Monitoring Underground Hydrogen Storage: An Integrated Multi-Domain Framework

Abstract

Underground hydrogen storage (UHS) is poised to emerge as a pivotal technology for large-scale and seasonal energy storage in future low-carbon energy systems. Nevertheless, ensuring its safe deployment necessitates implementation of monitoring strategies that account for the distinct physicochemical and microbiological characteristics of hydrogen. These characteristics cannot be directly transposed from underground gas storage (UGS) or carbon capture and storage (CCS) applications. In this study, we propose an integrated multi-domain monitoring framework for UHS developed through a thorough evaluation of European regulations; ISO and DNV standards; monitoring practices; and representative CCS, UGS, and UHS case studies. The framework includes a conceptual digital twin architecture for integrating heterogeneous monitoring data and supporting model updating, anomaly screening, and operational interpretation. It comprises five complementary monitoring domains: subsurface, near-surface, surface, remote, and digital. The integration of geophysical, geochemical, microbiological, atmospheric, and digital monitoring techniques, including 4D seismic surveys, fiber-optic sensing, hydrogen leakage detection systems, and satellite- and UAV-based observations, is a key aspect of this study. The analysis demonstrates that monitoring approaches developed for CCS and UGS provide a solid foundation for UHS but require adaptation to account for hydrogen’s high diffusivity, low viscosity, limited geochemical footprint, flammability, material compatibility issues, and potential for microbial conversion. The digital domain is proposed as an integration layer for monitoring data, model updating, anomaly screening, and decision support. Predictive and real-time capabilities require future field-scale implementation and validation. The proposed framework may provide a structured conceptual basis for the development of future UHS monitoring guidance, pilot applications, and regulatory requirements.

1. Introduction

Hydrogen is increasingly seen as an important component of the energy transition, although its use will depend on technological progress, economic viability, and regulatory frameworks. Thanks to the possibility of low-carbon or potentially zero-emission production from renewable energy sources [1] and a wide range of applications, it can play a significant role in the decarbonization of economies, especially in sectors that are difficult to electrify, such as heavy industry, aviation, shipping, and transport [2]. In addition, with the growing share of variable renewable energy sources such as photovoltaics and wind power, hydrogen is gaining importance as an energy storage medium [3]. It can act as a buffer for both the short-term demand balancing and seasonal balancing of an energy system. However, in order for hydrogen to perform this function effectively, an appropriate storage infrastructure must be developed [4].

Underground hydrogen storage (UHS) is one of the most promising solutions for large-scale and long-term storage of this gas [5]. Compared to surface storage methods, including the use of pressure vessels and cryogenic and chemical storage, UHS offers significantly greater storage capacity [6]. In addition, it has lower unit costs and is safer. It also has a lower environmental impact [7]. Geological formations (salt caverns, gas deposits, and deep aquifers) provide natural isolation, making them favorable environments for the long-term storage of hydrogen [8].

Despite growing interest in underground hydrogen storage and the increasing number of pilot projects, UHS monitoring remains poorly defined and methodologically underdeveloped. There are no dedicated and harmonized regulatory and technical frameworks defining comprehensive monitoring requirements specifically for underground hydrogen storage. In practice, UHS design and monitoring concepts are largely based on experience gained from underground gas storage (UGS) and geological carbon dioxide storage (CCS) technologies [6]. These technologies provide valuable references for the construction of wells and the management of their integrity as well as for the geophysical and geochemical monitoring of subsurface processes [9,10,11].

However, the unique physicochemical properties of hydrogen create challenges that do not occur with natural gas or CO₂ [12]. Hydrogen, the smallest molecule among gases, is characterized by extremely high mobility and diffusivity, allowing it to penetrate the micropores of cement [13-14] certain metals, and pores and cracks in rocks [15]. Consequently, significant technological, methodological, and regulatory gaps remain in areas such as precise leak detection, the durability of sealing materials, the calibration of gas migration models, and the validation of existing standards under hydrogen conditions. Another key safety consideration is hydrogen’s flammability: it has a broad flammability range in air (4–75 vol.%) and a very low ignition energy of approximately 0.02 mJ [8]. Its high diffusivity increases the risk of gas leakage from geological formations, while its low viscosity complicates flow and pressure control in porous media [16]. Furthermore, hydrogen exhibits significant chemical and microbiological reactivity [16,17,18,19]. It may interact with rock minerals, accelerate corrosion of steel components, and initiate biological processes leading to the formation of methane or hydrogen sulfide [17]. In addition, hydrogen may produce variable hydrogeochemical responses, making monitoring based on formation-water analysis particularly challenging [15].

Purpose and scope of this work

The main objective of this study was to develop a coherent and interdisciplinary monitoring framework for underground hydrogen storage, building on lessons learned and monitoring concepts developed for underground gas storage and carbon dioxide storage while accounting for hydrogen-specific physicochemical and microbiological behaviors.

Owing to the complexity of the physical, geochemical, microbiological, and operational processes in underground hydrogen storage systems, an integrated and multi-level monitoring approach is essential. The proposed approach encompasses five complementary domains: subsurface, near-surface, surface, remote, and digital. Their integration not only enables the detection of anomalies and potential leakage pathways but also the integrated assessment of hydrogen’s behavior, storage integrity, and operational conditions throughout the storage lifecycle.

