Simultaneous Seismic Deep Attribute Extraction and Attribute Fusion

Li, Kunhong; Zong, Jingjing; Fei, Yifeng; Liang, Jiajun; Hu, Guangmin

doi:10.1109/tgrs.2021.3113075

Cited by 12 publications

(2 citation statements)

References 38 publications

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“…The seismic attribute analysis process includes three parts: attribute extraction, attribute optimization and physical property prediction (Li et al., 2022). Seismic attributes can be categorized into physical attributes based on kinematic and dynamic characteristics, such as amplitude and phase, and geometric attributes related to seismic horizon geometry, such as curvature and azimuth (Di & AlRegib, 2019).…”

Section: Introductionmentioning

confidence: 99%

Seismic attribute transformation and porosity prediction of thin water‐rich sandstone based on Lambert W–R model

Li,

Chen,

Yin

et al. 2024

Geophysical Prospecting

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The seismic attributes of water‐rich sandstone contain much information about the rock's physical properties and seismic wave parameters. They are commonly used to predict the rock's physical properties (e.g., porosity). However, the seismic attributes of water‐rich sandstone are affected by porosity, water saturation, and thickness. To eliminate the influence of thickness on the porosity prediction of water‐rich sandstone and improve the accuracy of the porosity prediction, the authors propose a Lambert W‐R transform method to isolate the contribution of thickness and porosity from seismic attributes. Firstly, a rock physical model is used to calculate the equivalent elastic parameters of water‐rich sandstones with different porosity and water saturation. Secondly, the seismic attribute dataset of water‐rich sandstone is established by forward modeling the seismic response of the wedge‐shaped water‐rich sandstone model, and the selection of sensitive physical properties is completed. Then, the transformation parameters (ζAhRs and ηAhRs) are obtained by Lambert W‐R transformation, which is exponentially related to Instantaneous amplitude (Inst‐Amp). ζAhRs and ηAhRs are sensitive to thickness and porosity, respectively. Finally, an interpretative template for porosity prediction of water‐rich sandstone is established by cross‐plot analysis (ζAhRs and ηAhRs) and verified by a practical case. The verification results show that the porosity predicted by the interpretation template is consistent with drilling fluid consumption. However, it is lower than the porosity of logging constrained P‐wave impedance inversion.This article is protected by copyright. All rights reserved

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Section: Introductionmentioning

confidence: 99%

Seismic attribute transformation and porosity prediction of thin water‐rich sandstone based on Lambert W–R model

Li,

Chen,

Yin

et al. 2024

Geophysical Prospecting

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show abstract

“…It also serves as a potential tool for solving complex geological identifications. Therefore, it improves the value of seismic information in the application of oil and gas exploration and development [11].…”

Section: Introductionmentioning

confidence: 99%

Structural and seismic attribute analysis of the Paleocene carbonate reservoir from the Balkassar Field, Potwar Plateau, Pakistan

Khan,

Rehman

et al. 2024

Journal of Petroleum Research and Studies

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The structural and seismic properties of the Paleocene carbonate reservoir are re-evaluated, using 3D seismic data multi-attributes, to improve reservoir prediction accuracy rarely documented earlier. This study highlights a number of relevant post-stack seismic attributes for understanding the structural setup and seismic properties of a carbonate reservoir. The structural analysis was carried out using seismic interpretation, combined with multi-attribute analysis for prospect actualization and generation of a 3D structural model to determine the structural aspect. The structural interpretation reveals the presence of faults and an asymmetrical anticlinal structure demonstrating a four-way closure, confirming compressional tectonics. The high amplitude anomaly (-6 to 12) combined with the RMS attribute (23 to 32) suggests bright spots in the Paleocene carbonate reservoir and gas saturated zone, the variance attribute (0.05 to 0.03) highlights the presence of two major faults, and the lower instantaneous frequency demonstrates the presence of hydrocarbons. The attribute results indicate that the Lockhart Limestone possesses good reservoir potential as revealed by DHI (bright spot), gas saturated zone and a trapping mechanism supported by four-way structure closure in the region and can help to understand analogous carbonate reservoirs in similar geological settings around the world.

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GeoTrans: a transfer learning approach for estimating petrophysical properties from geophysical sensors data

Saikia,

Baruah

2024

Neural Comput & Applic

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Simultaneous Seismic Deep Attribute Extraction and Attribute Fusion

Cited by 12 publications

References 38 publications

Seismic attribute transformation and porosity prediction of thin water‐rich sandstone based on Lambert W–R model

Seismic attribute transformation and porosity prediction of thin water‐rich sandstone based on Lambert W–R model

Structural and seismic attribute analysis of the Paleocene carbonate reservoir from the Balkassar Field, Potwar Plateau, Pakistan

GeoTrans: a transfer learning approach for estimating petrophysical properties from geophysical sensors data

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