TY - JOUR

T1 - Dtw based automated seismic–well tie

AU - Butorin, A. V.

AU - Sevostyanov, A. I.

AU - Stulikov, S. K.

AU - Timirgalin, A. A.

N1 - Publisher Copyright: © 2019, Neftyanoe Khozyaistvo. All rights reserved.

PY - 2019

Y1 - 2019

N2 - 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.

AB - 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.

KW - Dynamic Time Warping (DTW) algorithm

KW - L2-norm

KW - Seismic

KW - Sequence

KW - Synthetic trace

KW - Tying

KW - Wavelet

UR - http://www.scopus.com/inward/record.url?scp=85077368171&partnerID=8YFLogxK

U2 - 10.24887/0028-2448-2019-12-30-32

DO - 10.24887/0028-2448-2019-12-30-32

M3 - Article

AN - SCOPUS:85077368171

VL - 2019

SP - 30

EP - 32

JO - НЕФТЯНОЕ ХОЗЯЙСТВО

JF - НЕФТЯНОЕ ХОЗЯЙСТВО

SN - 0028-2448

IS - 12

ER -