This study’s novelty lies in the integrated organization of UHS monitoring, focusing primarily on the technical and application-oriented aspects of the monitoring framework. The proposed framework integrates three conceptual components within a single UHS-specific structure: (i) regulatory and standardization relevance, (ii) assessment of the technical transferability of monitoring approaches from CCS and UGS to UHS, and (iii) an integrated monitoring architecture. This architecture is organized into the five complementary domains described above. The first four domains represent observational components of the monitoring system, while the digital domain provides a common layer for data integration and interpretation.

This framework supports the structured integration of monitoring technologies and monitoring information across the storage lifecycle, including their use in assessing storage integrity, detecting anomalies, and supporting operational interpretation. By linking regulatory and standardization-related relevance, technical transferability, and the five monitoring domains, the framework may provide a conceptual basis for the future development and evaluation of UHS monitoring approaches. Its practical implementation and validation will require testing in pilot and operational UHS projects.

The five-domain architecture is intended to be a common organizational framework for UHS rather than a uniform monitoring configuration. The selection, prioritization, and frequency of individual monitoring methods should be adapted to the type of storage and site-specific geological, hydrogeological, and operational conditions.

This study builds on previous work on UHS monitoring and regulatory aspects and advances it by integrating these elements within a dedicated UHS-specific framework that combines regulatory and standardization-related relevance, technical transferability, and a five-domain monitoring architecture.

2. Materials and Methods

This article presents a model for monitoring underground hydrogen storage developed on the basis of experience and legal and technical solutions used in underground natural gas and geological carbon dioxide storage. The methodology combines a literature analysis, a review of legal regulations and technical standards, an assessment of demonstration projects (UGS, CCS, and UHS), and conceptual modeling based on data integration in a digital twin environment. It uses a “regulatory read-across” approach (CCS and UGS → UHS), which involves mapping the requirements of the CCS Directive to hydrogen operating parameters. The digital twin component was developed at the conceptual architecture level. No field-scale implementation, AI/ML model training, or validation against operational UHS data was performed in this study.

Relevant scientific studies, regulatory documents, technical standards, and pieces of publicly available project information were identified through a targeted literature and document search using Scopus, ScienceDirect, OnePetro, and Google. In the searches, we used combinations of terms related to underground hydrogen storage, underground natural gas storage, carbon dioxide storage, and monitoring, together with related terms when relevant. The searches were intended to identify sources relevant to developing the proposed UHS monitoring framework rather than provide an exhaustive systematic review of the literature.

The analytical framework adopted in this study comprised three main stages. In the first stage, relevant regulatory frameworks and technical standards identified through the targeted search were reviewed with respect to their relevance to underground storage and monitoring requirements.

In the second stage, a comparative analysis of CCS, UGS, and emerging UHS technologies was carried out using a consistent set of criteria, including pressure, gas migration, geochemical processes, measurement technologies employed, and operating conditions. Particular attention was paid to the potential for transferring these solutions to conditions specific to hydrogen.

In the third stage, the results of the regulatory analysis and case studies were integrated into a ‘regulatory read-across’ matrix, which allowed the identification of elements that are directly transferable, require adaptation, and are not transferable. On this basis, we developed a conceptual monitoring model based on five functional domains, creating a coherent framework for analysis throughout the lifecycle of the installation.

To avoid conflating regulatory applicability with technical transferability, the regulatory read-across was assessed in regard to two separate dimensions. Regulatory relevance was classified as direct, indirect, or inapplicable. Direct relevance was assigned in cases where a provision explicitly applies to hydrogen/UHS or a general safety or operational requirement applicable to UHS; indirect relevance was assigned in cases where a provision originates from CCS, UGS, or another context but addresses a monitoring function relevant to UHS; and inapplicable indicates that no meaningful correspondence was identified.

Technical transferability was classified as directly transferable, H₂-specific adaptation required, or untransferable. Direct transferability indicates that the underlying monitoring principle can be applied to UHS without substantive modification; adaptation required indicates that the principle remains relevant but requires hydrogen-specific adjustment of sensors, criteria, interpretation, or operating conditions; and untransferable indicates that the requirement or method is specific to another stored fluid or application. The final classification was cross-checked by the authors, with differences resolved by consensus.

As part of the first stage, selected European and international legal frameworks and technical standards, serving as a reference for the design of UHS monitoring, were subjected to a detailed analysis. Particular attention was paid to Directive 2009/31/EC (CCS Directive) [20], the Seveso III Directive [21], and technical documents relevant to geological storage, monitoring, and hydrogen safety, including ISO 27914:2026 [22], ISO/TR 27923:2022 [23], DNV-RP-J203 [24], and ISO/TS 15916:2026 [25]. The edition, scope, and current status of the regulatory and standardization documents were verified against official sources in August 2026 [24,26].

Compliance of these regulations with UHS requirements was assessed using a comparison matrix, and gaps requiring further development were identified. This process allowed us to determine which elements of the CCS monitoring system could be adapted directly to UHS and which required adaptation to the specific characteristics of hydrogen.

The analysis was extended to include an assessment of the impact of hydrogen’s physicochemical properties (diffusivity, mobility, viscosity, and microbiological reactivity), which formed the basis for adapting regulatory requirements to the specific characteristics of UHS.

