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Application of principal component analysis on chemical data for reservoir correlation: A case study from Cretaceous carbonate sedimentary rocks, Saudi Arabia
AAPG Bulletin ( IF 2.7 ) Pub Date : 2021-04-15 , DOI: 10.1306/10142019105
Nikolaos A. Michael , Neil W. Craigie

A new method is presented to identify chemostratigraphic zones by applying principal component (PC) analysis and to interpret geological boundaries based on PC curves. The PC data were calculated using inductively coupled plasma–optical emission spectrometry and inductively coupled plasma–mass spectrometry, with data acquired for 50 chemical elements in the range Na–U. In the present study, a total of 832 core and cuttings samples were analyzed from four wells penetrating the Cretaceous Wasia Formation, southeastern Saudi Arabia.The conventional workflow involves plotting profiles for elements and elemental ratios, with 250 to 300 profiles produced for each study section. With so many variables to consider, it is a challenging and time-consuming process to produce chemostratigraphic frameworks, requiring expert knowledge of chemostratigraphy. By using only a few PC curves, as opposed to element or ratio profiles, it is easier for nonexperts to identify correlative boundaries. The PC parameters reflect changes in more than one group of elements and summarize geological changes. For example, in this study, PC2 parameter values relate to changes in depositional redox conditions.A close association was revealed between boundaries identified using PC and boundaries from an existing conventional chemostratigraphic study on the same wells. For example, PC zone E1-3 relates to the conventional zones C3-1b. The fact that some PC and conventional chemostratigraphic boundaries do not always coincide (e.g., conventional boundaries C2-1:C2-2 and C2-2:C2-3 exist within PC zone E2-1) means that the integrated correlation scheme is of higher resolution if these techniques were employed in isolation.

中文翻译:

主成分分析在化学数据与储层相关性中的应用-以沙特阿拉伯白垩纪碳酸盐岩沉积岩为例

提出了一种新的方法,通过应用主成分(PC)分析来识别化学地层区域,并基于PC曲线解释地质边界。PC数据是使用电感耦合等离子体发射光谱法和电感耦合等离子体质谱法计算的,所获得的数据来自Na-U范围内的50种化学元素。在本研究中,从沙特阿拉伯东南部白垩纪Wasia层的4口井中总共分析了832个岩心和岩屑样品,常规工作流程涉及绘制元素和元素比率的剖面图,每个研究剖面生成250至300剖面图。考虑到如此多的变量,产生化学地层学框架是一个具有挑战性和耗时的过程,需要化学地层学的专业知识。与元素或比率曲线相反,通过仅使用一些PC曲线,非专家可以更轻松地识别相关边界。PC参数反映了一组以上元素的变化并总结了地质变化。例如,在这项研究中,PC2参数值与沉积氧化还原条件的变化有关。使用PC识别的边界与来自同一井的现有常规化学地层学研究的边界之间存在密切联系。例如,PC区域E1-3与常规区域C3-1b相关。一些PC和常规化学地层边界并不总是重合的事实(例如,PC区域E2-1中存在常规边界C2-1:C2-2和C2-2:C2-3)意味着集成相关方案具有更高的如果孤立地使用这些技术,则分辨率较高。
更新日期:2021-04-15
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