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Research article · 2025 · Full text

International Journal of Geography Geology and Environment

Mineralogical and structural controls on gold mineralization in the Ashanti greenstone belt

Nathalie FortinD.R. MacPhersonMarie Lefebvre

Volume 7(1) · Pages 105–108 · DOI: 10.22271/27067483.2025.v7.i1b.550 ↗

Research areasGeological and Geochemical AnalysisGeochemistry and Geologic MappingGeochemistry and Geochronology of Asian Mineral Deposits

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Abstract

Author-written

Picture a narrow shear zone cutting through two-billion-year-old volcanic rock—within that deformation corridor, gold concentrations can jump from background levels of 5 parts per billion to economic grades above 8 grams per tonne in less than a metre. This research examined the mineralogical and structural controls on gold distribution across three mine sites in the Ashanti Greenstone Belt of southern Ghana, one of West Africa's most prolific gold provinces. A total of 128 drill-core samples were collected and analysed by reflected-light and scanning-electron microscopy, whole-rock geochemistry (fire assay Au; ICP-MS multi-element), and structural logging. Gold mineralisation was found to be concentrated in arsenopyrite-bearing quartz veins hosted within second-order shear zones that splay off the main Ashanti fault. Mean gold grade in shear-zone cores reached 8.74 g/t, compared with 2.13 g/t in disseminated sulphide zones away from structures. Arsenic showed the strongest geochemical association with gold (r = 0.91), followed by sulphur (r = 0.83) and antimony (r = 0.76). The results confirm that structural preparation—particularly dilatant jogs within shear networks—exerts first-order control on ore-shoot geometry, while arsenopyrite acts as the principal gold-hosting mineral phase.

Summary

Source-checked

Plain-language reading of the full paper, prepared with AI and checked against the text. Each point links to the authors' own words.

  1. Why it matters

    • The Ashanti Greenstone Belt is a major gold province, but the specific relationship between mineralogy and structure that controls gold concentration is not fully documented. View evidence ↗

      Why it matters

      The Ashanti Greenstone Belt is a major gold province, but the specific relationship between mineralogy and structure that controls gold concentration is not fully documented.

      In the paper's own words

      “The Ashanti Greenstone Belt has been mined for over a century, yet the interplay between mineralogy and structure that governs where gold concentrates remains incompletely documented at the deposit scale [1].”

      Page 1

      Found in: Introduction

      Read it in the full textOpen PDF at page 1 ↗
    • The region consists of Paleoproterozoic metavolcanic and metasedimentary rocks intersected by the Ashanti fault system, a shear zone exceeding 200 km in length. View evidence ↗

      Why it matters

      The region consists of Paleoproterozoic metavolcanic and metasedimentary rocks intersected by the Ashanti fault system, a shear zone exceeding 200 km in length.

      In the paper's own words

      “The belt is a northeast-trending Paleoproterozoic sequence of metavolcanic and metasedimentary rocks intruded by granodiorite and cut by the Ashanti fault system, a crustal-scale shear zone that extends for more than 200 km [2].”

      Page 1

      Found in: Introduction

      Read it in the full textOpen PDF at page 1 ↗
    • Two theories explain gold concentration: a structural model focusing on dilatant sites like jogs and bends, and a replacement model focusing on wall-rock reactivity and sulphidation. View evidence ↗

      Why it matters

      Two theories explain gold concentration: a structural model focusing on dilatant sites like jogs and bends, and a replacement model focusing on wall-rock reactivity and sulphidation.

      In the paper's own words

      “Two models compete: the structural model, which argues that gold is concentrated wherever shear-zone geometry creates dilatant sites—jogs, bends, and fault intersections—that act as chemical traps for ascending hydrothermal fluids [5]; and the replacement model, which emphasises wall-rock reactivity, particularly iron-rich lithologies that trigger sulphidation and gold precipitation regardless of structural setting [6].”

      Page 1

      Found in: Introduction

      Read it in the full textOpen PDF at page 1 ↗
  2. The question

    • The study aimed to test the structural and replacement models by mapping structural architecture, characterizing mineralogy and geochemistry, and identifying the best predictors for gold grade. View evidence ↗

      The question

      The study aimed to test the structural and replacement models by mapping structural architecture, characterizing mineralogy and geochemistry, and identifying the best predictors for gold grade.

      In the paper's own words

      “This research aimed to test these competing models by: (a) mapping the structural architecture of three deposits at the core-log scale, (b) characterising the mineralogy and geochemistry of ore and waste zones, and (c) determining which combination of structural and mineralogical variables best predicts gold grade [7].”

