The sand connectivity in object- and pixel-based models is inevitably controlled by the proportion of sand present, and these methods seem unable to generate models that reproduce systems with low connectivity at high net:gross ratios. A new workflow is described which addresses this limitation and permits poorly connected facies models conditioned to well data to be built. The approach combines the compression algorithm with multiple-point statistics (MPS) modelling. Geometrically transformed wells and appropriately scaled training images provide the inputs to the MPS modelling. The inverse transformation is applied to the resultant MPS model, leading to the creation of reservoir geomodels with realistic, user-defined connectivity while also honouring well data. The approach is described and validated using a range of models. Considerations of other potential workflows using different types of training image suggest that application of the compression algorithm may be necessary in general to achieve models with realistic connectivity using the simplest and most widely-available pixel-based MPS method (the SNESIM algorithm).

在基于对象和像素的模型中，沙子的连通性不可避免地受到存在的沙子的比例的控制，这些方法似乎无法生成模型，该模型能够以高的净毛比重现低连通性的系统。描述了一种新的工作流程，该工作流程解决了这一局限性，并允许建立以井数据为条件的连通性差的相模型。该方法将压缩算法与多点统计（MPS）建模相结合。几何变换的井和适当缩放的训练图像为MPS建模提供了输入。逆变换应用于所得的MPS模型，从而创建具有现实的，用户定义的连接性的油藏几何模型，同时还保留了油井数据。使用多种模型对这种方法进行了描述和验证。