Alisheva Zhanat, Al-Dujaili Ahmed N, Tileuberdi Nurbol, Muratova Samal, Omirzakova Elmira, Sanatbekov Miras, Kurmanbayev Olzhas, Alzhigitova Manat
Faculty of Geography and Environmental Sciences, Al-Farabi Kazakh National University, Almaty, Kazakhstan.
Petroleum Engineering Department, Amirkabir University of Technology, Tehran, Iran.
Sci Rep. 2025 Apr 4;15(1):11555. doi: 10.1038/s41598-025-96797-8.
This study focuses on modeling and analyzing filtration processes in oil reservoirs of small fields, using the Northern Karamandybas field as a case study. It examines the geological and physico-chemical characteristics of the oil-bearing reservoirs and presents a hydrodynamic model developed for the J-VII, J-VIII, and J-IX horizons. The model is built upon PVT analysis of oil, gas chromatography of dissolved gas, and incorporates detailed reservoir properties, oil characteristics, and the geological structure of productive formations. A key novelty of this research is the integration of geostatistical methods, history-matching techniques, and permeability distribution analysis to evaluate the efficiency of water injection in a highly heterogeneous reservoir. Unlike previous studies that rely solely on deterministic models, this study employs a data-driven approach that accounts for geological uncertainties, ensuring more reliable reservoir performance predictions. The adaptive water injection strategy optimizes injection rates based on real-time permeability variations, filling a critical gap in understanding the impact of heterogeneity on waterflooding efficiency. The modeling results demonstrate that water injection enhances production efficiency by maintaining reservoir pressure, improving oil displacement, and minimizing water-cut, thereby reducing development costs for reservoirs. The integration of stochastic modeling and historical data calibration ensures a balanced approach to reservoir management, improving forecasting accuracy. This research provides a foundation for further studies and practical recommendations for the optimal development of small, geologically complex oil fields.
本研究以卡拉曼德巴斯北部油田为例，重点对小型油田油藏中的渗流过程进行建模与分析。研究考察了含油储层的地质和物理化学特征，并给出了针对J - VII、J - VIII和J - IX地层开发的水动力模型。该模型基于原油的PVT分析、溶解气的气相色谱分析构建而成，并纳入了详细的储层特性、原油特征以及生产地层的地质结构。本研究的一个关键创新点在于整合地质统计学方法、历史拟合技术和渗透率分布分析，以评估高度非均质油藏中的注水效率。与以往仅依赖确定性模型的研究不同，本研究采用数据驱动方法，考虑了地质不确定性，确保了更可靠的油藏性能预测。自适应注水策略基于实时渗透率变化优化注水速率，填补了理解非均质性对注水效率影响方面的关键空白。建模结果表明，注水通过维持油藏压力、提高驱油效率和最小化含水率来提高生产效率，从而降低油藏开发成本。随机建模与历史数据校准的整合确保了油藏管理的平衡方法，提高了预测准确性。本研究为进一步研究以及小型地质复杂油田的优化开发提供了实用建议奠定了基础。
