Stratigraphic and lithofacies control on pore characteristics of Mississippian limestone and chert reservoirs of north-central Oklahoma

2018 ◽  
Vol 6 (4) ◽  
pp. T1001-T1022 ◽  
Author(s):  
Fnu Suriamin ◽  
Matthew J. Pranter

We have determined how stratigraphy and lithofacies control pore structures in the Mississippian limestone and chert reservoir of north-central Oklahoma. There are 17 lithofacies and 29 high-frequency cycles documented in the Mississippian interval of this study. The high-frequency cycles have thicknesses ranging from 0.3 to 30.5 m (1–100 ft) and are mainly asymmetric regressive phases. The pore characteristics, measured through digital-image analysis (DIA) of thin-sections photomicrographs ([Formula: see text]100), exhibit unique correlations with core porosity, permeability, and lithofacies within a sequence-stratigraphic framework. There are five fundamental correlations observed. First, porosity from DIA and laboratory core measurements has a strong positive relationship ([Formula: see text]). However, some values from DIA porosity yield relatively higher values, specifically in spiculitic mudstone wackestones and argillaceous spiculitic mudstone wackestones. The difference is hypothesized due to the presence of isolated nanopores that are not accessible by helium during measurement of core porosity. Second, the relationship between pore circularity and permeability is indeterminate. The indeterminate relationship is related to a complex internal pore network, intensive diagenetic alteration, an unconnected microfracture network, and isolated pores. Third, positive moderate to strong correlations ([Formula: see text]) between porosity and permeability are observed only in four lithofacies. Fourth, coarse-grained lithofacies within the uppermost depositional sequence of the Mississippian interval have a heterogeneous pore-size distribution, whereas fine-grained lithofacies tend to exhibit a homogeneous pore-size distribution. Fifth, higher reservoir quality is associated with the upper intervals of high-frequency shallowing-upward cycles. This confirms that the sequence-stratigraphic variability of lithofacies is important to predict reservoir quality and its distribution. An alternative graphical method of pore-size distribution is also developed. To be a useful “technique,” examples of the plot are demonstrated using samples in this study. The plot successfully provides simple identification of pore-size classes, quantitative percentage of pore-size class, dominant pore class, and approximate minimum and maximum pore size.

2019 ◽  
Vol 2019 ◽  
pp. 1-10
Author(s):  
Shengchao Ma ◽  
Zhenzhong Zhang ◽  
Kaiyue Shen ◽  
Xuedong He ◽  
Jun Li ◽  
...  

Many tons of porous carbon materials (including BC and IG-110) are contained in HTGR, which are serving as structural material and fuel matrix material. These materials would absorb moisture and other impurities when exposed to the environment, and these impurities (especially moisture) absorbed in the carbon material must be removed before the reactor operation to prevent corrosion reaction at high temperature (more than 500°C). As the pore microscopic structure characteristic is the significant factor affecting the gas adsorption and flow in the porous materials, the detailed 3D pore structures of the carbon materials (BC and IG-110) in HTGR were studied by Micro-XCT and HPMI methods in this paper. These pore structure characteristics include pore geometry, pore size distribution, and pore throat connectivity. The test results show that the pore size distribution of BC material is wide, and the pore diameter is obviously larger than that of IG-110. Pore connections in BC show radial shape connections at some special points, and the pore connectivity in IG-110 is very complex and presents a huge complex 3D pore network.


2000 ◽  
Vol 612 ◽  
Author(s):  
D. W. Gidley ◽  
W. E. Frieze ◽  
T. L. Dull ◽  
J. N. Sun ◽  
A. F. Yee

AbstractDepth profiled positronium annihilation lifetime spectroscopy (PALS) has been used to probe the pore characteristics (size, distribution, and interconnectivity) in thin, porous films, including silica and organic-based films. The technique is sensitive to all pores (both interconnected and closed) in the size range from 0.3 nm to 300 nm, even in films buried under a diffusion barrier. PALS may be particularly useful in deducing the pore-size distribution in closed-pore systems where gas absorption methods are not available. In this technique a focussed beam of several keV positrons forms positronium (Ps, the electron-positron bound state) with a depth distribution that depends on the selected positron beam energy. Ps inherently localizes in the pores where its natural (vacuum) annihilation lifetime of 142 ns is reduced by collisions with the pore surfaces. The collisionally reduced Ps lifetime is correlated with pore size and is the key feature in transforming a Ps lifetime distribution into a pore size distribution. In thin silica films that have been made porous by a variety of methods the pores are found to be interconnected and an average pore size is determined. In a mesoporous methyl-silsesquioxane film with nominally closed pores a pore size distribution has been determined. The sensitivity of PALS to metal overlayer interdiffusion is demonstrated. PALS is a non-destructive, depth profiling technique with the only requirement that positrons can be implanted into the porous film where Ps can form.


2019 ◽  
Author(s):  
Paul Iacomi ◽  
Philip L. Llewellyn

Material characterisation through adsorption is a widely-used laboratory technique. The isotherms obtained through volumetric or gravimetric experiments impart insight through their features but can also be analysed to determine material characteristics such as specific surface area, pore size distribution, surface energetics, or used for predicting mixture adsorption. The pyGAPS (python General Adsorption Processing Suite) framework was developed to address the need for high-throughput processing of such adsorption data, independent of the origin, while also being capable of presenting individual results in a user-friendly manner. It contains many common characterisation methods such as: BET and Langmuir surface area, t and α plots, pore size distribution calculations (BJH, Dollimore-Heal, Horvath-Kawazoe, DFT/NLDFT kernel fitting), isosteric heat calculations, IAST calculations, isotherm modelling and more, as well as the ability to import and store data from Excel, CSV, JSON and sqlite databases. In this work, a description of the capabilities of pyGAPS is presented. The code is then be used in two case studies: a routine characterisation of a UiO-66(Zr) sample and in the processing of an adsorption dataset of a commercial carbon (Takeda 5A) for applications in gas separation.


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