Tectonic Controls on Taupo Volcanic Zone Geothermal Expression: Insights From Te Mihi, Wairakei Geothermal Field

Abstract

Information on structure, stress, and their interrelationship is essential for understanding structurally controlled geothermal permeability. Active fault mapping, borehole image analysis, and well testing in the Te Mihi geothermal area, New Zealand, allows us to refine structural and fluid flow architecture of this resource. The Te Mihi area is structurally complex, comprising a set of NW dipping master faults containing pervasive SE dipping antithetic and splay structures in their hanging walls. These faults are also intersected by E‐W striking faults. A localized, N‐S striking structural trend is also observed at Te Mihi. In consideration with Global Navigation Satellite System velocity vectors, both active NE‐SW and E‐W striking faults create biaxial extension at Te Mihi, though the observed NE‐SW SHmax direction suggests that contemporary extension is NW‐SE dominated. Stress field perturbations coincide with structural complexities like fault splays and intersections and/or proximity to recently active E‐W and NE‐SW striking structures. Borehole fluid flow at Te Mihi is concentrated at NW dipping master fault intersections, travel time fractures on acoustic image logs, halo fractures on resistivity image logs, NE‐SW and E‐W striking fractures, intervals of high fracture density, and spatial concentrations of wide aperture fractures and recently active NE‐SW and E‐W striking fractures. This study suggests Te Mihi geothermal expression results from biaxial extension evident from active structural trend intersections and the predominance of NE‐SW and E‐W striking structures within permeable well zones. Biaxial extension is therefore an important control on crustal fluid flow within the Taupo Volcanic Zone and thus geothermal resource delineation.

Variable In Situ Stress Orientations Across the Northern Hikurangi Subduction Margin

“…The GVR image logs were statically and dynamically normalized to enhance resistivity contrasts for improved feature identification, with a 1 and 0.5 m normalization window used for the latter. Feature classification is based on criteria set out in McNamara et al (2019). Quality rankings and circular statistics for stress induced borehole features identified from the GVR image logs follow World Stress Map criteria (Heidbach, 2016).…”

Fracture characteristics of Lower Carboniferous carbonates in northern Belgium based on FMI log analyses

“…Johri et al (2014) did interpret damage zones around faults from image logs; they encountered damage zones of 50 to 80 m in total. McNamara et al (2019) found high fracture density zones both within and outside projected fault zones in four boreholes, in volcanic lithologies. A spatial correlation between fault zones and larger fracture densities was only found in one of the boreholes.…”

“…Since FMI and acoustic image logs result in an oriented image of the borehole wall, they provide valuable in situ information on the reservoir characteristics and are widely used to characterise geothermal reservoirs. Image logs have been studied to identify sedimentological and structural features in the subsurface, such as bedding planes, fractures and faults, and to obtain information on in situ stress orientations (Tenzer et al, 1991;Dezayes et al, 1995;Genter et al, 1997;Prensky, 1999;Trice, 1999;Poppelreiter et al, 2010;Massiot et al, 2015;Williams et al, 2016;McNamara et al, 2019). Fractures and bed boundaries and their characteristics were quantified from the FMI log of the MOL-GT-01 borehole.…”

Landsat-8 data for chromite prospecting in the Logar Massif, Afghanistan

“…Recently, Landsat image has been implemented in a various applications, e.g. in the ecology ( Salas et al., 2017 ), Environmental ( Wang and Li, 2017 ), in water resources ( Abdelaziz et al., 2008 ; Abdelaziz and Bakr, 2012 ; Abdelaziz and Merkel, 2012 ; Edet et al., 2014 ; Abdelaziz and Le, 2014 ; Abdelaziz and Bambi, 2016 ) geothermal resources ( Qin et al., 2011 ; McNamara et al., 2016 ), mineral exploration ( Mia and Fujimitsu, 2012 ), and Agriculture ( Prishchepov et al., 2012 ). Many researchers around the world have used remote sensing data to differentiate serpentinized ultramafic rocks, which are hold potential for many types of deposits (e.g.…”