Semi-auto horizon tracking guided by strata histograms generated with transdimensional Markov-chain Monte Carlo SCIE SCOPUS

Cited 3 time in WEB OF SCIENCE Cited 3 time in Scopus
Title
Semi-auto horizon tracking guided by strata histograms generated with transdimensional Markov-chain Monte Carlo
Author(s)
Cho, Yongchae; Jeong, Daein; Jun, Hyunggu
Publication Year
2020-06
Abstract
Although horizon interpretation is a routine task for building reservoir models and accurately estimating hydrocarbon production volumes, it is a labour-intensive and protracted process. Hence, many scientists have worked to improve the horizon interpretation efficiency via auto-picking algorithms. Nevertheless, the implementation of a classic auto-tracking method becomes challenging when addressing reflections with weak and discontinuous signals, which are associated with complicated structures. As an alternative, we propose a workflow consisting of two steps: (1) the computation of strata histograms using transdimensional Markov-chain Monte Carlo and (2) horizon auto-tracking using waveform-based auto-tracking guided by those strata histograms. These strata histograms generate signals that are vertically sharper and more laterally continuous than original seismic signals; therefore, the proposed workflow supports the propagation of waveform-based auto-picking without terminating against complicated geological structures. We demonstrate the performance of the novel horizon auto-tracking workflow through seismic data acquired from the Gulf of Mexico, and the Markov-chain Monte Carlo inversion results are validated using log data. The auto-tracked results show that the proposed method can successfully expand horizon seed points even though the seismic signal continuity is relatively low around salt diapirs and large-scale faults.
ISSN
0016-8025
URI
https://sciwatch.kiost.ac.kr/handle/2020.kiost/38637
DOI
10.1111/1365-2478.12933
Bibliographic Citation
GEOPHYSICAL PROSPECTING, v.68, no.5, pp.1456 - 1475, 2020
Publisher
WILEY
Subject
INVERSION
Keywords
Automatic picking; Seismic interpretation; Bayesian inversion
Type
Article
Language
English
Document Type
Article
Publisher
WILEY
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