Download estimating hot dry rock geothermal potential in kenya by emulating

ESTIMATING HOT DRY ROCK
GEOTHERMAL POTENTIAL IN KENYA BY
EMULATING WORLD’S ENGINEERED
GEOTHERMAL SYSTEMS
BY
MUTUA ERASTUS
I13/1407/2012
A DISSERTATION SUBMITTED IN
PARTIAL FULFILLMENT FOR THE
AWARD OF BSC (GEOLOGY)
APRIL 2016
UNIVERSITY OF NAIROBI
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Abstract
This project was aimed to estimate HDR energy potentials for Kenya by emulating world’s
engineered geothermal system. Engineered geothermal systems in countries such as US,
Australia and Europe (Soutz-sous Forets project in France) have been relied on for the
estimation.
The ideas and procedures used in US to estimate HDR energy potentials in the country were
emulated for estimations in Kenya. Geological aspects such as rock units, structural geology and
ideal geological requirements were also reviewed. Basement rock units with ideal characteristics
for HDR system development such as having appropriate heat values, slightly permeable and
having ‘directory’ faults are discussed in the review. Basement rocks in this case are considered
to be either metamorphic or igneous rocks. Also, near surface intrusion mostly of granitic
characteristics are reviewed to be good for HDR system developments. Granitic intrusions are
preferred for engineered HDR system development because of their homogeneity. Sedimentary
rocks, on areas of thick sediments (>3.5 km) are well lithified, with minimized porosity and
permeability just like the basement rock units. Therefore, on zones of high heat potentials (T
>300˚C), can be treated ideal for HDR geothermal system development.
Thermal data (temperature at depth) was predicted from measured heat flow values using various
variables such as Measured Heat Flow (Qo), Mantle Heat Flow (Qm), Thermal Conductivity (K),
Temperature: Surface (To) or at Depth (T), Radioactivity Heat Generation (A), Radioactivity
Depth Variable Constant (R), Layer Thickness (X). Temperature values were predicted for 3.5
km, 6.5 km and 10 km depths from the surface. These data sets were used to estimate HDR
energy potentials for Kenya.
ArcGIS 10.1, Oasis Montaj and Surfer 9 software were used in data analysis and interpretation.
ArcGIS and Oasis Montaj were used to carry out spatial analysis of the data sets used. Surfer was
used to create 3D view of heat flow data. Microsoft excel (spreadsheet) was used to create
thermal profiles for better visualization of heat potentials at depth and its dependency to geology
of the area.
Kenyan rift valley was found to possess highest heat flow and heat energy potentials. This is
because of its thin crust as compared to other regions of the country. However, at preferred depth
of 6.5 km, most parts of the country were found to possess productive heat energy values with
success of other parameter considerations such as availability of water, engineering
characteristics of the rock on the area, among others.
HDR energy potential maps, heat flow and temperature at depth contour maps were developed to
show the HDR potentials for Kenya.
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