost, and can be milled into particles and injected as a slurry. We demonstrate the feasibility of shallow geologic storage of carbon by a field experiment, and the injection process also raises the ground surface. The resulting CO2 storage and ground uplift rates upscale to a technique that could contribute to the mitigation of climate change by storing carbon as well as helping to adapt to flooding risks by elevating the ground surface above flood levels. A life-cycle assessment indicates that CO2 emissions caused by shallow geologic storage of carbon are a small fraction of the injected carbon.

Preface: Carbon Geological Utilization and Storage

Preface: Carbon Geological Utilization and Storage

A geochemically informed leak detection (GILD) model for CO2 injection sites

Early detection of CO2 leakage through monitoring is important to ensure long-term safety for geologic carbon storage (GCS). A geochemically informed leak detection (GILD) model has been developed for groundwater chemistry monitoring at CO2 injection sites. The GILD model integrates a geochemical model that simulates fluid chemistry changes in CO2 leakage events and a Bayesian belief network (BBN) model that evaluates monitoring observations to identify leakages. The geochemical model is implemented using Geochemists’ Workbench to assess fluid chemistry changes as a result of small CO2 leakage in an above-zone monitoring interval (AZMI) formation with varying mineral assemblages and background fluids. Response functions are fitted to the output of the geochemical model and are translated to conditional probabilities in the BBN model. The BBN model gives operational prediction of the leak probability given a set of groundwater monitoring measurements and the probability of detecting a leak at a given magnitude. The detection capabilities of multiple monitoring parameters are compared. For aquifers that contain calcite, it is valuable to incorporate other monitoring parameters with pH to increase the sensitivity of detection. For aquifers with no calcite, pH alone is a sensitive parameter. This research illustrates a method of identifying CO2 leakage into aquifers with both geochemical and statistical tools.

Microseismic Monitoring at the Farnsworth CO2-EOR Field

The Farnsworth Unit in northern Texas is a field site for studying geologic carbon storage during enhanced oil recovery (EOR) using CO2. Microseismic monitoring is essential for risk assessment by detecting fluid leakage and fractures. We analyzed borehole microseismic data acquired during CO2 injection and migration, including data denoising, event detection, event location, magnitude estimation, moment tensor inversion, and stress field inversion. We detected and located two shallow clusters, which occurred during increasing injection pressure. The two shallow clusters were also featured by large b values and tensile cracking moment tensors that are obtained based on a newly developed moment tensor inversion method using single-borehole data. The inverted stress fields at the two clusters showed large deviations from the regional stress field. The results provide evidence for microseismic responses to CO2/fluid injection and migration.

A quantitative risk assessment approach for developing contingency plans at a geologic carbon storage site

AbstractGeologic carbon storage (GCS) is an increasingly important technology for reducing carbon dioxide (CO2) emissions to the atmosphere. The leakage risks associated with GCS are an environmental and human health concern, however, and site operators must develop contingency plans that thoroughly consider leakage risks and identify potential mitigation strategies. Here, we use a GCS system model (the National Risk Assessment Partnership's Open‐Source Integrated Assessment Model, NRAP‐Open‐IAM) to evaluate different contingency plans for a hypothetical GCS site. In the scenario considered, an unplugged legacy well is discovered near the site after 5 years of CO2 injection. Our simulations show that the planned operation has a relatively high chance of causing brine leakage through the legacy well and into the two overlying aquifers, the shallower of which has potable water—an unacceptable outcome. To reduce this risk, we consider five remedial response scenarios that manipulate reservoir pressures through brine extraction, injection rate reduction, and early injection stopping. NRAP‐Open‐IAM is used to quantify the degree to which each scenario reduces the probability of brine leakage at the site amidst reservoir uncertainty. Evaluation of the different scenarios suggests that reduction of injection rates effectively reduces leakage risks while maintaining a substantial fraction of the initially intended cumulative CO2 storage. In the event of an emergency, the reservoir pressure management strategies considered here can provide operators more time while they pursue a more permanent solution. The analyses demonstrated here fit into a larger workflow we propose for evaluating the contingency plans of GCS sites. © 2023 Society of Chemical Industry and John Wiley & Sons, Ltd.

