The main goal of the research was to employ the unique data delivered by various methods to improve the determination of rock reservoir properties. Results of X-ray computed tomography (XRCMT), one of the newest techniques providing high-resolution images of rocks, were used to show that very precise information from this tool is complementary to results from other methods. Standard laboratory measurements (helium pycnometer, mercury injection porosimetry, permeameter) and sophisticated experiments (X-ray computed tomography and nuclear magnetic resonance spectroscopy) were performed to obtain and compare results. Four types of specimens: typical Miocene sandstone-mudstone-claystone rock samples, artificial corundum specimens, shale gas plugs, and limestone sample were investigated to obtain the porosity, permeability, density, and other parameters used in rock descriptions. Mutual relationships between selected groups of rock material properties were presented to provide an integral picture of rock characteristics. The XRCMT results were in general not influenced by lithology, but there were observed shaliness effects on the shape of pores, cross sections, and the tortuosity of porous channels. An analysis of the average porosity and the standard deviation of each XRCMT plot provided information about differences in the heterogeneity of a formation. Thus, the XRCMT method was recommended in pore space parameter determination for microfracture fluid propagation monitoring. There was also observed equivalence between part of the NMR signal from clay-bound water and the XRCMT volume subgroups in porosity/permeability—structural classes I and II. So, the use of the two-subsample approach in the XRCMT interpretation was promoted.

Open Access Published: 17 December 2016 Tight Reservoir Properties Derived by Nuclear Magnetic Resonance, Mercury Porosimetry and Computed Microtomography Laboratory Techniques. Case Study of Palaeozoic Clastic Rocks Paulina I. Krakowska¹ & Edyta Puskarczyk¹ Acta Geophysica volume 63, pages 789–814 (2015)Cite this article 342 Accesses 15 Citations Metrics details Abstract Results of the nuclear magnetic resonance (NMR) investigations, mercury porosimetry measurements (MP) and computed microtomography (micro-CT), applied to the tight Palaeozoic rocks from the depths lower than 3000 m, were presented to estimate their reservoir potential. NMR signal analysis and interpretation were performed. Based on NMR driven models, permeability and Free Fluid Index were calculated for data sets divided into homogeneous clusters. 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Krakowska & Edyta Puskarczyk Authors Paulina I. Krakowska View author publications You can also search for this author in PubMed Google Scholar Edyta Puskarczyk View author publications You can also search for this author in PubMed Google Scholar Corresponding author Correspondence to Paulina I. Krakowska. Rights and permissions Open Access This article is distributed under the terms of the Creative Commons Attribution 4.0 International License (https://creativecommons.org/licenses/by/4.0), which permits use, duplication, adaptation, distribution, and reproduction in any medium or format, as long as you give appropriate credit to the original author(s) and the source, provide a link to the Creative Commons license, and indicate if changes were made. Reprints and Permissions About this article Cite this article Krakowska, P.I., Puskarczyk, E. Tight Reservoir Properties Derived by Nuclear Magnetic Resonance, Mercury Porosimetry and Computed Microtomography Laboratory Techniques. Case Study of Palaeozoic Clastic Rocks. Acta Geophys. 63, 789–814 (2015). https://doi.org/10.1515/acgeo-2015-0013 Download citation Received: 04 May 2014 Accepted: 18 June 2014 Published: 17 December 2016 Issue Date: June 2015 DOI : https://doi.org/10.1515/acgeo-2015-0013 Share this article Anyone you share the following link with will be able to read this content: Get shareable link Sorry, a shareable link is not currently available for this article. Copy to clipboard Provided by the Springer Nature SharedIt content-sharing initiative Key words palaeozoic sedimentary rocks nuclear magnetic resonance mercury porosimetry computed microtomography

Permeability is a property of rocks which refers to the ability of fluids to flow through each substance. It depends on several factors as pore shape and diameter. Also the presence and type of clay has a large influence on the permeability value. Permeability can be measured on rock sample in the laboratory by injecting fluid through the rock under known condition, but this provides only point information. Due to the dependence of the parameter on many factors, the deterministic estimation of permeability based on laboratory measurement and well logs is problematic. Many empirical methods for determining permeability are available in the literature and interpretation systems. An interesting approach to the problem is the use of artificial neural networks based on laboratory measurement and modern, high-resolution logging tools. The authors decided to use MLP artificial neural networks, which allow permeability estimation and can be used both in the test well and applied to neighbouring wells. The network was checked in several variants. Obtained results show the legitimacy of using artificial neural networks in the issue of estimating permeability. However, they also show limitations resulting from the lack of accurate data or influence of geological setting and processes.