Pore Size, Tortuosity, and Permeability From NMR Restricted Diffusion in Organic-Rich Chalks

Author(s):  
Xinglin Wang ◽  
◽  
Philip M. Singer ◽  
Yunke Liu ◽  
Zeliang Chen ◽  
...  

Permeability estimation is crucial for formation evaluation, but faces challenges when used in low-permeability, unconventional formations. NMR well logging is often used to estimate formation permeability, but in many unconventional formations, the current NMR methods are not adequate. We have developed a new method to estimate permeability using a modified Carman-Kozeny model with pore size, tortuosity, and porosity information inferred from NMR restricted diffusion measurements. In this study, we focus on two low-permeability, organic-rich chalks (0.017 and 0.035 md) with connate water present. They are from the same formation but have different depths, TOC (total organic carbon), and bitumen content. These differences affect pore size, tortuosity, and permeability. The core samples are pressure saturated with two hydrocarbons—high-pressure methane or decane—with connate water present. NMR measurements are conducted under pressure to obtain the restricted diffusivity of the hydrocarbon-bearing pore space. In planning the NMR restricted diffusivity measurements, an optimum series of diffusion-encoding times are chosen for the unipolar stimulated-echo pulse sequence to obtain the correlation between the restricted diffusivity (D) and free diffusion length (LD). By applying the Padé fit to the restricted diffusivity, we can better estimate the diffusive tortuosity (τ) and pore-body size (d) of the hydrocarbon-filled pore space. The estimated pore-body size, tortuosity, and porosity from NMR are then used to predict permeability. We introduce a modified Carman-Kozeny model, which shows advantages over older methods like SDR and Timur-Coates models. The advantages of the new method are shown in organic-rich chalk with complex pore structures and organic matter. This new method can potentially be used for estimating permeability by well-logging and core-log integration.

2020 ◽  
Author(s):  
Xinglin Wang ◽  
◽  
Philip M. Singer ◽  
Zeliang Chen ◽  
George J. Hirasaki ◽  
...  

Fractals ◽  
2018 ◽  
Vol 26 (01) ◽  
pp. 1850006 ◽  
Author(s):  
YUXUAN XIA ◽  
JIANCHAO CAI ◽  
WEI WEI ◽  
XIANGYUN HU ◽  
XIN WANG ◽  
...  

Fractal theory has been widely used in petrophysical properties of porous rocks over several decades and determination of fractal dimensions is always the focus of researches and applications by means of fractal-based methods. In this work, a new method for calculating pore space fractal dimension and tortuosity fractal dimension of porous media is derived based on fractal capillary model assumption. The presented work establishes relationship between fractal dimensions and pore size distribution, which can be directly used to calculate the fractal dimensions. The published pore size distribution data for eight sandstone samples are used to calculate the fractal dimensions and simultaneously compared with prediction results from analytical expression. In addition, the proposed fractal dimension method is also tested through Micro-CT images of three sandstone cores, and are compared with fractal dimensions by box-counting algorithm. The test results also prove a self-similar fractal range in sandstone when excluding smaller pores.


2008 ◽  
Vol 607 ◽  
pp. 39-41
Author(s):  
Jerzy Kansy ◽  
Radosław Zaleski

A new method of analysis of PALS spectra of porous materials is proposed. The model considers both the thermalization process of positronium inside the pores and the pore size distribution. The new model is fitted to spectra of mesoporous silica MCM-41 and MSF. The resulting parameters are compared with parameters obtained from fitting the “conventional” models, i.e. a sum of exponential components with discrete or/and distributed lifetimes.


Energies ◽  
2019 ◽  
Vol 12 (2) ◽  
pp. 327 ◽  
Author(s):  
Qian Wang ◽  
Shenglai Yang ◽  
Haishui Han ◽  
Lu Wang ◽  
Kun Qian ◽  
...  

The petrophysical properties of ultra-low permeability sandstone reservoirs near the injection wells change significantly after CO2 injection for enhanced oil recovery (EOR) and CO2 storage, and different CO2 displacement methods have different effects on these changes. In order to provide the basis for selecting a reasonable displacement method to reduce the damage to these high water cut reservoirs near the injection wells during CO2 injection, CO2-formation water alternate (CO2-WAG) flooding and CO2 flooding experiments were carried out on the fully saturated formation water cores of reservoirs with similar physical properties at in-situ reservoir conditions (78 °, 18 MPa), the similarities and differences of the changes in physical properties of the cores before and after flooding were compared and analyzed. The measurement results of the permeability, porosity, nuclear magnetic resonance (NMR) transversal relaxation time (T2) spectrum and scanning electron microscopy (SEM) of the cores show that the decrease of core permeability after CO2 flooding is smaller than that after CO2-WAG flooding, with almost unchanged porosity in both cores. The proportion of large pores decreases while the proportion of medium pores increases, the proportion of small pores remains almost unchanged, the distribution of pore size of the cores concentrates in the middle. The changes in range and amplitude of the pore size distribution in the core after CO2 flooding are less than those after CO2-WAG flooding. After flooding experiments, clay mineral, clastic fines and salt crystals adhere to some large pores or accumulate at throats, blocking the pores. The changes in core physical properties are the results of mineral dissolution and fines migration, and the differences in these changes under the two displacement methods are caused by the differences in three aspects: the degree of CO2-brine-rock interaction, the radius range of pores where fine migration occurs, the power of fine migration.


