SFD® Technology
The Physics Behind SFD® Detection
For geophysicists and technical evaluators who want the full theoretical framework — how SFD® responds to subsurface conditions, the physics of anomalous vs. background states, and the design principles that make reservoir-scale detection possible.
What Creates an SFD®-Detectable Anomaly
The earth’s crust is inherently anisotropic — its physical properties vary with direction and depth, creating a complex three-dimensional stress and density landscape.
SFD® responds to subtle perturbations in this subsurface field that arise from geologic features of interest: faults, fault blocks, anticlines, carbonate bank edges, channel systems, and zones of over-pressured fluids. This family of features is commonly correlated with conditions favourable for hydrocarbon trapping.
In essence, changes in subsurface homogeneity are the fundamental physical contrast to which SFD® responds.
Subsurface Homogeneity
Diagram placeholder: an approved cross-section showing faults, traps, porous rock and surrounding heterogeneous formations. Show the contrast in subsurface homogeneity without inventing quantitative field data.
The Physics of Detection
In SFD® exploration, two subsurface states are distinguished:
Background condition
A random distribution of Δρ (change in density) with hydrostatic pressure gradients. No anomalous signal is generated.
Background Condition Diagram / Signal
Diagram placeholder: show heterogeneous surrounding formations, a random distribution of density changes (Δρ), and hydrostatic pressure gradients. Include an approved background signal example alongside the subsurface explanation. Label axes and units for any measured signal; do not invent waveform data.
Anomalous condition
An isolated homogeneous distribution of ρ due to enhanced porosity and fluid presence, bounded by abnormal stress gradients. The anomalous condition is further characterised by:
- A marked reduction in shear stress inside the reservoir
- A reorientation of the horizontal principal stresses around the reservoir
In general, porous rocks saturated with fluid exhibit a decrease in bulk density relative to surrounding formations. As more fluid accumulates in a trap with high porosity, the reservoir system becomes increasingly homogeneous — provided there is adequate permeability distribution — resulting in greater spatial subsurface contrast relative to the surrounding heterogeneous rock.
Anomalous Condition Diagram / Signal
Diagram placeholder: show a porous, fluid-filled reservoir bounded by abnormal stress gradients, with reduced internal shear stress and reoriented horizontal principal stresses. Pair it with an approved anomalous signal example using the same axes and scale as the background example. Label conceptual features clearly; do not invent measured signals.
The Role of Principal Stresses
In addition to subsurface density changes, the principal stresses play a significant role in the development of subsurface conditions associated with discontinuities:
- Fluid migration follows the direction of the maximum horizontal stress (SHmax)
- Fluid expulsion follows the direction of the minimum horizontal stress (Shmin)
- As fluid moves into reservoirs, SHmax reduces and Shmin increases as pore pressure increases
- Shear stress is further reduced as fluid accumulates in the reservoir
- Reservoir rock permeability distribution is controlled by SHmax — a high value indicates an increase in homogeneity
Investigations of stress changes and associated density contrasts have shown a physical relationship between the two at small scale.
These local-scale perturbations arise from a combination of mass-density variation and field transmission effects — the same contrasts to which SFD® is designed to respond.
SFD® Detection Design
The SFD® device is purpose-built to detect small-scale perturbations in gravitational potential energy (GPE). Its design centres on four principles:
Low-inertia sensing
— a lightweight sensing element that responds rapidly to subtle field variations
Sensitivity-optimised response
— the device is tuned to detect small perturbations that would otherwise fall below the noise floor
Continuous dynamic acquisition
— enables accumulation of GPE data along the survey line, building the signal resolution needed to characterise reservoir-scale features
Wave-based signal analysis
— signals are analysed as waveforms, capturing frequency and amplitude information rather than point-magnitude values alone
How the approaches complement each other
Where conventional gravimetry focuses on precise absolute measurement, SFD® is optimised for detection sensitivity — responding to the subsurface contrasts associated with large trapped fluid accumulations. The two approaches address different aspects of the subsurface and can be used together within a broader exploration programme.
From Signal to Prospect
Interpretation of SFD® signals involves a pattern recognition process. Based on extensive experience, recognisable SFD® signal patterns have been empirically correlated to a variety of subsurface geologic fluid trapping conditions. These patterns are especially pronounced within regions of fluid-filled porosity bounded by abnormal stress gradients.
Based on extensive empirical observation and past correlations with other geological and geophysical data, SFD® signal patterns have been applied to identify potential hydrocarbon traps across a range of geological settings, including thrust-fold belts, foreland basins, sub-salt plays, and extensional regimes.
Ladyfern Gas Field Signal
Signal example placeholder: the approved Ladyfern gas field example, Devonian carbonate reef, British Columbia, Canada. Annotate amplitude and frequency effects embedded in the SFD® signal.
Ladyfern gas field — Devonian carbonate reef, British Columbia, Canada.