Effect of foam quality on foam three phase displacement characteristics in porous media-A mechanistic numerical study

Foam technology has shown great potential in enhancing oil recovery as well as fulfilling carbon geological storage practices in mature and low permeability reservoirs. To reveal the mechanism of the foam quality effect on foam displacement behavior in underground formations, numerical studies on three-phase foam flow characteristics in porous media have been carried out based on the Stochastic Bubble Population Balance (SBPB) model. Through modifying the injection gas and liquid rate ratio, various foam qualities between 40% and 90% have been set, and the effect of foam quality was taken into account with higher foam quality corresponding to the larger maximum bubble density parameter in the SBPB model. Comprehensive numerical results, including the dynamic distribution curves of the oil, water, and foam phase saturation, oil phase pressure, and the foam bubble density along the flow direction, were obtained under different foam quality cases. Parameter investigations on the bubble generation rate and the oil viscosity were carried out as well. It is observed the pressure drop and water recovery rate of the foam flooding process increases monotonously with the increasing foam quality, while the ultimate oil recovery rate shows the highest value at the intermediate foam quality of 70%. The numerical results on the foam quality effect agree well with reported experimental observations, indicating the SBPB model could characterize in mechanism the three phase foam displacement behavior in porous media.

Experimental and modelling study of the interfacial tension of (n-decane + carbon dioxide + water) in the three phase region

The interfacial tensions (IFTs) between hydrocarbon-, water- and CO2-rich phases are important in the processes of carbonated water injection for enhanced oil recovery and carbon geological storage. In this work, the IFTs between decane-rich and water-rich phases, in the presence of the third CO2-rich phase, were measured by the pendant drop method and modelled with the density gradient theory at temperatures from 298.15 K to 353.15 K and at pressures up to the critical point pressure of (CO2 + decane) (maximum 11 MPa at 353 K). The dynamic IFT decreased over time due to CO2 adsorption on the interface and mass transfer into the decane-rich drop until equilibrium was reached. As expected, the equilibrium IFTs were observed to decrease with increasing pressure. At low pressures, the equilibrium IFTs decreased with increasing temperature while, at high pressures, the reverse was observed. By comparing the IFTs of ternary (decane + CO2 + H2O) system with those of binary (decane + H2O) system, it was found that CO2 could reduce system IFT, for example by 15.2 mN/m at T = 333 K and p = 10 MPa. The extent of reduction depends on the solubility of CO2 in the liquid phases and the adsorption amount at the interface. Furthermore, the equilibrium IFT was found to be linearly dependent on the CO2 concentration in the water-rich phase isothermally, and an empirical relation was developed with an average absolute deviation of 0.3 mN/m. Density gradient theory coupled with the volume translated CPA equation of state was found to provide an accurate description of the IFTs with an average absolute deviation of 0.8 mN/m, proving its capability of predicting IFTs of (alkane + CO2 + water) in the three-phase region. The density profile in the interfacial region is also demonstrated. There is an enrichment of CO2 molecules at the interface and the enrichment is more pronounced with increasing pressure or decreasing temperature.

Experimental determination of gas-water relative permeability for ultra-low-permeability reservoirs using crushed-rock samples: Implications for drill cuttings characterization

