Seismic Attributes

Seismic Attributes Applications in RESERVOIR Exploration

Practical Use of Seismic Attributes

Applications in Exploration & Reservoir Characterization

Fault and fracture detection (coherence, curvature, dip-azimuth).
Channel and stratigraphic feature mapping (spectral decomposition, RMS amplitude).
Hydrocarbon indicators (AVO, amplitude anomalies, attenuation).
Lithology discrimination (impedance inversion, elastic attributes).
Reservoir quality assessment (porosity, brittleness, fluid content).

Limitations & Challenges

Noise sensitivity: many attributes amplify acquisition or processing noise.
Non-uniqueness: the same attribute anomaly may result from different geological causes.
Dependence on data quality: poor signal-to-noise ratio reduces attribute reliability.
Interpretation complexity: requires integration with well data, rock physics, and geologic models.

Computation Approaches

Trace-based: computed from single traces (e.g., instantaneous amplitude).
Window-based: computed over time windows (e.g., RMS amplitude, average frequency).
Multi-trace: computed using multiple traces (e.g., coherence, curvature).
Model-based: involve inversion or forward modeling (e.g., impedance, fracture density).

Amplitude-related attributes

Reflection Strength

It represents the instantaneous amplitude of the seismic wavelet. It highlights the energy of reflections, making stratigraphic and fluid-related features clearer for reservoir characterization. Large reflection strength values indicate:

Strong acoustic impedance contrasts (e.g., lithology or fluid changes).
High reflectivity zones.

Instantaneous amplitude (envelope)

Instantaneous amplitude is the amplitude of the analytic signal at each time sample. Unlike raw amplitudes, instantaneous amplitude is always positive and independent of polarity. It measures the strength of reflectivity at each time instant.

1. Highlighting reflection energy

Stronger reflections → higher instantaneous amplitude.
Weak/gradual impedance contrasts → low amplitude.

2. Stratigraphic features

Channels, reefs, and other depositional bodies stand out.
Works well with attribute RGB blending (amplitude + frequency + phase).

3. Direct Hydrocarbon Indicators (DHIs)

Gas sands may appear as bright spots (abnormally high instantaneous amplitude).
Can be combined with instantaneous frequency and Q attributes for fluid vs. lithology discrimination.

Average energy

In seismic attribute analysis, average energy is a window-based attribute that measures the mean squared amplitude of a seismic trace over a given time window. it uses for identifying high-energy reflectors such as sands.

1. Highlighting strong reflectors over intervals

Helps map thick, high-impedance-contrast units (carbonates, basalt, thick sand bodies).

2. Reservoir characterization

High average energy zones may indicate clean, thick sands with strong impedance contrast.
Low-energy zones can point to shales or attenuated areas.

3. Noise suppression

Because energy is averaged, it is less sensitive to single spikes than instantaneous amplitude.

phase and frequency ATTRIBUTES

Instantaneous phase

Instantaneous phase represents the relative timing of oscillations in the seismic signal, independent of amplitude.

It highlights waveform polarity changes, continuity, and phase variations between reflectors.
Unlike amplitude-based attributes, instantaneous phase is amplitude-independent, making it useful in noisy or low-SNR data.

Applications in seismic interpretation:

Fault and stratigraphic feature interpretation (since subtle phase shifts may indicate changes in lithology or thickness).
Tuning analysis (phase helps detect interference effects).
Seismic-to-well tie (to check wavelet phase consistency).

Instantaneous frequency

It measures the local frequency content of the seismic signal at each point in time. Instantaneous frequency is sensitive to noise and phase unwrapping errors. Spikes may appear where amplitude is very low (since the phase can change abruptly).

Unlike Fourier frequency (which gives average frequency over a time window), instantaneous frequency is time-localized.
Useful for detecting thin beds, stratigraphic changes, and attenuation effects.

Applications in seismic interpretation:

Highlighting high-frequency anomalies (often linked to gas zones, thin beds, or fracture swarms).
Tracking tuning thickness variations.
Identifying attenuation zones caused by gas clouds or low-Q layers.

Dominant frequency

Dominant frequency is the frequency at which the seismic signal has the highest energy (maximum amplitude in the spectrum). It is usually obtained from the Fourier amplitude spectrum of a seismic trace or wavelet.

Applications in seismic interpretation:

Represents the average frequency of the seismic data.
Often used to describe the bandwidth and resolution of seismic data.
Higher dominant frequency → better vertical resolution (can resolve thinner beds).
Lower dominant frequency → deeper penetration (but lower resolution).