Regulatory and standardization relevance was classified as direct relevance, indirect relevance, or inapplicable, whereas technical transferability was classified as directly transferable, H₂-specific adaptation required, or untransferable.

In selecting case studies, we aimed to provide documented examples of monitoring practices from CCS, UGS, and emerging UHS projects and allow comparison of monitoring approaches developed for mature storage technologies with those currently applied or tested for hydrogen storage. The cases analyzed included Sleipner, Weyburn–Midale, and Ketzin (CCS); Aliso Canyon (UGS); and H₂CAST Etzel, HyStock, Etrez, and RAG (UHS). The analysis focused on monitoring approaches and operational experience potentially relevant to UHS while considering the need for hydrogen-specific adaptation.

A UHS monitoring model was developed on the basis of the structure of five functional domains, which constitute the conceptual framework for analyzing the entire lifecycle of the installation. The proposed model defines the following areas of UHS monitoring:

• The subsurface domain focuses on monitoring processes inside the storage formation and controlling the tightness and integrity of wells.
• The near-surface domain focuses on the analysis of gases and water in the transition zone to identify biochemical and geochemical processes and assess the effectiveness of sealing barriers.
• The surface domain covers the supervision of infrastructure and emissions in the vicinity of the installation for the early detection of hydrogen leaks.
• The remote domain uses satellite and drone observations to analyze terrain deformation and gas migration on a regional scale.
• The digital domain serves as an integration layer supporting data integration, model updating, anomaly screening, and operational interpretation.

Each domain was defined as a separate set of tools, parameters, and diagnostic functions, whose mutual integration enables dynamic analysis of changes in real time. A detailed description of the technologies assigned to each domain and their operating parameters is presented in Section 3.

3. Results

3.1. The Regulatory and Technical Basis for the Design of UHS Monitoring Systems

Analysis of legal regulations and technical standards within the framework of the “regulatory read-across” approach allowed identification of monitoring principles and requirements relevant to UHS and assessment of their potential technical transferability.

Among the CCS-related technical references, ISO 27914:2026 [22] provides requirements and recommendations for geological CO₂ storage across the project lifecycle, while ISO/TR 27923:2022 [23] specifically addresses injection operations, infrastructure, and monitoring, including baseline measurements and surface and downhole monitoring practices. DNV-RP-J203 provides complementary guidance on storage-site qualification, risk management, monitoring, and storage-performance verification [24].

For hydrogen-specific safety considerations, ISO/TS 15916:2026 provides general guidance on hydrogen hazards, properties, and safety aspects [25]. Its role in our analysis is therefore complementary, and it should not be interpreted as a dedicated standard for geological UHS monitoring.

The DNV-RP-J203 (2021) provides a systematic approach to selecting, qualifying, and managing geological CO₂ storage sites. It includes requirements and procedures related to risk management, monitoring, and storage-performance verification throughout the storage-project lifecycle, together with well assessment and management planning. The document also addresses the assessment and verification of site-specific monitoring and risk-management plans.

When these CCS-derived principles are applied to UHS, hydrogen-specific properties and effects, including high diffusivity and hydrogen embrittlement, must be considered, particularly in relation to monitoring-system design and long-term well integrity.

Figure 1 summarizes the relevance of the regulatory and standardization documents analyzed to key UHS monitoring functions, whereas

Table 1. Assessment of regulatory and technical frameworks for underground hydrogen storage monitoring, including scope definition and transferability rationale.

Regulation/Standard	Scope of UHS Monitoring	Technical Transferability	Transferability Rationale	Recommendations
Directive 2009/31/EC—Monitoring plan	Injection, storage-complex, migration, and leakage monitoring	H2-specific adaptation required	Framework is applicable; high H2 diffusivity/mobility requires appropriate sensor sensitivity.	Adapt monitoring objectives and methods to H2 behavior and storage type.
Directive 2009/31/EC—Corrective measures	Leakage response and remediation procedures	H2-specific adaptation required	General response principles apply, but hydrogen-specific thresholds depend on the monitoring environment and context.	Adapt CCS corrective actions to hydrogen scenarios.
Directive 2012/18/EU—Major-accident prevention and emergency planning	Safety management and emergency response	Directly transferable	Hydrogen is explicitly covered by Seveso III.	Integrate monitoring with safety and emergency-response procedures.
ISO 27914:2026—Geological storage	Site characterization, storage design, operation, risk management, and containment	H2-specific adaptation required	Geological-storage principles are relevant but developed for CO2.	Adapt to H2 properties, storage type, and failure mechanisms
DNV-RP-J203:2021—Well integrity and monitoring	Storage-site qualification, risk management, monitoring, performance verification, and well assessment	H2-specific adaptation required	Risk-based principles are transferable but developed for CO2.	Adapt hazards, indicators, and well-integrity criteria to UHS.
ISO/TS 15916:2026—Basic considerations for the safety of hydrogen systems	Hydrogen properties, hazards, and general safety considerations	Directly transferable	It provides H2-specific general safety guidance.	Use it as a complementary H2-safety reference.
ISO/TR 27923:2022—Injection operations, infrastructure and monitoring	Injection operations, wells and infrastructure, baseline, surface and downhole monitoring	H2-specific adaptation required	Monitoring practices are relevant but require H2-specific evaluation.	Adapt methods and criteria to H2 and site conditions.

evaluates the technical transferability of the identified monitoring principles and requirements to UHS conditions.

