| Summary: | Porosity and permeability are critical petrophysical properties for reservoir modelling as they represent the reservoir's ability to store and transmit fluids. These properties can be collected directly from tests on rock samples, interpreted from electrical logs or borehole tests, or calibrated by computer models. Two main features are desired from these properties, that they are a good representation of the actual geology and that they can be used at a scale suitable for computer modelling. Geothermal settings can hinder the collection of petrophysical data. The costs of operation of collecting samples, the response of the geophysical tools, and the satisfactory operation of equipment in hot environments, are examples. Alternative methods to source these properties are essential when the data is not feasible or possible to collect. A characterization method using textural descriptors to generate petrophysical rock types, or petrotypes, has been developed for volcanic and volcaniclastic rocks. Four descriptors observed on hand samples, consolidation, groundmass content, pore type, and pore-filling occurrence, are combined to classify rocks into petrotypes. Three main petrotypes were identified with ranges of porosity and permeability that could be applied for properties population with a probabilistic approach. Rocks with a similar combination of descriptors can be used as analogues in cases where petrophysical data is scarce but hand samples are available. This paper presents the application of petrotypes in the Huka Group of the Tauhara Geothermal Field in New Zealand. Descriptors were observed at different depths on samples from four wellbores. Rock samples were classified into petrotypes according to their descriptors, and petrotypes were interpolated in the studied depth intervals. Cross-sections between the wellbores are shown with the interpolation of petrotypes in 2-dimensions. This approach shows petrotypes derived from textural descriptors working as a source of porosity and permeability estimates and ...
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