6D Interpolation (SPRINT6D)

Structure PReserving INTerpolation – Improved imaging over the earths surface where 3D seismic acquisition limits are overcome with 6D technology.

6D Interpolation (SPRINT6D)

Proprietary and available only at Divestco, Structure Preserving Interpolation (SPRINT) improves imaging over the earths surface to overcome 3D seismic acquisition limitations.

With and Without 6D Interpolation (SPRINT6D)

Use slider to see the difference.

A crossline and its corresponding time slice (in colour) from a 3D super merge of 17 data sets.

(A) and (B) are without 6D interpolation showing uneven quality of the data which is due to the different acquisition parameters.

(C) and (D) are with 6D interpolation showing very good detail, and uniform quality of the data. (AAPG EXPLORER, 2016 July).

6D Interpolation Uniqueness

  • 6D Angular weighted MWNI (Minimum Weighted Norm Interpolation)
    (GeoConvention 2016, Best Paper Award)
  • De-aliasing capability, effective in data upsampling
  • AVO friendliness
  • Improved imaging over conventional 5D MWNI based methods
  • Structured and Stratigraphic imaging
  • 3D Merge applications. Optimize 3D field geometries for Azimuthal migration sampling
  • 4D Baseline and Monitor. Minimize field acquisition differences between surveys
  • 3C P-S Converted wave
  • 100% Research and development at Divestco

Of many elegant methods, 5D minimum weighted norm interpolation (MWNI) is the most popular method due to its ability to closely maintain the original input trace characteristics, including signal-to-noise, better than any other known method. Many industry 5D interpolation techniques, including 5D MWNI, start data fitting from the stable low frequency slices, one slice at a time, and recursively layer-by-layer work their way up to higher frequencies. This unconstrained fitting can lead to inaccurate results under challenging scenarios such as meager data support, upsampling of regularly missing data, or aliased dips.

The 6D interpolation method has an additional dimension along reflector multiangular directions to be added to the 5D MWNI in order to guide the a priori model in the frequency-wavenumber domain. Angular weights connect data information across all frequency-wavenumbers globally, which is crucial to de-aliasing of data, but is completely missing in the conventional 5D MWNI.

5D interpolation vs. 6D Interpolation

An inline from a 3D seismic volume from an area with structural features under aliased conditions and recovery methods.

(A) the complete data stack, which is also the control reference data to which other datasets are compared;

(B) the stack of 3:1 decimated gathers;

(C) stack from the conventional 5D interpolation using MWNI method;

(D) stack using the 6D interpolation method.

Notice that the data is aliased in (B), and so is not restored properly in (C) as is seen in the highlighting polygons. In (D) we see the data restored well and is comparable to the reference dataset in (A). (AAPG EXPLORER, 2016 July)

6D Interpolation Papers

2017 October

6D Interpolation of Seismic Data – Rationale, Practice and FAQs

6D Interpolation of Seismic Data – Rationale, Practice and FAQs

2016 July

Structure-preserving 6-D Interpolation

Structure-preserving 6-D Interpolation

Bolivarian Symposium
Memoir, 2016

Improving subsurface imaging in geological complex area: Structure PReserving INTerpolation in 6D (SPRINT6D)

Improving subsurface imaging in geological complex area: Structure PReserving INTerpolation in 6D (SPRINT6D)

SEG Annual Int’l Meeting,
Expanded Abstracts, 2015

SEG Annual Int’l Meeting, Expanded Abstracts, 2015

6D interpolation by incorporating angular weight constraints into 5D MWNI

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