In reflection seismology, a seismic attribute is a quantity extracted or derived from seismic data that can be analysed in order to enhance information that might be more subtle in a traditional seismic image, leading to a better geological or geophysical interpretation of the data. [1] Examples of seismic attributes can include measured time, amplitude, frequency and attenuation, in addition to combinations of these. Most seismic attributes are post-stack, but those that use CMP gathers, such as amplitude versus offset (AVO), must be analysed pre-stack. [2] They can be measured along a single seismic trace or across multiple traces within a defined window.
The first attributes developed were related to the 1D complex seismic trace and included: envelope amplitude, instantaneous phase, instantaneous frequency, and apparent polarity. Acoustic impedance obtained from seismic inversion can also be considered an attribute and was among the first developed. [3]
Other attributes commonly used include: coherence, azimuth, dip, instantaneous amplitude, response amplitude, response phase, instantaneous bandwidth, AVO, and spectral decomposition.
A seismic attribute that can indicate the presence or absence of hydrocarbons is known as a direct hydrocarbon indicator.
Amplitude attributes use the seismic signal amplitude as the basis for their computation.
A post-stack attribute that computes the arithmetic mean of the amplitudes of a trace within a specified window. This can be used to observe the trace bias which could indicate the presence of a bright spot.
A post-stack attribute that computes the sum of the squared amplitudes divided by the number of samples within the specified window used. This provides a measure of reflectivity and allows one to map direct hydrocarbon indicators within a zone of interest.
A post-stack attribute that computes the square root of the sum of squared amplitudes divided by the number of samples within the specified window used. With this root mean square amplitude, one can measure reflectivity in order to map direct hydrocarbon indicators in a zone of interest. However, RMS is sensitive to noise as it squares every value within the window.
A post-stack attribute that computes the maximum value of the absolute value of the amplitudes within a window. This can be used to map the strongest direct hydrocarbon indicator within a zone of interest.
AVO (amplitude versus offset) attributes are pre-stack attributes that have as the basis for their computation, the variation in amplitude of a seismic reflection with varying offset. These attributes include: AVO intercept, AVO gradient, intercept multiplied by gradient, far minus near, fluid factor, etc. [4]
The anelastic attenuation factor (or Q) is a seismic attribute that can be determined from seismic reflection data for both reservoir characterisation and advanced seismic processing.
A post-stack attribute that measures the continuity between seismic traces in a specified window along a picked horizon. It can be used to map the lateral extent of a formation. It can also be used to see faults, channels or other discontinuous features.
Although it should be used along a specified horizon, many software packages compute this attribute along arbitrary time-slices.
A post-stack attribute that computes, for each trace, the best fit plane (3D) or line (2D) between its immediate neighbor traces on a horizon and outputs the magnitude of dip (gradient) of said plane or line measured in degrees. This can be used to create a pseudo paleogeologic map on a horizon slice.
A post-stack attribute that computes, for each trace, the best fit plane (3D) between its immediate neighbor traces on a horizon and outputs the direction of maximum slope (dip direction) measured in degrees, clockwise from north. This is not to be confused with the geological concept of azimuth, which is equivalent to strike and is measured 90° counterclockwise from the dip direction.
A group of post-stack attributes that are computed from the curvature of a specified horizon. These attributes include: magnitude or direction of maximum curvature, magnitude or direction of minimum curvature, magnitude of curvature along the horizon's azimuth (dip) direction, magnitude of curvature along the horizon's strike direction, magnitude of curvature of a contour line along a horizon.
These attributes involve separating and classifying seismic events within each trace based on their frequency content. The application of these attributes is commonly called spectral decomposition. The starting point of spectral decomposition is to decompose each 1D trace from the time domain into its corresponding 2D representation in the time-frequency domain by means of any method of time-frequency decomposition such as: short-time Fourier transform, continuous wavelet transform, Wigner-Ville distribution, matching pursuit, among many others. Once each trace has been transformed into the time-frequency domain, a bandpass filter can be applied to view the amplitudes of seismic data at any frequency or range of frequencies.
Technically, each individual frequency or band of frequencies could be considered an attribute. The seismic data is usually filtered at various frequency ranges in order to show certain geological patterns that may not be obvious in the other frequency bands. There is an inverse relationship between the thickness of a rock layer and the corresponding peak frequency of its seismic reflection. That is, thinner rock layers are much more apparent at higher frequencies and thicker rock layers are much more apparent at lower frequencies. This can be used to qualitatively identify thinning or thickening of a rock unit in different directions.
Spectral decomposition has also been widely used as a direct hydrocarbon indicator.
In astronomy, a light curve is a graph of the light intensity of a celestial object or region as a function of time, typically with the magnitude of light received on the y-axis and with time on the x-axis. The light is usually in a particular frequency interval or band.
A spectrogram is a visual representation of the spectrum of frequencies of a signal as it varies with time. When applied to an audio signal, spectrograms are sometimes called sonographs, voiceprints, or voicegrams. When the data are represented in a 3D plot they may be called waterfall displays.
A spectrum analyzer measures the magnitude of an input signal versus frequency within the full frequency range of the instrument. The primary use is to measure the power of the spectrum of known and unknown signals. The input signal that most common spectrum analyzers measure is electrical; however, spectral compositions of other signals, such as acoustic pressure waves and optical light waves, can be considered through the use of an appropriate transducer. Spectrum analyzers for other types of signals also exist, such as optical spectrum analyzers which use direct optical techniques such as a monochromator to make measurements.
