Characteristic Periodic Variations of Surface Geothermal Features

This study aims to identify and interpret
characteristic periodic variations in surface
features by analyzing measurements of water level,
conductivity, temperature, rainfall and barometric
pressure data. The measurements are filtered using an
adaptive wavelet based filter to extract the
influence of earth and gravity tides, rainfall, and
barometric pressure. Fourier analysis is used to
further examine the content of the extracted signals.
A system dynamics model of a spring is formulated to
demonstrate fundamental heat and mass transfer. This
study aims to provide an understanding of the effects
of periodic forcing functions on geothermal features
based on high accuracy measurements taken at high
sampling rates. Once the amplitude and frequency of
any forcing functions have been identified, these can
be monitored to minimise the time to identify and
quantify any changes in reservoir characteristics.

Autorentext

Associate Professor Dr Jonathan Leaver works at Unitec Institute
of Technology, Auckland, New Zealand. Dr Leaver was formerly
Chief Petroleum and Geothermal Inspector for the Ministry of
Commerce. He holds a BE(Hons)(Civil), and a PhD (Mech) from the
University of Auckland and an MS(Petroleum) from Stanford University.

Klappentext

This study aims to identify and interpret
characteristic periodic variations in surface
features by analyzing measurements of water level,
conductivity, temperature, rainfall and barometric
pressure data. The measurements are filtered using an
adaptive wavelet based filter to extract the
influence of earth and gravity tides, rainfall, and
barometric pressure. Fourier analysis is used to
further examine the content of the extracted signals.
A system dynamics model of a spring is formulated to
demonstrate fundamental heat and mass transfer. This
study aims to provide an understanding of the effects
of periodic forcing functions on geothermal features
based on high accuracy measurements taken at high
sampling rates. Once the amplitude and frequency of
any forcing functions have been identified, these can
be monitored to minimise the time to identify and
quantify any changes in reservoir characteristics.