DTW based automated seismic–well tie

UDK: 550.834.05
DOI: 10.24887/0028-2448-2019-12-30-32
Key words: seismic, tying, Dynamic Time Warping (DTW) algorithm, synthetic trace, L2-norm, sequence, wavelet
Authors: A.V. Butorin (Gazpromneft NTC LLC, RF, Saint-Petersburg), A.I. Sevostyanov (Gazpromneft NTC LLC, RF, Saint-Petersburg), S.K. Stulikov (Gazpromneft NTC LLC, RF, Saint-Petersburg), A.A. Timirgalin (Gazpromneft NTC LLC, RF, Saint-Petersburg)

One of the key priorities of the Gazprom Neft Company is routine processes optimization. Nowadays, manual seismic-well tying feature is embedded in most of oil and gas engineers’ tools, but it is still time consuming task to fit two signals especially with no subjective assessments. At the same time there are a plenty of successful cases of application signals comparing and processing algorithms in a real world tasks such as voice recognition.

Method, described in this article, helps to fit synthetic trace, calculated by reflection coefficient and theoretical signal convolution, to seismic trace in a semi-automatic mode. Dynamic Time Warping, which is the base of proposed approach, has been applied to temporal sequences of video, audio, and graphics data — indeed, any data that can be turned into a linear sequence can be analyzed with DTW. Using this algorithm in a pure form helps to obtain perfect fitting of the seismic and well signals in terms of Pearson's correlation coefficient, but at the same time leads to unrealistic time-depth dependency and infinite interval velocity. Considering this, the idea behind proposed in this paper approach includes number of restrictions, which not allows algorithm to fit signals perfectly, but makes the final results more geologically justified. The resulting algorithm was tested on a model data as well as on a real world data.

References

1. Herrera R.H., Fomel S., Van der Baan M., Automatic approaches for seismic to well tying, Interpretation, SD-9-SD17, 2014, DOI: 10.1190/INT-2013-0130.1.

2. Munoz A., Hale D., Automatically tying well logs to seismic data: Center for Wave Phenomena, 2012, pp. 253–260.



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