Natural Gas Storage Site Research Articles

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.

Application of hybrid artificial intelligent models to predict deliverability of underground natural gas storage sites

Underground natural gas storage is a promising solution to lowering greenhouse gas emissions and attaining sustainable development goals. However, several issues prevent the application of storage projects on a global scale. An accurate estimation of the delivered amount of natural gas from each storage site might be used for supply and demand. Due to this fact, this study proposed hybrid intelligent models integrating the least square support vector machine (LSSVM), differential evolution (DE), imperialist competitive algorithm (ICA), cultural algorithm (CA), teaching learning-based optimization (TLBO), genetic algorithm (GA), and particle swarm optimization (PSO) for approximating the deliverability of underground natural gas storage in different geological formations. We have employed vast data sets of 782 reservoirs from depleted fields to train and validate the proposed intelligent models to predict underground natural gas storage deliverability in the USA. The visual and analytical assessments were used to investigate the performance of the developed intelligent systems. The predicted results showed that all of the intelligent models agreed with the recorded data. Moreover, the statistical indicators revealed that the LSSVM coupling TLBO model shows the highest accuracy in predicting the deliverability of natural gas storage in the depleted field among three intelligent models. Also, the optimal intelligent model accurately predicts 880 and 600 data measurements of saline aquifers and salt domes, respectively. The optimal intelligent model yields a root mean square error (RMSE) value of less than 0.022. The correlation factor (R2) is over 0.998, 0.999, and 0.906 for the depleted field, saline aquifers, and salt domes, respectively. The results highlight the importance of combining smart approaches with nature-inspired strategies in forecasting storage site deliverability. In light of these findings, researchers are better equipped to reduce petroleum energy usage and increase community acceptability of natural gas as part of the transition to green energy.

Dynamic Sealing Behavior of Sand Self-Juxtaposition Windows on a Trap-Bounding Fault in a Natural Gas Storage Site

Abstract An understanding of across-fault seals is essential for planning an injection/production strategy for a fault-bounded gas storage site. In addition, it is more likely to permit lateral leakage for a fault with sand self-juxtaposition windows. This paper is aimed at identifying the dynamic sealing behaviors of a sand self-juxtaposition fault on the geological and gas injection timescales. Banzhongbei gas storage site, China, was taken as a target area, and fault seals and hydrocarbon distributions within the original reservoirs were studied. The results showed that across-fault pressure differences of 0.085~0.146 MPa (equivalent to 41.6~71.5 m oil-column and 27.0~46.4 m gas-column heights) were supported by sand self-juxtaposition windows on the B816 fault, and the resultant absolute permeability (5.97×10−2~5.69×10−1 mD) of the fault was nearly 3~4 orders of magnitude lower than the average absolute permeability of reservoirs (1.16×102 mD). Gas composition contrasts, between the original and injection gas coupled with dynamic pressure monitoring data, indicated that lateral leakage occurred across sand self-juxtaposition windows under the condition of high across-fault pressure difference. However, the low-permeability fault showed strong negative influence on the efficiency of fluid flow in the model calculations and prolongs the timescales of pressure-difference decayed as much as 5 orders of magnitude relative to those of nonfault model calculations. These modeled dynamic sealing behaviors of sand self-juxtaposition windows may lead to a better understanding of the relative retardation of across-fault gas flow by weak sealing faults on the gas injection/production timescale.

Knowledge-based rigorous machine learning techniques to predict the deliverability of underground natural gas storage sites for contributing to sustainable development goals

This study presents a method to develop a series of unique deliverability smart models for underground natural gas storage (UNGS) in different types of target formations. The natural gas supply loop is defined by periodic mismatches between demand and supply. Efficient and faster approaches for forecasting UNGS deliverability may not only assist stakeholders but also the competitive natural gas industry. Due to this fact, this article suggests a series of robust deliverability estimation models for 387 UNGS sites in depleted fields, aquifers, and salt domes based on rigorous machine learning (ML) techniques. To this end, the potential of three ML algorithms, including Gaussian Process Regression (GPR), Least Squares Support Vector Machine (LSSVM), and Extra Tree (ET), is employed. To assess and compare the proposed models, statistical parameters including coefficient of determination (R2), root mean square error (RMSE), mean absolute error (MAE), and standard deviation (SD) were employed. Accordingly, in the case of depleted fields, the GPR, LSSVM, and ET paradigms show overall R2, RMSE, and MAE of 0.999999998, 4.75E−06, 0.00021, and 0.00021. For salt domes, the GPR, LSSVM, and ET models indicate overall R2, RMSE, and MAE of 0.987, 0.0046, and 0.11. Finally, for aquifers, the GPR, LSSVM, and ET algorithms represent overall R2, RMSE, and MAE of 0.999999997, 7.1094E−06, and 0.0002102. The prediction performance reveals that the GPR model is superior to the LSSVM and ET models. This study found that the proposed intelligent models could be utilized as a template for fast estimating the deliverability of UNGS in depleted fields, aquifers, and salt domes with high accuracy. In the end, the outcomes of this study contribute to a deeper understanding of the critical role of machine learning in resolving the difficulty of forecasting the UNSG on cleaner production and sustainable development strategies.

