Development of a Resistivity Model That Incorporates Quantitative Directional Connectivity and Tortuosity for Enhanced Assessment of Hydrocarbon Reserves

SPE Journal ◽  
2018 ◽  
Vol 23 (05) ◽  
pp. 1552-1565 ◽  
Author(s):  
Artur Posenato Garcia ◽  
Zoya Heidari
Keyword(s):  
Pore Space ◽  
Diffusivity Coefficient ◽  
Pore Scale ◽  
Rock Fabric ◽  
Rock Types ◽  
Resistivity Model ◽  
Directional Connectivity ◽  
Hydrocarbon Saturation ◽  
Reliable Quantification ◽  
Space Connectivity

Summary Success of the strategies to exploit hydrocarbon reservoirs depends on the availability of reliable information about pore structure and spatial distribution of fluids within the pore space. Reliable quantification of directional pore-space connectivity and characterization of pore architecture are, however, challenging. The objectives of this paper include (1) quantifying the directional connectivity of pore space [connected pore volume (PV)] and rock components, (2) identifying geometry-defined fabric features that contribute to the pore-connectivity variations within the same formation (e.g., tortuosity, constriction factor) and introducing analytical/numerical methods and mechanistic models to estimate them, and (3) improving assessment of hydrocarbon saturation by introducing a new resistivity model that incorporates the directional pore-space-connectivity factor. We introduce a new resistivity model that minimizes calibration efforts and improves assessment of hydrocarbon saturation in complex formations by incorporating a directional connectivity factor. The directional pore-space connectivity is defined as the geometry and texture of the porous media resulting from sedimentary and diagenetic processes, and is estimated with pore-scale images. The directional connectivity factor is a function of electrical tortuosity, and, therefore, we introduce a mechanistic equation that incorporates geometrical features of the pore space to accurately estimate electrical tortuosity. Then, we validate the new tortuosity model against results obtained from a semianalytical streamline algorithm in 3D pore-scale images from each rock type of interest in the formation. The actual electrical tortuosity obtained from numerical simulations is calculated with the geometry of the streamlines associated with the electric current and the corresponding time of flight (TOF) of electric charges. We successfully applied the introduced method to two carbonate formations. The results confirm that the introduced directional-connectivity factor can detect rock-fabric features, through quantifying the connected PV and tortuosity, and that it is a function of the directional-diffusivity coefficient. The quantification of rock fabric and pore-space connectivity improves the estimation of hydrocarbon saturation by 43% compared with conventional methods. The use of such a parameter for rock-fabric characterization from pore-scale images helps to decrease the need for calibration efforts in the interpretation of borehole geophysical measurements. Just a few cuttings from different rock types are sufficient for the proposed method.

Correlation of Pore Structure and Permeability by SEM-Image Analysis

1990 ◽  
Vol 48 (1) ◽  
pp. 428-429
Author(s):  
C. A. Callender ◽  
Wm. C. Dawson ◽  
J. J. Funk
Keyword(s):  
Image Analysis ◽  
Pore Structure ◽  
Imaging System ◽  
Pore Space ◽  
Simulation Models ◽  
Image Analyzer ◽  
Imaging Data ◽  
Sem Images ◽  
Thin Sections ◽  
Rock Types

The geometric structure of pore space in some carbonate rocks can be correlated with petrophysical measurements by quantitatively analyzing binaries generated from SEM images. Reservoirs with similar porosities can have markedly different permeabilities. Image analysis identifies which characteristics of a rock are responsible for the permeability differences. Imaging data can explain unusual fluid flow patterns which, in turn, can improve production simulation models.Analytical SchemeOur sample suite consists of 30 Middle East carbonates having porosities ranging from 21 to 28% and permeabilities from 92 to 2153 md. Engineering tests reveal the lack of a consistent (predictable) relationship between porosity and permeability (Fig. 1). Finely polished thin sections were studied petrographically to determine rock texture. The studied thin sections represent four petrographically distinct carbonate rock types ranging from compacted, poorly-sorted, dolomitized, intraclastic grainstones to well-sorted, foraminiferal,ooid, peloidal grainstones. The samples were analyzed for pore structure by a Tracor Northern 5500 IPP 5B/80 image analyzer and a 80386 microprocessor-based imaging system. Between 30 and 50 SEM-generated backscattered electron images (frames) were collected per thin section. Binaries were created from the gray level that represents the pore space. Calculated values were averaged and the data analyzed to determine which geological pore structure characteristics actually affect permeability.

