Standardized Automated Multiscale Imaging Technologies to Quantify Microstructure and Petrophysical Properties in a Range of Rock Types

Rock typing is critical in deepwater reservoir characterization to construct stratigraphic models populated with static and dynamic petrophysical properties. Rock typing based on multiple well logs is subject to large uncertainty in thinly bedded reservoirs because true physical properties cannot be resolved by low-resolution logging tools due to shoulder-bed effects. We have introduced a new Bayesian approach that inherently adopts the scientific method of iterative hypothesis testing to perform rock typing by simultaneously honoring different logging-tool physics in a multilayered earth model. In addition to estimating the vertical distribution of rock types with maximum likelihood, the Bayesian method quantifies the uncertainty of rock types and the associated petrophysical properties layer by layer. Bayesian rock classification is performed with a fast sampling technique based on the Markov-chain Monte Carlo method, thereby enabling an efficient search of rock types to obtain the final results. We have used a fast linear iterative refinement method to simulate nuclear logs and a 2D forward modeling code to simulate array-induction resistivity logs. A rock-type distribution hypothesis is considered acceptable only when all the observed well logs are reproduced with forward modeling. In a field case of offshore deltaic gas reservoir, the Bayesian method differentiates rock types that exhibit subtle petrophysical variations due to grain size change. The new method provides more than 77% agreement between log- and core-derived rock types, whereas conventional deterministic methods achieve only 60% agreement due to the presence of thin beds and laminations. Even though large uncertainty is observed in thinly bedded and laminated zones, the Bayesian rock-typing method still yields rock types and petrophysical properties that agree well with core-plug measurements acquired in these layers. As a result, the overall correlation between log-derived permeability and core-measured permeability is improved by approximately 16% when compared with conventional deterministic methods.

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Comparison of Petrophysical Properties of Porous Rocks Using NMR, Micro-CT, and Fluid Flow Simulations

Geosciences ◽

10.3390/geosciences11120500 ◽

2021 ◽

Vol 11 (12) ◽

pp. 500

Author(s):

Apoorv Jyoti ◽

Ralf R. Haese

Keyword(s):

Water Saturation ◽

Image Resolution ◽

Nuclear Magnetic Resonance Analysis ◽

Ct Image ◽

Petrophysical Properties ◽

Micro Ct ◽

Image Size ◽

Flow Simulations ◽

Transport Regime ◽

Rock Types

Micro-computed tomography (micro-CT) is increasingly utilized to image the pore network and to derive petrophysical properties in combination with modelling software. The effect of micro-CT image resolution and size on the accuracy of the derived petrophysical properties is addressed in this study using a relatively homogenous sandstone and a heterogenous, highly porous bioclastic limestone. Standard laboratory procedures including NMR (nuclear magnetic resonance) analysis, micro-CT analysis at different image resolutions and sizes and pore-scale flow simulations were used to determine and compare petrophysical properties. NMR-derived pore-size distribution (PSD) was comparable to the micro-CT-derived PSD at a resolution of 7 µm for both the rock types. Porosity was higher using the water saturation method as compared to the NMR method in both rocks. The resolution did not show a significant effect on the porosity of the homogeneous sandstone, but porosity in the heterogeneous limestone varies depending on the location of the sub-sample. The transport regime in the sandstone was derived by simulations and changed with the resolution of the micro-CT image. The transport regime in the sandstone was advection-dominated at higher image resolution and diffusion-dominated when using a lower image resolution. In contrast, advection was the dominant transport regime for the limestone based on simulations using higher and lower image resolutions. Simulation-derived permeability for a 400 Voxel3 image at 7 µm resolution in the Berea sandstone matched laboratory results, although local heterogeneity within the rock plays an integral role in the permeability estimation within the sub-sampled images. The simulation-derived permeability was highly variable in the Mount Gambier limestone depending on the image size and resolution with the closest value to a laboratory result simulated with an image resolution of 2.5 µm and a size of 300 Voxel3. Overall, the study demonstrates the need to decide on micro-CT parameters depending on the type of petrophysical property of interest and the degree of heterogeneity within the rock types.

