Spatial variability in petrophysical properties in Upper Maastrichtian chalk outcrops at Stevns Klint, Denmark

The spatial variability of porosity and permeability was determined for a section in the uppermost Maastrichtian chalk exposed in the Sigerslev quarry at Stevns Klint. The aims were threefold: (1) to quantify the spatial variability pattern and its link to geology by applying systematic variogram analysis procedure, (2) to detect potential cyclicity in the petrophysical properties in this pure and overtly homogeneous chalk, and (3) to compare the section with chalk reservoirs in the North Sea in order to asses to what extent this onshore sequence has a potential as an analogue of the offshore, more deeply buried chalk reservoirs. The interval is of comparable stratigraphic age to the uppermost reservoir zones in the Tor Formation of the North Sea chalk reservoirs. The variability and spatial correlation of porosity and permeability in both horizontal and vertical directions are interpreted in a geological context and show indications of small-scale heterogeneity at 15–25 cm scale, but the clear cyclic layering described from other chalk deposits is not recognised at this locality. The investigated outcrop is not a close analogue to North Sea reservoir chalk, but some aspects are common including basic material properties, porosity/permeability trends and the variability pattern. The outcrop has a potential as analogue for some of the onshore subsurface chalk successions at shallow burial depth that form important aquifers.     

Effects of iron black varnish on petrophysical properties of building sandstone

In zones washed by rain (façades, pinnacles, pilasters), fine siliceous sandstones are covered by a black varnish, which gives a dirty appearance to monuments. In composition, structure and areas covered by it, it differs from the usual black gypsum crust. Experiments carried out on blocks covered by black varnish show the modifications due to their growth. Results show that despite their low thickness and the coherence of the stone below, the accumulation of hydrophobic matters and the wetting-drying cycles modify the transfer properties of sandstones several centimeters below the surface. Thus, although sandstones seem to be protected by the black varnish, in the long run, a flake detachment process, in the areas covered by it, affects them. Therefore, damage to sandstones by black varnish can be explained by the fact that a wetting and drying cycle modifies the pore network.     

Physical properties and petrologic description of rock samples from an IOCG mineralized area in the northern Fennoscandian Shield, Sweden

The Tjårrojåkka Fe–Cu-prospect in northern Sweden is considered an example of a Fe-oxide Cu–Au (IOCG) deposit and is hosted in metamorphosed Paleoproterozoic volcanic and intrusive rocks. Rock samples from 24 outcrops were collected for petrophysical analysis (magnetic susceptibility, remanent magnetization, variation of magnetic susceptibility with temperature, Curie temperature and density). The major Cu-prospect in the area has been studied by magnetic and electron microprobe analyses of four selected rock samples. The samples are from an exploration well that intersects the main Cu-mineralized body.The magnetic analyses show that magnetite is the dominant magnetic mineral, while hematite and other Fe-minerals are present in minor amounts. The electron microprobe observations confirm the presence of magnetite and further indicate that hematite is an alteration product of magnetite. Moreover, microprobe observations indicate that Fe-sulfides are present in negligible amounts in the samples from the Tjårrojåkka area. The strong spatial relationship of Cu-minerals (e.g., chalcopyrite) and the oxidation of magnetite to hematite suggest that the presence of rocks with low magnetic susceptibility in areas dominated by high susceptibility rocks may be a signal of related Cu-prospects.     

How does water near clay mineral surfaces influence the rock physics of shales?

Clays and clay‐bearing rocks like shale are extremely water sensitive. This is partly due to the interaction between water and mineral surfaces, strengthened by the presence of nanometer‐size pores and related large specific surface areas. Molecular‐scale numerical simulations, using a discrete‐element model, show that shear rigidity can be associated with structurally ordered (bound or adsorbed) water near charged surfaces. Building on these and other molecular dynamics simulations plus nanoscale experiments from the literature, the water monolayer adjacent to hydrophilic solid surfaces appears to be characterised by shear stiffness and/or enhanced viscosity. In both cases, elastic wave propagation will be affected by the bound or adsorbed water. Using a simple rock physics model, bound water properties were adjusted to match laboratory measured P‐ and S‐wave velocities on pure water‐saturated kaolinite and smectite. To fit the measured stress sensitivity, particularly for kaolinite, the contribution from solid‐grain contact stiffness needs to be added. The model predicts, particularly for S‐waves, that viscoelastic bound water could be a source of dispersion in clay and clay‐rich rocks. The bound‐water‐based rock physics model is found to represent a lower bound to laboratory‐measured velocities obtained with shales of different mineralogy and porosity levels.     

