S3 mineral targeting for porphyry copper exploration using natural field electromagnetics and magnetics: A case study from the Huckleberry and Berg–Ootsa Cu–Mo porphyry projects, near Houston, BC, Canada

Abstract The Huckleberry project and porphyry copper–molybdenum mine and adjoining Berg and Ootsa porphyry projects are located approximately 90 km southwest of Houston, British Columbia (Figure 1). Together they form a large and rich mineral endowment, with as many as six known porphyry deposits and numerous occurrences, making them ideally suited for study using airborne geophysical methods. In 2021, Geotech Ltd. carried out a helicopter-borne natural field electromagnetic (NFEM) and magnetic survey over the Berg–Ootsa and Huckleberry projects that consisted of a combined 5251 line-km of coverage. Analyses of the airborne geophysical responses and 3D inversion results show that the known porphyry deposits all coincide with well-defined subcircular or tabular resistivity lows and similar coincident magnetic high signatures but with varying degrees of size and amplitude. These geophysical signatures are consistent with those previously found in NFEM and other airborne electromagnetic surveys over other calc-alkaline type porphyry deposits in the Western Cordillera. Other similar geophysical signatures are observed, but efficient targeting of potential porphyries over the vast survey area proves difficult due to the large number and their variable nature. A semiautomated mineral targeting approach was implemented that uses a relatively objective, machine-learning-assisted method, which combines structural complexities, self-organizing map classifications, and supervised deep neural network (SDNN) targeting. Using the Huckleberry deposit as a training area, the SDNN targeting approach was extended to a larger area covering the Berg–Ootsa–Huckleberry projects and has identified most of the known porphyry deposits and prospects, as well as new areas for follow-up.

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Publication Details

Journal
The Leading Edge
Published
2025-11-01
DOI
https://doi.org/10.1190/tle44110866.1
Primary Topic
Geophysical and Geoelectrical Methods
Type
article
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article

S3 mineral targeting for porphyry copper exploration using natural field electromagnetics and magnetics: A case study from the Huckleberry and Berg–Ootsa Cu–Mo porphyry projects, near Houston, BC, Canada

Karl Kwan, Shane Ebert, Jean M. Legault, Jim Miller-Tait et al.
The Leading Edge
Geophysical and Geoelectrical Methods
article

S3 mineral targeting for porphyry copper exploration using natural field electromagnetics and magnetics: A case study from the Huckleberry and Berg–Ootsa Cu–Mo porphyry projects, near Houston, BC, Canada

Karl Kwan, Shane Ebert, Jean M. Legault, Jim Miller-Tait, Lars Owe Nilsson, Derek Saxton
article en

Abstract

Abstract The Huckleberry project and porphyry copper–molybdenum mine and adjoining Berg and Ootsa porphyry projects are located approximately 90 km southwest of Houston, British Columbia (Figure 1). Together they form a large and rich mineral endowment, with as many as six known porphyry deposits and numerous occurrences, making them ideally suited for study using airborne geophysical methods. In 2021, Geotech Ltd. carried out a helicopter-borne natural field electromagnetic (NFEM) and magnetic survey over the Berg–Ootsa and Huckleberry projects that consisted of a combined 5251 line-km of coverage. Analyses of the airborne geophysical responses and 3D inversion results show that the known porphyry deposits all coincide with well-defined subcircular or tabular resistivity lows and similar coincident magnetic high signatures but with varying degrees of size and amplitude. These geophysical signatures are consistent with those previously found in NFEM and other airborne electromagnetic surveys over other calc-alkaline type porphyry deposits in the Western Cordillera. Other similar geophysical signatures are observed, but efficient targeting of potential porphyries over the vast survey area proves difficult due to the large number and their variable nature. A semiautomated mineral targeting approach was implemented that uses a relatively objective, machine-learning-assisted method, which combines structural complexities, self-organizing map classifications, and supervised deep neural network (SDNN) targeting. Using the Huckleberry deposit as a training area, the SDNN targeting approach was extended to a larger area covering the Berg–Ootsa–Huckleberry projects and has identified most of the known porphyry deposits and prospects, as well as new areas for follow-up.

The Leading EdgeVol. 44(11)
Surrey Memorial Hospital (CA), Imperial Metals (Canada) (CA), Jiangxi Copper (China) (CN), Petro Geotech (Canada) (CA)
Openalex Percentile: Top 65%
Geophysical and Geoelectrical Methods
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