基于地质地震条件的复杂障壁岛储层预测新方法及其在H油田的应用

Xin Chen, Suhong Zhang, J. Ou, Yufeng Ye, Lei Xu, Yingze Ma, Xiaodong Wei, Ke Yang, Gang Chen, Guofeng Zhou, Yaliang Xia, Xiao Yan, Zeren Zhang, Jingluan Liu, Xiao-ming Zhou
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引用次数: 0

摘要

为了提高储层预测结果的准确性,常规方法通常包括地震反演和地震属性分析。由于地震资料的垂向分辨率的限制,利用地震属性直接识别薄储层的难度较大。为了提高储层预测精度,提出了一种基于地质地震条件的储层表征新技术。新方法主要包括五个步骤。第一步是基于地质地震分析,如岩心资料、薄片分析、FMI测井、核磁共振测井和常规测井,进行沉积相分类。第二步是现代沉积模式优化和正演模拟。为了建立合理的沉积相模式,选择了一个类似堰洲岛的现代沉积模式。为了解地震资料的地质意义,在沉积相模型和岩石物理分析的基础上,设计了两种不同的主频率进行正演模拟。第三步是沉积相模型正演指导下的地震调理。下一步是地震约束随机反演,最后一步是储层表征和新井确认。该方法在A油田的应用表明,该方法不仅提高了地震再处理资料的识别能力,而且提高了储层表征结果的预测精度。这种新的储层描述技术可以综合现代沉积模型、井资料和地震资料等多学科信息,建立合理的沉积模型,通过调理提高地震资料的分辨率,在地震反演的基础上得到合理的储层描述结果。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
A New Reservoir Prediction Method Based on Geological Seismic Conditioning for Complex Barrier Island and Its Application at H Oil Field
In order to improve the accuracy of reservoir prediction results, the conventional method usually include seismic inversion, and seismic attribute analysis. Due to the limitation of the vertical resolution of seismic data, it is hard to identify the thin reservoir by seismic attributes directly. In order to improve the prediction accuracy of reservoir, this paper show a new reservoir characterization technique based on geological seismic conditioning. The new method mainly includes five steps. The first step is sedimentary facies classification based on the geological seismic analysis, such as core data, thin section analysis, FMI logging, NMR logging and conventional logging. The second step is modern sedimentary model optimization and forward modelling. In order to establish a reasonable sedimentary facies model, a similar barrier island modern sedimentary model was chosen. To understand the geological significance of seismic data, two different dominant frequency were designed for forward modelling based on the sedimentary facies model and petrophysical analysis. The third step is seismic conditioning under the guide of sedimentary facies model forward modelling. The next step is seismic constraint stochastic inversion, and the last step is reservoir characterization and new well confirm. The application of this method in A oilfield shows that the techniques not only improved the identification ability of the reprocessing seismic data, but also improved the prediction accuracy of the reservoir characterization results. This new reservoir characterization technique can integrated multidisplinary information, such as modern sedimentary model, well data and seismic data, to establish a reasonable sedimentary model, to enhance the resolution of seismic data by conditioning, and get an reasonable reservoir characterization results based on the seismic inversion.
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