Petrophysics and mineral exploration: a workflow for data analysis and a new interpretation framework

As mineral exploration seeks deeper targets, there will be a greater reliance on geophysical data and a better understanding of the geological meaning of the responses will be required, and this must be achieved with less geological control from drilling. Also, exploring based on the mineral system concept requires particular understanding of geophysical responses associated with altered rocks. Where petrophysical datasets of adequate sample size and measurement quality are available, physical properties show complex variations, reflecting the combined effects of various geological processes. Large datasets, analysed as populations, are required to understand the variations. We recommend the display of petrophysical data as frequency histograms because the nature of the data distribution is easily seen with this form of display. A petrophysical dataset commonly contains a combination of overlapping sub-populations, influenced by different geological factors. To understand the geological controls on physical properties in hard rock environments, it is necessary to analyse the petrophysical data not only in terms of the properties of different rock types. It is also necessary to consider the effects of processes such as alteration, weathering, metamorphism and strain, and variables such as porosity and stratigraphy. To address this complexity requires that much more supporting geological information be acquired than in current practice. The widespread availability of field portable instruments means quantitative geochemical and mineralogical data can now be readily acquired, making it unnecessary to rely primarily on categorical rock classification schemes. The petrophysical data can be combined with geochemical, petrological and mineralogical data to derive explanations for observed physical property variations based not only on rigorous rock classification methods, but also in combination with quantitative estimates of alteration and weathering. To understand how geological processes will affect different physical properties, it is useful to define three end-member forms of behaviour. Bulk behaviour depends on the physical properties of the dominant mineral components. Density and, to a lesser extent, seismic velocity show such behaviour. Grain and texture behaviour occur when minor components of the rock are the dominate controls on its physical properties. Grain size and shape control grain properties, and for texture properties the relative positions of these grains are also important. Magnetic and electrical properties behave in this fashion. Thinking in terms of how geological processes change the key characteristics of the major and minor mineralogical components allows the resulting changes in physical properties to be understood and anticipated.     

Energy of acoustic signals in a borehole

In the present article, the dependencies of the acoustic signal total energy and the energies of the wave packets of different types of the waves on the elastic parameters and permeability of rocks have been studied. We have considered traditional logging tools containing acoustical monopole source. Calculations were performed in a frequency range of dozens of kilohertz, typical for acoustic well logging. It was shown that in a typical high-velocity formation (v_s > v_f, where v_s and v_f are the velocities of the shear wave in the rock and of the compressional wave in the borehole fluid, respectively), the pseudo-Rayleigh waves, whose elastic properties depend mainly on the shear modulus of the rock, contributed significant energy to the total signal energy in the borehole. The energies of different wave packets depend on the permeability in different ways. The greatest sensitivity to permeability change has been shown by the acoustic signal total energy and the energy of the low-velocity part of the pseudo-Rayleigh wave packet. The theoretical analysis was illustrated by real sonic log data.     

The validity of generic trends on multiple scales in rock-physical and rock-mechanical properties of the Whitby Mudstone,United Kingdom

Finding generic trends in mechanical and physical rock properties will help to make predictions of the rock-mechanical behaviour of shales. Understanding the rock-mechanical behaviour of shales is important for the successful development of unconventional hydrocarbon reservoirs.This paper presents the effect of heterogeneities in mineralogy and petrophysical properties on the validity of generic trends on multiple scales in rock-mechanical and rock-physical properties of the Whitby Mudstone. Rock-mechanical laboratory experiments have been performed on Whitby Mudstone samples from multiple outcrops within five kilometres laterally in order to investigate the heterogeneity and possible trends on an outcrop scale. Unconfined compression tests and acoustic measurements have been conducted to obtain the rock-mechanical properties, including rock strength, Young's modulus, Poisson's ratio, and velocity anisotropy. The rock-physical properties, including mineralogy, porosity, and matrix density, were measured using X-ray fluorescence and helium pycnometry. Various methodologies have been applied to the resultant data in order to derive different brittleness indices.Significant heterogeneity in rock-mechanical and rock-physical properties is present on an outcrop scale. There is no obvious correlation between mineral content and rock-mechanical properties on an outcrop scale in the Whitby Mudstone. Comparison with shales from different basins show, however, correlations between composition and elastic properties. The presence of significant heterogeneities on an outcrop scale and between shales from different basins make it difficult to find generic trends in rock-physical and rock-mechanical properties.     

