A Multi-Scale Suitability Assessment Framework for Deep Geological Storage of High-Salinity Mine Water in Coal Mines

Abstract

Deep well injection and storage (DWIS) technology provides an effective alternative to address the high cost, energy intensity, and limited scalability of conventional treatments for high-salinity mine water from coal mines. However, the absence of a dedicated site suitability evaluation framework remains a major gap. Unlike previous approaches that directly applied CO₂ storage criteria, this study refines and restructures the framework based on a systematic analysis of the fundamental differences in mechanisms and risk characteristics unique to mine water storage. Building on the experience of CO₂ geological storage assessment, this study analyzes the key differences in fluid properties and storage mechanisms between water and CO₂ and, for the first time, establishes a comprehensive site suitability evaluation framework for mine water geological storage. The framework integrates three main dimensions—stability and safety, effectiveness, and socio-economic factors—covering 80 key parameters. The indicator system is organized hierarchically at the basin, target-area, and site levels, and incorporates a multi-scale weight adaptation mechanism that assigns scale-dependent weights to the most influential indicators at each evaluation level. An innovative evaluation methodology combining a “one-vote veto” mechanism, progressive filtering, and multi-factor weighted superposition is proposed to determine storage suitability. This work fills a critical research gap in systematic site selection for deep mine water storage in China. It offers theoretical guidance and an engineering paradigm for overcoming technological bottlenecks in high-salinity water treatment, enabling efficient and low-carbon disposal. The study has important implications for promoting the green transformation of the mining industry and achieving national carbon peaking and neutrality goals.

1. Introduction

The extraction of mineral resources often exerts substantial impacts on aquifers, leading to the generation of large volumes of mine water. The discharge and seepage of this water can cause serious contamination of both surface and groundwater systems. Statistics indicated that coal mining produced approximately 2.0 t of mine water per tonne of coal in the Netherlands [1] and about 3.0 t in the United Kingdom [2]. In China, where rapid industrialization continues to accelerate, the scale of mining activities and associated pollutant emissions is steadily increasing. Coal mining in China generates roughly 1.8 t of mine water per tonne of coal, with an annual output exceeding 8.0 × 10⁸ t. As in many other countries, the primary objectives of mine water management in China are to maximize water resource utilization and minimize environmental impacts. However, in certain mining areas, challenges such as excessive mine water inflow, low utilization efficiency, and the high treatment costs associated with high-salinity mine water have become increasingly prominent. These issues not only threaten mine construction and operational safety but also exert considerable pressure on environmental protection efforts, constraining the sustainable development of the mining industry [3,4].

Internationally, mine water utilization primarily includes mine production and domestic water use, agricultural irrigation, industrial supply, and environmental replenishment. In recent years, research and applications related to thermal energy storage, power generation, and reinjection have also been expanding. In China, conventional mine water treatment typically involves pre-treating the water in underground sumps before lifting it to the surface for centralized purification in large-scale wastewater treatment plants, after which it is reused on the surface or reinjected underground [5,6,7,8]. Certain treatment technologies, such as goaf-based purification, utilize the filtration and sedimentation effects of goaf voids and gangue materials to improve mine water quality for reuse in underground operations. However, these methods impose strict requirements on geological conditions, are unsuitable for large-scale mines, and have limited applicability. Patented underground mine water treatment systems demonstrate high treatment efficiency, stable effluent quality, and strong resistance to hydraulic shocks but are constrained by high capital and operational costs as well as large space requirements, making them impractical for large water volumes.

Reverse osmosis technology has been widely applied for high-salinity mine water treatment, yet it involves significant investment and energy consumption. Moreover, managing the concentrated brine and solid residues generated during membrane separation remains technically challenging, further restricting large-scale implementation. Overall, existing methods for treating high-salinity mine water are characterized by high treatment costs, substantial infrastructure demands, and considerable operational expenses, all of which impose heavy economic burdens on coal mining enterprises. For mines with exceptionally high inflow rates, adopting conventional deep treatment processes for comprehensive purification not only intensifies cost and energy pressures but also leads to resource inefficiency. High-salinity mine water from coal mines refers to the concentrate generated after treating mine water with reverse osmosis membrane processes. It is characterized by exceptionally high concentrations of low-molecular-weight ions such as Na⁺, K⁺, Cl⁻, and SO₄²⁻, with total dissolved solids (TDS) typically exceeding 10,000 mg/L. In contrast, concentrations of high molecular-weight ions—including total organic pollutants, ammonia nitrogen, total Fe, Al³⁺, Cu²⁺, and As³⁺—remain relatively low. The treatment of this high-salinity stream represents the “last-mile” challenge in mine water management. Conventional evaporative crystallization methods entail high capital and operating costs, increasing treatment expenses by over 4.2 dollars per ton on average, thereby imposing substantial cost pressures on coal mining operations while also leading to significant energy and resource waste [7]. Moreover, the resulting salt crystals exhibit complex compositions and limited industrial value, making them difficult to recover and reuse. Direct discharge of this concentrate would pose significant environmental risks. Under China’s “carbon peaking and carbon neutrality” goals, such approaches fail to achieve the desired outcomes for the green and harmless disposal of mine water. Consequently, the development of efficient and low-energy treatment pathways has become an urgent priority to advance sustainable mine water management.

Deep well injection and storage (DWIS) is an emerging disposal technology that involves injecting liquid or gaseous fluids into rock pores and micro-fractures at depths of 1500–3500 m below the Earth’s surface via deep wells. It serves as a safe environmental disposal approach that isolates fluids from the biosphere. The underlying principle exploits the confinement and degradation capacities of the deep geological environment—the “fourth environmental medium”—to prevent injected fluids from re-entering biogeochemical cycles and exerting adverse ecological effects [9,10]. Geological storage of high-salinity mine water not only drastically reduces treatment costs—with actual project evaluations indicating an 80% reduction in treatment expenditures and over 70% lower energy consumption—but also effectively mitigates environmental liabilities. This approach enables truly deep treatment and reuse of coal mine water, moving the industry closer to the goal of “zero liquid discharge.”

2. Current Research Status Domestically and Internationally

In the United States and several European countries, deep well injection represents one of the primary disposal methods for hazardous liquid and gaseous wastes [11,12,13]. According to statistics, wastewater generated during oil and gas extraction in the U.S. is typically injected into the deep subsurface through Class II injection wells. Approximately 180,000 such wells are distributed across states including Texas, California, Oklahoma, and Kansas, collectively injecting over 2.0 × 10⁹ gal (7.6 × 10⁶ m³) of high-salinity water underground each day [14]. Research by the U.S. Environmental Protection Agency (EPA) indicates that deep geological storage technology is safer than almost all other disposal methods, with leakage probabilities ranging between one in a million and one in four million in risk assessment scenarios [15,16,17]. In South Africa, the Kolomela iron ore mine injects about 3.6 × 10⁴ m³ of mine water per month into aquifers via boreholes [18]. Similarly, at the Mt. Whaleback iron ore mine in Australia, approximately 7.9 × 10⁶ m³ of mine water and surface runoff are injected annually into underground aquifers [19], achieving significant environmental and economic benefits.

