Multicriteria screening evaluation of geothermal resources on mine lands for direct use heating

Abstract

Direct use of geothermal energy is the oldest and most versatile form of utilizing geothermal energy. In the last decade, this utilization has significantly increased, especially with the installation of geothermal (ground-source) heat pumps. Many current and inactive mine land sites across the U.S. could be redeveloped with clean energy technologies such as direct use geothermal, which would revitalize former mining communities, help with reducing greenhouse gas emissions, and accelerate the transition to a clean energy economy. We present a multicriteria screening framework to evaluate various aspects of direct-use geothermal projects on mine lands. The criteria are divided into three categories: (1) technical potential, (2) demand and benefits, and (3) regulatory and permitting. We demonstrate the framework using publicly available data on a national scale (continental U.S.). Then, using an example of abandoned coal mines in Illinois and focusing on resource potential, we illustrate how this evaluation can be applied at the state or more local scales when a region’s characteristics drive spatial variability estimates. The strength of this approach is the ability to combine seemingly disparate parameters and inputs from numerous sources. The framework is very flexible—additional criteria can be easily incorporated and weights modified if input data support them. Vice versa, the framework can also help identify additional data needed for evaluating those criteria. The multicriteria screening evaluation methodology provides a framework for identifying potential candidates for detailed site evaluation and characterization.

Introduction

Direct use of geothermal energy is one of the oldest, most versatile, and most common forms of utilizing geothermal energy (Dickson and Fanelli 2003). Lund and Toth (2021) reported a significant increase in direct utilization of geothermal energy worldwide in the last 10+ years. Installations of geothermal (ground-source) heat pumps (GSHP) account for almost 60% of the thermal energy produced, and their increased deployment could lead to major reductions in electrical energy demand and greenhouse gas emissions (Liu et al. 2023). Additional uses of geothermal energy are for bathing and swimming (18%) and space heating (16%) (mostly for district heating, with some for industrial and agricultural uses). The U.S. is one of the five countries with the largest direct use installed capacity (40% for residential and 60% for industrial use). However, European countries dominate when capacity/capita is calculated. In the U.S., most units are sized for peak cooling load and are oversized for heating; thus, they are estimated to average only 2000 equivalent full-load heating hours per year (capacity factor of 0.23) (Lund and Toth 2021).

A typical geothermal system for direct heat use consists of two or more wells. Production wells produce hot water, while injection wells are used to reinject the water after heat is extracted. Reinjection is mainly applied to preserve aquifer pressure, allowing sustainable production, but also to avoid environmental contamination at the surface from geothermal fluids (Kaya et al. 2011; Diaz et al. 2016). The well arrangement of most systems is designed to produce energy efficiently for at least 25 years. Examples of geothermal systems from the Paris Basin in France (operational since the 1970s), the North German Basin in Germany (operational since the 1980s), the district heating system in Boise, Idaho, USA (operational since 1890), or a low-enthalpy system in Iceland (operational since the 1930s) demonstrate that lifetimes of 25 years or more are feasible (Rojas et al. 1987; Lopez et al. 2010; Comeau et al. 2021; Axelsson 2010; Mink 2017).

Limberger et al. (2018) presented a global resource assessment for geothermal energy within deep aquifers up to a depth of three kilometers for direct heat utilization, where greenhouse heating, spatial heating, and spatial cooling were considered. Their analysis shows that suitable aquifers underlay 16% of the Earth's land surface and store an estimated 4 × 10⁵ to 5 × 10⁶ EJ that can theoretically be used for direct heat applications. Even with a conservative recovery factor of 1% and an assumed lifetime of 30 years, the annual recoverable geothermal energy is in the same order as the world's final energy consumption of 363.5 EJ/yr. Mullane et al. (2016) conducted an assessment of the shallow, low-temperature geothermal resources in the United States that could be used for direct use applications and came up with estimates of 8 million and 800 million TWh of heat-in-place for low-temperature hydrothermal and Enhanced Geothermal Systems resources in the U.S., respectively.

Based on McCabe et al. (2016), thermal demand in the residential sector constitutes about 50% of thermal energy consumption in the United States. Space and water heating in the commercial sector accounts for about 30% of the total commercial energy consumption. Based on 2010 data, process heating and facility heating/ventilation/air conditioning were about 25% of the total energy consumed for manufacturing.