      Page 1

      Found in: Introduction

      Read it in the full textOpen PDF at page 1 ↗
  3. What they did

    • Researchers collected 128 drill-core samples from three mine sites: Obuasi (48), Bogoso (42), and Bibiani (38). View evidence ↗

      What they did

      Researchers collected 128 drill-core samples from three mine sites: Obuasi (48), Bogoso (42), and Bibiani (38).

      In the paper's own words

      “A total of 128 drill-core samples were collected from three active mine sites along the Ashanti Belt: Obuasi (48 samples), Bogoso (42 samples), and Bibiani (38 samples).”

      Page 2

      Found in: Introduction

      Read it in the full textOpen PDF at page 2 ↗
    • The study was conducted from March 2021 to September 2023. View evidence ↗

      What they did

      The study was conducted from March 2021 to September 2023.

      In the paper's own words

      “The research was conducted between March 2021 and September 2023 under institutional approval from the Halifax Academy of Coastal and Marine Research (Protocol HACMR/2021-027, approved 3 March 2021).”

      Page 2

      Found in: Introduction

      Read it in the full textOpen PDF at page 2 ↗
    • Structural domains were categorized into five types: shear-zone core, shear-zone margin, fold hinge, quartz-vein set, and disseminated sulphide. View evidence ↗

      What they did

      Structural domains were categorized into five types: shear-zone core, shear-zone margin, fold hinge, quartz-vein set, and disseminated sulphide.

      In the paper's own words

      “Structural domains were classified as shear-zone core, shear-zone margin, fold hinge, quartz-vein set, and disseminated sulphide based on core-log characteristics [4].”

      Page 2

      Found in: Methods

      Read it in the full textOpen PDF at page 2 ↗
  4. What they found

    • Shear-zone cores had the highest mean gold grade at 8.74 g/t, which is over four times higher than the 2.13 g/t found in disseminated sulphide zones. View evidence ↗

      What they found

      Shear-zone cores had the highest mean gold grade at 8.74 g/t, which is over four times higher than the 2.13 g/t found in disseminated sulphide zones.

      In the paper's own words

      “Table 1 confirms that shear-zone cores yielded the highest mean gold grade (8.74 g/t), more than four times the disseminated sulphide average (2.13 g/t).”

      Page 2

      Found in: Conclusion

      Read it in the full textOpen PDF at page 2 ↗
    • Quartz-vein sets had the second-highest mean gold grade at 6.48 g/t. View evidence ↗

      What they found

      Quartz-vein sets had the second-highest mean gold grade at 6.48 g/t.

      In the paper's own words

      “Quartz-vein sets ranked second (6.48 g/t), reflecting the well-known association between vein emplacement and dilatant structural sites.”

      Page 2

      Found in: Introduction

      Read it in the full textOpen PDF at page 2 ↗
    • Arsenic had the strongest correlation with gold (r = 0.91), followed by sulphur (r = 0.83) and antimony (r = 0.76). View evidence ↗

      What they found

      Arsenic had the strongest correlation with gold (r = 0.91), followed by sulphur (r = 0.83) and antimony (r = 0.76).

      In the paper's own words

      “Arsenic showed the strongest geochemical association with gold (r = 0.91), followed by sulphur (r = 0.83) and antimony (r = 0.76).”

      Page 1

      Found in: Discussion

      Read it in the full textOpen PDF at page 1 ↗
    • Samples containing arsenic concentrations above 1,000 ppm almost always had gold grades exceeding 6 g/t. View evidence ↗

      What they found

      Samples containing arsenic concentrations above 1,000 ppm almost always had gold grades exceeding 6 g/t.

      In the paper's own words

      “Samples with arsenic above 1,000 ppm almost invariably carried gold grades above 6 g/t”

      Page 3

      Found in: Results

      Read it in the full textOpen PDF at page 3 ↗
    • A combined structural and geochemical model explained 87% of gold grade variance, outperforming structural predictors alone (61%) or geochemical predictors alone (72%). View evidence ↗

      What they found

      A combined structural and geochemical model explained 87% of gold grade variance, outperforming structural predictors alone (61%) or geochemical predictors alone (72%).

      In the paper's own words

      “The combination of structural and geochemical predictors in the stepwise regression explained 87% of the variance in gold grade—significantly more than either predictor set alone (structural alone: 61%; geochemical alone: 72%).”

      Page 3

      Found in: Discussion

      Read it in the full textOpen PDF at page 3 ↗
  5. What it means

    • The authors conclude that a dual-control model using both structural and geochemical data provides a practical framework for exploration. View evidence ↗

      What it means

      The authors conclude that a dual-control model using both structural and geochemical data provides a practical framework for exploration.

      In the paper's own words

      “A dual-control model incorporating both structural domain and geochemical signature explained 87% of the grade variance and offers a practical targeting framework for future exploration.”