Domestically, the application of deep geological storage technology for treating high-salinity coal mine water remains relatively cautious, with limited related research, and the technology is still in its early developmental stage.

Suitability assessment and site selection for deep geological storage serve as the foundation and prerequisite for project implementation. Appropriate site selection ensures safety and stability in terms of reservoir capacity, caprock integrity, construction feasibility, and environmental risk, largely determining the success or failure of a storage project. The U.S. Underground Injection Control (UIC) regulations impose stringent site selection requirements for Class I wells used for hazardous waste injection, primarily aiming to prevent adverse impacts on underground sources of drinking water (USDWs) [15]:

Aquifers: Hazardous waste must be injected below the deepest USDW within a quarter-mile radius of the wellbore.

Regional Geological Condition Analysis: This includes (i) geological structure, stratigraphy, hydrogeological conditions, and regional seismicity; (ii) detailed analyses of lithology, aquifer hydraulics, and mineral resources; and (iii) understanding the regional geological context to predict the fate and migration pathways of injected fluids through modeling.

Storage–Seal Combination and Structure: (i) The injection zone must possess sufficient permeability, porosity, thickness, and areal extent to prevent fluid migration into USDWs; (ii) effective confining layers with low permeability must be present; (iii) strata should be continuous and free of faults or fractures to prevent vertical leakage; and (iv) at least one caprock layer must have adequate thickness, mechanical strength, and stress characteristics to restrict fracture propagation.

With respect to CO₂ geological storage, extensive research has been conducted globally on suitability assessment and site selection. The Carbon Sequestration Leadership Forum classifies CO₂ geological storage potential and suitability assessment into five hierarchical levels—national, basin, regional, target area, and site—providing a universal framework for global storage projects. Organizations such as the International Organization for Standardization (ISO) [20], the World Resources Institute (WRI) [21], and the U.S. National Energy Technology Laboratory (NETL) [22] evaluate potential sites in terms of geological safety, injectivity, storage capacity, environmental and socio-economic factors, and risk, proposing unified selection principles.

Regarding indicator systems for site selection, Bachu [23] of the Alberta Energy and Utilities Board proposed 15 basin-scale evaluation indicators covering tectonics, basin geometry, hydrocarbon potential, and socio-economic factors, laying the methodological foundation for basin-level site assessment. Chadwick et al. [24] identified key geological indicators for CO₂ storage in saline aquifers, including reservoir depth, thickness, porosity, permeability, and caprock integrity. Oldenburg et al. [25] of Lawrence Berkeley National Laboratory proposed nine secondary indicators (e.g., containment and depth) derived from three primary criteria: storage capacity, secondary trapping mechanisms, and dilution capacity. Grataloup et al. [26] from the French Geological Survey established four main evaluation dimensions—Storage, Risk, Regulation, and Socio-economics—and 11 secondary indicators including storage potential and constraints. Their approach commonly uses weighted scoring based on factors such as capacity, injectivity, operational safety, and economics. Rodosta et al. [27], following U.S. Department of Energy protocols, categorized indicators into three groups—regional geological characteristics, site-specific conditions, and social considerations—encompassing ten evaluation aspects such as formation depth and injectivity. Middleton et al. [28] developed integrated open-source tools SimCCS 2.0 and SCO₂T for coordinated optimization of CO₂ capture, transport, and storage infrastructure. Kim et al. [29] applied an evaluation framework comprising 9 geological, 7 subsurface, and 5 surface criteria to screen 516 potential sites across California, ultimately identifying 61 high-priority targets.

Drawing from these international frameworks, extensive domestic efforts have also been made to establish CO₂ storage site selection methodologies. Li Xiaochun et al. [30] divided 24 major sedimentary basins in China into 70 storage units and evaluated CO₂ storage potential in saline aquifers for each. Diao Yujie et al. [31] preliminarily developed a safety assessment indicator framework for CO₂ geological storage. The Research on China CO₂ Storage Site Selection Guide issued by the Administrative Center for China’s Agenda 21 [32] proposed selection methods and procedures for various storage entities, including oil and gas reservoirs, unmineable coal seams, and deep saline aquifers. Suitability Assessment and Demonstration Projects of CO₂ Geological Storage in China, edited by Guo Jianqiang et al. [33], defined the stages for evaluating CO₂ geological storage potential and suitability nationwide. Cao Molei et al. [34] established a two-level system comprising general feasibility indicators (8 elements) and target-area-specific indicators (16 elements) covering suitability and safety. Wang Zijian et al. [35], through statistical analysis of geological parameters, defined four dimensions—capacity, injectivity, safety, and economics—with nine sub-indicators. Qi Shengwen et al. [36,37] systematically reviewed site selection indicators for different reservoir types and constructed a five-scale evaluation framework integrating engineering geology, storage potential, and socio-economic factors. Li Ke et al. [38] emphasized capacity, efficiency, safety, and stability, identifying 12 critical selection elements. Mu Yu [39] developed a CCS site evaluation system for low-porosity, low-permeability sandstone reservoirs in the Ordos Basin. Xu Xiaoyi [40] provided a comprehensive review of Multi-Criteria Decision-Making (MCDM) approaches for site suitability assessment.

While the mature evaluation framework for CO₂ geological storage provides an important methodological foundation for this study, it should be noted that systematic site selection studies for deep geological storage of mine water remain limited both domestically and internationally. Given that both belong to the category of deep geological storage of fluids, drawing on the CO₂ storage evaluation framework serves as an essential starting point. However, fundamental differences exist between mine water and CO₂ in terms of fluid properties, storage mechanisms, and potential risks. Direct application of the CO₂ evaluation framework would lead to substantial inaccuracies in site assessment results. First, the application of deep geological storage to high-salinity coal mine water presents several unique challenges compared with CO₂ storage. The primary difficulty arises from differences in fluid properties that affect reservoir adaptability: the viscosity of water is approximately 100 times that of supercritical CO₂, its diffusivity is about one-tenth, and its surface tension is considerably higher. Under the same injection pressure, the radial migration range of water is much smaller. Therefore, when evaluating effectiveness, our system places greater emphasis on the macroscopic connectivity of the reservoir (e.g., sand-shale ratio, reservoir distribution continuity) rather than solely pursuing high porosity values.