Flooded underground mines and open pit mines have the potential to serve as large thermal reservoirs that can be harnessed using GSHPs to offset or replace costs from conventional heating sources. Several review papers summarize existing projects and discuss the benefits and challenges of this direct use of mining water (Jessop et al. 1995; Banks et al. 2003; Raymond et al. 2008; Peralta Ramos et al. 2015; Preene and Younger 2014; Walls et al. 2021; Hall et al. 2011; Chu et al. 2021; Dobson et al. 2023). The use of mine water for heating can represent a sustainable use of current and former mine land and support economic development in locations previously supported by mining activities.

Multicriteria geographic information system (GIS)-based screening approaches have been proposed for evaluating the potential for utilization of geothermal mine water (e.g., Arkay 2000; Richardson 2014; Richardson et al. 2016; Madera-Martorell 2020; Comeau et al. 2021) as well as other types of geothermal resources (e.g., Kimball 2011; Getman et al. 2015; Trumpy et al. 2015; Sosa Massaro et al. 2021; DeAngelo et al. 2024). This paper provides a GIS framework to evaluate various aspects of direct-use geothermal projects on mine lands.

For the rest of the paper, we will first describe the methodology and summarize the screening criteria for developing the direct use of the sites’ geothermal resources for a local area’s heating and cooling needs based on a literature review. Then, we will demonstrate how to use these screening criteria and the framework to identify locations with favorable characteristics for geothermal energy direct use on existing and former mine land, close to the end users, where demand exists. The screening methodology will be demonstrated using publicly available data on a national scale (continental U.S.). The same methodology can be applied to a state, regional, or local scale if data with such resolution are available. The evaluation will include examples of abandoned coal mines in Illinois. We illustrate how information available at the state level or more local scale affects spatial variability estimates based on a region's characteristics.

Methodology

Evaluation method

A level of assessment of geothermal resources on mine lands for direct use heating depends on the availability of tools and databases. Databases can be on a national, regional/state, or township/local scale. The resolution of the data controls assessment accuracy. The criteria that are needed for site potential evaluation fall into five major categories: technical potential, commercial potential, regulatory framework, environmental limitations, and social license (Fig. 1). Only a small number of potential sites will satisfy all requirements (light green shaded area in Fig. 1). For example, it is not enough that a site has ideal technical specifications if it is located where it is impossible to obtain land permits or too far from end users. Similarly, if economic, social, and permitting aspects are favorable, but technical performance is not satisfactory, this will degrade or exclude this site from further consideration.

Fig. 1

Major criteria categories for site potential evaluation

We present a GIS-based methodology that quantifies this process using data from the first three categories. Environmental limitations and social license categories are site-specific and relevant to local scale evaluation. The methodology can be applied across scales. It can be a single or multiple-step process based on existing information at hand. The goal is to rank subregions or multiple sites within the defined area of interest, where a more detailed evaluation is justified. At each step, zooming in on smaller, highly prospective areas for which new information on a finer scale needs to be assembled and the evaluation repeated to identify potential locations for detailed site evaluation and characterization.

The flowchart in Fig. 2 describes the steps and how these criteria can be incorporated into the analysis using publicly available data on a national scale (continental U.S.). The examples of abandoned coal mines in Illinois illustrate how information available at the state level or more local scale affects spatial variability estimates based on a region's characteristics.

Fig. 2

Methodology flowchart

Our assessment was performed in ESRI’s ArcMap, but any commercial (e.g., ESRI/Golden Software/Blue Marble Geographics), open source (e.g., QGIS), or scripting (e.g., Matlab or Python) software can be used to perform this feasibility analysis workflow. Following the steps in Fig. 2, we searched online accessible databases for available data types needed to demonstrate this approach. We also performed an extensive literature review, and any paper maps or databases were digitized for use in ArcMap. In cases where one database contained no spatial information but had a data qualifier (e.g., well name or the API (American Petroleum Institute) number, a unique number assigned to every oil and gas well) present in a georeferenced database, we combined them by cross-referencing or using the Join function from the spatial analysis toolbox. If a dataset extended beyond our area of interest, we used the Clip function to trim the data to that area. Our analysis requires data in a raster format. Data from existing databases, e.g., borehole temperatures, were interpolated to a required scale (e.g., continental U.S.). Data in a vector format, e.g., heat demand data, were converted into a raster format using the Polygon to Raster function. Areas that did not have data with the required accuracy were blanked (white color). This data exclusion depended on the evaluation scale (e.g., continental U.S., state, region, or local). Data binning was done using the Reclassify function, and the Algebra Raster Calculator and Algebra Summation were used to produce favorability maps discussed in Sects. "National scale evaluation" and "State or regional scale evaluation".