Monitoring natural gas storage using Synthetic Aperture Radar: are the residuals informative?

SUMMARY Estimates of line-of-sight (LOS) displacements from Interferometric Synthetic Aperture Radar (InSAR) observations serve as the basis of the long-term monitoring of an operating natural gas storage site at Honor Rancho in California. An inversion algorithm is used to estimate the portion of the signal that is attributable to deformation within the gas storage reservoir, located at a depth of around 3 km. Removing this contribution produces residuals that are used to characterize the background variation is surface deformation at the gas storage facility and to determine a threshold that can signify unusually large residuals. An application to almost 7 yr of InSAR data, from 2011 until 2018, indicates that there are intervals of heightened residuals as well as brief episodes of anomalously large misfits. An examination of the spatial distributions of the individual residual LOS displacements indicates larger displacements in an alluvial valley just south of the reservoir, with rapid spatial variations in sign, indicating a rather shallow origin. Furthermore, the two anomalous events also involve rapid spatial variations in the LOS displacement residuals directly above the storage facility. The results demonstrate that the technique of extracting residuals after removing the reservoir signal is a useful approach, even in the case of this deep reservoir, and is a promising method for long-term monitoring.

Associations among particulate matter, hazardous air pollutants and methane emissions from the Aliso Canyon natural gas storage facility during the 2015 blowout

In October of 2015, a large underground storage well at the Aliso Canyon natural gas storage facility experienced a massive methane leak (also referred to as “natural gas blowout”), which resulted in the largest ever anthropogenic release of methane from a single point source in the United States. Additional sampling conducted during the event revealed unique gas and particle concentrations in ambient air and a characteristic “fingerprint” of metals in the indoor dust samples similar to samples taken at the blowout site. We further investigated the association between the Aliso Canyon natural gas storage site and several measured air pollutants by: (a) conducting additional emission source studies using meteorological data and correlations between particulate matter, methane, and hazardous air pollutants (HAPs) collected during the natural gas blowout at distances ranging from 1.2 to 7.3 km due south of well SS25, (b) identifying the unique i/n-pentane ratio signature associated with emissions from the blowout event, and (c) identifying characteristics unique to the homes that tested positive for air pollutants using data collected from extensive indoor environmental assessment surveys. Results of air quality samples collected near Aliso Canyon during the final weeks of the event revealed that elevated levels of several HAP compounds were likely influenced by the active natural gas blowout. Furthermore, the final attempts to plug the well during the days preceding the well kill were associated with particle emissions likely from the well site. Together, this investigation suggests uncontrolled leaks or blowout events at natural gas storage facilities have the potential to release harmful pollutants with adverse health and environmental consequences into proximate communities. With this evidence, our recommendations include facility-specific meteorological and air quality data-collection equipment installed at natural gas storage facilities and support of environmental surveillance after severe off-normal operation events.

Underground coal mine workings as potential places for Compressed Air Energy Storage

The article gives a brief overview of current developments and projects of Compressed Air Energy Storage (CAES). Typical CAES configurations such as Adiabatic CAES and Diabatic CAES are described. The concept of air storage in isolated workings of closed coal mine is presented taking into account availability of such places in the Silesian Coal Basin of southern Poland. The article also discusses major challenges of such concept such as insulation of underground workings, geomechanical stability of workings and site availability. As a proof of concept examples of underground coal mines converted into natural gas storage sites are given. Types of underground workings that could serve as a part of potential compressed storage site are listed and an example of volume calculation available in coal mine for storage is given.