Hydrogen-specific monitoring requirements cannot be defined by a single universal sensitivity range. Required sensor performance depends on the monitoring objective and measurement environment, and sensor detection limits should not be equated with operational or safety thresholds. Accordingly, the proposed framework does not prescribe universal detection, warning, shutdown, or reporting thresholds; these should be defined according to the monitoring objective, sensor characteristics, measurement environment, and site-specific operational conditions. Hydrogen-specific physical properties may also affect the performance of individual monitoring methods and therefore require method- and site-specific evaluation.

3.2. Case Studies: UGS, CCS, and UHS Projects

Owing to the lack of experience with industrial underground hydrogen storage, the analysis was based on case studies of related technologies for underground natural gas storage and geological CO₂ storage as well as UHS projects. These projects provide valuable information on the effectiveness of monitoring techniques, data integration, and risk assessment methods that can be adapted to UHS systems [27,28,29].

Experience with UGS has led to the development of advanced methods for leak detection and operational safety control for underground natural gas storage, while in CCS projects, monitoring has focused on tracking CO₂ migration and assessing formation retention [10].

An integrated measurement approach is employed in the use of the technologies under review, encompassing geophysical, geochemical, wellbore, and environmental methods. Experience from projects such as Sleipner, Ketzin, and Aliso Canyon shows that techniques such as 4D seismic and DAS/DTS systems are effective in monitoring subsurface structures. However, their application in UHS conditions requires consideration of hydrogen’s specific properties (see

Table 2. Monitoring approaches and key insights from selected CCS, UGS, and UHS projects.

Project	Type	Main Monitoring Technologies	Key Project Experience	Relevance to UHS	Source
Sleipner (Norway)	CCS	4D seismic, modeling	CO2 plume tracking	Geophysical monitoring; H2-specific evaluation needed	[30]
Weyburn–Midale (Canada)	CCS	Seismic, InSAR, and groundwater chemistry	Integrated long-term monitoring	Multi-domain monitoring; H2-specific adaptation needed	[31,32]
Ketzin (Germany)	CCS	4D seismic, ERT, gas/water sampling	Integrated multi-method monitoring	Multi-method approach; H2-specific sensitivity assessment needed	[33]
Aliso Canyon (USA)	UGS	DAS/DTS, microseismic, gas/pressure sensors	Leakage and pressure monitoring	Relevant to well and operational monitoring; H2-specific adaptation needed	[34]
H2CAST Etzel (Germany)	UHS	Fiber optics, modeling, cavern deformation	Cavern integrity monitoring	Directly relevant to salt-cavern UHS	[35]
HyStock (The Netherlands)	UHS	H2 sensors, leak tests, water geochemistry	H2-specific monitoring tests	Directly relevant to UHS sensor and leak monitoring	[36]
Etrez (France)	UHS	Cyclic storage tests	Cyclic storage operation	Relevant to cyclic UHS monitoring	[27]
RAG (Austria)	UHS	Hybrid CH4/H2 storage, grid integration	H2-containing gas storage	Relevant to dynamic storage monitoring	[28]

).

Current pilot projects directly dedicated to hydrogen (HyStock, H2CAST Etzel, and Etrez) serve as a key source of data for calibrating sensor systems and verifying predictive models for hydrogen’s properties. Technical innovations, such as early-warning systems and cavern leak tests, enable comprehensive assessment of the suitability of monitoring systems throughout an installation’s entire lifecycle (Figure 2).

Recent studies have revealed the growing role of data-integration and AI/ML methods in modeling and anomaly screening; however, their application to operational UHS monitoring remains dependent on appropriate training data and validation [37,38]. Solutions based on machine learning and deep neural networks allow precise prediction of gas–rock interactions and the creation of location suitability maps. Implementation of these tools translates into a higher level of safety and better-informed operational decisions in UHS installations.

An analysis of case studies indicates that many of the monitoring technologies developed in the CCS and UGS projects have the potential to form the basis of UHS systems. However, they require adaptation to the properties of hydrogen. Although geophysical methods, such as those using 4D seismic and fiber-optic DAS/DTS systems, are highly effective at detecting changes in a reservoir, their effectiveness may be limited in the case of H₂ because of its weaker geophysical signature.

Similarly, leak detection and surface-monitoring systems developed for natural gas may be applicable to UHS but require hydrogen-specific sensor selection, calibration, and interpretation to account for hydrogen-specific migration behavior.

3.3. Monitoring Challenges for Hydrogen in Comparison to CCS and UGS Technologies

Recent research (2026) has emphasized the development of integrated monitoring systems as a response to these limitations, with these systems being based on multi-physical approaches and data analysis. The importance of seismic monitoring for detecting hydrogen migration and identifying potential leaks is emphasized [37], as is the growing role of machine learning methods in modeling gas dispersion and optimizing injection processes [38,39]. Another major field of study is the creation of technologies and materials that guarantee well integrity, including cementitious materials that are resistant to deterioration in a hydrogen atmosphere [13,14,40]. At the same time, the importance of microbiological and geochemical processes that could impact the stability of a storage system is stressed [41]. From a systems perspective, there is an increasing focus on multi-physical approaches that integrate thermal, hydraulic, mechanical, and chemical processes, particularly under cyclic operating conditions [42,43].