Screening criteria

Using information from review papers that described existing projects, we created a list of parameters that were identified as important for the project's success, including challenges that might be reasons for go/no-go decisions during the evaluation process. Appendix Table 2 summarizes the parameters relevant to the site scale. These screening criteria were used to identify mines suitable for minewater geothermal energy (MWG) in southeastern Ohio (Richardson 2014; Richardson et al. 2016; Madera-Martorell 2020) and in Quebec and Nova Scotia, Canada (Arkay 2000; Comeau et al. 2021). Many of these parameters are unavailable on a national or regional scale as the cost of obtaining them would be prohibitive or impossible to acquire them.

Operational and non-operational mines present significant resource potential for clean technologies, including geothermal. There is a vast potential for developing abandoned mining sites for mine water geothermal projects in the U.S. The U.S. Department of the Interior (Enhanced Abandoned Mine Land Inventory System, https://amlis.osmre.gov/Map.aspx) database contains an inventory of 48,529 abandoned coal mine sites (blue symbols in Fig. 3) and 64,883 locations of inactive metal mining operations in the U.S. have been recorded in the U.S. Geological Survey (USGS) Mineral Resources Data System (https://mrdata.usgs.gov/general/map-us.html) (violet symbols in Fig. 3). These inventories do not include active mine sites, which could also be utilized for similar geothermal systems.

Fig. 3

Inactive metal mine locations (violet) and abandoned coal mine sites (blue)

Although there are many potential abandoned mining sites, some may not be suitable for developing the direct use of the sites for a local area's heating and cooling needs. Criteria are needed to identify potential sites for the intended utilization. Based on previous reviews of minewater geothermal energy (MWG) systems (Banks et al. 2003; Watzlaf and Ackman 2006; Younger and Loredo 2008; Hall et al. 2011; Richardson 2014; Richardson et al. 2016; Farr et al. 2016; Adams et al. 2019; Madera-Martorell 2020; Díaz-Noriega et al. 2020; Farr and Busby 2021; Monaghan, et al. 2022), a series of initial screening criteria have been identified and characterized into three categories including: (1) assessing the resource potential, (2) identifying potential uses for the resource, assessing market potentials and determining the economic viability of this use, and (3) evaluating the regulatory and permitting framework.

The rock type determines its thermal conductivity coefficient. In addition to temperature and heat flux, the geothermal energy of mine water is also dependent on the position of the mine in the regional groundwater cycle and the area’s geothermal gradient.

Nonactive or abandoned mines are often filled with groundwater and runoff. This water volume can be used in direct heating through GSHP systems. This geothermal resource leverages existing underground gallery networks or open pits. The energy extracted or transferred using heat pumps can be used to heat and cool residential, commercial, and industrial buildings, greenhouse complexes, or data centers. Important factors in determining a GSHP system’s feasibility include the water's temperature and the reservoir’s size. The optimal reservoir temperature can sometimes provide direct heating or cooling. However, in most cases, with moderate temperatures, a heat pump is used to either extract heat from water or deliver heat to water. If heat pumps are combined with gas-powered boilers, higher-temperature water for domestic hot water needs can be provided.

Water chemistry assessment is important to configure the GSHP system optimally and anticipate scaling and corrosion risks. The suitability of existing fluids or required treatments depends on the system type. In an open-loop system, extracted groundwater passes through a heat transfer system and is reinjected into the source reservoir or disposed of as surface water. A closed-loop system has a piping system with a fluid circulation in contact with the reservoir, and the heat transfer system interacts with the circulating fluid. While open-loop systems are more common and straightforward, a closed-loop configuration can be used for mines with contamination issues or insufficient water volume.

