Remote sensing investigations combined with Geographical investigation systems (GIS) provide a rapid and cost-effective method for prospecting hydrothermal and geothermal systems. Most geothermal systems in Kenya are found in remote areas where accessibility is difficult. This study was carried out on Paka volcano which is located in the Kenyan rift valley. The aim of the study was to use remote sensing and GIS to investigate hydrothermal minerals and structures associated with geothermal activities. The study involves use of Landsat TM image classification using ENVI 5.1 and ArcGIS. Lineament extraction was done using PCI geomatics 2015 while Rose diagrams were generated using Rockworks 16. The research has shown that lithological, hydrothermal mineralization and structural maps can be generated form Landsat TM images using remote sensing and GIS. It has been shown that faults trend in the Northeast, North and Northwest direction. Hydrothermal minerals that are rich in iron and clays occur on Paka volcano mountain and its neighbouring areas.
The effects of climate change and unpredictable weather patterns have affected hydro-power generation in Kenya. This has influenced the strategies in the power sector towards stimulating growth and development of geothermal energy. Geothermal exploration in Kenya started in the 1960s with the drilling of two geothermal wells in Olkaria [
The presence, abundance and stability of hydrothermal alteration minerals depend on lithology, pressure, temperature, permeability and fluid composition of the system. Through the study of alteration minerals, estimate of subsurface temperature and any changes can be deduced [
Paka is one of the geothermal prospects in the Kenyan Rift. It is defined by a shield volcano, and is characterized by intense and widespread geothermal surface activity manifested in the form of fumaroles, hot grounds and hydrothermally altered rocks. Over the last two decades, detailed geological geothermal investigations have become less visibly considered in exploration of geothermal resources, due to budgetary constraints; yet there is high demand for energy for the Republic of Kenya. There is need to evaluate this problem by coming up with other ways which are cost effective for doing geothermal exploration. Most equipment for geothermal exploration can be quite expensive; for instance geophysical equipment are very costly as compared to remote sensing softwares. Some areas are also insecure and inaccessible. Therefore there is need to use a method of geothermal exploration; which will cater for these problems.
This project aims at mapping lithology, structurers, and characterizing clays of Paka volcano in the Kenyan Great Rift Valley. Identifying and interpreting hydrothermal minerals (clays) is useful in surface geothermal exploration. Clays related to surface geothermal activity act as mineral geothermometers and guide in pointing out the best drilling targets by indicating possible up flow and outflow zones. Information about clay minerals also helps in defining the hydrology of a geothermal reservoir. The existence of structures plays an important role in creating a flow path through which hydrothermal fluids are transported to the surface; hence the need to map them. The eruption centres are useful, in that they indicate the magma chamber below the system is still active. By using techniques of remote sensing; volcanic activity, geological formations and alteration mineral zones can be detected and mapped on a regional scale. The use of remote sensing is accurate and it covers a large area at once. It is also cost-effec- tive, in terms of spatial resolution.
The Paka volcano is in Rift valley (
Paka is composed of trachytic and basaltic lavas and pyroclastic deposits. The
geology of Paka seems to be highly influenced by tectonism and volcanism. The evolutionary history may be broadly divided into two periods of Trachytic volcanism separated by basaltic activity and faulting. Volcanic activity commenced by 390 Ma and has continued to within 10 Ma. Much of the shields forming lavas are covered by trachytic pyroclastic deposits which are seen to cover the areas around the volcano.
Surface geothermal activity is manifested in form of hot ground, steaming ground and fumaroles. Geothermal activity covers an area of approximately 32 km2; extending northwards across the summit area and down the northern flanks of the volcano. Geothermal activity within the main zone is mostly controlled by faults which trend NNE, associated with pumice cones and scoria
aligned along the fractures. Highest temperatures are found within areas of steaming ground, evidenced by red, purple and white clays. Areas of geothermal extinction (
The hottest ground and strongest fumaroles are found at the caldera, on the south western rim of the cone. Basalt and scoria have been altered to purple, red and white clays with sulfates. At the base of the caldera, trachyte have been altered to kaolinite and alunite (white clays). At the southern flanks, pyroclastics have been altered to red clays and lower temperatures are noted. There are no hot springs in Paka. There are pools of warm water which form within the craters by condensation from fumaroles on almost-vertical rock surfaces.