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Database of Petrophysical Properties of the Mid-German Crystalline High

10.5194/essd-2020-211 ◽

2020 ◽

Author(s):

Sebastian Weinert ◽

Kristian Bär ◽

Ingo Sass

Keyword(s):

Large Scale ◽

Reservoir Characterization ◽

Numerical Models ◽

Sampling Location ◽

Petrophysical Properties ◽

Laboratory Equipment ◽

Rock Types ◽

Matrix Permeability ◽

Area Of Interest ◽

Sampling Campaign

Abstract. Petrophysical properties are a key element for reservoir characterization but also for interpreting the results of various geophysical exploration methods or geophysical well logs. Furthermore, petrophysical properties are commonly used to populate numerical models and are often critically governing the model results. Despite the common need of detailed petrophysical properties, data is still very scarce and often not available for the area of interest. Furthermore, both the online research for published property measurements or compilations, as well as dedicated measurements campaigns of the selected properties, which requires comprehensive laboratory equipment, can be very time-consuming and costly. To date, most published research results are often focused on a limited selection of parameters only and hence, researching various petrophysical properties, needed to account for the thermal-hydraulic-mechanical behavior of selected rock types or reservoir settings, can be very laborious. Since for deep geothermal energy in central Europe, the majority of the geothermal potential or resource is assigned to the crystalline basement, a comprehensive database of petrophysical properties comprising rock densities, porosity, rock matrix permeability, thermal properties (thermal conductivity and diffusivity, specific heat capacity) as well as rock mechanical properties as compressive and shear wave velocities, unconfined compressive strength, Young’s modulus, Poisson’s ratio, tensile strength and triaxial shear strength was compiled by measurements conducted at the HydroThermikum lab facilities of the Technical University of Darmstadt. Analyzed samples were mostly derived from abandoned or active quarries and natural or artificial outcrops such as road cuts, river banks or steep hill slopes. Furthermore, samples of the cored deep wells Worms 3 (samples from 2175–2195 m), Stockstadt 33R (samples from 2245–2267 m), Weiterstadt 1 (samples from 2502–2504 m), Tiefbohrung Groß-Umstadt/Heubach, B/89–B02 and the cored shallow wells Forschungsbohrung Messel GA 1 and 2 as well as GWM17 Zwingenberg, GWM1A Zwingenberg, Langenthal BK2/05, EWS267/1 Heubach, and archive samples of the Institut für Steinkonservierung e.V. in Mainz originating from a comprehensive large scale sampling campaign in 2007 were investigated. The database (Weinert et al. 2020b, https://doi.org/10.25534/tudatalib-278) aims to provide easily accessible petrophysical properties of the Mid-German Crystalline High, measured on 224 locations in Bavaria, Hesse, Rhineland-Palatinate and Thuringia and comprising 26,951 single data points. Each data point is addressed with the respective metadata such as sample identifier, sampling location, petrography and if applicable stratigraphy and sampling depth (in case of well samples).

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Petrophysical Properties of an Iraqi Carbonate Reservoir Using Well Log Evaluation

Iraqi Journal of Chemical and Petroleum Engineering ◽

10.31699/ijcpe.2020.1.8 ◽

2020 ◽

Vol 21 (1) ◽

pp. 53-59

Author(s):

Sarah S. Zughar ◽

Ahmad A. Ramadhan ◽

Ahmed K. Jaber

Keyword(s):

Water Saturation ◽

Carbonate Reservoir ◽

Petrophysical Properties ◽

Indicator Method ◽

Rock Types ◽

Fluid Saturation ◽

Unit Thickness ◽

Average Formation ◽

Porous Zone ◽

Mud Filtration

This research was aimed to determine the petrophysical properties (porosity, permeability and fluid saturation) of a reservoir. Petrophysical properties of the Shuiaba Formation at Y field are determined from the interpretation of open hole log data of six wells. Depending on these properties, it is possible to divide the Shuiaba Formation which has thickness of a proximately 180-195m, into three lithological units: A is upper unit (thickness about 8 to 15 m) involving of moderately dolomitized limestones; B is a middle unit (thickness about 52 to 56 m) which is composed of dolomitic limestone, and C is lower unit ( >110 m thick) which consists of shale-rich and dolomitic limestones. The results showed that the average formation water resistivity for the formation (Rw = 0.021), the average resistivity of the mud filtration (Rmf = 0.57), and the Archie parameters determined by the picket plot method, where m value equal to 1.94, n value equal to 2 and a value equal to 1. Porosity values and water saturation Sw were calculated along with the depth of the composition using IP V3.5 software. The interpretation of the computer process (CPI) showed that the better porous zone holds the highest amount of hydrocarbons in the second zone. From the flow zone indicator method, there are four rock types in the studied reservoir.

