A New Method of Identification of Water-Flooded Layers Based on HistGBDT Algorithm—A Case of the Penglai 19-3 Oilfield

To address the challenge of identifying water-flooded layers in the high-porosity, high-permeability, and strongly heterogeneous reservoirs of the Guantao Formation in the Penglai 19-3 Oilfield, research on water-flooded layer identification methods was systematically conducted. The logging characteristics of oil layers and water-flooded layers at different levels overlap considerably, which limits the accuracy of traditional identification methods. Meanwhile, the Archie equation shows significantly reduced applicability during the moderate and strong water-flooding stages. A water-flooded layer identification model was constructed using HistGBDT, and performance comparison between the base model and the optimized model reveals that the latter achieves a test accuracy of 91.6%. Compared with BPNN and SVM, the optimized HistGBDT model demonstrates substantially higher test accuracy and better generalization performance. Based on six sets of logging data, the optimized HistGBDT model developed enables the accurate identification of oil layers and multi-level water-flooded layers. It provides a reliable technical approach for tapping remaining oil in the high-water-cut stage of the Penglai 19-3 Oilfield and offers a new method and engineering reference for water-flooded layer identification in similar high-porosity, high-permeability heterogeneous reservoirs in the Bohai Bay Basin.

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Publication Details

Journal
Processes
Published
2025-10-09
DOI
https://doi.org/10.3390/pr13103219
Citations
1
Primary Topic
Geological and Geophysical Studies
Type
article
Field-Weighted Citation Impact
2.35

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article

A New Method of Identification of Water-Flooded Layers Based on HistGBDT Algorithm—A Case of the Penglai 19-3 Oilfield

Xin Nie, Chaomo Zhang, Zhansong Zhang, W. B. Yan et al.
1 citations
Processes
Geological and Geophysical Studies
2.35
article

A New Method of Identification of Water-Flooded Layers Based on HistGBDT Algorithm—A Case of the Penglai 19-3 Oilfield

Xin Nie, Chaomo Zhang, Zhansong Zhang, W. B. Yan, H. Q. Zhang, Hengyang Lv
article en
1 citations

Abstract

To address the challenge of identifying water-flooded layers in the high-porosity, high-permeability, and strongly heterogeneous reservoirs of the Guantao Formation in the Penglai 19-3 Oilfield, research on water-flooded layer identification methods was systematically conducted. The logging characteristics of oil layers and water-flooded layers at different levels overlap considerably, which limits the accuracy of traditional identification methods. Meanwhile, the Archie equation shows significantly reduced applicability during the moderate and strong water-flooding stages. A water-flooded layer identification model was constructed using HistGBDT, and performance comparison between the base model and the optimized model reveals that the latter achieves a test accuracy of 91.6%. Compared with BPNN and SVM, the optimized HistGBDT model demonstrates substantially higher test accuracy and better generalization performance. Based on six sets of logging data, the optimized HistGBDT model developed enables the accurate identification of oil layers and multi-level water-flooded layers. It provides a reliable technical approach for tapping remaining oil in the high-water-cut stage of the Penglai 19-3 Oilfield and offers a new method and engineering reference for water-flooded layer identification in similar high-porosity, high-permeability heterogeneous reservoirs in the Bohai Bay Basin.

ProcessesVol. 13(10)
Yangtze University (CN)
National Natural Science Foundation of China
Openalex Percentile: Top 10%
Geological and Geophysical Studies
2.35
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A New Method of Identification of Water-Flooded Layers Based on HistGBDT Algorithm—A Case of the Penglai 19-3 Oilfield — Xin Nie, Chaomo Zhang, et al. · Processes (2025) | TGRS Research Map | TGRS