scholarly journals Determination of macro-scale soil properties from pore-scale structures: model derivation

2018 ◽  
Vol 474 (2209) ◽  
pp. 20170141 ◽  
Author(s):  
K. R. Daly ◽  
T. Roose
Keyword(s):  
Pore Space ◽  
Solid Particles ◽  
Underlying Structure ◽  
Pore Scale ◽  
Homogenization Procedure ◽  
Macro Scale ◽  
Model Derivation ◽  
Scale Structures ◽  
Homogenization Scheme

In this paper, we use homogenization to derive a set of macro-scale poro-elastic equations for soils composed of rigid solid particles, air-filled pore space and a poro-elastic mixed phase. We consider the derivation in the limit of large deformation and show that by solving representative problems on the micro-scale we can parametrize the macro-scale equations. To validate the homogenization procedure, we compare the predictions of the homogenized equations with those of the full equations for a range of different geometries and material properties. We show that the results differ by ≲ 2 % for all cases considered. The success of the homogenization scheme means that it can be used to determine the macro-scale poro-elastic properties of soils from the underlying structure. Hence, it will prove a valuable tool in both characterization and optimization.

Detecting Skrugard by CSEM — Prewell prediction and postwell evaluation

2014 ◽  
Vol 2 (3) ◽  
pp. SH67-SH77 ◽  
Author(s):  
Lars Ole Løseth ◽  
Torgeir Wiik ◽  
Per Atle Olsen ◽  
Jan Ove Hansen
Keyword(s):  
Data Acquisition ◽  
Barents Sea ◽  
Hydrocarbon Exploration ◽  
Seismic Structure ◽  
Well Location ◽  
Resistivity Logs ◽  
Resistivity Model ◽  
Joint Interpretation ◽  
Hydrocarbon Saturation ◽  
Scenario Testing

The discovery of Skrugard in 2011 was a significant milestone for hydrocarbon exploration in the Barents Sea. The result was a positive confirmation of the play model, prospect evaluation, and the seismic hydrocarbon indicators in the area. In addition, the well result was encouraging for the CSEM interpretation and analysis that had been performed. Prior to drilling the 7220/8-1 well, EM resistivity images of the subsurface across the prospect had been obtained along with estimates of hydrocarbon saturation at the well position. The resistivity distribution was derived from extensive analysis of the multiclient CSEM data from 2008. The analysis was based on joint interpretation of seismic structures and optimal resistivity models from the CSEM data. The seismic structure was furthermore used to constrain the resistivity anomaly to the Skrugard reservoir. Scenario testing was then done to assess potential alternative models that could explain the CSEM data in addition to extract the most likely reservoir resistivity. Estimates of hydrocarbon saturation followed from using petrophysical parameters from nearby wells and knowledge of the area, combined with the most likely resistivity model from CSEM. Our results from the prewell study were compared to the postwell resistivity logs, for horizontal and vertical resistivity. We found a very good match between the estimated CSEM resistivities at the well location and the corresponding well resistivities. Thus, our results confirmed the ability of CSEM to predict hydrocarbon saturation. In addition, the work demonstrated limitations in the CSEM data analysis tools as well as sensitivity to acquisition parameters and measurement accuracy. The work has led to more CSEM data acquisition in the area and continued effort in development of our tools for data acquisition and analysis.