Hydrogen’s high mobility and diffusivity may increase the risk of migration through geological and engineered barriers and require the use of sensitive and selective detection methods. However, the detection sensitivity required depends on the monitoring objective and measurement environment in question and cannot be defined by a universal ppm–ppb range. Sensor detection limits should also be distinguished from operational and safety thresholds, which are application- and site-specific. Another characteristic of hydrogen that distinguishes it from CO₂ and methane is its broad flammability range in air (4–75% vol.) and very low ignition energy (0.02 mJ) [8]. These properties are relevant to the design of safety and response systems but should not be directly interpreted as monitoring-alarm thresholds. Accordingly, surface safety systems may require redundant detection, warning, and emergency-response functions, while the corresponding thresholds should be defined according to the corresponding monitoring environment, sensor performance, and site-specific operational conditions.

Substantial challenges remain in transferring monitoring approaches from CCS and UGS to UHS because several methods require adaptation to hydrogen-specific physicochemical and biogeochemical behaviors. Hydrogen’s migration behavior may reduce the effectiveness of some detection methods developed for CO₂ or CH₄, particularly when the measurable physical contrast is limited. Furthermore, the lack of clear geochemical signatures hinders interpretation of hydrogeochemical data, which, in the case of CCS, constitute a fundamental monitoring tool.

The microbiological processes occurring in the subsurface environment also pose a significant challenge. These processes include the activity of methanogens and sulfate-reducing bacteria, which can lead to hydrogen conversion and the generation of secondary gases, such as CH₄ and H₂S. Material degradation is an additional concern. Hydrogen embrittlement may affect metallic well components, while hydrogen-related interactions may also influence the long-term performance of well cement. These effects have direct implications for well integrity and the long-term integrity of storage systems.

Consequently, the ‘regulatory read-across’ approach can only be applied conditionally, requiring adaptation to the specific characteristics of hydrogen on a case-by-case basis in terms of both measurement technologies and the interpretation of monitoring data. Monitoring effectiveness is affected by the different nature of hydrogen migration relative to gases that are traditionally stored underground. Because of its high mobility and rapid dispersion, hydrogen may form less distinct accumulation zones, which are difficult to identify using geophysical methods. The limited resolution of 4D seismic data in such circumstances has been widely discussed in the context of CO₂ monitoring, highlighting potential challenges in detecting gases with low physical contrast [29,44]. Consequently, effective UHS monitoring requires more-sensitive detection methods and the integration of various measurement techniques, particularly in cases of dispersed gas migration.

These requirements support the need for integrated, multi-domain monitoring combining complementary measurements and data interpretation.

The differences and technological limitations identified (

Table 3. Comparative overview of regulatory and technical monitoring frameworks in the UGS, CCS, and UHS domains.

Domain/Area	UGS	CCS	UHS
Regulatory framework	National gas/mining laws; Gas Directive 2009/73/EC	Directive 2009/31/EC; ISO 27914:2026; ISO/TR 27923:2022	Emerging “read-across” from CCS/UGS; linked to Seveso III
Subsurface	2D/3D seismic, PT logging, cement tests	3D/4D seismic, microseismic, optical sensors	High-res 4D seismic, DAS/DTS, H2-selective sensors
Near-surface	Monitoring of groundwater and soil gas (CH4)	Geochemical monitoring (pH, Eh, gases)	Weak geochemical signal; biochemical process monitoring
Surface	Infrastructure cheques; methane detectors	Gas detection in emission risk zones	High-sensitivity H2 sensors (MEMS, TDLAS, IR)
Remote	InSAR, GNSS (used occasionally)	InSAR/GNSS for ground stability	Site-specific use of InSAR, GNSS and/or UAV-based observations for surface-deformation monitoring and model validation
Digital	Standard SCADA systems	Integrated monitoring and data-management platforms	Digital data integration; model updating and anomaly screening
Safety systems	Basic well and pressure control	Leakage response and pressure management	Redundant detection, automatic shutdown, ventilation, early-warning systems

) clearly indicate that an effective UHS monitoring system cannot be a simple copy of CCS or UGS systems. It must be designed in a dedicated manner, accounting for hydrogen’s low geochemical signature and the risk of its biochemical conversion, the latter of which determines the selection of sensor technologies presented in the multi-domain model.

3.4. UHS Monitoring Model Proposal

In order to overcome the technological and regulatory limitations identified, a conceptual five-domain UHS monitoring model was designed. This model integrates experience pertaining to the CCS and UGS technologies with new requirements resulting from the physicochemical properties of hydrogen.

The five domains are not intended to be merely a spatial classification of monitoring technologies. They represent complementary monitoring functions within a common architecture. For a given monitoring objective, the framework links the relevant domain with the parameter to be observed and the appropriate monitoring method, while data from the observational domains are subsequently integrated and interpreted within the digital domain. This functional relationship enables monitoring of information from different spatial scales and measurement systems to be considered within a common structure throughout the storage lifecycle.

The framework is intended to support the organization and integration of monitoring activities rather than to replace site-specific risk or failure-mode assessment; consequently, the selection and prioritization of monitoring methods should be adapted to the corresponding storage configuration, operational conditions, and site-specific monitoring objectives.

