济阳坳陷储层地震地质综合预测技术研究

济阳坳陷具有复杂多样的沉积体系和储集类型,形成了复杂的隐蔽油藏系统,储层预测是该坳陷油藏勘探的关键。为此,针对坳陷中4种类型的储集层:陡坡带砂砾岩扇体、洼陷带浊积砂和三角洲及前缘滑塌浊积扇、缓坡带滩坝砂、坳陷期河道砂体等,分别探讨了它们各自的预测难点,并设计了相应的综合地震地质预测技术系列,即①采用相干、地层切片、三维可视化解释、谱分解等技术对河道砂体进行浏览—精细种子点追踪解释—薄层河道砂厚度计算的河流相储层预测技术系列;②采用古地形分析、地震几何属性分析、波阻抗反演等技术进行扇体—扇体内幕—有效储层预测的陡坡带砂砾岩体描述技术系列;③采用波形分析、倾角建模反演等技术进行定区带、定砂体的洼陷带浊积砂体预测技术系列;④采用古地形、波形分析、伪熵属性、高分辨率反演等技术进行定靶区、定目标的滩坝砂岩储层预测技术系列。在胜利油田隐蔽油藏储层预测中,利用这些地震地质预测技术获得了良好效果,年增探明储量1×108t。

The integrated seism-geology prediction techniques for different reservoir type in Jiyang Depression

Jiyang Depression is a typical continental rift basin. Its revservoir has characteristics of multi-sources and lateral variation, there exist four types of reservoir: glutenite fans in steep slop region, delta front slump turbidite fans in sag region, beach bar sand bodies in gentle slop region and channel sand bodies shaped at structure depression stage. Successful reservoir prediction relies on the combination of various techniques according to the seism-geology characters of reservoir. As for reservoirs in Jiyang Depression, following integrated seism-geology prediction techniques series were designed: For fluvial facies reservoirs, adopting coherence analysis, stratigraphical slices and 3-D visualization to scan channel sand bodies, subtly interpreting sand bodies with seed point tracking, using spectrum decomposition to calculate the thickness of channel sand bodies; For glutenite fans, using palaeotopography and geometrical attribute a-nalysis to predict the fans distribution and describe their interior conditions, using impedance inversion technique to predict the effective reservoirs; For delta- front slump turbidite fans, applying waveform analysis and inversion based on the stratigraphical dip modeling to predict the distribution of the promising sand bodies; For beach bar sand bodies, choosing palaeotopography, waveform analysis, pseudo-entropy and high-resolution inversion to identify the hopeful sand bodies and farther to specify exploitation targets. Satisfied effect has been achieved by using above techniques series in subtle reservoir prediction in Shengli oil field.