Decomposition by Prony method and its components filtering

PSS-Geo performed a statistical analysis of techniques in comparison with classical exploration methods for more than 30 000 km 2D seismic lines, and for about 60 000 km2 of 3D data. Particular, for the Barents Sea anomalies maps were constructed down to Carboniferous-Devon age.

PSS-Geo introduced application of Q-factor for detecting reservoirs and interpretation of Sealing and leaking faults when not well data available. Please see our publications.

A distinctive feature of the Prony decomposition, in comparison with other decompositions, is that it is based on attenuated sinusoid, and therefore, is the closest to the nature of seismic trace. Moreover, while wavelet based and other transformations are dependent on frequency, time and/or window, the Prony transform takes into account Q-factor and phase, and does not depend on the chosen window (Mitrofanov, 2011). Thus, the Prony Decomposition or Transform has an advantage.

 

The decomposition establishes a discrete spectrum associated with a set of shot-time intervals located along the analyzed trace, and can be expressed as

When data is decomposed, some of these parameters can filter it. Filtering data by e.g. frequency only, could be considered as an analogue of the well-known band-pass filtering with a better resolution both in time and space domains, providing an opportunity to analyze a wave field in more detail (G. Mitrofanov, 2011). The output will be traces with one or more parameters. It is used widely, e.g., in power systems (Hauer J.F., 1990) and radar signatures characterization (Moses, 1989).

In geo exploration, the decomposition can be used to solve various geological, and production tasks. It can involve an analysis of target horizons characteristics and a prediction of possible prospects. While other seismic frequency decomposition methods allows to analyze structural elements only, the Prony method helps to identify areas with frequency-dependent effects: the anomalous values of seismic energy scattering (dispersion). Such effect can be deep and lateral variations in reservoir properties, in particular, the anomalies of high pore pressure (Helle H. B, 1993).

Prony Filtering tests have been performed on a large number of mathematical and physical models. Extensive research was required due to the non-linearity of the procedure. During the research, these aspects were analyzed: seismic signal form influence, stability of the procedure for noise, signals resolution, etc. The investigations confirmed that this technique is effective for analyzing reservoir structure, contouring of oil/gas production areas, and for determining productive reservoir propertiesTo some extent, these results were expected because the seismic signal is similar to the damping sinusoid, and the damping coefficient is related to the Q factor, which plays a significant role in the description of lithology, fluid content and pressure variations. 

PSS-Geo performed a statistical analysis of techniques in comparison with classical exploration methods for more than 30 000 km 2D seismic lines, and for about 60 000 km2 of 3D data. Particular, for the Barents Sea anomalies maps were constructed down to Carboniferous-Devon age.

 

 

- Vita V. Kalashnikova, Arif Butt and Stéphanie Guidard. Prony Decomposition for Sealing and Leaking fault analysis. GeoConvention2018, Calgary, May 7-11

See Poster, pdf

- Determination of faults and capsrocks permeability by evaluating the attenuation factor of seismic signals. V. Kalashnikova & T. Sharafutdinov.

2021. Part 1. Theory (April (3) 308). Karotazhnik.                  

          & Part 2. Application (coming in June) (in rus). Karotazhnik.

Sealing_LeakingFaults.png

The new advances in the Reservoir Characterisation from Pre Stacks Solutions-Geo: Prony and Phase Decompositions had been presented at SEG/DGS 4-5 March 2018 | Manama, Bahrain

Q-factor expressed from Prony transformed signal.
It indicated zones of damped amplitudes, particular fluid accumulation zones, reservoirs.

 Data courtesy of Spectrum AS

 Data courtesy of Exploro AS & PSS-Geo AS

 Data courtesy of TGS

Sealing-black, Leaking-white
Sealing-black, Leaking-white

press to zoom
Fluid migration derections-yellow
Fluid migration derections-yellow

press to zoom
Sealing-black, Leaking-white
Sealing-black, Leaking-white

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Frequency Decomposition - Prony filtered data
 24,36,45 Hz in RGB color blend, 3D analysis, for structural elements.

 Data courtesy of Exploro AS & PSS-Geo AS

Skrugard

Oil

Geophysical interpretation based on Seismic inversion and Rock Physic templates. Predicted reservoir layers are in yellow, possible hydrocarbons rocks are in green. See more...