The division of domains was justified by the need to separate data sources according to the scope of observation (storage site → surface → digital integration) and ensure full coverage of the installation’s lifecycle, from the pre-operational phase (baseline) to operation and post-operational monitoring. Each domain includes a separate set of tools, parameters, and diagnostic functions, and their integration supports consistent interpretation of monitoring information across the storage lifecycle.

In the proposed monitoring model, data integration is performed within the digital domain. Data obtained from measurement systems covering the subsurface, near-surface, surface, and remote domains are conceptually organized within the five-domain framework shown in Figure 3. Continuous operational data may be integrated through SCADA systems, while periodic subsurface, near-surface, surface, and remote-sensing datasets are incorporated as they become available. Before integration, the data undergo appropriate quality control and harmonization. The digital twin provides a conceptual layer for integrating these heterogeneous datasets, supporting model updating, anomaly screening, and operational interpretation, while AI/ML methods may be used as optional analytical tools when sufficient training and validation data are available. Figure 4 illustrates the corresponding data-flow architecture, linking data acquisition, processing and quality control, digital twin-based integration and model updating, and operational interpretation and decision support.

Digital twins in underground gas storage support the development of integrated reservoir representations that combine production data, three-dimensional geological models, and advanced process simulations, potentially supporting operational monitoring, forecasting of operating conditions, and early detection of anomalies. Integrated systems based on the digital twin concept may include data layers, simulation, and 3D visualization, enabling optimization of the injection–withdrawal cycle, risk management, equipment integrity control, and operational variant planning. This approach can support the digital and intelligent management of gas storage facilities throughout their lifecycles [45].

Monitoring methods within this framework should also be distinguished according to their detection mechanisms. Direct methods measure H₂ concentrations or gas composition, whereas indirect methods detect changes associated with storage behavior or potential migration, such as pressure, temperature, geophysical responses, deformation, and geochemical changes. Consequently, seismic, ERT, InSAR, GNSS, LiDAR, and UAV-based observations should be interpreted primarily as indirect monitoring methods rather than as direct H₂ detection techniques. Their applicability depends on the expected signal, site conditions, and spatial and temporal resolution required for the monitoring objective.

The proposed model comprises five functional monitoring domains (

Table 4. Proposed monitoring domains for UHS: technical and diagnostic specifications.

Domain	Targeted Hazards/Diagnostic Functions	Main Parameters Monitored	Lifecycle Applications
Subsurface	Detection of H2 microleaks in well cement; assessment of caprock integrity and geomechanical stability Reservoir behavior; formation integrity; active and legacy well integrity; loss of zonal isolation; gas migration	Dynamic pressure/temperature, fracture activity, interlayer migration, pressure, temperature, flow rate, annular pressure, casing/cement integrity indicators, formation response	Baseline, operational, post-closure
Near-surface	Identification of biochemical H2 consumption; tracking geochemical signals of gas migration in the transition zone	H2, CH4, CO2, pH, Eh, dissolved gases, microbial indicators	Baseline, operational, post-closure
Surface	Early detection of H2 emissions near wellheads; monitoring of infrastructure integrity and fire risk	Gas concentration, emission flux, temperature, infrastructure condition	Operational
Remote	Validation of geomechanical models; regional observation of terrain deformation anomalies	Vertical displacement, surface deformation, spatial deformation patterns	Baseline and post-closure
Digital	Data integration; model updating; anomaly screening; and operational interpretation	Integrated monitoring variables, model–data consistency, anomaly indicators and data quality	Full lifecycle integration

) that together form an integrated and multi-level operational safety system:

• The subsurface domain includes reservoir monitoring and formation integrity control. It uses PT sensors, well logging, fiber optic DAS/DTS systems, and optical microphones to detect micro-vibrations and interlayer leaks. Its purpose is to continuously assess geomechanical stability and detect H₂ microleaks in areas close to the wells.
• The near-surface domain covers the shallow subsurface transition zone in which gas migration and associated geochemical and microbiological changes can be monitored in soil, the unsaturated zone, and groundwater. Its vertical extent is site-specific and depends on local geological and hydrogeological conditions, transport processes, and monitoring objectives. Monitoring may include gas and water analyses, chromatography, mass spectrometry, and redox and pH measurements performed to identify gas migration and biogeochemical processes. It allows identification of microbiological transformations (e.g., methanogenesis) and evaluation of the effectiveness of natural sealing barriers.
• The surface domain covers monitoring of infrastructure and emissions in the vicinity of the installation. It uses MEMS/MPS sensors, TDLAS spectroscopy, and IR cameras for monitoring H₂ emissions and local thermal or infrastructure anomalies. It supports the detection of H₂ emissions and local temperature or infrastructure anomalies in the vicinity of wells and surface facilities.
• The remote domain uses remote-sensing and geodetic observations, including InSAR, GNSS, LiDAR, and UAV-based surveys, primarily to monitor surface deformation and other indirect surface expressions that are potentially associated with storage behavior. Data from this domain can support geomechanical-model validation and assessment of spatial deformation patterns associated with storage operations.
• The digital domain serves as an integration layer for information from the other four monitoring domains. It may combine SCADA data, PVT, reservoir and geomechanical models, GIS-based information, and, when appropriate, AI/ML-based analytical tools. Its function is to support data integration, model updating, anomaly screening, and operational interpretation.