Chemotaxis under flow disorder shapes microbial dispersion in porous media 

2021 ◽  
Author(s):  
Pietro de Anna ◽  
Amir A. Pahlavan ◽  
Yutaka Yawata ◽  
Roman Stocker ◽  
Ruben Juanes
Keyword(s):  
Porous Media ◽  
Dispersion Coefficient ◽  
Pore Space ◽  
Low Flow ◽  
Pore Scale ◽  
Porous Rocks ◽  
Chemical Gradients ◽  
Deep Earth ◽  
Bacterium Bacillus Subtilis ◽  
Bacterium Bacillus

<div> <div> <div> <p>Natural soils are host to a high density and diversity of microorganisms, and even deep-earth porous rocks provide a habitat for active microbial communities. In these environ- ments, microbial transport by disordered flows is relevant for a broad range of natural and engineered processes, from biochemical cycling to remineralization and bioremediation. Yet, how bacteria are transported and distributed in the sub- surface as a result of the disordered flow and the associ- ated chemical gradients characteristic of porous media has remained poorly understood, in part because studies have so far focused on steady, macroscale chemical gradients. Here, we use a microfluidic model system that captures flow disorder and chemical gradients at the pore scale to quantify the transport and dispersion of the soil-dwelling bacterium Bacillus subtilis in porous media. We observe that chemotaxis strongly modulates the persistence of bacteria in low-flow regions of the pore space, resulting in a 100% increase in their dispersion coefficient. This effect stems directly from the strong pore-scale gradients created by flow disorder and demonstrates that the microscale interplay between bacterial behaviour and pore-scale disorder can impact the macroscale dynamics of biota in the subsurface.</p> </div> </div> </div>

Pore-scale Mixing and the Evolution from Anomalous to Normal Hydrodynamic Dispersion

2021 ◽  
Author(s):  
Marco Dentz ◽  
Alexandre Puyguiraud ◽  
Philippe Gouze
Keyword(s):  
Porous Media ◽  
Large Scale ◽  
Molecular Diffusion ◽  
Pore Space ◽  
Breakthrough Curves ◽  
Heterogeneous Porous Media ◽  
Hydrodynamic Dispersion ◽  
Pore Scale ◽  
Sandstone Sample ◽  
Flow Variability

<p>Transport of dissolved substances through porous media is determined by the complexity of the pore space and diffusive mass transfer within and between pores. The interplay of diffusive pore-scale mixing and spatial flow variability are key for the understanding of transport and reaction phenomena in porous media. We study the interplay of pore-scale mixing and network-scale advection through heterogeneous porous media, and its role for the evolution and asymptotic behavior of hydrodynamic dispersion. In a Lagrangian framework, we identify three fundamental mechanisms of pore-scale mixing that determine large scale particle motion: (i) The smoothing of intra-pore velocity contrasts, (ii) the increase of the tortuosity of particle paths, and (iii) the setting of a maximum time for particle transitions. Based on these mechanisms, we derive an upscaled approach that predicts anomalous and normal hydrodynamic dispersion based on the characteristic pore length, Eulerian velocity distribution and Péclet number. The theoretical developments are supported and validated by direct numerical flow and transport simulations in a three-dimensional digitized Berea sandstone sample obtained using X-Ray microtomography. Solute breakthrough curves, are characterized by an intermediate power-law behavior and exponential cut-off, which reflect pore-scale velocity variability and intra-pore solute mixing. Similarly, dispersion evolves from molecular diffusion at early times to asymptotic hydrodynamics dispersion via an intermediate superdiffusive regime. The theory captures the full evolution form anomalous to normal transport behavior at different Péclet numbers as well as the Péclet-dependence of asymptotic dispersion. It sheds light on hydrodynamic dispersion behaviors as a consequence of the interaction between pore-scale mixing and Eulerian flow variability. </p>

Capillary-Dominated Fluid Displacement in Porous Media

2019 ◽  
Vol 51 (1) ◽  
pp. 429-449 ◽  
Author(s):  
Kamaljit Singh ◽  
Michael Jung ◽  
Martin Brinkmann ◽  
Ralf Seemann
Keyword(s):  
Porous Media ◽  
Pore Space ◽  
Contact Angles ◽  
Pore Scale ◽  
Fluid Displacement ◽  
Invasion Pattern ◽  
Theoretical Considerations ◽  
Displacement Processes ◽  
Synchrotron Microtomography ◽  
Relevant Material