Second, concerning storage mechanisms and long-term behavior, CO₂ storage relies on structural, solubility, and mineral trapping mechanisms, with reactions between CO₂ and surrounding rocks typically dominated by “acidification.” In contrast, mine water storage is governed primarily by gravity-driven displacement and water-rock chemical reactions. Its high concentrations of ions such as Ca²⁺, Mg²⁺, and SO₄²⁻ can easily lead to the precipitation and scaling of minerals like gypsum [41,42,43], or the dissolution of certain cements, weakening rock strength. This “softening” effect poses a unique threat to long-term safety. Consequently, our system not only increases the weight of the caprock mechanical stability indicator to quantify the long-term strength degradation risk but also innovatively introduces the mine water-specific indicator of reservoir-caprock geochemical compatibility to predict the potential for chemical scaling or the formation of dissolution channels.

Furthermore, in stratified sedimentary formations lacking conductive structures, liquid water primarily flows downward under gravity, with weak lateral migration and negligible upward flow, so CO₂ storage is primarily concerned with caprock integrity to prevent gaseous phase buoyancy-driven leakage across layers. The core risk of mine water storage lies in lateral seepage and potential contamination of adjacent aquifers, especially drinking water sources. This fundamental distinction leads our system to increase the weighting of the hydrodynamic regime and the assessment of reservoir lateral sealing capacity. Whether the regional hydrodynamic field is “hydraulically confined” directly determines the migration extent of the mine water plume, an aspect whose importance is often underestimated in CO₂ assessments.

Finally, socio-economic indicators play a more prominent role in mine water storage evaluation. Because mine water possesses resource utilization potential, its reuse is prioritized whenever technically feasible. Geological storage becomes the preferred disposal pathway only when reuse is technologically impractical or the cost of treating reverse osmosis brine is prohibitively high. Thus, resource attributes and policy constraints must be carefully assessed. While CO₂ storage emphasizes caprock integrity to prevent buoyant gas escape, mine water storage focuses on lateral leakage risks. As economic performance and feasibility are critical, aspects such as source–sink matching, construction conditions, and overall cost must be prioritized. With capture and transport costs significantly reduced, the focus of mine water storage shifts primarily toward optimal site selection.

This study aims to investigate the feasibility, key scientific issues, and technical challenges associated with applying deep geological storage technology to the disposal of high-salinity mine water in China. Building on theoretical research and engineering practice, and drawing extensively from CO₂ storage site evaluation systems, this study integrates China’s geological background with the realities of current research and engineering practice. It systematically analyzes key issues in existing CO₂ site evaluation frameworks from a fundamental perspective and, based on three hierarchical levels—basin, target area, and site—and three categories of indicators—stability and safety, effectiveness, and socio-economics—compiles and optimally selects domestic and international indicators. The final objective is to establish a three-tier classification standard and construct a comprehensive indicator system for assessing the suitability of deep geological storage of high-salinity coal mine water. This framework aims to overcome current technical bottlenecks, minimize environmental risks from the site selection stage, and lay the foundation for improving relevant technologies and management systems for deep geological storage in China.

3. Suitability Assessment Indicators for Mine Water Geological Storage

Drawing upon the CO₂ geological storage site selection framework and the engineering experience accumulated from deep mine water storage projects—particularly in the Ordos Basin—this study establishes a comprehensive indicator system encompassing three core dimensions: Stability and Safety, Effectiveness, and Socio-economics (Figure 1).

3.1. Stability and Safety (Engineering Geological Conditions)

Deep geological storage can induce a variety of geological risks, including fault reactivation, leakage through tectonic fractures, structural instability, induced seismicity, caprock failure, and hydraulic dispersion. Among these, the engineering geological conditions, particularly the reservoir–caprock assemblage, play a decisive role in mitigating risks and ensuring safe long-term storage.

Injection of mine water into deep formations alters the pore pressure and effective stress field, which may lead to shear failure, fault activation, or tensile fracturing of the caprock. These processes could potentially trigger leakage, surface displacement, or induced seismic events. Therefore, assessing the engineering geological conditions is a primary prerequisite for ensuring the industrial-scale feasibility and safety of mine water geological storage.

To comprehensively characterize the geological background of potential storage sites, 34 fundamental engineering geological indicators are proposed, classified across five hierarchical levels—Regional, Basin, Target Area, Site, and Injection Zone.

These include: 1. Nature of sedimentary basin; 2. Geothermal heat flow; 3. Geothermal gradient; 4. Active fault development; 5. Fault and fracture density; 6. Volcanic development zone; 7. Distance to volcanic activity zone; 8. Peak ground acceleration; 9. Historical seismicity; 10. Distance to seismic belt; 11. Geomorphological type; 12. Terrain characteristics; 13. Topographic slope; 14. Caprock lithology; 15. Degree of faulting in caprock; 16. Caprock thickness; 17. Caprock density; 18. Caprock porosity; 19. Caprock permeability; 20. Mechanical stability of caprock; 21. Caprock continuity; 22. Leakage index; 23. Number of caprock layers; 24. Reservoir-Caprock Geochemical Compatibility; 25. Sedimentary facies; 26. Reservoir pressure coefficient; 27. Hydrodynamic regime; 28. Hydrostatic pressure gradient; 29. Distance to subsidence area; 30. Distance to fractured zones; 31. Geological hazard susceptibility; 32. Adverse geological processes; 33. Dominant wind direction; 34. Vegetation condition.

3.2. Effectiveness (Effective Storage Potential)

The storage effectiveness of a geological formation primarily depends on the geological characteristics, mechanical properties, and hydrogeological conditions of the reservoir–caprock system. These parameters determine the storage capacity, injectivity, and retention performance, ensuring that mine water can be stored safely and stably in deep formations over the long term.

Field investigations in deep, low-porosity and low-permeability sandstone reservoirs of the Ordos Basin demonstrate that the total thickness of the storage sand body and the sand-to-shale ratio are critical determinants of storage potential. It is worth noting that locally measured core porosity and permeability values alone do not necessarily represent the overall reservoir storage potential.