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Water saturation modeling using modified J-function constrained by rock typing method in bioclastic limestone

Oil & Gas Science and Technology – Revue d’IFP Energies nouvelles ◽

10.2516/ogst/2020059 ◽

2020 ◽

Vol 75 ◽

pp. 66

Author(s):

Ya Deng ◽

Rui Guo ◽

Zhongyuan Tian ◽

Limin Zhao ◽

Dandan Hu ◽

...

Keyword(s):

Water Saturation ◽

Free Water ◽

Petrophysical Properties ◽

Saturation Model ◽

Typing Method ◽

Thin Sections ◽

Rock Types ◽

Rock Typing ◽

Wireline Logs ◽

Mercury Injection Capillary Pressure

Combining both geological and petrophysical properties, a reliable rock typing scheme can be achieved. Two steps are included in rock typing. Step 1: rocks are classified into lithofacies based on core observations and thin sections; Step 2: lithofacies are further subdivided into rock types according to petrophysical properties such as MICP (Mercury Injection Capillary Pressure) and K-Phi relationships. By correlating rock types to electrofacies (clusters of log data), we can group the target formation into 12 rock types. Then it is possible to predict the distributions of rock types laterally and vertically using wireline logs. To avoid the defect of the classical J-function saturation model that includes permeability which is quite uncertain especially in carbonate rocks, a modified J-function was created and used in the paper. In this function, water saturation is simply expressed as a function of height above free water level for a specific rock type. Different water saturation models are established for different rock types. Finally, the water saturation model has been successfully constructed and verified to be appropriate.

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Database of petrophysical properties of the Mid-German Crystalline Rise

Earth System Science Data ◽

10.5194/essd-13-1441-2021 ◽

2021 ◽

Vol 13 (3) ◽

pp. 1441-1459

Author(s):

Sebastian Weinert ◽

Kristian Bär ◽

Ingo Sass

Keyword(s):

Large Scale ◽

Reservoir Characterization ◽

Numerical Models ◽

Sampling Location ◽

Petrophysical Properties ◽

Laboratory Equipment ◽

Rock Types ◽

Matrix Permeability ◽

Area Of Interest ◽

Sampling Campaign

Abstract. Petrophysical properties are a key element for reservoir characterization but also for interpreting the results of various geophysical exploration methods or geophysical well logs. Furthermore, petrophysical properties are commonly used to populate numerical models and are often critically governing the model results. Despite the common need for detailed petrophysical properties, data are still very scarce and often not available for the area of interest. Furthermore, both the online research for published property measurements or compilations, as well as dedicated measurement campaigns of the selected properties, which require comprehensive laboratory equipment, can be very time-consuming and costly. To date, most published research results are often focused on a limited selection of parameters only, and hence researching various petrophysical properties, needed to account for the thermal–hydraulic–mechanical behaviour of selected rock types or reservoir settings, can be very laborious. Since for deep geothermal energy in central Europe, the majority of the geothermal potential or resource is assigned to the crystalline basement, a comprehensive database of petrophysical properties comprising rock densities, porosity, rock matrix permeability, thermal properties (thermal conductivity and diffusivity, specific heat capacity) as well as rock mechanical properties as compressional and shear wave velocities, unconfined compressive strength, Young's modulus, Poisson's ratio, tensile strength and triaxial shear strength was compiled from measurements conducted at the HydroThermikum lab facilities of the Technical University of Darmstadt. Analysed samples were mostly derived from abandoned or active quarries and natural or artificial outcrops such as road cuts, riverbanks or steep hillslopes. Furthermore, samples of the cored deep wells Worms 3 (samples from 2175–2195 m), Stockstadt 33R (samples from 2245–2267 m), Weiterstadt 1 (samples from 2502–2504 m), Tiefbohrung Groß-Umstadt/Heubach, B/89–B02 and the cored shallow wells (Forschungsbohrung Messel GA 1 and 2) as well as GWM17 Zwingenberg, GWM1A Zwingenberg, Langenthal BK2/05, EWS267/1 Heubach, and archive samples of the Institut für Steinkonservierung e.V. in Mainz originating from a comprehensive large-scale sampling campaign in 2007 were investigated. The database (Weinert et al., 2020b; https://doi.org/10.25534/tudatalib-278) aims to provide easily accessible petrophysical properties of the Mid-German Crystalline Rise, measured on 224 locations in Bavaria, Hessen, Rhineland-Palatinate and Thuringia and comprising 26 951 single data points. Each data point is addressed with the respective metadata such as the sample identifier, sampling location, petrography and, if applicable, stratigraphy and sampling depth (in the case of well samples).