Relative permeability controls fluid flow through rocks, with applications to hydrocarbon production, geologic carbon and energy storage. However, significant challenges are associated with the measurement of relative permeability for rocks with matrix permeability in the microdarcy to nanodarcy range. The primary objectives of this study are therefore to 1) propose an integrated experimental and modeling approach for gas relative permeability (krg) evaluation using crushed-rock samples and 2) perform a proof-of-concept study to demonstrate that gas–liquid relative permeability can be determined for ultra-low-permeability (unconventional) reservoir samples that have been crushed to certain grain sizes (20–35 mesh size).In this study, the water vapor ad-/desorption technique was employed to provide a wide range of water saturations (Sw). The evolution of water distribution in the shale matrix with a change in Sw was investigated by using a modified low-pressure adsorption (LPA) technique. A recently-developed numerical model was modified to estimate effective permeability to gas at each saturation level. Four clay-rich shales from the Duvernay (Canadian) and Kyalla (Australian) formations were analyzed.The vapor ad-/desorption technique provided an efficient approach to saturate the studied samples. By changing relative humidity in sealed desiccators using different salt solutions, a maximum Sw of 83% was obtained for organic-matter rich samples, and 99% for organic-matter lean shales. As interpreted using the modified LPA technique applied at different saturation levels, water is held in films in mineral-associated macro-/mesopores, and can block access to organic-matter pores through the formation of water clusters, significantly reducing the accessible organic-matter porosity and gas effective permeability. Imbibition krg decreases rapidly and significantly (over 90%) when Sw reaches approximately 0.3–0.4 for samples containing significant amounts of water-sensitive clay minerals (Kyalla #2) and TOC (Duvernay #2). Relative permeability hysteresis occurs for Duvernay #2 and Kyalla #1. Overall, the use of crushed-rock samples (non-matrix/fracture system), and application of the vapor sorption technique, results in a small amount of hysteresis.A laboratory-based method for measuring gas relative permeability of ultra-low-permeability reservoirs using crushed-rock samples is provided for the first time, with important applications to the energy and carbon capture industries.

High-resolution geologic modeling and CO2 flow simulation of a realistic clastic deltaic 3D model derived from a laboratory flume tank experiment

Carbon sequestration in geologic reservoirs is a proven method for reducing carbon dioxide (CO2) emissions from industrial point sources. Subsurface deltaic deposits are attractive candidates for CO2 storage projects due to their common occurrence as host to significant hydrocarbon and hydrologic resources, and are highly prospective for subsurface storage of large volumes of CO2. This research informs subsurface passive margin deltaic reservoir characterization and fluid flow performance for geologic carbon storage. The objective of this research is to create a high-resolution geocellular digital model that honors both the large-scale stratigraphic architecture and local vertical and lateral facies heterogeneity represented in deltaic environments of deposition. We present a novel approach to reservoir model generation by utilizing a previously generated meter-scale physical flume sand tank analog experiment to represent realistic deltaic stratigraphic architectures and facies distributions. The result is an extremely high-resolution geologic model that can be used for a variety of applications, including single and multiphase fluid flow simulation. An application is presented using the example model to simulate buoyant fluid (CO2) migration and resulting saturation distribution. Results emphasize the importance of recognizing sequence stratigraphic architectures in deltaic depositional settings for predicting CO2 migration and retention (storage capacity).

Perspectives on geologic carbon storage

Geologic carbon storage (GCS) is a fundamental pillar of carbon management that helps mitigate greenhouse gas emissions and addresses the negative effects of climate change. Viable CO2 storage sites share some of the same elements required for successful petroleum systems. For example, while reservoir, seal, and trap are required, migration pathway and timing are not important for CO2 storage, because rather than withdrawing fluid from a trap, CO2 storage involves injection into a geologic trap. Conceptually, this represents a form of reverse production. Numerous petroleum traps around the world, as well as naturally occurring CO2-producing fields and natural gas storage sites attest that safe, long-term storage is possible. Research over the past two decades identified five methods of Geologic Carbon Storage which have been validated through several demonstration and pilot projects around the world: (1) storage in depleted oil and gas fields, (2) use of CO2 in enhanced hydrocarbons recovery (3) storage in saline formations/aquifers, (4) injection into deep unmineable coal seams, and (5) in-situ/ex-situ carbon mineralization. The greatest volumetric potential for GCS is found in saline aquifers which are present throughout the world’s sedimentary basins.