Detection limits and spatial and temporal resolution are method-, instrument-, and site-specific and therefore not prescribed universally within the proposed framework.

Monitoring requirements may vary considerably depending on the corresponding geological storage configuration. In salt caverns, cavern geometry and integrity, pressure cycling, well integrity, and surface leakage detection are prioritized. In depleted hydrocarbon reservoirs, monitoring is more focused on reservoir pressure and flow behavior, well integrity, gas distribution, and fluid–rock–microbe interactions. In saline aquifers, pressure propagation, gas distribution, caprock behavior, and hydrogeochemical changes become particularly relevant. Accordingly, the five-domain architecture remains common to all storage configurations, whereas the priority, applicability, and frequency of individual monitoring methods are storage- and site-specific.

The proposed division into four physical domains—underground, near-surface, surface, and remote—allows multi-scale observation of storage facilities, from the immediate vicinity of the wells to the regional scale. The near-surface domain plays an important role in detecting anomalies through the analysis of geochemical and microbiological changes in soil gas and groundwater. Its spatial extent should be defined on a site-specific basis according to geological and hydrogeological conditions and monitoring objectives. The surface domain, on the other hand, is an operational interface, focusing on infrastructure integrity and emission detection using high-sensitivity sensors, allowing the measurements of the wells to be linked to observations from satellites made within the remote domain.

Monitoring processes in the subsurface environment can be supplemented by in situ approaches, including analyzing fluid–rock–microbe interactions, sampling fluids under reservoir conditions, and using isotopic tracers to identify biogeochemical processes. These methods are used in studies of underground gas storage and CCS. However, in the context of hydrogen storage, they are still in the developmental stage and require further validation [11,41,46,47]. These methods foster a better understanding of the biogeochemical processes and potential mechanisms of hydrogen loss.

The cyclical nature of the injection and withdrawal of hydrogen causes stress changes in the rock mass, which can lead to geomechanical fatigue and the formation of microfractures, affecting the integrity of the formation and the seal. Consequently, geomechanical monitoring techniques—such as microseismics and fiber optic systems (DAS/DTS)—that can detect stress changes and microcrack activity are significant in the subsurface domain [42,48,49,50,51,52].

Well integrity constitutes a distinct monitoring function within the subsurface domain. For active UHS wells, monitoring should include the condition of casings, tubing, packers, wellhead components, and the cement sheath, together with pressure and temperature measurements and annular-pressure surveillance. Relevant indicators may include pressure anomalies, loss of zonal isolation, and corrosion or material degradation, including hydrogen-related embrittlement of metallic components. Downhole logging and fiber-optic systems such as DAS/DTS can provide complementary information on mechanical or thermal anomalies. The selection and frequency of individual integrity measurements should be defined on a site- and well-specific basis.

Where legacy or abandoned wells are present within or near a storage complex, their integrity should be considered separately, with monitoring focused on potential loss of isolation and indications of gas migration along the wellbore.

Integrity criteria, inspection intervals, and intervention thresholds should therefore be established for the specific well design, operating conditions, and regulatory context rather than being prescribed universally within the present framework.

The digital domain is conceived as an integration layer rather than as a fully implemented predictive digital twin. The digital representation may include monitoring variables such as pressure, temperature, flow rate, gas composition, annular pressure, surface deformation, and selected geochemical or well-integrity indicators. Quality-controlled observations from the monitoring domains are used to update the relevant physical and operational models, including PVT, reservoir, and geomechanical models where applicable. Continuous data streams may support frequent model updating, whereas periodic geophysical, geochemical, and remote-sensing datasets are incorporated when available. Measurement uncertainty, data quality, and model–data mismatch should be considered when interpreting anomalies.

AI/ML is treated as an optional analytical component rather than a prerequisite of the framework. Its application requires sufficient training data and independent validation before it can be used reliably for prediction or anomaly classification.

In the proposed architecture, the digital twin functions as an integration layer that combines data from individual monitoring domains into a single coherent analytical system. Continuous operational data may be integrated through SCADA systems, while periodic subsurface, near-surface, surface, and remote-sensing datasets can be incorporated as they become available. Before integration, the observations undergo appropriate data-quality control and harmonization. These data then serve as input for numerical models and analytical algorithms, aiding in the identification of anomalies and the assessment of changes in reservoir parameters over time. The results of these analyses are then used to update the digital twin model, reflecting the current state of the storage system and supporting decision-making processes. Feedback between observations and models can support model refinement, adjustment of monitoring activities, and operational review.

The following is an illustrative example of the intended data flow: An unexpected pressure deviation detected by well or reservoir sensors would first undergo data-quality checks and be compared with related measurements. If the deviation persists, the observation could be used to update the relevant operational or reservoir model and compare the observation with expected system behavior. The anomaly would then be interpreted together with measurement uncertainty and available observations from other monitoring domains. A confirmed deviation could support intensified monitoring, inspection, or operational review according to site-specific criteria. This example illustrates the intended workflow of the digital domain and does not constitute field validation of the framework.

No single set of monitoring methods is therefore universally applicable to all UHS sites. Method selection should be based on the storage configuration, site characteristics, monitoring objective, expected measurable response, and required spatial and temporal resolution.

