论文部分内容阅读
地质统计学反演具有较高的空间分辨率,在储层预测中应用广泛,其反演精度受地质框架模型、纵/横向变程和岩性比例等多个因素的影响.传统方法主要从反演角度通过参数测试的方式开展参数对反演精度影响的研究,进而求取合适的反演参数.该参数求取方式效率低,反演结果精度不高,不能完全准确地反应储层空间变化特征.针对这一问题,本文采用从模型正演及其相应反演角度开展参数对反演精度影响的研究,并对反演参数求取方法进行了阐述.首先论述了地质框架模型及变差函数的地质含义,并以渤海W油田明化镇组下段储层特征为指导,构建了曲流河沉积典型的堆叠型和侧叠型地质模型,进而开展模型正演及相应的地质框架模型、纵向变程和横向变程对反演精度影响的研究.分析表明:1)基于高分辨率层序地层格架构建的地质框架模型有助于反演精度的提高;2)合适的变程能够提升反演分辨率.纵向变程的求取应综合考虑最小地质体大小、地震采样率等因素,而横向变程的求取应以地质信息为指导;3)开发阶段以砂层组级别地质框架模型为约束,结合储层特征求取反演参数的方法赋予了参数明确的地质含义,反演结果清晰表征了储层内部砂体叠置及空间展布特征,有助于提高薄储层表征精度,为开发后期的井位部署和井位调整提供依据.
The inversion of geostatistics has high spatial resolution and is widely used in reservoir prediction, and its inversion accuracy is affected by many factors such as the geological framework model, vertical / horizontal variation and lithologic proportion, etc. The traditional method mainly consists of inversion Angle parameter test to study the influence of parameters on the inversion accuracy and then find the appropriate inversion parameters.The method is inefficient and the accuracy of the inversion results is not high enough to accurately reflect the spatial variation of the reservoir In order to solve this problem, this paper studies the effect of parameters on the inversion accuracy from the perspective of forward modeling and its corresponding inversion, and explains the method of calculating inversion parameters.Firstly, the geological framework model and the variation function And the reservoir characteristics of the lower part of Minghuazhen Formation in Bohai W Oilfield as a guide, the typical stacked and side-by-side geological models of Meandering River sediments are constructed, and the model forward and corresponding geological framework models are developed. The vertical The results show that: 1) the geological framework model based on the high-resolution sequence stratigraphic framework contributes to the improvement of the inversion accuracy; 2) The suitable variation range can improve the inversion resolution.The calculation of the longitudinal variation should take into account the factors such as the minimum geological body size and the seismic sampling rate, while the horizontal variation should be guided by geological information; 3) The sandstone-group-level geological framework model is constrained, and the method of retrieving the inversion parameters in combination with reservoir characteristics gives explicit geological meaning to the parameters. The inversion results clearly characterize the sand body overburden and spatial distribution in the reservoir and are helpful To improve the characterization accuracy of thin reservoirs and provide the basis for well location deployment and well location adjustment in the later development stage.