Effects of abiotic processes on the correlation between pH and pO2 in the Norwegian Sea: Implications for GCS monitoring

In the absence of abiotic sources of CO2, variation in pCO2 and pO2 is expected to be inversely correlated in the water column due to biogenic processes. It has previously been suggested to use this correlation for leakage monitoring of offshore geological carbon storage (GCS) sites. In this study the aim is to investigate the extent of this correlation in ocean water masses with different origin and history in the Norwegian Sea, as well as in water masses in the vicinity of an active hydrothermal vent field at Mohn's Ridge, where pH is used as a proxy for pCO2. Over a hydrothermal vent site, a strong correlation between pH and pO2 is observed from 0 to 1700 m, whereas at depths >1700 m there is no correlation, likely due to CO2 emissions from the hydrothermal vents. However, at a reference site nearly 200 km from the hydrothermal vents, the intermediate Arctic water masses (700 – 1600 m depth) also show pH-pO2 correlations that are inconsistent with biogenic processes, but less pronounced compared to the hydrothermal vent site. These findings show that the suitability of this monitoring strategy will depend on a thorough site-specific evaluation of pH/CO2 and O2 relationships of relevant water masses.

Influence of two-phase displacement characteristics on the storage efficiency and security of geological carbon storage

In the mitigation of greenhouse gas emissions, the storage efficiency and security of geological carbon storage (GCS) are the focus of attention, and both of them are closely related to the displacement behavior between immiscible two phases. In this study, CO2-water two-phase displacement experiments were conducted on six samples with various pore structures using nuclear magnetic resonance and magnetic resonance imaging technology to characterize the fluid distribution and determine displacement patterns. The displacement property was found to be closely related to the heterogeneity and anisotropy of pore structure. The two-phase displacement instability gradually evolved from tonguing (logCa > −2.94) to capillary fingering (logCa < −2.03), and then further evolved into viscous fingering (logCa > −2.03). Nevertheless, rocks with good connectivity and high permeability will restrain the occurrence of unstable displacement even if logCa is in the favorable range. Combined analyses of displacement patterns and pore structure can provide effective means for the evaluation of reservoir and caprock. For rocks dominated by micropores, their displacement pattern is more likely to correspond to time-consuming piston-like displacement. Their high sealing efficiency is characterized by high capillary displacement pressure and low effective gas permeability, which allow them to be considered as caprocks. For rocks with lower capillary displacement pressure and higher effective gas permeability, their lower residual water saturation makes them more suitable as favorable reservoirs for GCS. Reservoir rocks with stable piston-like displacement exhibit the highest displacement efficiency, while the difference of displacement rates in pores with diverse sizes caused by the fingering or tonguing phenomena weakens the displacement efficiency.

Reviews

Geophysical Monitoring for Geologic Carbon Storage, edited by Lianjie Huang, 2022.

Aqueous formate solution for enhanced water imbibition in oil recovery and carbon storage in carbonate reservoirs

This paper presents an experimental study of the injection of aqueous formate solution into oil-wet carbonate porous media at different formate concentrations and acidity levels. The research was motivated by the potential use of aqueous formate solution as a wettability modifier in enhanced oil recovery and/or a carbon carrier in geological carbon storage in carbonate reservoirs. However, the wettability alteration of carbonate rocks by formate has not been tested at elevated concentrations of formate or in any coreflood. The experimental program in this research consists of aqueous stability, wettability alteration, and three dynamic imbibition experiments with fractured carbonate cores with varying formate concentrations up to 30 wt% and initial pH between 6 and 7.With an excess amount of calcite powder, the 20 wt% formate solution in 15000 ppm NaCl brine showed essentially the same pH history as the base NaCl brine, where calcite dissolution caused the solution pH to increase to a stable value near 9. None of the samples studied in this research showed solid precipitation. Material balance of dynamic imbibition data indicated that the imbibition of formate into the matrix was most significant in coreflood #1, in which 30 wt% formate solution was injected into a fractured carbonate core. A large gradient in formate concentration between the fracture and the matrix likely caused the rapid mass transfer. Then, calcite dissolution and the resulting formate species caused wettability alteration to enhance water imbibition, which in turn expelled the oil in the matrix.The incremental oil recovery factor was 9.1 % for 30 wt% formate (pH = 7; coreflood #1), 2.9 % for 5 wt% formate (pH = 7; coreflood #2), and 7.0 % for 5 wt% formate + HCl (pH = 6; coreflood #3). A greater oil recovery factor resulted from a greater concentration of formate and a reduced pH. This is the first time corefloods were performed with aqueous formate solution at elevated concentrations up to 30 wt%.