Geometric attributes

Dip

The dip attribute measures the apparent slope (inclination) of seismic reflectors in either the inline or crossline direction. Dip typically is derived by analyzing the local slope of seismic events using techniques like Cross-correlation of adjacent traces, Coherency-based dip estimation (semblance, eigenstructure), Gradient methods in 3D volumes.
Applications in seismic interpretation:

Reflector dip indicates the geological tilt of strata (anticlines, synclines, monoclines).
Sudden dip changes often indicate faults, unconformities, or stratigraphic terminations.
Dip attributes are also used as inputs for other seismic attributes, such as dip-steered filtering, curvature, and coherence enhancement.

Edge Map

An edge map attribute highlights sudden lateral changes in seismic data, such as reflector terminations, faults, or stratigraphic edges. It is essentially a discontinuity or edge-detection attribute derived from the seismic amplitude field. It is Computed by measuring local variations (gradients) of seismic amplitudes or other attributes. It is computed based on image processing techniques like Amplitude gradients (inline & crossline derivatives), Variance or semblance (low values = discontinuities), Coherence or similarity attributes and Applying filters like Sobel, Laplacian, or Canny edge detectors to seismic slices.

Applications in seismic interpretation:

Highlights reflector terminations (onlaps, truncations, channel edges).
Detects faults (linear or curvilinear discontinuities).
Helps in identifying geobodies like channels, reefs, carbonate build-ups.

Coherency

The coherency (coherence) attribute measures the similarity (or continuity) of seismic waveforms between neighboring traces.

High coherence traces look very similar laterally continuous reflectors.
Low coherence traces differ strongly discontinuities (faults, channels, stratigraphic edges).

Applications in seismic interpretation:

Fault & fracture detection (faults show up as sharp lineaments of low coherence).
Stratigraphic interpretation (highlight channel boundaries, reefs, carbonate buildups, levees).
Horizon interpretation (improves accuracy by following coherent reflectors).
Seismic facies analysis (distinguish continuous vs. chaotic deposits).

Spectral decomposition attributes

Spectral Energy

Decompose seismic signals into frequency components (Fourier, wavelet, or S-transform based). Help visualize channels, reefs, and thin beds by tuning frequency slices. The spectral energy attribute is a seismic attribute that measures how much signal energy is contained within a certain frequency band at each time and location in the seismic data. Different geological features (channels, reefs, thin beds, faults) have distinct frequency responses. By analyzing spectral energy at specific frequency bands, interpreters can highlight subtle stratigraphic and structural details not visible in the broadband seismic.

Applications in seismic interpretation:

Thin-bed analysis: Thin beds interfere constructively/destructively at specific frequencies, so spectral energy can detect them.
Reservoir characterization: Identifies stratigraphic features, lithologic changes, and depositional environments.
Tuning analysis: Pinpoints the dominant frequency at which bed thickness is best resolved.
Attribute maps: Generating frequency-dependent maps of spectral energy helps visualize channels, pinch-outs, and other stratigraphic features.

Peak Frequency

The peak frequency attribute is another spectral decomposition–based seismic attribute, but instead of looking at the energy distribution across all frequencies, it extracts the frequency at which the maximum spectral energy occurs within a given time window. Seismic reflections are band-limited. Their dominant frequency shifts with attenuation, absorption, and thickness effects. As seismic waves travel, higher frequencies are absorbed more strongly, causing the peak frequency to shift downward with depth (a phenomenon linked to Q attenuation). Lithology, fluid content, and bed thickness also influence the frequency response.

Applications in seismic interpretation:

Attenuation / Q analysis: Peak frequency decreases with depth, so mapping it helps estimate attenuation and reservoir quality.
Thin-bed tuning: Thin beds often cause constructive interference at certain frequencies peak frequency shifts can indicate bed thickness.
Lithology / fluid discrimination: Reservoirs may shift the peak frequency compared to background shales.
Stratigraphic imaging: Helps highlight channels, reefs, and unconformities when mapped across an area.

Q Attenuation

The Q attenuation attribute (often just called Q attribute or seismic attenuation attribute) is a seismic attribute that quantifies how much seismic energy is lost due to intrinsic absorption and scattering in the subsurface. When we talk about Q attenuation as an attribute, we mean deriving an estimate of Q (or inverse Q) from the seismic data at each time/depth sample. The attribute often measures the rate of peak-frequency shift or exponential amplitude decay with time.

Attenuation is related to rock properties and fluids. Gas zones often show strong attenuation (low Q). Tight formations or carbonates usually have high Q. Thus, Q attenuation attributes are direct hydrocarbon indicators (DHIs) in some cases.

Applications in seismic interpretation:

Reservoir characterization: Detects gas/oil zones due to low-Q anomalies.
Lithology discrimination: Different rocks absorb seismic energy differently.
Fracture detection: Scattering from fractures lowers Q.
Seismic imaging improvement: Q-compensation improves resolution.

seismic attributes