After acquiring Landsat 7 ETM satellite image and the DEM from the internet, these data sets were processed using the necessary softwares (ENVI 5.1 and Arc GIS 10.3). A lithological map, structural map and hydrothermal alteration maps were developed. These three maps are important geological data sets in evaluating a geothermal resource.
The methods performed in this study employed the image processing and analyzing geospatial imagery techniques provided by software ENVI 5.1 to carry out the lithological classification on Landsat TM image of the study area. The methodology consisted of three steps which are pre-processing, lithological classification, and post-processing. Maximum Likelihood classification was chosen to perform the supervised classification. Landsat TM satellite data was downloaded from http://earthexplorer.usgs.gov/acquired on10-Feb-2014. The bands used for the composites were band 7, band 4 and band 1 in Red, Green and Blue channels respectively in ENVI software. The training sites were developed after running unsupervised classification to assess the suitable classification algorithm and optimal number of classes. Supervised image classification was conducted using maximum likelihood classifier. Sieving and clumping of the resulting classes was carried out for the vectorized classification derivatives. The final lithological map was developed using ArcGIS 10.1.
Knowlegde based feature extraction method was used to digitize structures and eruption centres from the image composite. The data preparation was done in Envi 5.1 where Landsat TM (Bd 7/R, Bd 4/G, Bd 1/B) composite was developed and exported to ArcGIS 10.1 software. To facilitate identification of the structures and eruption centers, the composite image was draped over a digital elevation model to contrast the structures and eruption centers from other features. The structures and the eruption centers were digitized.
Landsat 7 ETM image and DEM were obtained. Band combinations were done in ENVI. The faults and eruption centres were overlayed with DEM and digitized in Arc GIS. A structure (fault) map with eruption centres was developed.
The spectral bands of Landsat TM are well-suited for recognizing assemblages of alteration minerals. Recognition of hydrothermally altered rocks that may be associated with mineral deposits can thus be identified and mapped. There are numerous methods that can be used to map alteration using remotely sensed data. In this study, band ratio method was used. Band ratio method is the very simple and powerful technique in the remote sensing. Basic idea of this technique is to emphasize or exaggerate the anomaly of the target object. Each object has its own spectral reflectance pattern indifferent wavelength portion. Spectral reflectance curve is a kind of fingerprint of the object. The object or rock unit may have high reflectance value in some spectral portion, however, it may absorb in another spectral region.
The reflectance spectra of the common hydrothermal clay minerals; Alunite, illite, kaolinite, and montmorillonite have distinctive absorption reflectance minima at wavelengths within the bandpass of Landsat TM band 7 as shown in
rocks have similar values in band 5. The reflectance of unaltered rocks in band 7 is similar to that in band 5. Therefore, the 5/7 ratio for unaltered rocks is unity 1.00. Altered rocks, however, have lower reflectance in band 7 because of the absorption caused by the minerals shown in
Iron oxides and sulfates are the second group of minerals associated with hydrothermally altered rocks. The spectra of the iron minerals have low blue reflectance in Landsat TM band 1 and high red reflectance in Landsat TM band 3. Iron-stained hydrothermally altered rocks therefore have high values in a 3/1 ratio image.
Color composite ratio images were produced by combining three ratio images in blue, green, and red.
Generally the following steps were followed in carrying out the band ratio analysis of alteration minerals:
1) Converting the Landsat TM data to surface reflectance data using dark object subtraction atmospheric correction algorithm in Envi 5.1;
2) Carrying out the band ratios (5/7, 3/1 and 3/5 respectively) and computing statistics of the results;
3) Resampling of the results of the band rations to 8 bit prior to density slicing and extraction of alteration mineral spectra and anomalous areas;
4) Preparation of the final anomaly maps in ArcGIS 10.1.
