哈萨克斯坦Karachaganak油田碳酸盐岩储层三维模型成岩特征

C. Albertini, F. Bigoni, A. Francesconi, R. Lazzeri, A. Vercellino, O. Borromeo, Tatyana Gabellone, A. Consonni, C. Geloni
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引用次数: 0

摘要

喀喇恰甘纳克碳酸盐岩油气田储层质量受成岩作用影响较大。其中,替代白云化作用影响孔隙度、渗透率和不可还原含水饱和度,硬石膏的沉淀降低了孔隙度和渗透率。因此,根据符合井数据的地质一致性规则,在油藏3D模型中分析和描述了这种影响过程。野外成岩研究分为五个步骤:岩心资料研究、岩性测井分析、水文过程识别、水文过程反应输运模拟、三维岩性模型建立。根据岩心资料和岩性测井资料估算白云岩分布,结果主要局限于古隆起侧翼。与各地层单元碳酸盐古隆起浅埋作用的Kohout地热对流机制相关的三维场尺度反应输运模拟结果证实了这一分布规律。最终的岩性3D模型与该水文过程一致,并使用随机模拟中的验证数据集井数据进行校准。根据岩性测井分析和岩心资料估计,硬石膏的分布通常只占储层体积的几个百分比,而且主要分布在储层的上部(小于250米,低于上覆的昆古里亚蒸发岩底部)。硬石膏与昆固里卤水的扩散向下渗透有关,也与白云化作用有关。在局部也观察到高浓度硬石膏的出现,但通常与裂缝充填有关,有时也在储层的较深部分。这些事件与利用同沉积裂缝网络的盐水渗透有关,特别是沿着碳酸盐岩岸(海王星岩脉)的侧翼。这种水文过程得到了二维反应输运模型的支持。事实上,硬石充填裂缝可能会对储层流动路径产生重大影响,因此,根据埃尼用于识别次地震不连续面(trac - sibilla)的专有工作流程,基于地震属性(连续性和曲率),应用了识别这些海王星堤的工作流程。目前估算的白云岩分布约占现场规模岩性的15%,但在碳酸盐岩堆积的侧翼,几乎没有井调查的边缘区域,高达60%,但影响了油田总GBV的30%左右。因此,在三维储层模型中,由于白云岩的存在,油田侧翼的岩石物理特征受到影响,即孔隙度、渗透率增加,含水饱和度不可降低。此外,通过识别硬石膏填充的次地震不连续面,可以更好地描述影响三维模型流动路径的渗透率挡板。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
Carbonate Reservoir 3D Model Diagenetic Characterization – Karachaganak Field – Kazakhstan
The reservoir quality of Karachaganak Carbonates Field results significantly affected by diagenetic processes. In particular, the replacive dolomitization affects porosity, permeability and irreducible water saturation while the precipitation of anhydrite reduces both porosity and permeability. Such impacting processes were therefore analysed and described in the reservoir 3D Model following geologically consistent rules that honour well data. The field scale diagenetic study was performed following five steps: Core data studies Lithological logs analysis Hydrological processes identification Hydrological processes reactive transport simulations 3D Lithological model building The dolomite distribution, estimated from the lithological log analysis and cores data, results mainly confined on the flanks of the paleo-high. This distribution was endorsed by the results of 3D field scale reactive transport modelling related to Kohout geothermal convection mechanism acting in the shallow burial of the carbonate paleo-high at each stratigraphic unit. The final lithological 3D Model was built consistently with this hydrological process calibrated with well data used as verification data set in the stochastic simulations. The anhydrite distribution, estimated from lithological log analysis and cores data, is, generally, present in a few percentage of volume and, mainly, in the upper section of the reservoir (less than 250 m, below the bottom of the overlaying Kungurian evaporites). This anhydrite was related to diffuse downward percolation of the Kungurian brine and, marginally, to dolomitization. The occurrence of higher concentration of anhydrite was also locally observed but generally connected to fracture infill and, sometimes, also in the deeper section of the reservoir. These events were related to brine percolation exploiting a network of syn-depositional fractures, particularly along the flanks of the carbonate bank (Neptunian dykes). Such hydrological processes was endorsed by 2D reactive transport modelling. In fact, the anhydrite infilling fractures may have a significant impact on the reservoir flow path and therefore a workflow for identification of these Neptunian dykes was applied, based on seismic attributes (Continuity and Curvatures) according to the Eni proprietary workflow utilized for the identification of sub-seismic discontinuities (Tfrac-Sibilla). The so estimated dolomite distribution represents about the 15% of the lithology at field scale but up to the 60% on the flanks of the carbonate build-up, marginal areas investigated by very few wells but impacting on about the 30% of the field total GBV. Accordingly, the petrophysical characteristics of the field flanks result affected, in the 3D Reservoir Model, by the presence of dolomite, i.e. increased porosity, permeability and irreducible water saturation. Moreover, the identification of the sub-seismic discontinuities filled by anhydrite allows a better description of the permeability baffles affecting the 3D model flow paths.
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