敏感属性与参数反演融合定量预测煤体结构

煤体结构与煤储层是否富气、高产密切相关，煤体结构定量预测尤其重要。为此，以沁水盆地马必东三维区3^#煤为例，通过计算常用的地震属性与储层参数在煤体结构预测方面的有效性，发现煤体结构最佳敏感地震属性为纹理属性，最佳敏感储层参数为电阻率。纹理属性平面变化自然，断层清晰，但纵向分辨率低；而电阻率参数反演纵向分辨率高，井点处反演结果与对应的测井曲线吻合良好，但横向变化不自然，不能识别断层。因此将纹理属性与电阻率参数反演结果相融合，优势互补，最终得到的原生煤比率符合煤储层沉积规律，实现了煤体结构的定量预测。经后续开发井证实，该预测结果可高效指导下一步生产实践，所采用的融合技术思路可为其他地区煤体结构预测提供借鉴。

Coal structure quantitative prediction with sensitive-attribute and parameter-inversion fusion

Coal structures are closely related to the gas production of coal reservoirs,so the coal structure quantitative prediction is essential.We analyze seismic sensitive attributes and inversion sensitive parameters on a 3D seismic dataset in Coal 3^#,Mabi,Qinshui Basin.It is found that the most sensitive attribute is the texture,and the most sensitive is resistivity of logging data.The texture attribute change is relatively smooth in the horizontal direction,and makes faults clear,but its vertical resolution is low.On the other hand,the vertical resolution for inversed resistivity is high,and the inversed data in well positions is consistent with logging curves,but its horizontal change is not smooth,and fault identification is impossible.With the texture-attribute and inversed-resistivity fusion,the coal structure quantitative prediction is achieved,which is proved by the late well drilling.Our practice and experience demonstrate the validity of the proposed approach and may provide a useful reference for similar conditions.