Land use, ownership, regulatory and permitting requirements also need to be evaluated. This can be done in an early-stage screening process to eliminate the areas known to be excluded, even if they would have high resource potential. Once a site with favorable technical assessment is identified, these requirements must be evaluated and fulfilled locally. The regulatory and permitting framework for geothermal resource use on mine land is complex, and it varies depending on the location of the project, the land ownership, and the type of geothermal project envisioned. These regulations vary from state to state and also depend on whether the project involves federal, state, tribal, or private land. The Bureau of Land Management (BLM) typically oversees the permitting and regulation of geothermal power projects on federal land, and has identified potential sites where geothermal development might be possible (e.g., Brookhart et al. 2009). Projects on tribal lands add an additional set of requirements. Because tribal entities have sovereignty over their territory, approval from tribal governments is required for any geothermal projects to be located on these lands.

The regulatory and permitting framework for GSHPs varies on a state-by-state basis and may be subject to local requirements. Permitting requirements depend on whether any drilling is required or whether a proposed system would interact with the local aquifers. These systems are typically expected to be designed and installed using the best practices guidelines of the International Ground Source Heat Pump Association (IGSHPA 2017).

The use of a flooded mine for a GSHP system may have additional regulatory and permitting requirements, especially if the water in the mine contains hazardous constituents at levels above certain thresholds, such as acid mine water. The level of concern may vary—if the system uses a closed-loop heat exchanger within the flooded mine workings so that water within the mine is not withdrawn, then the risk of contamination is much lower. Many abandoned mines are classified as hazardous waste sites, and may have significant legal liabilities that could be incurred by anyone repurposing the mine site.

In addition to assessing technical and commercial potential and understanding the permitting and regulations, it is also important to identify regions and communities that would benefit from these resources but might not have the resources to develop such projects. The Justice40 is an example of an initiative that provides a ranking for identifying disadvantaged communities. These are examples of additional input layers that can be incorporated into our methodology in the future.

Application

Technical potential

The subsurface temperature is an important parameter that determines the energy potential of a geothermal resource. MWG also depends on the mine's position in the regional groundwater cycle and the area’s geothermal gradient. Coal mines are typically located in the upper few hundred meters; mineral mines tend to be deeper. The water within abandoned underground mines is thermally stable and contains more heat than saturated soils and bedrock in similar geological settings (Watzlaf and Ackman 2007). We use temperature maps at 100, 300, 500, and 1000 m depths to cover both types of mines. Temperatures at depths less than 500 m were estimated from the Southern Methodist University (SMU) database of bottom-hole temperatures (http://geothermal.smu.edu/static/DownloadFilesButtonPage.htm?). Estimated temperatures at 500 and 1000 m depths were from Geothermal Prospector (Getman et al. 2015) and Mullane et al. (2016). Lower surface temperatures and lower geothermal gradients are typical for the Northeast and the Midwest of the U.S. (e.g., Illinois). The geothermal gradient in the Western U.S. is higher in general (e.g., Colorado).

Figure 4 shows the estimated temperature at depths of 100, 300, 500, and 1000 m for the entire U.S. Temperatures are spatially heterogeneous and increase with depth. At depths of 100 and 300 m, temperatures vary from 10 to 40 °C in both states and are reasonable for heating and cooling applications; at depths of 500 and 1000 m, temperatures are significantly higher in Colorado than in Illinois and thus have higher heating potential. Coal mines in Illinois are typically within the top 100 m, and Fig. 4a is the most representative of this region, whereas mineral mines in Colorado can be found down to 1000 m. Therefore, a temperature map in Fig. 4a–d closest to the mine depth of interest would be selected and used for the resource evaluation.

Fig. 4

Estimated temperatures (°C) at depths a 100, b 300, c 500, and d 1000 m (a and b source SMU 2017, c and d after Getman et al. 2015)

Commercial potential

Residential use of heat is primarily correlated with average outdoor temperatures. According to the 2020 Residential Energy Consumption Survey (RECS) data by the U.S. Energy Information Administration (https://www.eia.gov/consumption/residential/data/2020), households in colder climates use space heating more intensely and tend to consume more energy for heating than households in warmer parts of the country. Both Colorado and Illinois belong to a colder climate region. In 2020, Illinois reported a total energy consumption of 142.72 TWh (487 trillion British Thermal Units, TBtu), 0.16 MWh/m² (51600 Btu/ft²), $9.58/m² ($0.89/ft²). For Colorado, these numbers were 58.0 TWh (198 TBtu), 0.14 MWh/m² (43700 Btu/ft²), and $7.21/m² ($0.67/ft²), respectively.