Prediction of pressure and temperature changes in the salt caverns of Tuz Golu underground natural gas storage site while withdrawing or injecting natural gas by numerical simulations

Tuz Golu (Salt Lake) Underground Gas Storage (UGS) Project in Turkey is being implemented. In some of salt caverns, natural gas is currently stored. While analyzing the data of Tuz Golu UGS project, it was observed that this location is appropriate for safe underground natural gas storage due to its rock salt with high purity and very low permeability. In this study, many numerical simulations for a salt cavern in Tuz Golu UGS project at different gas withdrawal and injection rates were conducted by using TOUGH + RealGasBrine simulator. According to the results of these numerical simulations, the temperature inside salt cavern reduced below 0 °C from 53 °C within 20 days at a rate of gas withdrawal of 3.33 million standard m3/day due to Joule-Thomson effect. The temperature inside salt cavern reduced below 0 °C within 25 days, 40 days, and 60 days at a rate of gas withdrawal of 2.5, 1.67, and 0.833 million standard m3, respectively. In order to avoid fracture around the walls of salt cavern, the temperature change inside salt cavern should not be higher than 30 °C. In the numerical simulations, there is no gas seepages from the salt cavern to other neighbor salt caverns, which are 600 m away owing to very low permeability of salt rock in the study area. The implication of this study is that gas withdrawal and gas injection profiles are quite important to keep the temperature inside salt caverns at an optimum range for safe natural gas storage.

Reusing abandoned natural gas storage sites for compressed air energy storage

This study aims to investigate the feasibility of reusing uneconomical or abandoned natural gas storage (NGS) sites for compressed air energy storage (CAES) purposes. CAES is recognised as a viable means of high-capacity short- to mid-term energy storage. However, the widespread implementation of CAES is limited to geological and geographical settings and requires substantial infrastructure and capital investment. Utility-scale CAES requires a suitable trap that can contain compressed air without significant loss or leakage. Reusing of existing NGS systems and converting them into CAES can reduce the costs of exploration, geomechanical risk assessment and drilling into the trap, as well as the infrastructure cost, compressors and inter/after coolers. The cost, therefore, would be limited to acquirement of the site and installation of turbines, recuperators and transmission lines. The present study compares the net stacked benefit of converting NGS sites into CAES against that of conventional energy storage and development of CAES from the ground up. While site-specific economic analyses and technological viability are needed prior to large-scale implementation, results of this feasibility study suggest that reusing NGS sites for CAES has the potential to offer a cost-effective alternative for utility-scale energy storage.

Assessment of geological resource potential for compressed air energy storage in global electricity supply

This paper presents the geological resource potential of the compressed air energy storage (CAES) technology worldwide by overlaying suitable geological formations, salt deposits and aquifers. For this study, the world is divided into 145 regions, which are aggregated to 9 major regions. The potential of CAES in each region is assessed and a relevant map is provided. Three constraints have been implemented, allowing for 1%, 5% and 10% of the selected area to be considered for CAES. Among all major regions, in the most conservative constraint (1% of the total area), North America is the leader with 0.26% suitability of its total area, followed by Sub-Saharan Africa and South America at 0.20% and 0.19%, respectively. A sensitivity analysis is implemented to evaluate the validity and reliability of the results. Three scenarios are considered: Optimistic, Moderate and Pessimistic. Underground natural gas storage data for the US is used due to freely and publicly available data. The natural gas storage site is assumed to have the same structure as CAES. The sensitivity analysis shows that the accuracy of the findings lie in the range of 66–85% and 63–82%, depending on the scenarios and reservoir types. The results clearly reveal that CAES is a promising energy storage technology for electricity supply in most of the regions. This research presents the groundwork to identify the untapped potential of CAES, which can be also utilized for the second generation of CAES such as adiabatic CAES and isothermal CAES.

MiReCOL: Remediation of Shallow Leakage from a CO2 Storage Site

Within the EU-funded project MiReCOL (Remediation and Mitigation of CO2 Leakage; project number 608608), a comprehensive review was undertaken of techniques available for the remediation of leakage of CO2 to the near surface environment, here defined as the depth range of typical remediation techniques used by the pollution clean-up industry. The review drew from existing relevant fields of experience such as the remediation of groundwater pollution; the remediation of industrial waste; CO2-EOR, natural gas storage sites; the geothermal energy industry; the construction of dams (as barriers to subsurface fluid flow); pilot scale CCS projects and natural analogues.

Analysis of fault leakage from Leroy underground natural gas storage facility, Wyoming, USA

Leroy natural-gas storage site is an anticlinal, fault-bounded, aquifer-storage system located in Wyoming, USA. Based on its abundant data, uncontrolled leakage history and subsequent control by the facility operators, a modeling framework was developed for studying reservoir behavior, examining pressure and gas-inventory histories, as well as gas and brine leakage, and evaluating the sensitivity of that behavior to uncertainty about reservoir properties. A three-dimensional model capturing the bounding fault, layered geologic stratigraphy, and surface topography was calibrated by history data of reservoir pressure and gas inventory. The calibrated model predicted gas arrival at the ground surface that was consistent with the timing of observed gas bubbling into a creek. A global sensitivity analysis was performed to examine the parameters influencing fault leakage, and a geomechanical stability analysis was conducted to investigate the likelihood of fault reactivation. In general, it is shown that a discrete leakage pathway is required to explain the observed gas leakage and its subsequent operational control by reducing reservoir pressures. Specifically, the results indicate that fault leakage is a plausible explanation for the observed gas leakage. The results are relevant to other natural-gas storage sites, as well as other subsurface storage applications of buoyant fluids, such as CO2.

