Constraining gravity and magnetic inversions for mineral exploration

Transcription

1 Constraining gravity and magnetic inversions for mineral exploration Nick Williams 1&2, Doug Oldenburg 1 & Peter Lelièvre 1 1 University of British Columbia Geophysical Inversion Facility 2 Geoscience Australia Sponsors:

2 Both density models explain the gravity data equally well. Which is the most reliable prediction of the subsurface?

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4 Inversion Inversion and constraints Seeks a 3D physical property model that explains observed geophysical data Calculation is non-unique: many solutions are possible Finding a solution is easy. Finding a realistic solution is harder Constraints Impose preferences or limitations on inversion Ensure recovered model is consistent with geology and explains the geophysics Types: Geological observations Geological interpretations Mathematical constructs that approximate geology

5 UBC GIF inversion approach Numerical optimisation problem Seeks model with small & smooth characteristics Smallness Deviations from a supplied reference model are small Add only as much detail as needed to fit the data Smoothness 1) Deviations from reference model are distributed smoothly, or 2) Model itself is smooth Constraints implemented using 4 main parameters

6 UBC GIF constraint implementation 1) Reference model Model of expected physical properties based on existing geological knowledge

7 UBC GIF constraint implementation 2) Smallness weights ( ( 1) Reliability of the supplied reference model

8 UBC GIF constraint implementation 3) Property bounds, lower & upper Range of properties allowed in each cell

9 UBC GIF constraint implementation 4) Smoothness weights (sharp < 1; smooth > 1) How smoothly or sharply properties change across each cell face, in each direction (north, east, vertical) Based on geological structures/trends

10 Recovering Desired Geometries A simple constraint is the overall geometry of the model (default) Aspect ratio 1:1 Aspect ratio 5:1 Aspect ratio 1:3 Assigned using length scales in each direction: L x = A x 2 Δx L y = A y 2 Δy L z = A z 2 Δz Length scale Aspect ratio Cell width

11 Recovering Desired Geometries

12 Inversion goals What do you want from the inversion modelling? Obtain a final 3D synthesis of all geological/geophysical data and interpretations? Mature geological understanding Highly developed geological interpretations/models Option 1: Inversion as end product Obtain an initial or updated 3D base map for future interpretation and targeting? Limited geological understanding Minimal geological data/models Option 2: Inversion as base map

13 Option 1: Inversion as an end product Create full 3D interpretation of geological surfaces Time, money, and data intensive, and difficult to update Model is one interpretation inversion tests one hypothesis Identifies where interpretations are inconsistent with the data Requires smooth model-difference difference inversion: sharp boundaries along contacts where model changes Reference model Constrained inversion result Joutel VHMS example sources: Fallara et al. (2003), Marquis et al. (2003), Oldenburg and Pratt (2007)

14 Option 2: Inversion as a base map Supply raw geological observations directly as constraints Minimal interpretation Quick and relatively easy results, consistent with geology May predict new features/targets best for exploration Requires smooth model inversion: smoothly extrapolate properties away from observations

15 Types of inversion smoothness Option 1: Full 3D model work around Option 2: Limited observations

16 Synthetic example, basic constraints Map + 2 drill holes

17 But we know more than that Extrapolate observations along strike to capture expected continuity of geology Based on observed or inferred structural orientations Reference property no buffers Reference property with buffers

18 Synthetic example, extrapolated constraints Map + 2 drill holes + buffers

19 Synthetic example, basic constraints Map + 2 drill holes

20 A real example Perseverance nickel sulphide deposit, Western Australia Archean granite-greenstone greenstone terrane Established mine seeking extensions to ore reserves Available geological data: Outcrop geology map ESRI ArcView shapefile Basement geology shapefile interpretation District-wide drilling database: Density measurements Geology observations Density measurements on 30 surface rocks Partial 3D geological model created from drilling and potential field interpretation

21 Gravity data Default inversion result Recovered densities 1 km 500 m Explains the gravity data Smooth, minimal structure Doesn t t match known geology

22 Add surface mapping + thickness of regolith (~ m) + denser basement rocks Reproduces variable-thickness regolith Enhances density contrasts Refines targets Still fits the gravity data Default result 500 m Geological constraints 500 m Constrained result 500 m

23 Add all geological knowledge + drilling + basement map interpretation + partial 3D geology model Reproduces variable-thickness regolith Still fits the gravity data Geologically realistic Default result 500 m Geological constraints 500 m Constrained result 500 m

24 Summary Geological constraints ensure inversion is consistent with geophysics and geology Mandatory for most problems Geological knowledge can be translated directly into the appropriate constraint parameters Must clearly define the problem to be solved Inversion as an end product Substantial geological interpretation prior to inversion Provides a final synthesis of all information Inversion as a base map Use raw geological constraints to derive base map to plan data acquisition, targeting, and interpretation Continually refined throughout exploration program

25 Project sponsors Acknowledgments BHP Billiton for data and permission to publish Ph.D. supervisors Doug Oldenburg & Dick Tosdal Colleagues MDRU-GIF inversion project: Dianne Mitchinson, Nigel Phillips GIF: Roman Shekhtman Geoscience Australia: Richard Lane