In Paka the main lithology are lavas and alluvium. The lavas mainly include trachyte and basalts. These shows that the rocks are bimodal in nature such that we have the basic rocks represented by basalts at one end and acidic rocks represented by trachyte at one end. This indicates a very dynamic magmatism where differentiation has occurred in magma chamber and new rejection of magma as inferred by the basalts. Other magmatic activity is represented by volcaniclastics. This means that actually a magma chamber exists below Paka, where differentiation occurs at top of the chamber represented by gases and more sillic material erupted at the volcaniclastic. The presence of magma chamber is an indication that a heat source is present that drives the geothermal system under Paka volcano.
Alluvium on the other hand is a factor of topography and erosion where low lying areas usually transected by flood waters are where these deposits are found. The geological structures are well defined by The DEM image and previous maps. Structures are important in geothermal system as fluid flow conduits, mainly hot water and steam. Usually down flow and up flow structures occur for recharge and conduit for a geothermal system respectively. The up flow structures are usually targeted for drilling in Paka geothermal manifestations occur along mapped structures.
Hydrothermal alteration are usually mapped by observation in the field, they are as indicators of geothermal system. They also infer structural trends. The important hydrothermal alterations are the clay alteration.
The following lithological map was obtained in Arc GIS after performing unsupervised and supervised image classification in ENVI 5.1
The lithology of Paka consists of mostly trachytes and basalt rocks, with volcanic flows and few mugearites as shown from remote sensing technique (
The structures identified in Paka volcano are mainly faults (
The structures that were identifiable from the landsat images were faults. This was possible by the aid of elements of visual interpretation. The shadow effect enabled digitization of these faults. Most of the lineaments trend in the North Eas, Northt and North West direction as shown rose diagram (
Most; if not all structures, are aligned in N-S orientation (
Eruption centres are points of lava outflow (
Combined map of eruption centres and structural map (
Most faults occur in basalts and trachyte rocks. The faults trend in the NE to NNE direction.
Hydrothermally altered zones are indicated by the blue and red colours. These areas are mainly along the fault zones. This shows that hydrothermal alterations (clays); which are geothermal manifestations are mainly structure controlled. The areas in red represent iron minerals which are heavy, they are weathered and eroded materials deposited in erosional channels or low-lying area where alluvium are also deposited.
The clay minerals occur along fault zones, which represent leakages areas and are good indicators of presence of a geothermal system in Paka volcano (
This study aimed to use the ability of remote sensing techniques to locate hydrothermal minerals and geological structures. The study site was selected in the rift valley where most of the geothermal centers exist. The area covered was about 2400 square kilometers. The achievement of the goal of the application of remote sensing techniques on studied Paka volcano led to the realization of different lithologies around Paka Mountain. Hydrothermal minerals (Sericite and Kaolinite) on Paka volcano were also detected by Landsat TM. Hydrothermal minerals (Sericite and Kaolinite) are observed along the faults. The association of the fault and hydrothermal minerals indicates that the fluids that caused mineralization were generated through the faults. Mineralization might have taken place due to geothermal activities on the Mountain. Structural lineaments (faults and fractures) around the volcano trend in the North-South direction. Rose
diagram shows that most of the lineament trend in the Northeast, North and Northwest. These lineaments are mainly the faults which seem to follow the trend of the major Kenya rift valley that trends in the North-South direction.
Achieng, J., Mutua, J., Mibei, G., Olaka, L. and Waswa, A.K. (2017) Mapping of Hydrothermal Minerals Related to Geothermal Activities Using Remote Sensing and GIS: Case Study of Paka Volcano in Kenyan Rift Valley. International Journal of Geosciences, 8, 711-725. https://doi.org/10.4236/ijg.2017.85039