During site selection, reservoir thickness, burial depth, porosity, permeability, and caprock integrity are the most significant parameters influencing effective storage potential. Accordingly, 34 representative indicators have been identified and refined across three spatial levels: 1. Basin area; 2. Basin depth; 3. Tectonic unit area; 4. Sedimentary formation thickness; 5. Caprock burial depth; 6. Reservoir burial depth; 7. Reservoir thickness; 8. Reservoir aspect ratio; 9. Reservoir density; 10. Porosity; 11. Permeability; 12. Coefficient of permeability variation; 13. Sand-to-shale ratio; 14. Interlayer heterogeneity; 15. Continuity of reservoir distribution; 16. Stratified reservoir distribution; 17. Number of reservoir layers; 18. Reservoir injectivity; 19. Number of reservoir–caprock assemblages; 20. Initial mineral volume fraction; 21. Water saturation; 22. Salinity of formation water; 23. Exploration maturity; 24. Chemical composition of aquifer water; 25. Data availability; 26. Resource potential; 27. Storage potential; 28. Storage potential per unit area; 29. Service life; 30. Effective storage coefficient; 31. Injection index; 32. Operating pressure of injection well; 33. Injection well volume; 34. Injection rate.

3.3. Socio-Economics (Socio-Economic Context)

Geological bodies are inherently discontinuous, which may cause stored mine water to migrate or leak, thereby generating cascading impacts on groundwater systems, soil environments, ecosystems, the atmosphere, and public health. Moreover, socio-economic factors—including employment, energy demand, and human–environment interactions—should also be incorporated into site selection and risk assessment.

From a socio-economic perspective, geological storage of mine water is only justified when utilization or treatment is technologically infeasible or economically nonviable, such as in the case of high-salinity brine from reverse osmosis processes. Consequently, both resource value and policy requirements must be carefully evaluated.

To account for these aspects, 11 socio-economic indicators are proposed: 1. Population density; 2. Distance to residential areas; 3. Public acceptance and regulations; 4. Current land use; 5. Economic viability; 6. Water resource protection and utilization policies; 7. Status of protected plant species; 8. Mine water inflow volume; 9. Mine water quality; 10. Transport Distance; 11. Mineral resource distribution within the formation; 12. Located in Protected Area?

4. Construction of the Geological Storage Suitability Evaluation System at Multiple Scales

At the basin level (scale of 1:4,000,000 or smaller), site selection is guided by the results of mine water suitability and storage capacity assessments, aiming to identify basins with high geological storage potential. The focus is placed on regional stability and safety, primarily considering geological integrity, tectonic setting, structural development, reservoir–caprock configuration, and geothermal conditions (Figure 2).

At the target area level (scale of 1:500,000 or smaller), the evaluation integrates geological suitability and storage capacity results to determine the most promising target zones within selected basins. The emphasis shifts to engineering geological stability, involving detailed consideration of fault development, hydrogeological conditions, potential geological hazards, and the structural relationship between reservoirs and caprocks.

At the site level (scale of 1:50,000 or smaller), the assessment focuses on key engineering parameters and risk control, including reservoir–caprock porosity and permeability characteristics, petrophysical properties, and rock mechanical parameters. The objective is to delineate well sites or blocks suitable for project deployment, emphasizing storage effectiveness and injection-induced risk management. Detailed evaluations are conducted on reservoir hydrogeology, mechanical integrity, and continuity of reservoir–caprock systems to determine storage potential and injection parameters, while also incorporating socio-economic considerations.

Drawing on indicator systems developed for CO₂ geological storage site selection in basins such as Ordos, Songliao, Tarim, Junggar, and Turpan–Hami, the basin-level suitability indicators (

Table 1. Suitability evaluation table of site selection indexes under basin level (Stability and Safety Indicators).

Primary Indicator	Secondary Indicator	Suitable	Moderate	Unsuitable
Stability & Safety	Geothermal Heat Flow (mW/m2)	[30, 50)	[50, 90]	>90
	Geothermal Gradient (°C/100 m)	<2	[2, 4]	>4
	Development of Active Faults	Far from active fault zone (>25 km), no active faults pass through	Relatively close to active faults (<25 km), no active faults pass through or Neogene faults pass through with insignificant Holocene activity	Active faults pass through, but they are small-scale, weakly active, or located on a major active fault zone or its intersection, with strong fault activity
	Volcanic Development Zone	Low-occurrence volcanic zone	Occurring volcanic zone	High-occurrence volcanic zone
	Distance to Volcanic Zone (km)	>250	[25, 250]	<25
	Peak Ground Acceleration (g)	<0.05	[0.05, 0.1]	>0.1
	Historical Seismicity	Historical seismic gap	M ≤ 6	M > 6
	Distance to Seismic Zone (km)	>250	[25, 250]	<25
	Caprock Lithology	Gypsum rock, mudstone/calcareous mudstone	Sandy mudstone, silty mudstone, argillaceous siltstone, argillaceous sandstone	Argillaceous siltstone, argillaceous sandstone, fractured limestone, coarse clastic sandstone
	Burial Depth (Main Caprock) (m)	[800, 1200)	[1200, 3500]	>3500 or <800
	Thickness (Single layer of main caprock) (m)	>100	[30, 100]	<30
	Caprock Permeability (×10−3 μm2)	<0.0001	[0.0001, 0.01]	>0.01
	Continuity	Continuous, stable	Relatively continuous or moderately continuous, relatively stable	Poorly continuous or discontinuous, relatively unstable or unstable
	Number of Layers	Multiple sets, good quality	Multiple sets or one set, relatively good quality	One set or none, poor quality
	Reservoir-Caprock Geochemical Compatibility	Similar water chemistries, no potential for scaling/dissolution	Minor scaling/dissolution risk, manageable via engineering controls	Severe risk of scaling or mineral dissolution
	Hydrodynamic Effect	Hydraulic confinement	Hydraulic sealing	Hydraulic migration and dispersion

and

Table 2. Suitability evaluation table of site selection indexes under basin level (Effectiveness Indicators).

Primary Indicator	Secondary Indicator	Suitable	Moderate	Unsuitable
Effectiveness	Tectonic Unit Area (km2)	>5000	[500, 5000]	<500
	Sedimentary Formation Thickness (m)	>3500	[1600, 3500]	<1600
	Reservoir Burial Depth (m)	[800, 3500]	[800, 3500]	>3500 or <800
	Reservoir Thickness (m)	>100	[20, 100]	<20
	Reservoir Porosity (%)	>5	[1, 5]	<1
	Reservoir Permeability (×10−3 μm2)	>1	[0.01, 1]	<0.01
	Reservoir Sand-to-Shale Ratio (%)	>60	[20, 60]	<20
	Interlayer Heterogeneity (Sandbody Continuity) (m)	>2000	[600, 2000]	<600
	Number of Reservoir Layers (Regional)	Multiple sets	Potentially exist	None
	Number of Reservoir-Caprock Combinations (Regional)	Multiple sets	Potentially exist	None
	Exploration Maturity	Under development	Moderate exploration maturity	Low or no exploration
	Data Support Status	Sufficient and reliable data	Moderate data	Insufficient data
	Resource Potential (Oil, Gas, Coal Scale)	Large	Sufficient, generally reliable	Moderate
	Storage Potential (×108 t)	>50	[50, 150]	<50
	Storage Potential per Unit Area (×104 t/km2)	>150	[0.5, 50]	<0.5

) show that larger tectonic units and thicker formations typically exhibit higher geological stability, making them more favorable for storage. Thicker, multi-layered, and low-permeability caprocks with good continuity provide sealing capacity. Optimal reservoir burial depth ranges from 800 to 3500 m, balancing adequate pressure and temperature conditions. Greater reservoir thickness, porosity, permeability, sand–shale ratio, interlayer heterogeneity, and a higher number of reservoir–caprock combinations all enhance storage potential. High exploration maturity and comprehensive data availability further enhance site suitability.

