2021-11-19 | CGS Admin

The CGS has long been involved in researching the characteristics of geothermal energy across the state, publishing more than 30 reports on various aspects of this important renewable resource. In that regard we thought we would re-introduce some of that research and how it is accomplished. One particular metric that is used to generally classify a geothermal energy resource is called the geothermal gradient. This is a critical feature on our MS-51 Interpretive Geothermal Gradient Map of Colorado.

The geothermal gradient is the rate of increase of temperature with increasing depth in the Earth’s interior. The most accurate values are derived from a series of temperature measurements at different depths in a well, but these data are in the minority. Most geothermal gradients are derived from a single temperature measurement at the bottom of a well. The gradient is then calculated from difference between the bottom-hole temperature (BHT) and the mean annual surface ground temperature at the well site divided by the depth of the well. The result is most commonly expressed in units of degrees Celsius per kilometer (°C/km) or degrees Fahrenheit per 100 feet (°F/100 ft): 10°C/km = 0.55°F/100 ft.

Geothermal gradient measurements are made at specific locations within a well. Temperatures must vary smoothly, however, so there is an expectation that geothermal gradients will vary smoothly between measurements. Inevitably there are insufficient measurements to characterize all variations and details in a temperature and geothermal gradient. Any attempt to draw contours between geothermal gradient measurements is an interpretation. We therefore call the contour map of geothermal gradients an interpretive geothermal gradient map.

Three significant factors should be recognized as interpretive in using a geothermal gradient map. The first is that gradients can change significantly with depth. Heat flow may not be vertical, especially in sedimentary basins with salt domes, but the geothermal gradient is most likely to change vertically with rock type as thermal properties of the rock change. Coal and shale have low thermal conductivity and are associated with high thermal gradients; evaporites (salt and dolomite) have high thermal conductivity and are associated with low thermal gradients. Where these rock types are stacked vertically the geothermal gradient could change by as much as a factor of six. In addition, the mode of heat transfer can change from conduction to convection by groundwater flow. In vertical sections dominated by groundwater flow, the geothermal gradient can drop to zero or even negative. Extrapolation of geothermal gradients to depths greater than the deepest temperature measurement used in the calculation of the geothermal gradient is definitely an interpretation.

The second factor is the depth of measurement. A variety of different data sources have been compiled to contour the maps presented in MS-51. Most of these data are bottom-hole temperature data from oil and gas wells. In parts of some basins, such as the Denver Basin the depths of these data may exceed 3 km (9,850 ft). In other basins, such as the Raton Basin, most of the wells are shallower than 1 km (3,300 ft). In the mountain regions of Colorado gradient data are primarily compiled from detailed temperature logs from mineral exploration boreholes. Some of these boreholes exceed 1 km (3,300 ft) in depth, but many are shallower than 500 m (1,650 ft). Thus, the depth at which the geothermal gradients represent direct measurements varies with the data source.

The third factor is that most of the oil and gas well bottom-hole temperature data are underestimates of the undisturbed rock temperatures. During drilling, one purpose of the circulating drilling mud is to cool the drill bit. The mud then also cools the rock. Bottom-hole temperature measurements are generally made before rock at the bottom of the hole has re-heated from cooling by the drilling mud. The precise cooling and recovery time is different in every hole. General cooling corrections have been calculated and these have been applied to the data used in the maps presented below. However, they also represent a source of uncertainty in the data.

The MS-51 Interpretive Geothermal Gradient Map of Colorado—a general guide to where geothermal resources are likely to be found in Colorado—includes three map plates, two report documents, a geothermal gradient database, as well as the Geographic Information System (GIS) data files that were used to generate the maps.

The data included in MS-51 are also given as extrapolated temperatures to depth, but one should heed the cautions suggested above about the depths of temperature measurements. Geothermal gradient data points for the map are shown as black dots. The density of these control (data) points is quite variable. The density of data is highest around Mt. Princeton Hot Springs area—which includes the Hortense hot spring—is the hottest hot spring system in Colorado and shown enlarged as an inset map on the main map. This high density of data indicates that where very high geothermal gradients are found, they are likely to be very localized. In many other areas of the state, for example the central and western Gunnison valley, there are few or no data points. Single high (or low) gradient values may be contoured as broad anomalies such as the large anomaly over Rico in southwestern Colorado. The high geothermal gradients at Rico are real, but the extent of the anomaly shown on the map is questionable. However, no data currently exist to justify drawing it smaller. As we gather more data, we are learning that with “hot spots,” Mt Princeton is the more common size of a geothermal anomaly, not the size indicated for Rico.

One area in which the geothermal gradient anomaly does appear to be relatively large in area is the Raton Basin, the southernmost basin in Colorado to the east of the Front Range. New data from this basin indicate that, while not extending quite as far east as shown on the current map, the thermal anomaly covers most of the eastern portion of the basin. Gradients in the basin are generally high, but very slow water flow from west to east appears to be transferring heat from west to east and increasing gradients generally to the east. As more data are compiled and more is learned about the nature of individual geothermal anomalies, this map will be refined and become more useful at a sub-regional level.

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Energy, Geology

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2010s, case study, CGS, energy, geochemistry, geothermal, groundwater, hydrothermal, resources, RockTalk, water