Understanding the spatial variation in demand for low-temperature resources at a local resolution is important for the potential market assessment. The analysis by McCabe et al. (2016) characterized the heat by space and water heating demand in the residential and commercial sectors, process heat demand in the manufacturing sector, and space heating demand in the agricultural sector on a county-level scale. The total residential, commercial, industrial, and agriculture heating demands are shown in Fig. 5, with white color indicating no data available, e.g., in Fig. 5c, d. Thermal demand in the residential sector constitutes about 50% of thermal energy consumption in the United States (McCabe et al. 2016). Many counties with high demand, especially in the residential and commercial sectors, are also those with large populations. This suggests a strong relationship between thermal energy consumption and population centers. We use these aggregate layers (after McCabe et al. 2016) to demonstrate our methodology. As new survey data become publicly available, individual factors (e.g., climate region, population, space, or water heating demands) that go into these estimates can be evaluated using our methodology, and demand estimates can be updated.

Fig. 5

Total annual a residential, b commercial, c manufacturing, and d agricultural heating demand in terawatt hours (TWh) (after McCabe et al. 2016)

Regulations and permitting process

A favorable hydrologic regime and a sufficient and reliable water source near the geothermal resource are important to maximize system efficiency. However, it is also essential to identify other uses and demands on existing water resources. The direct use heating application needs must be balanced with other demands, such as drinking, industrial, and agricultural uses. Figure 6 is used to illustrate how water quality information and related regulations may be incorporated into the analysis. Figure 6 shows spatial variations (depicted on a county level) in water quality in terms of total dissolved solids (TDS) in the upper 700 m across the continental U.S. used for the brackish water assessment (Getman et al. 2015; Tidwell et al. 2013). This information can be used in multiple ways. It could be used as a proxy to determine whether a resource is secured for drinking water supplies (TDS < 1000 ppm) or available for this application. Alternatively, it can be used to identify locations with high TDS values, where water treatment might be necessary before being used in direct use so as not to cause potential problems, e.g., due to corrosion or scaling. It should be noted that the local groundwater quality of a mine site might differ significantly from the county average, and thus site-specific data would be used for any detailed evaluation of a particular candidate site.

Fig. 6

Groundwater total dissolved solids (TDS) variations across the U.S. for the upper 700 m (after Getman et al. 2015)

Land ownership, environmental regulations, and permitting requirements are other factors that influence the evaluation of whether a possible location is favorable for direct-use heat generation. Figures 7 and 8 are examples illustrating how that information can be incorporated into our multicriteria analysis. Figure 7 illustrates land restrictions and review process time due to cultural or tribal resources. Category C1 has no resources present and less than 3 months review time, C2 manageable resources and ~ 4 months review time, and C3 resource complications and more than 6 months review time. Other types of areas with land use restrictions include military bases, wilderness, and national park lands. Figure 8 depicts an estimated processing time for permitting applications on federal land (Getman et al. 2015). Category C1 has no restrictions, C2 processing time less than 3 years, C3 processing time more than 3 years, and C4 is no-go. We use existing regulations and permitting requirements governing the use of geothermal resources. Additional requirements may be imposed because of a project being on active, reclaimed, or abandoned mine land. These regulations might be different for lower-temperature geothermal resources associated with mines. If that information becomes available, it can easily replace the one currently used.

Fig. 7

Cultural and tribal resources review requirements (after Getman et al. 2015)

Fig. 8

Permitting requirements on federal land (after Getman et al. 2015)

National scale evaluation

The available information from all categories needs to be evaluated across scales. We demonstrate the methodology on a national scale using currently publicly available information. As new data become available, they can be easily added to the analysis, and ranking parameters recalculated. While preserving spatial variation, each parameter was categorized into three subgroups: technical feasibility, demand, and regulations/permitting, as shown in Figs. 1 and 2.

