Automatic approaches for seismic to well tying Roberto H. Herrera 1 , Sergey Fomel 2 , and Mirko van der Baan 1 Abstract Tying the synthetic trace to the actual seismic trace at the well location is a labor-intensive task that relies on the interpreter’s experience and the similarity metric used. The traditional seismic to well tie suffers from sub- jectivity by visually matching major events and using global crosscorrelation to measure the quality of that tying. We compared two automatic techniques that will decrease the subjectivity in the entire process. First, we evalu- ated the dynamic time warping method, and then, we used the local similarity attribute based on regularized shaping filters. These two methods produced a guided stretching and squeezing process to find the best match between the two signals. We explored the proposed methods using real well log examples and compared to the manual method, showing promising results with both semiautomatic approaches. Introduction Reliable well-seismic tying is a crucial step in seismic interpretation to correlate subsurface geology to ob- served seismic data. Even though the method involves a well-known workflow (Hall, 2013), it turns out to be a hardly repeatable experiment. The ease and quality of the tying procedure depend on the availability of high- quality logs, the estimation of a suitable wavelet, and the interpreter’s experience. Excellent recipes by White and Simm (2003) and two short essays by Newrick (2012) describe good practices in the tying procedure. An initial statistical wavelet is estimated from the seis- mic data and convolved with the reflectivity calculated from the well logs (sonic log and bulk density log) to generate the first synthetic trace. Then, the interpreter finds the best match between the generated synthetic and the actual seismic trace. Following these steps does not guarantee the “correct” tie (Anderson and Newrick, 2008) because the entire process is prone to pitfalls due to subjectivities in interpretation and procedures. The above-cited papers are good practices to follow to reach the best outcomes with the available tools. In this paper, we concern ourselves with the specific steps of optimal matching and quantifying the quality of that match. Hence, we assume that all the basic principles have been followed (White and Simm, 2003; Anderson and Newrick, 2008) and that we have a synthetic trace and a seismic trace to find the optimum match between both signals. The first issue comes from the fact that the quality of the tie between the synthetic and the seismic trace is based on the correlation coefficient, which is limited to linear features. The time-variant nature of the seismic wavelet adds nonlinearities to the trace that cannot be easily followed by a linear metric, such as the correla- tion coefficient further represented in equation 1. We compare two nonlinear approaches to match these time series. Our procedures substitute the manual stretching and squeezing step by an optimization algorithm, which is still supervised by the interpreter. This improves the repeatability of the tying, while the critical and often abused stretch and squeeze (Newrick, 2012) is still under control. The first alternative to perform the auto- mated tying is based on dynamic time warping (DTW) (Herrera and Van der Baan, 2012a, 2014), and the sec- ond approach faces the nonlinearity correction using the local similarity attribute (LSIM) (Fomel, 2007a). Both techniques share the quality-control step by monitoring the relative velocity change produced by the tying. Nonlinear correlation of seismic time series has been previously explored in the context of well-to-well cor- relation (Lineman et al., 1987; Zoraster et al., 2004), in which well logs from different wells are correlated to infer common earth features. The crosscorrelation was unable to follow local distortions such as stretching or shrinking of stratigraphic intervals, typical of logs collected even from closely spaced wells. Essentially, these methods aim to correlate common features in various logs (Anderson and Gaby, 1983). An early ap- proach to DTW is presented by Martinson et al. (1982) and Martinson and Hopper (1992). They develop a mapping function able to track stretching and squeez- ing in time series based on a correlation technique to 1 University of Alberta, Department of Physics, Edmonton, Alberta, Canada. E-mail: rhherrer@ualberta.ca; mirko.vanderbaan@ualberta.ca. 2 The University of Texas at Austin, Bureau of Economic Geology, Austin, Texas, USA. E-mail: sergey.fomel@beg.utexas.edu. Manuscript received by the Editor 27 August 2013; published online 20 March 2014. This paper appears in Interpretation, Vol. 2, No. 2 (May 2014); p. SD101–SD109, 6 FIGS. http://dx.doi.org/10.1190/INT-2013-0130.1. © 2014 Society of Exploration Geophysicists and American Association of Petroleum Geologists. All rights reserved. t Special section: Well ties to seismic data SD101 SD101 Downloaded 03/31/14 to 142.244.194.34. Redistribution subject to SEG license or copyright; see Terms of Use at http://library.seg.org/