Abstract
Geothermal heat is one of the most important sources of renewable energy. Thus, increasing geothermal energy production for electricity has become a target of many countries worldwide. A thorough geological investigation is required to ensure the success of geothermal energy production. Investigating hydrothermal alteration products is among the things of concern because the spatial distribution of hydrothermal alteration minerals within geothermal systems can provide insight into the systems' characteristics, including thermal, permeability, and fluid chemistry arrangements. The techniques used to investigate hydrothermal alteration in geothermal systems are currently developing rapidly with new advancements in technology.
Infrared spectroscopy has been part of hydrothermal alteration mineral analysis procedures in geothermal research and exploration for the last 20 years. However, the more advanced version of this technique – infrared imaging spectroscopy (IRIS) – has only recently begun to be used in geothermal studies. This research investigates how IRIS can benefit the study of geothermal resources in an operational context. This research specifically aims to assess the IRIS capability to provide relevant, accurate and detailed mineralogical information from geothermal drill cuttings. This research also aims to develop a procedure that is applicable to the general geothermal exploration community at large. This research used hyperspectral images of cuttings from the Rantau Dedap geothermal system in Indonesia.
This research begins by investigating the prospects of IRIS application in the geothermal exploration industry. It is done by reviewing the use of infrared spectroscopy, here referred to as spot-based IRS, in geothermal works. The review defines how this method benefits the analysis of hydrothermal alteration products in geothermal systems. Afterwards, reviews of the works applying IRIS to geothermal studies were done to understand the progress of adapting the technique to the geothermal samples and context. Since the mineral exploration community has extensively applied IRIS, the experiences of the mineral exploration community on applying the technique were also reviewed to seek for opportunities in how the geothermal community should apply the technique.
The next step was defining a robust processing chain to create IRIS-based mineral maps on geothermal drill cuttings. It is done by first applying the commonly used classification algorithm that can handle a large dataset – Spectral Angle Mapper (SAM) – to evaluate its applicability on geothermal cuttings. Since the results were unsatisfactory, a new knowledge-based classification algorithm – the decision-tree algorithm – was developed. Knowledge of spectral characteristics of minerals and knowledge of geothermal geology were integrated when building the algorithm. In this algorithm, the minerals are classified based on their diagnostic absorption features, which will minimize the effect of external factors, such as the background shape of the spectra. The algorithm was structured to capture indicator minerals for acidic fluid environments and favourable high temperatures at an early stage, which is preferred, especially in mineral mixtures. The decision-tree algorithm classifies most minerals that commonly occur in geothermal systems. Therefore, it is expected that the algorithm can be applied to other geothermal systems without making many adjustments. The results showed that the decision-tree-classified images generally have high pixel classification accuracy for most minerals.
Since previous works indicated that infrared spectroscopy is more sensitive to identifying clay minerals than other hydrothermal alteration minerals, this research specifically analysed clay-separated samples on three analysis methods (IRIS, spot-based IRS, and XRD) to understand how the three methods differ in detecting clay minerals. The three methods' practicality (i.e., procedure and turn-around time) and the results (i.e., detected clay mineral types and their detection frequency) were compared to suggest practical clay identification procedures for future implementation, especially for the geothermal industry. The analysis was done on both whole-rock samples (IRIS, spot-based IRS, and XRD) as well as clay-separated samples (spot-based IRS and XRD). The spot-based IRS and XRD clay analysis measured samples in air-dried and glycolated states.
Based on this research results, a combination of whole-rock XRD, whole-rock IRIS, and glycolated whole-rock IRIS is recommended for application, especially for geothermal exploration. This research shows that the glycolation treatment provided an aid to distinguish smectite, illite-smectite interlayered, and smectite and illite that occur spatially close in spot-based clay IRS spectra. The glycolation treatment on whole-rock samples is believed to bring the same advantages in spot-based IRS and, thus also, IRIS. When the IRIS technique is not accessible, the spot-based IRS is a comparable yet more affordable alternative to IRIS. A combination of whole-rock XRD, whole-rock spot-based IRS, and glycolated whole-rock spot-based IRS should give similar results.
In the last stage of this research, the IRIS mineral identification results were brought into the context of geothermal systems. As cuttings from the Rantau Dedap geothermal system were studied, the IRIS mineral classification results were used to infer this system's geothermal/hydrothermal characteristics. The IRIS's ability to detect less abundant minerals helped to find indications of magmatic input in parts of the system that had not been detected before. The case study of Rantau Dedap also confirms the relationships between clay mineral type and magnetotelluric resistivity values, as well as the relationships between smectite occurrence and methylene blue stain test results.
Since IRIS does not require a complex sample treatment or changes in the sample state, it is suitable for application in every stage of geothermal system development, from exploration to production and monitoring; only the measurement's benefits might differ for each development stage. When applied in the exploration stage, IRIS provides ‘complete’ mineralogical composition and distribution early, increasing the confidence level of the studied geothermal system characteristics interpretation. In this stage, this technique can also be the first scanning tool for materials or samples that require further analysis. When applied during the production and monitoring stage, the mineralogical composition obtained from IRIS can help improve or even revise the studied geothermal system model. Furthermore, IRIS has great potential to be applied more than just as a mineral identification tool. With its high-resolution imaging advance, IRIS can assist in identifying the potential permeability of the system. It can also be applied as a monitoring tool.