The electrical conductivity of Posidonia black shales — from magnetotelluric exploration to rock samples

We carried out a magnetotelluric field campaign in the South–East Lower Saxony Basin, Germany, with the main goal of testing this method for imaging regional Posidonia black shale sediments. Two‐dimensional inversion results of the magnetotelluric data show a series of conductive structures correlating with brine‐saturated sediments but also with deeper, anthracitic Westphalian/Namurian coals. None of these structures can be directly related with the Posidonia black shale, which appears to be generally resistive and therefore difficult to resolve with the magnetotelluric method. This assumption is supported by measurements of electrical resistivity on a set of Posidonia shale samples from the Hils syncline in the Lower Saxony basin. These rock samples were collected in shallow boreholes and show immature (0.53% Ro), oil (0.88% Ro), and gas (1.45% Ro) window thermal maturities. None of the black shale samples showed low electrical resistivity, particularly those with oil window maturity show resistivity exceeding 10⁴ Ωm. Moreover, we could not observe a direct correlation between maturity and electrical resistivity; the Harderode samples showed the highest resistivity, whereas the Haddessen samples showed the lowest. A similar trend has been seen for coals in different states of thermal maturation. Saturation of the samples with distilled and saline water solutions led to decreasing electrical resistivity. Moreover, a positive correlation of electrical resistivity with porosity is observed for the Wickensen and Harderode samples, which suggests that the electrical resistivity of the Posidonia black shale is mainly controlled by porosity.     

Joint parameter estimation from magnetic resonance and vertical electric soundings using a multi‐objective genetic algorithm

Magnetic resonance sounding (MRS) has increasingly become an important method in hydrogeophysics because it allows for estimations of essential hydraulic properties such as porosity and hydraulic conductivity. A resistivity model is required for magnetic resonance sounding modelling and inversion. Therefore, joint interpretation or inversion is favourable to reduce the ambiguities that arise in separate magnetic resonance sounding and vertical electrical sounding (VES) inversions. A new method is suggested for the joint inversion of magnetic resonance sounding and vertical electrical sounding data. A one‐dimensional blocky model with varying layer thicknesses is used for the subsurface discretization. Instead of conventional derivative‐based inversion schemes that are strongly dependent on initial models, a global multi‐objective optimization scheme (a genetic algorithm [GA] in this case) is preferred to examine a set of possible solutions in a predefined search space. Multi‐objective joint optimization avoids the domination of one objective over the other without applying a weighting scheme. The outcome is a group of non‐dominated optimal solutions referred to as the Pareto‐optimal set. Tests conducted using synthetic data show that the multi‐objective joint optimization approximates the joint model parameters within the experimental error level and illustrates the range of trade‐off solutions, which is useful for understanding the consistency and conflicts between two models and objectives. Overall, the Levenberg‐Marquardt inversion of field data measured during a survey on a North Sea island presents similar solutions. However, the multi‐objective genetic algorithm method presents an efficient method for exploring the search space by producing a set of non‐dominated solutions. Borehole data were used to provide a verification of the inversion outcomes and indicate that the suggested genetic algorithm method is complementary for derivative‐based inversions.     

Seismic driven probabilistic classification of reservoir facies for static reservoir modelling: a case history in the Barents Sea

In this paper we present a case history of seismic reservoir characterization where we estimate the probability of facies from seismic data and simulate a set of reservoir models honouring seismically‐derived probabilistic information. In appraisal and development phases, seismic data have a key role in reservoir characterization and static reservoir modelling, as in most of the cases seismic data are the only information available far away from the wells. However seismic data do not provide any direct measurements of reservoir properties, which have then to be estimated as a solution of a joint inverse problem. For this reason, we show the application of a complete workflow for static reservoir modelling where seismic data are integrated to derive probability volumes of facies and reservoir properties to condition reservoir geostatistical simulations. The studied case is a clastic reservoir in the Barents Sea, where a complete data set of well logs from five wells and a set of partial‐stacked seismic data are available. The multi‐property workflow is based on seismic inversion, petrophysics and rock physics modelling. In particular, log‐facies are defined on the basis of sedimentological information, petrophysical properties and also their elastic response. The link between petrophysical and elastic attributes is preserved by introducing a rock‐physics model in the inversion methodology. Finally, the uncertainty in the reservoir model is represented by multiple geostatistical realizations. The main result of this workflow is a set of facies realizations and associated rock properties that honour, within a fixed tolerance, seismic and well log data and assess the uncertainty associated with reservoir modelling.