As the evaluation scale narrows to the target area level (

Table 3. Suitability evaluation table of site selection indexes under target area level (Stability and Safety Indicators).

Primary Indicator	Secondary Indicator	Suitable	Moderate	Unsuitable
Stability & Safety	Geothermal Heat Flow (mW/m2)	[30, 50)	[50, 90]	>90
	Geothermal Gradient (°C/100 m)	<2	[2, 4]	>4
	Development of Active Faults	No active faults within 25 km, and no active faults exist within the peripheral 25 km range	No active faults within the target area, but active faults exist within the peripheral 25 km range	Whether active faults develop within the target area and its periphery remains unclear
	Peak Ground Acceleration (g)	<0.05	[0.05, 0.1]	>0.1
	Historical Seismicity	Historical seismic gap	M ≤ 6	M > 6
	Caprock Lithology	Gypsum rock, mudstone, calcareous mudstone, evaporite	Sandy mudstone, silty mudstone, argillaceous siltstone, argillaceous sandstone	Argillaceous siltstone, argillaceous sandstone, shale, tight limestone
	Caprock Burial Depth (m)	<1000	[1000, 2700]	>2700
	Thickness (Single layer) (m)	>20	[10, 20]	<10
	Thickness (Cumulative) (m)	>300	[150, 300]	<150
	Caprock Permeability (×10−3 μm2)	<0.0001	[0.0001, 0.01]	>0.01
	Mechanical Stability	Stable	Relatively stable	Unstable (one-vote veto)
	Distribution Continuity	Continuous	Relatively continuous	Relatively discontinuous
	Number of Layers	Multiple sets	One set	None (one-vote veto)
	Reservoir-Caprock Geochemical Compatibility	Similar water chemistries, no potential for scaling/dissolution	Minor scaling/dissolution risk, manageable via engineering controls	Severe risk of scaling or mineral dissolution
	Hydrodynamic Effect	Hydraulic confinement	Hydraulic sealing	Hydraulic migration and dispersion (one-vote veto)

and

Table 4. Suitability evaluation table of site selection indexes under target area level (Effectiveness Indicators).

Primary Indicator	Secondary Indicator	Suitable	Moderate	Unsuitable
Effectiveness	Reservoir Thickness (m)	>80	[30, 80]	[10, 30)
	Reservoir Porosity (Average) (%)	>15	[10, 15]	[5, 10)
	Reservoir Permeability (Average) (×10−3 μm2)	>5	[1, 5]	<1
	Reservoir Permeability Variation Coefficient	<0.5	[0.5, 0.6]	>0.6
	Interlayer Heterogeneity (Sandbody Continuity) (m)	>2000	[600, 2000]	<600
	Reservoir Distribution Continuity (m)	>2000	[600, 2000]	<600
	Reservoir Body Layered Distribution	Easily migrates to positions with relatively lower pressure or lower structure within the layered reservoir body
	Number of Reservoir Layers	Multiple sets	Potentially exist	None
	Located at Reservoir-Caprock Interface?	No	No	Yes
	Multi-layer Caprock-Reservoir Form	Multi-layer caprock-reservoir form, which may increase or decrease leakage risk
	Single-layer Caprock-Reservoir Form	Single-layer caprock-reservoir form with thick caprock, but once breached, the storage system fails completely
	Storage Potential (×106 t)	>50	[0.5, 50]	<0.5
	Storage Potential per Unit Area (×104 t/km2)	>100	[10, 100]	<10

), large-scale parameters such as basin area, formation thickness, and exploration maturity show limited variability and can be excluded. At this scale, attention is focused on reservoirs with shallower burial depth, thicker and more continuous caprocks, high sealing capacity, low permeability, and good mechanical integrity. Greater reservoir thickness, porosity, permeability, and interlayer heterogeneity, combined with smaller permeability variation coefficients, correspond to greater storage potential. In layered reservoirs, injected water tends to migrate toward structurally lower positions or zones of lower pressure.

At the site level (

Table 5. Suitability evaluation table of site selection indexes under site level (Stability and Safety Indicators).

Primary Indicator	Secondary Indicator	Suitable	Moderate	Unsuitable
Stability & Safety	Geothermal Heat Flow (mW/m2)	<50	[50, 70]	>70
	Geothermal Gradient (°C/100 m)	<2	[2, 3]	>3
	Development of Active Faults	No active faults within 25 km, and no active faults exist within the peripheral 25 km range	No active faults within the site area, but active faults exist within the peripheral 25 km range	Whether active faults develop within the site area and its periphery remains unclear
	Development of Faults and Fractures	Limited fractures, no faults	Moderate fracture development, no faults	Large fractures, moderate fault development
	Peak Ground Acceleration (g)	<0.05	[0.05, 0.1]	>0.1
	Historical Seismicity	Historical seismic gap	M ≤ 6	M > 6
	Geomorphological Type	Fixed dunes	Bedrock hills or semi-fixed dunes	Water bodies
	Topographic Slope (°)	[0, 10)	[10, 25]	>25
	Caprock Lithology	Evaporites or tight mudstone	Argillaceous rocks	Shale and tight limestone
	Fault/Fracture Development in Caprock	Limited faults and fractures	Moderate faults, moderate fractures	Major faults, major fractures (one-vote veto)
	Buffer Layers	Multiple sets	One set	None
	Reservoir Lithology	Clastic rock	Clastic rock, carbonate rock mixed	Carbonate rock
	Burial Depth (Main Caprock) (m)	[800, 1200)	[1200, 1700]	>1700
	Thickness (Single layer of main caprock) (m)	>100	[50, 100]	<50
	Permeability (×10−3 μm2)	<0.01, stable	[0.01, 1]	>1
	Mechanical Stability	Stable	Relatively stable	Unstable (one-vote veto)
	Distribution Continuity	Regionally continuous distribution	Basically continuous distribution	Discontinuous, localized distribution
	Number of Layers	Multiple sets, good quality	Multiple sets, moderate quality	One set
	Reservoir Sedimentary Facies	Fluvial, Delta	Turbidite, Alluvial Fan	Beach Bar and Biogenic Reef
	Reservoir Pressure Coefficient	<0.9	[0.9, 1.1]	>1.1
	Reservoir-Caprock Geochemical Compatibility	Similar water chemistries, no potential for scaling/dissolution	Minor scaling/dissolution risk, manageable via engineering controls	Severe risk of scaling or mineral dissolution
	Distance to Coal Mining Subsidence Area (km)	>25	[20, 25]	<20
	Distance to Jointed/Fractured Zone (km)	>25	[20, 25]	<20
	Susceptibility to Geological Hazards	Low susceptibility	Low-Medium susceptibility	High susceptibility (one-vote veto)
	Located in mining subsidence area, karst collapse area, land subsidence area, desert activity area, volcanic activity area?	No	No, but potential impact	Yes (one-vote veto)
	Below the highest water level of rivers, lakes, reservoirs, or floodplain?	No	No, but potential impact	Yes (one-vote veto)