We had four subsurface temperature layers, four demand layers, and three layers for illustrating how regulations and permitting information can be incorporated into the screening methodology. All temperature ranges, including the low-temperature range (10–16 °C), were considered suitable for direct use heating applications. The TDS in Fig. 6 was used for both technical and regulation categories related to water quality or availability, with * indicating the inadequate rating for the technical aspect in Table 1. This range is rated suitable from the regulation side. The opposite is true for TDS < 1000 ppm, suitable on the technical side but unsuitable on the regulation side. We chose the most conservative assessment, combined them, and used this input layer only once. The evaluation was done for each demand layer (e.g., residential heating) at one depth (e.g., 100 m) at the time; hence, we had five input parameters that were assigned one of three possible numbers: 0 (no, inadequate), 1 (maybe, possible), or 2 (yes, suitable) as specified in Table 1. Data binning was done using the Reclassify function. The maximum total suitability rank could be ten. These maps were then used to calculate favorability ranking: favorable, maybe favorable, and unfavorable. We used the Algebra Raster Calculator and Algebra Summation tools in these two steps. In our example, the weights were equal for all input layers, and favorability ranking bins were of equal size (e.g., 33% for each of the three bins in the minimum–maximum range). However, these weights and ranges can be easily modified when additional information provides more accurate estimations or specific screening objectives need to be evaluated. Note that the accuracy of estimates depends on the input layers' resolution. The county (regional) scale was the finest resolution in our example.

Table 1 Input parameter categories

Users can develop the input layers’ binning criteria depending on what they deem as the most important data for their project goals. The framework allows users to evaluate the trade-offs of two or more input parameters from these three subgroups. Figure 9 shows calculated favorability maps when considering (a) residential, (b) commercial, (c) manufacturing, or (d) agricultural heating needs and information of the upper 100 m. These maps were generated by tallying the rankings for each data layer. Favorable regions are shown in blue, less favorable in green, and unfavorable regions are shown in red. Similar maps were produced for the other depths. White areas in Fig. 9c, d indicate no data in respective demand input layers.

Fig. 9

Favorability maps for a residential, b commercial, c manufacturing, or d agriculture heating end use. Blue represents favorable, green represents possibly favorable, and red represents unfavorable regions

Any input layer can be easily updated with new information or new layers added. The strength of the multicriteria screening evaluation is the ability to combine information for many parameters and from various sources. The weights can be modified, or additional criteria can be easily added if input data support them.

These maps illustrate the screening methodology on a national scale. They can be used to identify regions with favorable conditions that should be further evaluated on a finer scale (see Sect. "State or regional scale evaluation") or provide insights on missing data.

State or regional scale evaluation

A state-wide or regional evaluation would follow for each prospective area identified by the presented methodology in Sect. "National scale evaluation". The amount and accuracy of the information varies from state to state. State or USGS digital databases are becoming more available, but the information about old, abandoned mines is typically in a paper form and not readily available. The USGS Mineral Resources Data System assigns a grade to a mine based on the amount and consistency of available information (Schweitzer 2019). We illustrate these steps with data from Illinois. Although we only focus on resource potential, other technical aspects can be evaluated similarly.

The excavated volume of a mine (V) can be calculated using the thickness of a coal seam (h), the area of the mine (A), and a coefficient (coef) that accounts for pillars and other structures present in mines (e.g., coef = 0.7 or 70% of the total volume). This coefficient can be adjusted based on available mine information. For example, in Illinois room-and-pillar mines, the amount of coal removed from the production areas ranged from 40 to 70%. In the post-1959 longwall mining method, 100% of coal was extracted in the panel areas. Andrews et al. (2020) reported similar numbers of void spaces.

$$\it V = A \times h \times {\text{coef}}$$

For a 1.0 km² area, a coal seam thickness of 1.0 m, and coef = 0.7, the volume is 0.0007 km³. This number grows proportionally larger with increased thickness, multiple coal seams, or a larger area. Using the approximate density of water of 1000 kg/m³, one can calculate the mass (density × volume). The amount of heat (q) extractable from mines can be computed using

$$\it q= m \times c \times {\text{ d}}T,$$

where m is mass, c is the heat capacity of water, which is approximately 4.19 kJ/kg·°C, and dT is a temperature change. For each degree of temperature change (i.e., dT = 1 °C), the estimated heat extracted is 2.9 × 10⁹ kJ using the volume above.

The Illinois State Geological Survey (ISGS) provides ample GIS data on coal mines (https://isgs.illinois.edu/research/coal/maps). For our analysis, we used maps of coal seam depths and thicknesses (not shown), the map of abandoned coal mines (Fig. 3), and favorability maps (Fig. 9) to estimate those regions' potential volume and extractable heat. Over twenty counties account for most of the abandoned coal mines, but not all of these counties show heat demand. Coal seam thickness in these counties varies from 1–2 m (39%), 3–7 m (25%), 7–9 m (29%), to 13–20 m (< 7%). Two coal units (Danville and Colchester) are present in most locations. Figure 10 shows calculated volumes for each unit and total volumes for 22 counties.