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An Aquifer Model for Fissured Reservoirs

Society of Petroleum Engineers Journal ◽

10.2118/4434-pa ◽

1975 ◽

Vol 15 (05) ◽

pp. 385-398 ◽

Cited By ~ 31

Author(s):

P.J. Clossman

Keyword(s):

Pressure Distribution ◽

Performance Studies ◽

Rock Type ◽

Porous Matrix ◽

Carbonate Reservoirs ◽

Basic Rock ◽

Petrophysical Properties ◽

Reservoir Performance ◽

Rock Types ◽

The Matrix

Abstract A model has been developed for describing aquifer influx in a fissured reservoir. This model includes petrophysical properties of good and poor rock, as petrophysical properties of good and poor rock, as well as fissure parameters. For the applications considered thus far, it has been found that flow in the fissures dominates the aquifer performance and that rock properties and spacing between fissures are of lesser importance. For a given aquifer, the fissure permeability and fissure volume fraction appear to be important parameters, as are rock permeability and porosity in cases of a high permeability and porosity in cases of a high percentage of poor rock. percentage of poor rock Introduction The use of material balance has been well established in analysis of reservoir performance. For water drive reservoirs, it is usually desirable to have a functional description of aquifer behavior. Such a description is provided by the functions obtained by van Everdingen and Hurst for homogeneous and isotropic reservoirs. This method uses one set of values of permeability, porosity, and compressibility, and usually requires some history matching or curve fitting for determining the best values. Functions analogous to those of van Everdingen and Hurst also would be useful in reservoir performance studies of fissured reservoirs. Any performance studies of fissured reservoirs. Any attempt to formulate a realistic model for such systems, however, will usually confront the problem of insufficient knowledge of aquifer properties. There usually will be a comparatively large number of degrees of freedom corresponding to parameters introduced into the theory. Nevertheless, such a model should provide insight into the relative importance of certain variables. It may also serve as a framework in which more accurate information, if eventually obtained, could be used. Pressure behavior was used to study fissured reservoir properties by Pollard, who characterized the pressure buildup by three exponentials. These exponentials corresponded to a skin near the well, transient behavior in the fracture system, and transient flow of fluid from matrix to fissures. A characteristics feature of fissured reservoir systems and the reservoir fast fluid pressure response of the fissure system compared with response in the porous matrix. A model that treats this aspect porous matrix. A model that treats this aspect appropriately as proposed by Warren and Root, who assumed that flow of fluid from matrix to fissures could be treated as quasi-steady state. The problem of transient pressure distribution within an actual block of the reservoir was thereby circumvented. This model was further studied by Odeh. Kazemi replaced the network of fractures with an equivalent set of horizontal fractures and solved numerically for pressure distribution in fissures and matrix. Because the dimensionless time scale based on fracture properties and well radius was long, Warren and Root and Odeh were able to use the long-time solution for the constant terminal rate case of pressure behavior in an oil reservoir. In the present instance, the inner aquifer radius may be quite large, so that we must consider smaller dimensionless times, and will require a general solution. The actual times of interest, however, will not be so small as to invalidate the model. This model is being considered for use in fissured carbonate reservoirs where two basic rock types, defined in terms of porosity, are sometimes specified. In such cases, the rock permeabilities usually are very much smaller than the fissure permeability, The matrix can be considered as permeability, The matrix can be considered as being made up of good and poor rock. Wide variations in rock type are often encountered in carbonate reservoirs. The designations of good and "poor" are largely arbitrary. A typical example would be: good porosity greater than 12 percent, and poor-porosity 2 to 12 percent, with the remainder poor-porosity 2 to 12 percent, with the remainder of the rock nonproductive. In some cases, however, it may be sufficient to specify only one rock type. In studying the constant terminal pressure case it is desirable to reformulate the fissured reservoir model to include the additional features of change, boundary conditions and two basic rock types. SPEJ P. 385

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Correlation of Pore Structure and Permeability by SEM-Image Analysis

Proceedings, annual meeting, Electron Microscopy Society of America ◽

10.1017/s0424820100180896 ◽

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.

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