Geochemistry of shallow aquifers and soil gas surveys in a feasibility study at the Rivara natural gas storage site (Po Plain, Northern Italy)

A geochemical survey, in shallow aquifers and soils, has been carried out to evaluate the feasibility of natural gas (CH4) storage in a deep saline aquifer at Rivara (MO), Northern Italy. This paper discusses the areal distribution of CO2 and CH4 fluxes and CO2, CH4, Rn, He, H2 concentrations both in soils and shallow aquifers above the proposed storage reservoir. The distribution of pathfinder elements such as 222Rn, He and H2 has been studied in order to identify potential faults and/or fractures related to preferential migration pathways and the possible interactions between the reservoir and surface. A geochemical and isotopic characterization of the ground waters circulating in the first 200m has allowed to investigation of (i) the origin of the circulating fluids, (ii) the gas–water–rock interaction processes, (iii) the amount of dissolved gases and/or their saturation status. In the first 200m, the presence of CH4-rich reducing waters are probably related to organic matter (peat) bearing strata which generate shallow-derived CH4, as elsewhere in the Po Plain. On the basis of isotopic analysis, no hints of thermogenic CH4 gas leakage from a deeper reservoir have been shown. The δ13C(CO2) both in ground waters and free gases suggests a prevalent shallow origin of CO2 (i.e. organic and/or soil-derived). The acquisition of pre-injection data is strategic for the natural gas storage development project and as a baseline for future monitoring during the gas injection/withdrawing period. Such a geochemical approach is considered as a methodological reference model for future CO2/CH4 storage projects.

3D baseline seismics at Ketzin, Germany: The C O2 SINK project

A 3D 25-fold seismic survey with a bin size of 12 by [Formula: see text] and about [Formula: see text] of subsurface coverage was acquired in 2005 near a former natural gas storage site west of Berlin, as part of the five-year EU funded [Formula: see text] project. Main objectives of the seismic survey were to verify earlier geologic interpretations of structure based on vintage 2D seismic and borehole data and to map, if possible, the reservoir pathways in which the [Formula: see text] will be injected at [Formula: see text] depth, as well as providing a baseline for future seismic surveys and planning of drilling operations. The uppermost [Formula: see text] are well imaged and show an anticlinal structure with an east-west striking central graben on its top that extendsdown to the target horizon. About [Formula: see text] of throwis seen on the bounding faults. No faults are imaged near the planned drill sites. Remnant gas, cushion and residual gas, is present near the top of the anticline in the depth interval of about [Formula: see text] and has a clear seismic signature; both higher amplitudes in the reservoir horizons and velocity pulldown are observed. Amplitude mapping of these remnant gas horizons shows that they do not extend as far south as the injection site, which is located on the southern flank of the anticline. Amplitude anomalies, gas chimneys along an east-west striking fault, show that the stored or remnant gas either has been or is presently migrating out of the reservoir formations. Summed amplitude mapping of the planned injection horizon indicates that this lithologically heterogeneous formation may be more porous at the injection site.

Natural and industrial analogues for leakage of CO2 from storage reservoirs: identification of features, events, and processes and lessons learned

Instances of gas leakage from naturally occurring CO2 reservoirs and natural gas storage sites serve as analogues for the potential release of CO2 from geologic storage sites. This paper summarizes and compares the features, events, and processes that can be identified from these analogues, which include both naturally occurring releases and those associated with industrial processes. The following conclusions are drawn: (1) carbon dioxide can accumulate beneath, and be released from, primary and secondary shallower reservoirs with capping units located at a wide range of depths; (2) many natural releases of CO2 are correlated with a specific event that triggered the release; (3) unsealed fault and fracture zones may act as conduits for CO2 flow from depth to the surface; (4) improperly constructed or abandoned wells can rapidly release large quantities of CO2; (5) the types of CO2 release at the surface vary widely between and within different leakage sites; (6) the hazard to human health was small in most cases, possibly because of implementation of post-leakage public education and monitoring pro- grams; (7) while changes in groundwater chemistry were related to CO2 leakage, waters often remained potable. Lessons learned for risk assessment associated with geologic carbon sequestration are discussed.