Liquid invasion into a porous medium is a phenomenon of great importance in both nature and technology. Despite its enormous importance, there is a surprisingly sparse understanding of the processes occurring on the scale of individual pores and of how these processes determine the global invasion pattern. In particular, the exact influence of the wettability remains unclear besides the limiting cases of very small or very large contact angles of the invading fluid. Most quantitative pore-scale experiments and theoretical considerations have been conducted in effectively two-dimensional (2D) micromodels and Hele–Shaw geometries. Although these pioneering works helped to unravel some of the physical aspects of the displacement processes, the relevance of 2D models has not always been appreciated for natural porous media. With the availability of X-ray microtomography, 3D imaging has become a standard for exploring pore-scale processes in porous media. Applying advanced postprocessing routines and synchrotron microtomography, researchers can image even slow flow processes in real time and extract relevant material parameters like the contact angle from the interfaces in the pore space. These advances are expected to boost both theoretical and experimental understanding of pore-scale processes in natural porous media.

scholarly journals Transport Simulations on Scanning Transmission Electron Microscope Images of Nanoporous Shale

Energies ◽  
2020 ◽  
Vol 13 (24) ◽  
pp. 6665
Author(s):  
Laura Frouté ◽  
Yuhang Wang ◽  
Jesse McKinzie ◽  
Saman Aryana ◽  
Anthony Kovscek
Keyword(s):  
Gas Permeability ◽  
Pore Space ◽  
Knudsen Diffusion ◽  
Transport Processes ◽  
Pore Scale ◽  
Pore Networks ◽  
Scanning Transmission Electron ◽  
Transmission Electron ◽  
Scanning Transmission ◽  
Stem Tomography

Digital rock physics is an often-mentioned approach to better understand and model transport processes occurring in tight nanoporous media including the organic and inorganic matrix of shale. Workflows integrating nanometer-scale image data and pore-scale simulations are relatively undeveloped, however. In this paper, a workflow is demonstrated progressing from sample acquisition and preparation, to image acquisition by Scanning Transmission Electron Microscopy (STEM) tomography, to volumetric reconstruction to pore-space discretization to numerical simulation of pore-scale transport. Key aspects of the workflow include (i) STEM tomography in high angle annular dark field (HAADF) mode to image three-dimensional pore networks in µm-sized samples with nanometer resolution and (ii) lattice Boltzmann method (LBM) simulations to describe gas flow in slip, transitional, and Knudsen diffusion regimes. It is shown that STEM tomography with nanoscale resolution yields excellent representation of the size and connectivity of organic nanopore networks. In turn, pore-scale simulation on such networks contributes to understanding of transport and storage properties of nanoporous shale. Interestingly, flow occurs primarily along pore networks with pore dimensions on the order of tens of nanometers. Smaller pores do not form percolating pathways in the sample volume imaged. Apparent gas permeability in the range of 10−19 to 10−16 m2 is computed.

Pore-Scale Joint Evaluation of Dielectric Permittivity and Electrical Resistivity for Assessment of Hydrocarbon Saturation Using Numerical Simulations

SPE Journal ◽  
2016 ◽  
Vol 21 (06) ◽  
pp. 1930-1942 ◽  
Author(s):  
Huangye Chen ◽  
Zoya Heidari
Keyword(s):  
Electrical Resistivity ◽  
Spatial Distribution ◽  
Dielectric Permittivity ◽  
Pore Structure ◽  
Maximum Error ◽  
New Method ◽  
Pore Scale ◽  
Resistivity Measurements ◽  
Hydrocarbon Saturation ◽  
Permittivity Measurements