Physics-informed machine learning for fault-leakage reduced-order modeling

Geologic carbon storage (GCS) is a promising technology for mitigating CO2 emissions. The overall success of GCS depends on safe operations that are informed by risk assessment and have proper mitigation plans in place. Performing quantitative probabilistic risk assessment for a GCS site using traditional reservoir simulators can be challenging due to the high computational costs. To overcome this challenge, the US Department of Energy’s National Risk Assessment Partnership (NRAP) project has developed an integrated assessment modeling approach that utilizes computationally efficient reduced-order models (ROM) for simulating various parts of a GCS storage site to quantify uncertainty. In this study, we develop a reduced-order model for fault leakage risk assessment. We use a deep learning approach to build the reduced-order model. We perform a sensitivity analysis and find that the deep learning model yields high accuracy with a much smaller computational cost than full-physics simulation. We also evaluate the performance of the model in scenarios where simulations are not possible to run, providing analysis not previously performed in fault-leakage ROM analyses. Based on a sensitivity analysis of the model, we suggest a simplified conceptual model for fault leakage and site monitoring.

Modeling-Based Assessment of Deep Seismic Potential Induced by Geologic Carbon Storage

Abstract Induced seismicity is an inherent risk associated with geologic carbon storage (GCS) in deep rock formations that could contain undetected faults prone to failure. Modeling-based risk assessment has been implemented to quantify the potential of injection-induced seismicity, but typically simplified multiscale geologic features or neglected multiphysics coupled mechanisms because of the uncertainty in field data and computational cost of field-scale simulations, which may limit the reliable prediction of seismic hazard caused by industrial-scale CO2 storage. The degree of lateral continuity of the stratigraphic interbedding below the reservoir and depth-dependent fault permeability can enhance or inhibit pore-pressure diffusion and corresponding poroelastic stressing along a basement fault. This study presents a rigorous modeling scheme with optimal geological and operational parameters needed to be considered in seismic monitoring and mitigation strategies for safe GCS.

Gas adsorptions of geological carbon storage with enhanced gas recovery

Understanding gas adsorptions in porous media is of critical importance to numerous academic research and industrial applications. Here, adsorptions of methane and carbon dioxide, which are primary compositions of natural gas and carbon capture and storage (CCS) processes, on different minerals are specifically investigated and their effects on reservoir productions and carbon storage processes are evaluated. First, an improved simplified local-density (SLD) model is developed to calculate the gas adsorptions by considering the complex porous composition and confinement effects induced phenomena. Then, the improved SLD model is embedded into a self-developed field simulation program to analyse the production processes of a selected large-scale gas reservoir. The proposed improved adsorption model is validated to be accurate for various multiscale minerals at different temperature and pressure conditions. By using the coupling with reservoir numerical simulation, the adsorption model is successfully up-scaled to practical field scale which is efficient and effective for predicting gas productions and analysing relevant influential factors, such as temperature, pressure and reservoir physical properties. The proposed theoretical approach provides strong technical support for future natural gas productions and CCS projects with its capability of calculating gas adsorptions on different minerals and practical gas field productions.

