Mathematical Geosciences ( IF 2.6 ) Pub Date : 2020-11-16 , DOI: 10.1007/s11004-020-09903-z Sophie Viseur , Juliette Lamarche , Clément Akriche , Sébastien Chatelée , Metzger Mombo Mouketo , Bertrand Gauthier
Fracture density is an important parameter for characterizing fractured reservoirs. Stochastic object-based simulation algorithms that generate fracture networks commonly rely on a fracture density to populate the reservoir zones with individual fracture surfaces. Reservoirs, including fracture corridors, represent particular challenges in petroleum reservoir studies. Indeed, it is difficult to identify fracture corridor zones objectively and precisely along one-dimensional well data, which are characterized by high fracture densities compared to diffuse fractures. To estimate fracture density, a common practice is to graphically depict only fracture corridors on fracture cumulative intensity curves. In this paper, an approach is proposed to formalize this technique using hypothesis testing. This method precisely compartmentalizes the well data into several zones having specific fracture densities. The method consists of the following steps: (i) dividing the diagram into zones depending on a priori drastic changes in density, (ii) computing the local accurate fracture density for each zone and (iii) clustering the zones characterized by similar densities statistically. The key point is to couple regression and hypothesis testing. The regression aims at computing local average fracture density and the hypothesis testing aims at clustering zones for which the densities are statistically the most similar. The proposed approach is dedicated to one-dimensional fracture surveys, such as well data and outcrop scanlines. First, a synthetic case study is presented to prove the ability to highlight changes in fracture density. Second, the procedure is applied on a scanline dataset collected in a quarry (Calvisson, SE France) to show the usefulness of characterizing fracture corridors.
中文翻译:
断裂密度变化的精确计算:在断裂通道上测试的新方法
裂缝密度是表征裂缝性储层的重要参数。生成裂缝网络的基于随机对象的模拟算法通常依赖于裂缝密度,以各个裂缝表面填充储层区域。包括裂缝通道在内的储层是石油储层研究中的特殊挑战。确实,很难沿着一维井数据客观准确地识别裂缝走廊带,而一维井数据的特征是与分散裂缝相比裂缝密度高。为了估算裂缝密度,通常的做法是在裂缝累积强度曲线上仅以图形方式描绘裂缝通道。在本文中,提出了一种使用假设检验将该技术形式化的方法。该方法将井数据精确划分为几个具有特定裂缝密度的区域。该方法包括以下步骤:(i)根据先验密度的急剧变化,(ii)计算每个区域的局部准确裂缝密度,以及(iii)统计地表征具有相似密度的区域。关键是要结合回归和假设检验。回归旨在计算局部平均裂缝密度,假设检验针对密度在统计上最相似的聚类区域。提议的方法专用于一维裂缝调查,例如井数据和露头扫描线。首先,提出了一个综合案例研究,以证明突出显示裂缝密度变化的能力。其次,将该程序应用于采石场(法国卡尔维森,法国)中收集的扫描线数据集,以显示表征裂缝通道的有用性。