Summary Complex pore geometry and composition, as well as anisotropic behavior and heterogeneity, can affect physical properties of rocks such as electrical resistivity and dielectric permittivity. The aforementioned physical properties are used to estimate in-situ petrophysical properties of the formation such as hydrocarbon saturation. In the application of conventional methods for interpretation of electrical-resistivity (e.g., Archie's equation and the dual-water model) and dielectric-permittivity measurements [e.g., complex refractive index model (CRIM)], the impacts of complex pore structure (e.g., kerogen porosity and intergranular pores), pyrite, and conductive mature kerogen have not been taken into account. These limitations cause significant uncertainty in estimates of water saturation. In this paper, we introduce a new method that combines interpretation of dielectric-permittivity and electrical-resistivity measurements to improve assessment of hydrocarbon saturation. The combined interpretation of dielectric-permittivity and electrical-resistivity measurements enables assimilating spatial distribution of rock components (e.g., pore, kerogen, and pyrite networks) in conventional models. We start with pore-scale numerical simulations of electrical resistivity and dielectric permittivity of fluid-bearing porous media to investigate the structure of pore and matrix constituents in these measurements. The inputs to these simulators are 3D pore-scale images. We then introduce an analytical model that combines resistivity and permittivity measurements to assess water-filled porosity and hydrocarbon saturation. We apply the new method to actual digital sandstones and synthetic digital organic-rich mudrock samples. The relative errors (compared with actual values estimated from image processing) in the estimate of water-filled porosity through our new method are all within the 10% range. In the case of digital sandstone samples, CRIM provided reasonable estimates of water-filled porosity, with only four out of twenty-one estimates beyond 10% relative error, with the maximum error of 30%. However, in the case of synthetic digital organic-rich mudrocks, six out of ten estimates for water-filled porosity were beyond 10% with CRIM, with the maximum error of 40%. Therefore, the improvement was more significant in the case of organic-rich mudrocks with complex pore structure. In the case of synthetic digital organic-rich mudrock samples, our simulation results confirm that not only the pore structure but also spatial distribution and tortuosity of water, kerogen, and pyrite networks affect the measurements of dielectric permittivity and electrical resistivity. Taking into account these parameters through the joint interpretation of dielectric-permittivity and electrical-resistivity measurements significantly improves assessment of hydrocarbon saturation.

Pore Scale Modeling of Brine Dependent Pore Space Evolution in Carbonates

2013 ◽  
Author(s):  
Janne Pedersen ◽  
Jan Ludvig Vinningland ◽  
Espen Jettestuen ◽  
Merete Vadla Madland ◽  
Aksel Hiorth
Keyword(s):  
Pore Space ◽  
Pore Scale ◽  
Scale Modeling ◽  
Pore Scale Modeling

scholarly journals Pore-Scale Imaging of the Oil Cluster Dynamic during Drainage and Imbibition Using In Situ X-Ray Microtomography

Geofluids ◽  
2018 ◽  
Vol 2018 ◽  
pp. 1-13 ◽  
Author(s):  
Junjian Li ◽  
Yajun Gao ◽  
Hanqiao Jiang ◽  
Yang Liu ◽  
Hu Dong
Keyword(s):  
Specific Surface ◽  
Capillary Pressure ◽  
Surface Area ◽  
Specific Surface Area ◽  
Pore Space ◽  
Relative Volume ◽  
Pore Scale ◽  
X Ray ◽  
Cluster Dynamic ◽  
Remaining Oil

We imaged water-wet and oil-wet sandstones under two-phase flow conditions for different flooding states by means of X-ray computed microtomography (μCT) with a spatial resolution of 2.1 μm/pixel. We systematically study pore-scale trapping of the nonwetting phase as well as size and distribution of its connected clusters and disconnected globules. We found a lower Sor, 19.8%, for the oil-wet plug than for water-wet plug (25.2%). Approximate power-law distributions of the water and oil cluster sizes were observed in the pore space. Besides, the τ value of the wetting phase gradually decreased and the nonwetting phase gradually increased during the core-flood experiment. The remaining oil has been divided into five categories; we explored the pore fluid occupancies and studied size and distribution of the five types of trapped oil clusters during different drainage stage. The result shows that only the relative volume of the clustered oil is reduced, and the other four types of remaining oil all increased. Pore structure, wettability, and its connectivity have a significant effect on the trapped oil distribution. In the water sandstone, the trapped oil tends to occupy the center of the larger pores during the water imbibition process, leading to a stable specific surface area and a gradually decreasing oil capillary pressure. Meanwhile, in oil-wet sandstone, the trapped oil blobs that tend to occupy the pores corner and attach to the walls of the pores have a large specific surface area, and the change of the oil capillary pressure was not obvious. These results have revealed the well-known complexity of multiphase flow in rocks and preliminarily show the pore-level displacement physics of the process.

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