4. Discussion

Our analysis indicates that regulatory and technical frameworks developed for CCS and UGS provide useful reference points for UHS monitoring, but their relevance and technical transferability differ. The CCS Directive provides an established framework for geological-storage monitoring, whereas Seveso III is directly relevant to major-accident prevention and emergency planning involving hydrogen. Both Directives therefore address different but complementary aspects of safety and can serve as important points of reference for UHS. However, neither of them provides a comprehensive regulatory framework specifically dedicated to underground hydrogen storage.

This study’s contribution should therefore be distinguished from the novelty of the individual monitoring methods. Existing technologies and monitoring concepts provide the technical basis for the framework, whereas this study structurally organizes them into five complementary monitoring domains and combines this architecture with explicit regulatory/standardization relevance and technical-transferability assessment. The framework also defines the complementary role of the observational domains and their integration within a common digital layer.

The regulatory analysis also shows that legal relevance should be distinguished from technical transferability. A regulatory or standardization document may provide relevant monitoring principles without its technical requirements being directly transferable to hydrogen storage. This distinction is particularly important because hydrogen-specific properties, storage configurations, and site conditions affect the applicability of individual monitoring approaches.

The most relevant CCS-related technical references for this monitoring framework are ISO 27914:2026, ISO/TR 27923:2022, and DNV-RP-J203. Together, these documents cover complementary aspects of geological CO₂ storage, including injection operations and infrastructure, monitoring, risk management, and storage-performance verification. Because they were developed for CO₂ storage, their application to UHS should be regarded as technical read-across requiring hydrogen-specific evaluation rather than direct transfer. ISO/TS 15916:2026 provides a complementary reference for general hydrogen safety considerations.

In the absence of a dedicated harmonized UHS monitoring framework, regulatory and technical read-across from CCS and UGS provides a practical interim approach. In the longer term, the development of UHS-specific regulatory guidance and harmonized technical standards may improve consistency in monitoring design, operational requirements, and reporting.

Detailed mapping of individual failure modes to monitoring indicators, site-specific trigger criteria, and corrective responses requires project-specific assessment and falls outside the scope of this conceptual monitoring framework.

From a technical perspective, a key challenge consists of integrating and interpreting heterogeneous data collected at different spatial and temporal scales across the subsurface, near-surface, surface, and remote domains. The digital domain provides a conceptual layer for combining these datasets, updating relevant models, and supporting cross-domain interpretation.

AI/ML methods may support anomaly screening and model updating when sufficient training and validation data are available. However, their role within the proposed framework remains optional, and their predictive performance cannot be assumed without site-specific validation. Similarly, the digital twin should presently be regarded as a conceptual data-integration and model-updating environment rather than as a proven real-time early-warning system.

Existing UHS pilot projects provide emerging operational experience relevant to monitoring-system development, but the available evidence remains limited and does not yet cover the full range of geological settings and operating conditions considered for UHS. Further field-scale data are therefore required in order to evaluate method performance, refine monitoring strategies, and validate integrated monitoring concepts.

From a practical perspective, the proposed five-domain architecture provides a common organizational structure, but its implementation should remain storage- and site-specific. No single combination of monitoring methods can be prescribed universally for salt caverns, depleted hydrocarbon reservoirs, and saline aquifers.

Further work is particularly needed in four areas:

• The development of UHS-specific technical and regulatory guidance;
• The development and validation of hydrogen-sensitive detection methods and materials resistant to hydrogen-related degradation;
• Field-scale integration and validation of multi-domain monitoring data and models;
• Evaluation of digital twin and AI/ML applications using representative operational UHS datasets.

The digital twin component of the proposed framework remains conceptual and has not been validated using field-scale UHS data. Consequently, its predictive performance, update frequency, anomaly-classification capacity, and operational decision-support functions cannot yet be quantified. Future implementation will require site-specific calibration and validation against monitoring data from pilot or operational UHS projects. This limitation is particularly relevant to AI/ML applications, which depend on the availability and quality of suitable training and validation datasets.

The results support a multi-domain approach in which established practices from CCS and UGS are adapted to hydrogen-specific conditions rather than transferred directly. The proposed architecture provides a structured basis for integrating complementary monitoring information, while its practical performance and the effectiveness of its digital component remain to be demonstrated through field-scale UHS applications.

5. Conclusions

The results of the technical and regulatory analysis indicate that monitoring approaches developed for CCS and UGS cannot be directly transferred to UHS without considering hydrogen-specific properties and storage conditions. Their application generally requires H₂-specific adaptation and integration of complementary monitoring methods across different domains.

The main contribution of the proposed framework is the integration of five complementary monitoring domains with regulatory and standardization relevance and technical-transferability assessment within a common UHS-specific monitoring architecture.

The five-domain architecture provides a common organizational structure, while the selection and priority of individual monitoring methods should remain storage- and site-specific.

The digital domain is proposed as a conceptual integration layer for combining monitoring data, supporting model updating, anomaly screening, and operational interpretation. As the proposed framework has not yet been validated using field-scale UHS data, its predictive and real-time capabilities remain to be demonstrated. Further development should therefore focus on field-scale testing and refinement of the framework, together with the development of UHS-specific technical and regulatory guidance.