Detection of Near-Surface Permeable Zones Based on Spatial Correlation Between Radon Gas Concentration and DTM-Derived Lineament Density

Radon-222 (Rn) concentrations in soil gas have been used to locate near-surface permeable zones (e.g., fractures, faults) along which hydrothermal fluids ascend in geothermal fields. However, permeable zone detection over a field is often difficult owing to limited numbers and locations of Rn data points. This study aims to develop methodology to enable the regional detection of permeable zones by multivariate geostatistical modeling of Rn concentrations using the Wayang Windu geothermal field (WWGF) in West Java, Indonesia as a model case. Rn concentrations were measured using sampled gases from 17 shallow drill holes with 3–5 m depth over a 5.30 × 9.20 km area. The measurements were repeated over five periods in 2016–2017. To supplement the Rn point data, we produced a digital terrain model with 20-m resolution using an unmanned aerial vehicle and extracted lineaments using the modified segment tracing algorithm (m-STA). Three types of lineament density maps with a grid-cell size of 0.25 × 0.25 km were prepared for the densities of lineament frequency (number), total length and number of intersections in a unit cell. The Rn concentrations measured during the five periods were mapped over the WWGF by the collocated cokriging method using Rn concentrations as the primary variable (point data) and lineament density as the secondary variable (within the grid-cell data). A fuzzy logic approach was then applied to assess permeability as an index of 0–1 by overlaying the estimated Rn concentrations and three types of lineament density. The detected permeable zones mainly overlap with the geothermal manifestations and regional faults, and the permeable indexes generally correspond with Rn concentrations from eight new drill holes, which verify the effectiveness of the proposed method.