,

Table 6. Suitability evaluation table of site selection indexes under site level (Effectiveness Indicators).

Primary Indicator	Secondary Indicator	Suitable	Moderate	Unsuitable
Effectiveness	Reservoir Thickness (Main Reservoir) (m)	>80	[30, 80]	<30
	Reservoir Formation Dip Angle	<10°	[10°, 15°]	>15°
	Reservoir Sand-to-Shale Ratio	≥60%	50–60%	<50%
	Sandstone Porosity (%)	>5	[0.1, 5]	<0.1
	Sandstone Permeability (×10−3 μm2)	>1	[0.01, 1]	<0.01
	Reservoir Permeability Variation Coefficient	<0.5	[0.5, 0.6]	>0.6
	Interlayer Heterogeneity (Sandbody Continuity) (m)	>1200	[600, 1200]	<600
	Reservoir Distribution Continuity (m)	>2000	[600, 2000]	<600
	Reservoir Body Layered Distribution	Easily migrates to positions with relatively lower pressure or lower structure within the layered reservoir body
	Number of Reservoir Layers	Multiple sets	Potentially exist	None (one-vote veto)
	Hydrodynamic Effect	Hydraulic sealing	Hydraulic confinement	Hydraulic migration and dispersion
	Reservoir Injectivity (Main Reservoir) (m3/h)	>100	[50, 100]	<50
	Number of Reservoir-Caprock Combinations	Multiple sets	Potentially exist	None (one-vote veto)
	Original Formation Water Salinity (g/L)	(10, 50]	[3, 10]	<3 or >50
	Storage Potential (×104 t)	>900	[300, 900]	<300
	Storage Potential per Unit Area (×104 t/km2)	>100	[30, 100]	<30
	Well Service Life (years)	>10	[5, 10]	<5
	Effective Storage Coefficient (%)	>8	[2, 8]	<2
	Injection Index (m3)	>10−14	[10−15, 10−14]	<10−15
	Injection Well Operating Pressure (Pa)	Less than caprock breakthrough pressure and failure pressure of well materials	Equal to caprock breakthrough pressure and failure pressure of well materials	Greater than caprock breakthrough pressure and failure pressure of well materials
	Injection Well Volume (m3/h)	Less than storage capacity	Equal to storage capacity	Exceeds storage capacity
	Injection Well Rate (m3/h)	>300	50~300	<50

and

Table 7. Suitability evaluation table of site selection indexes under site level (Socio-economic Indicators).

Primary Indicator	Secondary Indicator	Suitable	Moderate	Unsuitable
Socio-economics	Population Density (persons/km2)	<25	[25, 50]	>50
	Distance to Residential Area (m)	>1200	[800, 1200]	<800
	Public Acceptance and Regulations	High public acceptance, sound regulations	Moderate public acceptance, regulations need modification	Public opposition (one-vote veto)
	Current Land Use	Unused land such as desert	Grassland, woodland, cultivated land, garden land	Residential, industrial/mining land, transportation land, water bodies, etc.
	Economic Viability	Good economic viability	Moderate economic viability	Not economically viable (one-vote veto)
	Water Resource Protection and Utilization Policies	Compliant	Compliant	Non-compliant (one-vote veto)
	Located in Protected Area?	No, and >10 km away	No, but potential impact	Yes (one-vote veto)
	Status of Protected Plant Species	None, Low	Few, Moderate	Many, High
	Mine Water Inflow Volume	>100 m3	[50, 100] m3	<50 m3
	Mine Water Quality	TDS ≥ 10,000, almost no organic matter	10,000 ≥ TDS > 1000, almost no organic matter	TDS < 1000, contains organic matter
	Transport Distance	Underground or <100 m	100~200 m	>200 m
	Mineral Resource Status in Formation	No mineral resources overlain	Minerals present, but no mutual impact	Mineral resources overlain (one-vote veto)

), where detailed survey and exploration data are available, evaluation focuses on both safety and effectiveness. Greater caprock thickness, multilayered structure, low permeability, and high sealing capacity enhance storage safety. Meanwhile, reservoirs with greater total thickness, higher porosity and permeability, and more reservoir–caprock combinations provide better storage capacity. However, as demonstrated in the Ordos Basin, deep, low-porosity, and low-permeability thick sandstones can also possess significant storage potential—indicating that porosity and permeability are not the sole determining factors. At this scale, socio-economic indicators such as policy feasibility, mine water inflow and quality, and economic viability become essential decision-making factors.

5. Methodology for Constructing a Weighting System for the Suitability Assessment of Mine Water Geological Storage

5.1. Suitability Assessment Methodology

This study establishes a comprehensive evaluation methodology based on the Analytic Hierarchy Process (AHP) [44,45]. The methodology first deconstructs the overall objective into three criterion layers: stability & safety, effectiveness, and socio-economic factors, which are subsequently refined into refined into a three-tier hierarchical indicator system comprising 80 parameters. Through expert consultation and construction of judgment matrices, quantitative weights are assigned to indicators at each level. A multi-scale weight adaptation mechanism is incorporated to ensure scale-consistent evaluations across basin, mining area, and site levels. Finally, systematic and quantifiable classification criteria are developed through a “one-vote veto” pre-screening process and comprehensive suitability-index calculation, providing end-to-end methodological support for site selection decisions, from macroscopic screening to microscopic verification (Figure 3).