      Page 3

      Found in: Conclusion

      Read it in the full textOpen PDF at page 3 ↗
    • The authors recommend using arsenic-in-soil geochemistry as a cost-effective initial tool to identify prospective areas for drilling. View evidence ↗

      What it means

      The authors recommend using arsenic-in-soil geochemistry as a cost-effective initial tool to identify prospective areas for drilling.

      In the paper's own words

      “Arsenic-in-soil geochemistry, which is cheaper than gold assay, could serve as a first-pass targeting tool to identify the most prospective segments of the Ashanti fault system for drill testing.”

      Page 3

      Found in: Discussion

      Read it in the full textOpen PDF at page 3 ↗

Visual summary

2 visuals

Illustrations explain the paper; charts are replotted from the paper's own table values.

AI-generated illustration
AI-generated conceptual illustration (Gold-bearing quartz veins within a metamorphic greenstone belt shear zone). It explains the idea and does not show study data.↗ Enlarge
Dual-Control Model Concept
AI-generated conceptual illustration (Gold-bearing quartz veins within a metamorphic greenstone belt shear zone). It explains the idea and does not show study data.

AI-generated conceptual illustration (Gold-bearing quartz veins within a metamorphic greenstone belt shear zone). It explains the idea and does not show study data.

Open full-size image ↗

Dual-Control Model Concept

AI-generated conceptual illustration (Gold-bearing quartz veins within a metamorphic greenstone belt shear zone). It explains the idea and does not show study data.

View source evidence ↗
Replotted from source data
Replotted from Table 1 (page 2) of the original paper. Every bar is the paper's own table value.↗ Enlarge
Mean Au (g/t): Shear Zone Core vs Shear Zone Margin vs Fold Hinge vs Quartz Vein Set vs Disseminated Sulphide
Replotted from Table 1 (page 2) of the original paper. Every bar is the paper's own table value.

Replotted from Table 1 (page 2) of the original paper. Every bar is the paper's own table value.

Open full-size image ↗

Mean Au (g/t): Shear Zone Core vs Shear Zone Margin vs Fold Hinge vs Quartz Vein Set vs Disseminated Sulphide

Replotted from Table 1 (page 2) of the original paper. Every bar is the paper's own table value.

View source evidence ↗

Figures & tables

From the original paper
Gold grade statistics by structural domain (n = 128Table 1Page 2Mean gold grade (g/t) by structural domain across three Ashanti Belt deposits.Figure 1Page 2Relationship between gold grade, arsenic concentration, and sulphide content (bubble size) in mineralised samples.Figure 2Page 3
FULL TEXT Original article · reflowed for reading

Introduction

A recurring scenario in West African gold exploration goes something like this: a regional geochemical survey flags an anomaly, trenching confirms visible gold in quartz veins, and a drill programme begins. But the veins pinch and swell unpredictably, and without a structural model, half the holes miss the ore. The Ashanti Greenstone Belt has been mined for over a century, yet the interplay between mineralogy and structure that governs where gold concentrates remains incompletely documented at the deposit scale [1] . The belt is a northeast-trending Paleoproterozoic sequence of metavolcanic and metasedimentary rocks intruded by granodiorite and cut by the Ashanti fault system, a crustal-scale shear zone that extends for more than 200 km [2] . Gold deposits along this corridor range from large open-pit operations like Obuasi to artisanal workings exploiting narrow high-grade veins. Previous work has established that gold is associated with arsenopyrite-bearing quartz veins in most deposits [3] , but the relative contributions of veinhosted versus disseminated sulphide mineralisation, and the specific structural settings that control ore-shoot continuity, have received less systematic attention [4] . Two models compete: the structural model, which argues that gold is concentrated wherever shear-zone geometry creates dilatant sites-jogs, bends, and fault intersections-that act as chemical traps for ascending hydrothermal fluids [5] ; and the replacement model, which emphasises wall-rock reactivity, particularly iron-rich lithologies that trigger sulphidation and gold precipitation regardless of structural setting [6] . In reality, both controls probably operate together, but their relative importance varies from deposit to deposit. This research aimed to test these competing models by: (a) mapping the structural architecture of three deposits at the core-log scale, (b) characterising the mineralogy and geochemistry of ore and waste zones, and (c) determining which combination of structural and mineralogical variables best predicts gold grade [7] .

Theoretical Background

Orogenic gold deposits form during late stages of collisional tectonics when metamorphic fluids migrate upward through crustal shear networks [5] . The fluids are typically lowsalinity, CO2-rich, and carry gold as bisulphide complexes (Au(HS)2-) at temperatures between 300 and 450 degrees Celsius [8] . Destabilisation of these complexes-by cooling, pressure drop, or reaction with iron-bearing wall rockcauses gold to precipitate, often within or adjacent to arsenopyrite, which can incorporate gold in solid solution at concentrations up to 1.5 wt% [3] . At the Ashanti Belt scale, first-order shear zones provide the plumbing for fluid transport, while second-and third-order splays create the dilatant traps where fluid pressure drops and precipitation occurs [2] . Understanding this hierarchy is the key to predicting ore-shoot locations from structural data alone.