In mathematics, physics, electronics, control systems engineering, and statistics, the frequency domain refers to the analysis of mathematical functions or signals with respect to frequency, rather than time, as in time series. Put simply, a time-domain graph shows how a signal changes over time, whereas a frequency-domain graph shows how the signal is distributed within different frequency bands over a range of frequencies. A complex valued frequency-domain representation consists of both the magnitude and the phase of a set of sinusoids at the frequency components of the signal. Although it is common to refer to the magnitude portion as the frequency response of a signal, the phase portion is required to uniquely define the signal.
Reflection seismology is a method of exploration geophysics that uses the principles of seismology to estimate the properties of the Earth's subsurface from reflected seismic waves. The method requires a controlled seismic source of energy, such as dynamite or Tovex blast, a specialized air gun or a seismic vibrator. Reflection seismology is similar to sonar and echolocation.
A vector signal analyzer is an instrument that measures the magnitude and phase of the input signal at a single frequency within the IF bandwidth of the instrument. The primary use is to make in-channel measurements, such as error vector magnitude, code domain power, and spectral flatness, on known signals.
A time–frequency representation (TFR) is a view of a signal represented over both time and frequency. Time–frequency analysis means analysis into the time–frequency domain provided by a TFR. This is achieved by using a formulation often called "Time–Frequency Distribution", abbreviated as TFD.
In geophysics and reflection seismology, amplitude versus offset (AVO) or amplitude variation with offset is the general term for referring to the dependency of the seismic attribute, amplitude, with the distance between the source and receiver. AVO analysis is a technique that geophysicists can execute on seismic data to determine a rock's fluid content, porosity, density or seismic velocity, shear wave information, fluid indicators.
Geophysical survey is the systematic collection of geophysical data for spatial studies. Detection and analysis of the geophysical signals forms the core of Geophysical signal processing. The magnetic and gravitational fields emanating from the Earth's interior hold essential information concerning seismic activities and the internal structure. Hence, detection and analysis of the electric and Magnetic fields is very crucial. As the Electromagnetic and gravitational waves are multi-dimensional signals, all the 1-D transformation techniques can be extended for the analysis of these signals as well. Hence this article also discusses multi-dimensional signal processing techniques.
The method of reassignment is a technique for sharpening a time-frequency representation by mapping the data to time-frequency coordinates that are nearer to the true region of support of the analyzed signal. The method has been independently introduced by several parties under various names, including method of reassignment, remapping, time-frequency reassignment, and modified moving-window method. The method of reassignment sharpens blurry time-frequency data by relocating the data according to local estimates of instantaneous frequency and group delay. This mapping to reassigned time-frequency coordinates is very precise for signals that are separable in time and frequency with respect to the analysis window.
In statistical signal processing, the goal of spectral density estimation (SDE) or simply spectral estimation is to estimate the spectral density of a signal from a sequence of time samples of the signal. Intuitively speaking, the spectral density characterizes the frequency content of the signal. One purpose of estimating the spectral density is to detect any periodicities in the data, by observing peaks at the frequencies corresponding to these periodicities.
The Hilbert–Huang transform (HHT) is a way to decompose a signal into so-called intrinsic mode functions (IMF) along with a trend, and obtain instantaneous frequency data. It is designed to work well for data that is nonstationary and nonlinear. In contrast to other common transforms like the Fourier transform, the HHT is an algorithm that can be applied to a data set, rather than a theoretical tool.
Hilbert spectral analysis is a signal analysis method applying the Hilbert transform to compute the instantaneous frequency of signals according to
In geophysics, seismic inversion is the process of transforming seismic reflection data into a quantitative rock-property description of a reservoir. Seismic inversion may be pre- or post-stack, deterministic, random or geostatistical; it typically includes other reservoir measurements such as well logs and cores.
Heavy oil production is a developing technology for extracting heavy oil in industrial quantities. Estimated reserves of heavy oil are over 6 trillion barrels, three times that of conventional oil and gas.
In seismology, a seismic trace refers to the recorded curve from a single seismograph when measuring ground movement. The name comes from the curve plotted by a seismograph as the paper roll rotated and the needle left a trace from which information about the subsurface could be extracted. Today's instruments record the data digitally and the word trace has come to mean the digital curve.
In reflection seismology, the anelastic attenuation factor, often expressed as seismic quality factor or Q, quantifies the effects of anelastic attenuation on the seismic wavelet caused by fluid movement and grain boundary friction. As a seismic wave propagates through a medium, the elastic energy associated with the wave is gradually absorbed by the medium, eventually ending up as heat energy. This is known as absorption and will eventually cause the total disappearance of the seismic wave.
In reflection seismology, a hydrocarbon indicator (HCI) or direct hydrocarbon indicator (DHI) is an anomalous seismic attribute value or pattern that could be explained by the presence of hydrocarbons in an oil or gas reservoir.
Geophysical signal analysis is concerned with the detection and a subsequent processing of signals. Any signal which is varying conveys valuable information. Hence to understand the information embedded in such signals, we need to 'detect' and 'extract data' from such quantities. Geophysical signals are of extreme importance to us as they are information bearing signals which carry data related to petroleum deposits beneath the surface and seismic data. Analysis of geophysical signals also offers us a qualitative insight into the possibility of occurrence of a natural calamity such as earthquakes or volcanic eruptions.
Seismic data acquisition is the first of the three distinct stages of seismic exploration, the other two being seismic data processing and seismic interpretation. Seismic acquisition requires the use of a seismic source at specified locations for a seismic survey, and the energy that travels within the subsurface as seismic waves generated by the source gets recorded at specified locations on the surface by what are known as receivers.