(1)

Construction of the Hierarchical Structure Model

The overall objective of suitability assessment for mine water geological storage was decomposed into three criterion layers: Stability & Safety (A₁), Effectiveness (A₂), and Socio-economic Factors (A₃). Based on this, each criterion layer was further refined into 80 specific evaluation indicators, establishing a three-level hierarchical structure consisting of the objective layer, criterion layer, and indicator layer.

(2)

Construction of Judgment Matrices and Weight Calculation

Fifteen experts from geological engineering, environmental science, and mining economics were invited to perform pairwise comparisons of the relative importance of indicators at the same level using the Saaty 1–9 scale, thereby constructing judgment matrices. The normalized weight vector (W) and the maximum eigenvalue (λ_max) for each matrix were calculated using the standard “sum-product method” (

Table 8. Calculation and judgment matrix of suitability weight using the Saaty 1–9 scale.

Criterion	Stability & Safety	Effectiveness	Socio-Economic
Stability & Safety	1	1.5	2
Effectiveness	1/1.5	1	1.5
Socio-economic	1/2	1/1.5	1

Calculation Results: Stability & Safety: 42%; Effectiveness: 33%; Socio-economic: 25%.

) [45,46].

Step 1: Normalize the judgment matrix by columns (Equation (1)):

$${\overline{a}}_{ij}=a_{ij}/{\sum }_{k=1}^n{a}_{kj}$$

(1)

Step 2: Sum the normalized matrix by rows (Equation (2)):

$${\overline{W}}_i={{\sum }_{j=1}^n\overline{a}}_{ij}$$

(2)

Step 3: Normalize the resulting row sum vector to obtain the weight vector (Equation (3)):

$$W_i={\overline{W}}_i/{{\sum }_{i=1}^n\overline{W}}_i$$

(3)

Step 4: Calculate the maximum eigenvalue (Equation (4)):

$${\lambda }_{max}={\sum }_{i=1}^n{\displaystyle \frac{(AW{)}_i}{n{W}_i}}$$

(4)

where (AW)ᵢ denotes the i-th element of the vector AW.

(3)

Consistency Check

To ensure the logical consistency of expert judgments, a consistency check was performed for each judgment matrix. The procedure is described as follows [47,48,49,50]:

Step 1: Calculate the Consistency Index (CI) via Equation (5):

$$CI={\displaystyle \frac{{\lambda }_{max}-n}{n-1}}$$

(5)

Step 2: Query the Average Random Consistency Index (RI):

Consult the standard RI value table based on the order n of the matrix.

Step 3: Calculate the Consistency Ratio (CR) via Equation (6):

$$CR={\displaystyle \frac{CI}{RI}}$$

(6)

When CR < 0.10, the consistency of the judgment matrix is considered acceptable; otherwise, the judgment matrix needs to be adjusted until it satisfies the consistency requirement. All matrices in this study passed the consistency check: CR = 0.008 < 0.1.

5.2. Multi-Scale Weight Adaptation Method

To address the characteristics of different evaluation scales (basin, mining area, and site) and the varying availability of indicators, this study proposes a scale-dependent weight adaptation method. This method dynamically adjusts local weights from the global weights by introducing a scale importance coefficient and a data credibility coefficient, maintaining system consistency while ensuring the relevance of evaluations at each scale.

For a specific scale (e.g., basin level), the adapted weight for indicator “i” is calculated through Equation (7):

$$W_{scale,i}={\displaystyle \frac{W_{global,i}\cdot I_{scale,i}\cdot C_{scale,i}}{\sum _{j\in {\Phi }_{scale}}(W_{global,j}\cdot I_{scale,j}\cdot C_{scale,j})}}$$

(7)

where

W_scale,i: The adapted weight of indicator “i” at the specific evaluation scale.

W_global,i: The global weight of indicator “i” within the overall weight system.

I_scale,i: Scale importance coefficient, representing the relative importance of the indicator in decision-making at the current scale, ranging from 0–1, determined via the Delphi method.

C_scale,i: Data credibility coefficient, assessed based on the typical acquisition method, precision, and coverage of the indicator’s data at the current scale, ranging from 0–1.

Φ_scale: The subset of indicators selected for use at the current scale.

Scale Importance Coefficient (I_scale,i): In basin-scale evaluation, regional indicators (e.g., “sedimentary basin type”) are assigned high values (0.9–1.0), while site-specific detail indicators are assigned low values (0.1–0.3). In site-scale evaluation, engineering safety and socio-economic indicators receive high values, while the weights of regional indicators are correspondingly reduced.

Data Credibility Coefficient (C_scale,i): Determined based on data source reliability. For instance, regional geophysical data have high credibility (0.8–1.0) in basin-scale evaluation but low credibility (0.3–0.5) in site-scale evaluation; field drilling and measured data have the highest credibility (0.9–1.0) in site-scale evaluation.

5.3. Comprehensive Suitability Index Calculation and Classification

(1)

Indicator Standardization and Scoring

Each indicator is classified and scored based on its actual condition:

Suitable (5 points): Indicates the indicator condition is superior, fully meeting or exceeding the requirements for mine water geological storage, with very low risk or significant benefit.

Moderate (3 points): Indicates the indicator condition basically meets the requirements but has certain limitations or requires detailed demonstration, with risk and benefit at a moderate and acceptable level.

Unsuitable (1 point): Indicates the indicator condition fails to meet the basic requirements for storage, posing high risk or significant negative impact.

(2)

“One-vote veto” Mechanism

Certain indicators are designated as “one-vote veto” indicators: To strictly ensure the absolute safety and environmental regulatory compliance of the storage project, an independent “one-vote veto” mechanism is established outside the weighted scoring system. This mechanism targets critical limiting factors that can directly disqualify a site as “Unsuitable” if not met. These factors primarily involve:

Extreme Geological Conditions (V₁): Developed active faults, volcanic zones, high seismicity, high susceptibility to geological hazards within the study area; location within mining subsidence areas, karst collapse areas, land subsidence areas, active desert areas; elevation below the highest water level of rivers, lakes, reservoirs, or floodplains.

Regulatory and Ecological Red Lines (V₂): Lack of public acceptance and regulatory compliance, conflicts with water resource protection policies, economic infeasibility.

Critical Technical Barriers (V₃): Absence of a cap rock, existence of direct hydraulic connection between the aquifer and other strata.

