Increase in porosity and permeability resolution for thin-bedded Miocene formation in Carpathian Foredeep using different clustering methods

IF 2.3 4区 地球科学 Acta Geophysica Pub Date : 2024-08-14 DOI:10.1007/s11600-024-01409-0
Sebastian Waszkiewicz, Paulina Krakowska-Madejska
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Abstract

The accurate interpretation of well-logging data is a crucial stage in the exploration of gas- and oil-bearing reservoirs. Geological formations, such as the Miocene deposits, present many challenges related to thin layers, whose thickness is often less than the measurement resolution. This research emphasizes the potential of utilizing electrofacies in such challenging environments. The application of electrofacies not only allows for the grouping of intervals with similar physical characteristics but can also be useful for estimating porosity and permeability parameters. For this purpose, various clustering methods were tested, including the 2D indexed and probabilized self-organizing map (IPSOM) method with and without supervision. Subsequently, the usefulness of the obtained results to improve the estimation of porosity and permeability parameters with the help of artificial neural networks was verified. As a result of the conducted analyses, significantly better results were obtained compared to classical petrophysical interpretation. The calculated porosity and permeability parameters were characterized by much greater variability and alignment with laboratory measurements on porosity and permeability. The best results were obtained for the IPSOM method, but the other methods did not differ significantly. In conclusion, the studies have shown a positive result of applying clustering methods, including the IPSOM method, to improve the estimation of permeability and porosity parameters in complicated, thinly-layered formations.

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采用不同聚类方法提高喀尔巴阡山前深海中新世薄层的孔隙度和渗透率分辨率
准确解释测井数据是含气和含油储层勘探的关键阶段。中新世矿床等地质构造的薄层厚度往往小于测量分辨率,这给我们带来了许多挑战。这项研究强调了在这种具有挑战性的环境中利用电积层的潜力。电弧面的应用不仅可以将物理特征相似的区间分组,还可以用于估算孔隙度和渗透率参数。为此,对各种聚类方法进行了测试,包括有监督和无监督的二维索引和概率自组织图(IPSOM)方法。随后,在人工神经网络的帮助下,验证了所获结果对改进孔隙度和渗透率参数估算的有用性。分析结果表明,与传统的岩石物理解释相比,所获得的结果要好得多。计算出的孔隙度和渗透率参数具有更大的可变性,并与实验室测量的孔隙度和渗透率相一致。IPSOM 方法的结果最好,但其他方法的结果差异不大。总之,研究表明,应用聚类方法(包括 IPSOM 方法)来改进复杂薄层地层中渗透率和孔隙度参数的估算具有积极意义。
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来源期刊
Acta Geophysica
Acta Geophysica GEOCHEMISTRY & GEOPHYSICS-
CiteScore
3.80
自引率
13.00%
发文量
251
期刊介绍: Acta Geophysica is open to all kinds of manuscripts including research and review articles, short communications, comments to published papers, letters to the Editor as well as book reviews. Some of the issues are fully devoted to particular topics; we do encourage proposals for such topical issues. We accept submissions from scientists world-wide, offering high scientific and editorial standard and comprehensive treatment of the discussed topics.
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