ISSN 1004-4140
    CN 11-3017/P

    鄂南含煤地层岩石物理建模下的叠前多维相控薄砂岩预测

    Pre-stack Multidimensional Facies-controlled Thin Sandstone Prediction under Rock Physics Modeling of Coal-bearing Strata in the Southern Ordos Basin

    • 摘要: 鄂尔多斯盆地南部地区下石盒子组分流河道砂单层厚度薄,在有限的地震分辨率下,下伏山西−太原煤层反射的旁瓣与薄砂体的反射耦合在一起,难以对储层响应特征进行准确分析;此外,在进行岩石物理分析时,该地区还存在测井曲线质量差、横波资料不足等问题,导致储层定量预测存在一定困难。针对上述问题,本文在多参数拟合提高测井曲线质量的基础上,依据Xu-White岩石物理模型的理论进行多次建模和分步融合,建立了一套砂−泥−煤三相岩石物理建模技术流程,有效改善测井曲线质量,并提高横波速度预测的精度,为后续反演提供合理的测井信息。此外,针对上述储层预测问题,本文提出一种适合研究区的多维相控叠前地质统计学反演方法:首先根据已有的地质认识和测井信息,分析与河道砂相关的地震属性,提取符合沉积变化规律的二维岩相概率密度作为石盒子组储层的平面约束;然后利用煤层反演体,结合贝叶斯判别原理,提取三维煤相概率密度作为下伏煤层的空间约束,最后同时综合二维和三维约束共同开展叠前地质统计学反演。本方法的预测结果综合考虑下伏煤层和砂岩储层的耦合特征,有效降低薄储层预测的多解性,在实际中应用效果较好,钻井吻合度得到明显提高。

       

      Abstract: In the southern region of the Ordos Basin, the thin, single-layer distributary channel sands in the Lower Shihezi Formation cause coupling between the sidelobes of the underlying Shanxi-Taiyuan coal seam reflections and the reflections of thin sand bodies within a limited seismic resolution, making it difficult to accurately analyze the reservoir response characteristics. Additionally, challenges in petrophysical analysis arise owing to the poor quality of the logging curves and insufficient shear wave data in this area block, which impede quantitative reservoir prediction. To address these issues, based on the improvement of logging curve quality through multi-parameter fitting this study establishes a three-phase (sand-mud-coal) rock physics modeling workflow by conducting multiple modelings and stepwise integrations in accordance with the theory of the Xu-White rock physics model. This workflow effectively improves the quality of logging curves and enhances the accuracy of shear wave velocity prediction, thereby providing reasonable logging information for subsequent inversions. Furthermore, to address the reservoir prediction problems mentioned above, this study introduces a multidimensional facies-controlled pre-stack geostatistical inversion method suitable for the study area. First, based on the existing geological understanding and well log information, seismic attributes related to channel sands were analyzed, and a two-dimensional lithofacies probability density conforming to sedimentary variation patterns was extracted as a planar constraint for the Shihezi Formation reservoir. Then, using the coal seam inversion volume combined with Bayesian discrimination principles, a three-dimensional coal facies probability density was extracted as a spatial constraint for the underlying coal seam. Finally, both two- and three-dimensional constraints were comprehensively integrated to conduct a pre-stack geostatistical inversion. The prediction results obtained using this method comprehensively considered the coupling characteristics of the underlying coal seams and sandstone reservoirs, effectively reducing the uncertainty in predicting thin reservoirs. This method has shown a good practical application result, with a significant improvement in drilling accuracy.

       

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