(3)

Multi-scale Suitability Index Calculation

After screening via the “one-vote veto” mechanism, the Comprehensive Suitability Index (S) for suitability evaluation at any scale is calculated via Equation (8):

$$\mathrm{S} = \left[{\mathrm{W}}_{\mathrm{stab}}\left({\sum }_{\mathrm{i}\in {\mathsf{\Phi }}_{\mathrm{stab}}}{\mathrm{W}}_{\mathrm{stab},\mathrm{i}}{\mathrm{S}}_{\mathrm{i}}\right)+{\mathrm{W}}_{\mathrm{eff}}\left({\sum }_{\mathrm{j}\in {\mathsf{\Phi }}_{\mathrm{eff}}}{\mathrm{W}}_{\mathrm{eff},\mathrm{j}}{\mathrm{S}}_{\mathrm{j}}\right)+{\mathrm{W}}_{\mathrm{soc}}\left({\sum }_{\mathrm{k}\in {\mathsf{\Phi }}_{\mathrm{soc}}}{\mathrm{W}}_{\mathrm{soc},\mathrm{k}}{\mathrm{S}}_{\mathrm{k}}\right)\right]·V_1{V}_2\cdots V_n$$

(8)

where

S: The Composite Suitability Index, representing the overall suitability degree of a site for mine water geological storage. Its theoretical value range is [0, 5].

W_stab, W_eff, W_soc: These are the first-level weights for the three major criterion layers—Stability&Safety, Effectiveness, and Socio-economic factors, respectively. As determined in Section 5.1, their values are 0.42, 0.33, and 0.25.

Φ_stab, Φ_eff, Φ_soc: These denote the subsets of indicators actually selected for the Stability & Safety, Effectiveness, and Socio-economic criteria, respectively, at the current evaluation scale.

W_stab,i, W_eff,j, W_soc,k: These are the local weights of indicator i, j, k relative to its respective criterion layer (Stability & Safety, Effectiveness, Socio-economic). These weights have been adapted for the current evaluation scale (basin, mining area, or site) according to Equation (7) and satisfy the condition Equation (9):

$${\sum }_{\mathrm{i}{\mathsf{\Phi }}_{\mathrm{stab}}}{\mathrm{W}}_{\mathrm{stab},\mathrm{i}}= 1$$

(9)

The above formulation applies to the Stability & Safety subset, with analogous conditions holding for the other two criterion subsets.

S_i, S_j, S_k: These are the standardized assignment scores (Suitable = 5, Moderate = 3, Unsuitable = 1) for indicator i, j, k, respectively, based on their actual conditions.

V_n: This represents a “one-vote veto” indicator. It takes a value of 1 if the disqualifying conditions such as extreme geological conditions (V₁), regulatory and ecological red lines (V₂) and critical technical barriers (V₃) are absent in the area, and 0 if one of them are present.

(4)

Suitability Classification

Based on the calculated Comprehensive Suitability Index (S), the evaluation results are classified into three levels, providing clear decision guidance, as summarized in

Table 9. Suitability Classification Criteria.

Suitability Class	Composite Index (S)	Description and Engineering Recommendation
Suitable	S > 4.0	Site conditions are superior, with low risk and significant benefits. Recommended for priority consideration and may proceed directly to the next phase.
Moderate	3.0 ≤ S ≤ 4.0	Site conditions are generally adequate but have shortcomings. Detailed demonstration is recommended, requiring in-depth analysis of weak points and development of mitigation measures.
Unsuitable	S < 3.0	Site has multiple critical deficiencies, high risk, or poor effectiveness. Not recommended as a storage site and should be excluded from further consideration.

:

6. Conclusions

Suitability assessment is a prerequisite for implementing geological storage projects. While CO₂ geological storage has established a mature international site selection framework, the distinct physicochemical properties of mine water necessitate a specialized evaluation system.

By moving beyond the limitations of traditional CO₂ storage evaluation frameworks, this study systematically clarifies the fundamental differences in fluid migration, geochemical interactions, and core risks between mine-water and CO₂ storage, and further proposes a multi-scale, multi-factor suitability assessment framework for deep mine-water geological storage. Based on the three core categories—Stability and Safety, Effectiveness, and Socio-economics—a total of 80 key parameters were identified and structured into three spatial levels: Basin, Target Area, and Site. Dominant indicators at each level were clarified, forming a systematic and hierarchical site selection indicator system.

This study establishes a quantitative methodology based on the AHP combined with a multi-scale weight adaptation mechanism. The proposed “one-vote veto + multi-factor overlay” evaluation method, coupled with dynamic weight adjustment across basin, mining-area, and site scales, enables holistic and quantitative decision support from macroscopic screening to microscopic verification.

The proposed system fills a major research gap in deep mine water geological storage site selection in China. By combining international CO₂ storage experience with the geological and hydrogeological characteristics of domestic mining regions, it provides a robust theoretical foundation and technical framework for future site selection, risk assessment, and large-scale demonstration projects.

7. Challenges and Future Perspectives

7.1. Key Challenges and Limitations

The current research lacks dynamic quantitative characterization of the rock-fluid-chemical multiphysics coupling processes triggered by mine water injection. Key mechanisms—such as the grout slurry diffusion behavior in fractures, rock strength softening induced by water-rock reactions, and rockburst-like instability due to injection pressure perturbations—remain insufficiently elucidated and quantified.

Although the established indicator system clarifies the fundamental differences between mine water and CO₂ storage, it has not yet been integrated with the specific geological features of typical Chinese coal basins (e.g., low-permeability reservoirs in the Ordos Basin, high in situ stress conditions in the Junggar Basin) to develop regionalized threshold criteria and detailed evaluation protocols, thereby limiting its precision and operational applicability in specific mining regions.

The synergistic potential and integration pathways between mine water storage and other subsurface technologies—such as geothermal energy extraction and goaf energy storage—have not been sufficiently explored. The current evaluation framework fails to quantify interactive effects, such as thermal field variations and surrounding rock deformation under multi-technology coupling, thus constraining the realization of comprehensive subsurface benefits.

7.2. Future Research Directions

Develop dynamic process prediction models to advance the understanding of multiphysics coupling mechanisms. Key efforts will include: constructing mine water migration and storage prediction tools by leveraging grout slurry diffusion theory [51]; and establishing constitutive relationships for water-rock chemical softening through laboratory experiments and numerical simulations [52,53,54].

Build uncertainty-informed decision-making frameworks to enhance evaluation capabilities in data-scarce regions. This involves combining the entropy weight method with machine learning to rapidly screen key parameters using geophysical and remote sensing data; and identifying core variables affecting storage safety through sensitivity analysis [55,56].

Conduct regional demonstration projects to validate and refine the evaluation system. Implement injection tests and long-term monitoring in typical geological units such as the Ordos Basin and Junggar mining area; utilize hydrodynamic models and microseismic monitoring networks to verify the regional applicability of the indicator system [56,57]; and progressively develop tailored evaluation guidelines for China’s major coal basins.