Fig. 10

Coal seam volumes for Colchester (blue), Danville (orange) units, and total (grey) in selected counties

The total calculated volumes range from 0.15 to 24.5 km³. Applying the coefficient for void volume estimation, coef = 0.4 and 0.7, that volume reduces to 0.06 and 0.1 km³ at the lower end and to 9.8 and 17 km³ at the upper end. The estimated heat extracted for each temperature degree change is 2.5 × 10¹¹ kJ, 4.2 × 10¹¹ kJ, 41.1 × 10⁹ MJ, and 71.2 × 10⁹ MJ, respectively.

Using the favorability maps, one can create a county ranking to identify where additional data are needed. For example, data related to other technical aspects of an area with favorable resource potential should be collected. The top ten counties with an estimated total void volume above 7 km³ are overlayed on the residential (Fig. 11a) and commercial (Fig. 11b) heating favorability map with the location of abandoned mines. The information similar to Appendix Table 2 would need to be gathered for selected counties or regions of interest on a finer scale. When higher-resolution data become available, the resource estimates and demand can be updated using the same methodology. This methodology can be used to build a computational tool as a part of future work.

Fig. 11

a Residential and b commercial heating favorability maps (color maps), counties with the highest estimated void space (variable color outline), and abandoned mine locations (blue and violet symbols)

Local scale evaluation

Once a potential area is identified and all information is available on the local scale, the evaluation could be done using the same methodology. One factor that Richardson et al. (2016) and Menendez et al. (2020) note is that the end users need to be close to the geothermal mine water resource for it to be a commercially viable system. This can be achieved by adding another layer with a distance of the end user from a mine by using the Buffer function. The output can be used to recalculate how much of the estimated void volume and possible extracted heat belongs to an individual mine, on the technical feasibility side, who the end users are, and what their needs are in the mine vicinity, on the demand side.

The volume and connectivity of the underground workings for current and former mine land can change over time due to settling and tectonic activity. Hence, it is essential to locate the abandoned subsurface mine workings accurately, assess if sufficient volumes of water are present to meet the heating and cooling needs (e.g., Lee 2015), and develop 3D models of the mine structure to predict how water will flow through the underground mine workings (e.g., Farr and Busby 2021). For an open-loop system, the effect of the return water temperature on the intake temperature over time needs to be considered, including whether circulation flow rates in the mine are sufficient to avoid thermal stratification (e.g., Liu et al. 2016; Farr and Busby 2021).

Water chemistry is also an important factor to consider. The presence of oxygenated waters can change the chemical behavior, especially with respect to the formation of iron colloids, hydroxides, and oxides that can lead to clogging. Installing closed-loop systems inside the submerged mine workings (e.g., Farr et al. 2016; Hall et al. 2011; Korb 2012; Peralta Ramos et al. 2015; Rodriguez and Diaz 2009) or designing systems that are under positive pressure, or using nitrogen to limit the entry of air into the system are technological solutions to be considered to combat this problem.

When site-specific data on the hydrology and thermal regime of selected mines are available, numerical models can be constructed to predict the performance and economics of mine water geothermal systems (e.g., Adams et al. 2019; Bao et al. 2019; Chudy 2022; Rodríguez Díez and Díaz-Aguado 2014; Díaz-Noriega et al. 2020; Farr et al. 2016; Frejowski et al. 2021; Hahn et al. 2022; Menéndez et al. 2020; Monaghan et al. 2022; Perez Silva et al. 2022).

Conclusions

To reduce greenhouse gas emissions, transition to a clean energy economy, and revitalize former mining communities, there is an opportunity to redevelop many inactive mines land sites across the U.S. with clean energy technologies such as direct use heating. We present a framework that can be used across multiple scales (from national to local scale) to evaluate multiple factors that impact direct-use geothermal projects on mine lands. The strength of the multicriteria screening evaluation is the ability to combine and assess parameters that belong to disparate data categories (e.g., technical, economic, and social characteristics). While previous research has been focused on a specific aspect, e.g., technical feasibility or heat demand, this methodology allows us to evaluate these data together. The weights can be modified, or additional criteria can be easily added if input data support them. The multicriteria screening evaluation methodology provides a framework for identifying potential candidates for detailed site evaluation and characterization.

Appendix

See Table2.

Table 2 Screening criteria for mine water geothermal resource utilization