1999 ◽  
Vol 2 (02) ◽  
pp. 149-160 ◽  
Author(s):  
D.K. Davies ◽  
R.K. Vessell ◽  
J.B. Auman

Summary This paper presents a cost effective, quantitative methodology for reservoir characterization that results in improved prediction of permeability, production and injection behavior during primary and enhanced recovery operations. The method is based fundamentally on the identification of rock types (intervals of rock with unique pore geometry). This approach uses image analysis of core material to quantitatively identify various pore geometries. When combined with more traditional petrophysical measurements, such as porosity, permeability and capillary pressure, intervals of rock with various pore geometries (rock types) can be recognized from conventional wireline logs in noncored wells or intervals. This allows for calculation of rock type and improved estimation of permeability and saturation. Based on geological input, the reservoirs can then be divided into flow units (hydrodynamically continuous layers) and grid blocks for simulation. Results are presented of detailed studies in two, distinctly different, complex reservoirs: a low porosity carbonate reservoir and a high porosity sandstone reservoir. When combined with production data, the improved characterization and predictability of performance obtained using this unique technique have provided a means of targeting the highest quality development drilling locations, improving pattern design, rapidly recognizing conformance and formation damage problems, identifying bypassed pay intervals, and improving assessments of present and future value. Introduction This paper presents a technique for improved prediction of permeability and flow unit distribution that can be used in reservoirs of widely differing lithologies and differing porosity characteristics. The technique focuses on the use and integration of pore geometrical data and wireline log data to predict permeability and define hydraulic flow units in complex reservoirs. The two studies presented here include a low porosity, complex carbonate reservoir and a high porosity, heterogeneous sandstone reservoir. These reservoir classes represent end-members in the spectrum of hydrocarbon reservoirs. Additionally, these reservoirs are often difficult to characterize (due to their geological complexity) and frequently contain significant volumes of remaining reserves.1 The two reservoir studies are funded by the U.S. Department of Energy as part of the Class II and Class III Oil Programs for shallow shelf carbonate (SSC) reservoirs and slope/basin clastic (SBC) reservoirs. The technique described in this paper has also been used to characterize a wide range of other carbonate and sandstone reservoirs including tight gas sands (Wilcox, Vicksburg, and Cotton Valley Formations, Texas), moderate porosity sandstones (Middle Magdalena Valley, Colombia and San Jorge Basin, Argentina), and high porosity reservoirs (Offshore Gulf Coast and Middle East). The techniques used for reservoir description in this paper meet three basic requirements that are important in mature, heterogeneous fields.The reservoir descriptions are log-based. Flow units are identified using wireline logs because few wells have cores. Integration of data from analysis of cores is an essential component of the log models.Accurate values of permeability are derived from logs. In complex reservoirs, values of porosity and saturation derived from routine log analysis often do not accurately identify productivity. It is therefore necessary to develop a log model that will allow the prediction of another producibility parameter. In these studies we have derived foot-by-foot values of permeability for cored and non-cored intervals in all wells with suitable wireline logs.Use only the existing databases. No new wells will be drilled to aid reservoir description. Methodology Techniques of reservoir description used in these studies are based on the identification of rock types (intervals of rock with unique petrophysical properties). Rock types are identified on the basis of measured pore geometrical characteristics, principally pore body size (average diameter), pore body shape, aspect ratio (size of pore body: size of pore throat) and coordination number (number of throats per pore). This involves the detailed analysis of small rock samples taken from existing cores (conventional cores and sidewall cores). The rock type information is used to develop the vertical layering profile in cored intervals. Integration of rock type data with wireline log data allows field-wide extrapolation of the reservoir model from cored to non-cored wells. Emphasis is placed on measurement of pore geometrical characteristics using a scanning electron microscope specially equipped for automated image analysis procedures.2–4 A knowledge of pore geometrical characteristics is of fundamental importance to reservoir characterization because the displacement of hydrocarbons is controlled at the pore level; the petrophysical properties of rocks are controlled by the pore geometry.5–8 The specific procedure includes the following steps.Routine measurement of porosity and permeability.Detailed macroscopic core description to identify vertical changes in texture and lithology for all cores.Detailed thin section and scanning electron microscope analyses (secondary electron imaging mode) of 100 to 150 small rock samples taken from the same locations as the plugs used in routine core analysis. In the SBC reservoir, x-ray diffraction analysis is also used. The combination of thin section and x-ray analyses provides direct measurement of the shale volume, clay volume, grain size, sorting and mineral composition for the core samples analyzed.Rock types are identified for each rock sample using measured data on pore body size, pore throat size and pore interconnectivity (coordination number and pore arrangement).


2018 ◽  
Vol 6 (2) ◽  
pp. 535-547 ◽  
Author(s):  
Chuanjie Fang ◽  
Sungil Jeon ◽  
Saeid Rajabzadeh ◽  
Liang Cheng ◽  
Lifeng Fang ◽  
...  

A new method was used to tailor the surface pore size of PVDF hollow fiber membranes in the TIPS process by the co-extrusion of different solvents at the outer layer of the extruded polymeric solution.


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