Abstract
The WZ oilfield is characterized by a small production range, low recovery degree, strong reservoir heterogeneity, and complex fracture distribution. At present, there is no quantitative evaluation method for fractures of different scales. This causes problems that include an unclear understanding of reservoirs’ physical properties and remaining oil distribution and seepage characteristics. In this paper, multi-scale fracture prediction and a quantitative characterization method of a fractured carbonate reservoir are studied using three-dimensional seismic imaging logging and regional tectonic stress field distribution data. On the basis of analogs, variance cube, curvature, and the Pompano through-flowline system, large-scale crack recognition is carried out. Combined with the maximum positive curvature attribute, fracture density, and fracture direction interpreted by imaging logging, a small- and medium-sized fracture model is established. Finally, the multi-scale fracture prediction is carried out. This study has important theoretical significance for accurately describing and characterizing the multi-scale fracture distribution law and guiding the fine development of oilfields.
Highlights
The WZ reservoir type is a buried hill, fractured vuggy zone gas-cap block bottom water reservoir. This reservoir type is characterized by strong heterogeneity and complex fracture distribution (Libo et al 2018)
Curvature attribute is another type of attribute body that is sensitive to discontinuities in seismic data, which can be
On the basis of the rose diagram of fractures interpreted by A1h and A2h imaging logging, it can be seen that the results of thinned fault likelihood (TFL) attributes show good correspondence with imaging logging
Summary
The WZ reservoir type is a buried hill, fractured vuggy zone gas-cap block bottom water reservoir. Al-Dossary and Marfurt proposed the curvature calculation of multispectral volume (Al-Dossary and Marfurt 2006), which can be used to identify small irregular geological features Comprehensive research on limestone reservoir characteristics is lacking, as is targeted prediction methods for fractures of different scales. This research paper employs core, conventional logging, formation micro-imager logging, and geophysical data to identify and quantitatively evaluate fractures in multi-scale limestone reservoirs. For large-scale fractures, the seismic attributes suitable for the prediction of large-scale fractures in the study area are optimized by extracting and optimizing the 3D seismic attributes and combining it with the development of faults and the development characteristics of fracture formation in imaging logging.
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