Work

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

Year: 2025

Type: article

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.

Source: Processes

DOI: 10.3390/pr13103219

Authors: Hao Zhang, Zhansong Zhang, Xin Nie, Chaomo Zhang, Hengyang Lv, Wenjun Yan

Institution: Yangtze University

Language: English

Topic: Hydrocarbon exploration and reservoir analysis

Subfield: Mechanics of Materials

Field: Engineering

Domain: Physical Sciences

Open Access status: gold

Estimated APC paid: $2,896

Funder: National Natural Science Foundation of China