Two‐dimensional transient‐extracting transform for characterization of complex tight channel reservoirs

ABSTRACT As one of the most promising types of tight oil and gas reservoirs for continental sedimentation in China, complex tight channel reservoirs have important research significance. However, this type of reservoir is characterized by thin sand bodies, vertical multistage development, complex lateral changes and tight lithology, making their exploration and development extremely difficult. We propose a new time–frequency analysis method termed the two‐dimensional transient‐extracting transform, which introduces a space–time window to capture the lateral information of seismic signals. This paper defines a two‐dimensional transient‐extracting operator, which provides highly concentrated time–frequency representations for transient signals with time–frequency curves almost parallel to the time and space axes. Then, on the basis of the relationship between the frequency and wavenumber, the wavenumber parameter is determined through two‐dimensional transient‐extracting transform energy maximization. Finally, a laterally continuous and energy‐concentrated time–frequency spectrum is obtained. Compared with the other methods, the proposed method results in better lateral continuity, more concentrated energy and the ability to clearly differentiate thin stacked seismic reflections, enabling precise characterization of the channels. The wedge model and actual data show that the proposed method can describe the morphology of complex tight channel sand bodies more clearly and reliably than other methods.

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Publication Details

Journal
Geophysical Prospecting
Published
2025-04-07
DOI
https://doi.org/10.1111/1365-2478.70023
Primary Topic
Machine Fault Diagnosis Techniques
Type
article
Field-Weighted Citation Impact
0.00

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Two‐dimensional transient‐extracting transform for characterization of complex tight channel reservoirs

Ying Hu, Hui Chen, Jia Zhang, Chen Xuping et al.
Geophysical Prospecting
Machine Fault Diagnosis Techniques
article

Two‐dimensional transient‐extracting transform for characterization of complex tight channel reservoirs

Ying Hu, Hui Chen, Jia Zhang, Chen Xuping, Xie Yutao
article en

Abstract

ABSTRACT As one of the most promising types of tight oil and gas reservoirs for continental sedimentation in China, complex tight channel reservoirs have important research significance. However, this type of reservoir is characterized by thin sand bodies, vertical multistage development, complex lateral changes and tight lithology, making their exploration and development extremely difficult. We propose a new time–frequency analysis method termed the two‐dimensional transient‐extracting transform, which introduces a space–time window to capture the lateral information of seismic signals. This paper defines a two‐dimensional transient‐extracting operator, which provides highly concentrated time–frequency representations for transient signals with time–frequency curves almost parallel to the time and space axes. Then, on the basis of the relationship between the frequency and wavenumber, the wavenumber parameter is determined through two‐dimensional transient‐extracting transform energy maximization. Finally, a laterally continuous and energy‐concentrated time–frequency spectrum is obtained. Compared with the other methods, the proposed method results in better lateral continuity, more concentrated energy and the ability to clearly differentiate thin stacked seismic reflections, enabling precise characterization of the channels. The wedge model and actual data show that the proposed method can describe the morphology of complex tight channel sand bodies more clearly and reliably than other methods.

Geophysical ProspectingVol. 73(5)
Chengdu University of Technology (CN)
National Natural Science Foundation of China, China National Offshore Oil Corporation, Chengdu University of Technology, Chengdu Science and Technology Bureau, State Key Laboratory of Geohazard Prevention and Geoenvironment Protection, Chengdu University, Natural Science Foundation of Sichuan Province
Openalex Percentile: Top 93%
Machine Fault Diagnosis Techniques
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