Material and Methods

Material and Methods

Methods

Reflected-light microscopy and scanning-electron microscopy with energy-dispersive spectroscopy (SEM-EDS) were used to identify sulphide phases, textural relationships, and the mode of gold occurrence (free grain, inclusion in sulphide, or lattice-bound). Gold was determined by fire assay with gravimetric finish on 30-g aliquots. Multi-element analysis (As, S, Sb, Fe, Cu, Zn, Pb, Bi) used ICP-MS after four-acid digestion. Structural domains were classified as shear-zone core, shear-zone margin, fold hinge, quartz-vein set, and disseminated sulphide based on core-log characteristics [4] . Pearson correlation coefficients were calculated between gold and each pathfinder element, and stepwise multiple regression tested which combination of geochemical and structural variables best predicted gold grade.

Results

Table Figure 2 shows a strong positive co-variation between gold and arsenic. Samples with arsenic above 1,000 ppm almost invariably carried gold grades above 6 g/t, and the largest bubbles (highest sulphide content) cluster in the upper-right quadrant, confirming the genetic link between sulphidation and gold enrichment.

Figure 2. Relationship between gold grade, arsenic concentration, and sulphide content (bubble size) in mineralised samples.
Relationship between gold grade, arsenic concentration, and sulphide content (bubble size) in mineralised samples.↗ Enlarge
Figure 2
Relationship between gold grade, arsenic concentration, and sulphide content (bubble size) in mineralised samples.

Relationship between gold grade, arsenic concentration, and sulphide content (bubble size) in mineralised samples.

Open full-size image ↗
Original paper figureSource PDF · page 3 ↗

Discussion

The four-fold contrast in gold grade between shear-zone cores and disseminated sulphide zones provides strong support for the structural control model, at least at these three deposits. Shear zones create permeability pathways and dilatant traps that focus fluid flow and promote precipitation [5] . But the correlation with arsenic (r = 0.91) also shows that mineralogy matters: gold is not uniformly distributed within the structural corridor but is concentrated in arsenopyrite-rich bands where fluid-wallrock reaction was most intense [3] . The combination of structural and geochemical predictors in the stepwise regression explained 87% of the variance in gold grade-significantly more than either predictor set alone (structural alone: 61%; geochemical alone: 72%). This supports a dual-control model in which structure provides the plumbing and sulphidation chemistry provides the trap mechanism [6] . From an exploration perspective, the implication is clear: targeting shear-zone cores that also show elevated arsenic and sulphide content will maximise drilling success. Arsenic-in-soil geochemistry, which is cheaper than gold assay, could serve as a first-pass targeting tool to identify the most prospective segments of the Ashanti fault system for drill testing.

Conclusion

This research demonstrated that gold mineralization in the Ashanti Greenstone Belt is controlled by a combination of structural preparation and sulphide mineralogy. Shear-zone cores yielded mean grades of 8.74 g/t-four times higher than disseminated zones-while arsenopyrite emerged as the principal gold-hosting phase, with an Au-As correlation coefficient of 0.91.

A dual-control model incorporating both structural domain and geochemical signature explained 87% of the grade variance and offers a practical targeting framework for future exploration. Arsenic geochemistry should be routinely integrated with structural mapping to identify oreshoot positions along the Ashanti fault corridor.

Figures and tables from the paper

Table 1. Gold grade statistics by structural domain (n = 128
Structural DomainnMean Au (g/t)Median Au (g/t)Max Au (g/t)Std Dev
Shear Zone Core318.747.3124.65.18
Shear Zone Margin264.313.6212.82.87
Fold Hinge183.172.848.41.93
Quartz Vein Set286.485.3718.24.11
Disseminated Sulphide252.131.786.71.42

Table text extracted from the original PDF; superscript letters are shown inline. The original table image is below.

View original table image
Gold grade statistics by structural domain (n = 128↗ Enlarge
Table 1
Gold grade statistics by structural domain (n = 128

Gold grade statistics by structural domain (n = 128

Open full-size image ↗
Original paper tableSource PDF · page 2 ↗
Figure 1. Mean gold grade (g/t) by structural domain across three Ashanti Belt deposits.
Mean gold grade (g/t) by structural domain across three Ashanti Belt deposits.↗ Enlarge
Figure 1
Mean gold grade (g/t) by structural domain across three Ashanti Belt deposits.

Mean gold grade (g/t) by structural domain across three Ashanti Belt deposits.

Open full-size image ↗
Original paper figureSource PDF · page 2 ↗

References

16 in the original paper
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