Study Explores Potential of Carbon Leakage in Denver-Julesburg Basin Wells

_ This article, written by JPT Technology Editor Chris Carpenter, contains highlights of paper SPE 210256, “Wellbore-Integrity Impact on Carbon Leakage To Ensure Safe Geological Sequestration,” by Yanrui Ning, SPE, and Ali Tura, Colorado School of Mines. The paper has not been peer reviewed. _ In the complete paper, poorly understood leakage potential is researched to quantify the carbon-leakage rate along one legacy well when carbon is injected into a storage formation in the Denver-Julesburg (DJ) Basin. The authors’ results indicate that, for secure carbon sequestration, a good geological storage site should be kept away from wells that have a surface casing depth of 476 ft or shallower and that were drilled before 1994. The effective well permeability highly affects leakage rate, suggesting the importance of estimating the most-representative value or range for this parameter. Introduction To estimate risks associated with geological carbon storage, the National Risk Assessment Partnership (NRAP) Open-Integrated Assessment Model (IAM) tool used in this study presents a modeling approach that can couple efficient reservoir and wellbore components with low computational cost. Two wellbore model components, the open-wellbore model and the multisegmented-wellbore model, were studied to estimate the leakage rate during and after carbon-injection operations. The effective permeability of the disturbed zone outside the well casing is an important parameter in leakage models. However, estimating a reasonable range for the effective well permeability of the disturbed zone remains a challenge. For this study, a more than 1-sq-mile section in the Wattenberg Field of the DJ Basin was used. The goal was to quantify the leakage rate when carbon dioxide (CO2) escapes through a well 1,100 ft from the CO2 injector. First, a reservoir simulation model was built to reflect the pressure and saturation changes during the 30-year injection period and the 100-year postinjection period. This model, based on an ongoing field study, included the CO2 injector, the legacy well that is the potential pathway of CO2 leakage, and the carbon storage formation. Study Area Carbon Storage Potential in Colorado. The top-ranked CO2 emission facilities in Colorado are above the DJ Basin. According to carbon-emission data, 13 facilities in Colorado, including five coal plants, emitted more than 0.7 million tons of CO2 in 2020. All the coal plants are scheduled to be retired by 2034. All eight CO2 emission facilities are in the DJ Basin, with half of those in the Wattenberg Field. This makes the DJ Basin, especially the Wattenberg Field, a good target for carbon storage. The stacked formations of oil and gas reservoirs and saline aquifers in the DJ Basin are potential CO2-storage formations. The current drilling activities with multistage fracture stimulation of horizontal wells target the oil- and gas-producing zones of Niobrara through Greenhorn. These oil and gas producers penetrate the shallower Pierre sandstone formation. This study quantifies the carbon-leakage risk when the Pierre sandstone is the carbon-storage formation and when one nearby Niobrara legacy well penetrates the storage formation and may behave as a potential leakage pathway.

Derisking geologic carbon storage from high-resolution time-lapse seismic to explainable leakage detection

Geologic carbon storage represents one of the few truly scalable technologies capable of reducing the CO2 concentration in the atmosphere. While this technology has the potential to scale, its success hinges on our ability to mitigate its risks. An important aspect of risk mitigation concerns assurances that the injected CO2 remains within the storage complex. Among the different monitoring modalities, seismic imaging stands out due to its ability to attain high-resolution and high-fidelity images. However, these superior features come at prohibitive costs and time-intensive efforts that potentially render extensive seismic monitoring undesirable. To overcome this shortcoming, we present a methodology in which time-lapse images are created by inverting nonreplicated time-lapse monitoring data jointly. By no longer insisting on replication of the surveys to obtain high-fidelity time-lapse images and differences, extreme costs and time-consuming labor are averted. To demonstrate our approach, hundreds of realistic synthetic noisy time-lapse seismic data sets are simulated that contain imprints of regular CO2 plumes and irregular plumes that leak. These time-lapse data sets are subsequently inverted to produce time-lapse difference images that are used to train a deep neural classifier. The testing results show that the classifier is capable of detecting CO2 leakage automatically on unseen data with reasonable accuracy. We consider the use of this classifier as a first step in the development of an automatic workflow designed to handle the large number of continuously monitored CO2 injection sites needed to help combat climate change.