Infrared spectroscopy has been part of hydrothermal alteration mineral analysis procedures in geothermal research and exploration for the last 20 years. However, the more advanced version of this technique – infrared imaging spectroscopy (IRIS) – has only recently begun to be used in geothermal studies. This research investigates how IRIS can benefit the study of geothermal resources in an operational context. This research specifically aims to assess the IRIS capability to provide relevant, accurate and detailed mineralogical information from geothermal drill cuttings. This research also aims to develop a procedure that is applicable to the general geothermal exploration community at large. This research used hyperspectral images of cuttings from the Rantau Dedap geothermal system in Indonesia.
This research begins by investigating the prospects of IRIS application in the geothermal exploration industry. It is done by reviewing the use of infrared spectroscopy, here referred to as spot-based IRS, in geothermal works. The review defines how this method benefits the analysis of hydrothermal alteration products in geothermal systems. Afterwards, reviews of the works applying IRIS to geothermal studies were done to understand the progress of adapting the technique to the geothermal samples and context. Since the mineral exploration community has extensively applied IRIS, the experiences of the mineral exploration community on applying the technique were also reviewed to seek for opportunities in how the geothermal community should apply the technique.
The next step was defining a robust processing chain to create IRIS-based mineral maps on geothermal drill cuttings. It is done by first applying the commonly used classification algorithm that can handle a large dataset – Spectral Angle Mapper (SAM) – to evaluate its applicability on geothermal cuttings. Since the results were unsatisfactory, a new knowledge-based classification algorithm – the decision-tree algorithm – was developed. Knowledge of spectral characteristics of minerals and knowledge of geothermal geology were integrated when building the algorithm. In this algorithm, the minerals are classified based on their diagnostic absorption features, which will minimize the effect of external factors, such as the background shape of the spectra. The algorithm was structured to capture indicator minerals for acidic fluid environments and favourable high temperatures at an early stage, which is preferred, especially in mineral mixtures. The decision-tree algorithm classifies most minerals that commonly occur in geothermal systems. Therefore, it is expected that the algorithm can be applied to other geothermal systems without making many adjustments. The results showed that the decision-tree-classified images generally have high pixel classification accuracy for most minerals.
Since previous works indicated that infrared spectroscopy is more sensitive to identifying clay minerals than other hydrothermal alteration minerals, this research specifically analysed clay-separated samples on three analysis methods (IRIS, spot-based IRS, and XRD) to understand how the three methods differ in detecting clay minerals. The three methods' practicality (i.e., procedure and turn-around time) and the results (i.e., detected clay mineral types and their detection frequency) were compared to suggest practical clay identification procedures for future implementation, especially for the geothermal industry. The analysis was done on both whole-rock samples (IRIS, spot-based IRS, and XRD) as well as clay-separated samples (spot-based IRS and XRD). The spot-based IRS and XRD clay analysis measured samples in air-dried and glycolated states.
Based on this research results, a combination of whole-rock XRD, whole-rock IRIS, and glycolated whole-rock IRIS is recommended for application, especially for geothermal exploration. This research shows that the glycolation treatment provided an aid to distinguish smectite, illite-smectite interlayered, and smectite and illite that occur spatially close in spot-based clay IRS spectra. The glycolation treatment on whole-rock samples is believed to bring the same advantages in spot-based IRS and, thus also, IRIS. When the IRIS technique is not accessible, the spot-based IRS is a comparable yet more affordable alternative to IRIS. A combination of whole-rock XRD, whole-rock spot-based IRS, and glycolated whole-rock spot-based IRS should give similar results.
In the last stage of this research, the IRIS mineral identification results were brought into the context of geothermal systems. As cuttings from the Rantau Dedap geothermal system were studied, the IRIS mineral classification results were used to infer this system's geothermal/hydrothermal characteristics. The IRIS's ability to detect less abundant minerals helped to find indications of magmatic input in parts of the system that had not been detected before. The case study of Rantau Dedap also confirms the relationships between clay mineral type and magnetotelluric resistivity values, as well as the relationships between smectite occurrence and methylene blue stain test results.
Since IRIS does not require a complex sample treatment or changes in the sample state, it is suitable for application in every stage of geothermal system development, from exploration to production and monitoring; only the measurement's benefits might differ for each development stage. When applied in the exploration stage, IRIS provides ‘complete’ mineralogical composition and distribution early, increasing the confidence level of the studied geothermal system characteristics interpretation. In this stage, this technique can also be the first scanning tool for materials or samples that require further analysis. When applied during the production and monitoring stage, the mineralogical composition obtained from IRIS can help improve or even revise the studied geothermal system model. Furthermore, IRIS has great potential to be applied more than just as a mineral identification tool. With its high-resolution imaging advance, IRIS can assist in identifying the potential permeability of the system. It can also be applied as a monitoring tool.
Original language | English |
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Qualification | Doctor of Philosophy |
Awarding Institution |
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Supervisors/Advisors |
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Award date | 9 Oct 2024 |
Place of Publication | Enschede |
Publisher | |
Print ISBNs | 978-90-365-6202-7 |
Electronic ISBNs | 978-90-365-6203-4 |
DOIs | |
Publication status | Published - 9 Oct 2024 |