How Porosity and Permeability Vary Spatially With Grain Size, Sorting, Cement Volume, and Mineral Dissolution In Fluvial Triassic Sandstones: The Value of Geostatistics and Local Regression

Although it is well known that sandstone porosity and permeability are controlled by a range of parameters such as grain size and sorting, amount, type, and location of diagenetic cements, extent and type of compaction, and the generation of intergranular and intragranular secondary porosity, it is less constrained how these controlling parameters link up in rock volumes (within and between beds) and how they spatially interact to determine porosity and permeability. To address these unknowns, this study examined Triassic fluvial sandstone outcrops from the UK using field logging, probe permeametry of 200 points, and sampling at 100 points on a gridded rock surface. These field observations were supplemented by laser particle-size analysis, thin-section point-count analysis of primary and diagenetic mineralogy, quantitiative XRD mineral analysis, and SEM/EDAX analysis of all 100 samples. These data were analyzed using global regression, variography, kriging, conditional simulation, and geographically weighted regression to examine the spatial relationships between porosity and permeability and their potential controls. The results of bivariate analysis (global regression) of the entire outcrop dataset indicate only a weak correlation between both permeability porosity and their diagenetic and depositional controls and provide very limited information on the role of primary textural structures such as grain size and sorting. Subdividing the dataset further by bedding unit revealed details of more local controls on porosity and permeability. An alternative geostatistical approach combined with a local modelling technique (geographically weighted regression; GWR) subsequently was used to examine the spatial variability of porosity and permeability and their controls. The use of GWR does not require prior knowledge of divisions between bedding units, but the results from GWR broadly concur with results of regression analysis by bedding unit and provide much greater clarity of how porosity and permeability and their controls vary laterally and vertically. The close relationship between depositional lithofacies in each bed, diagenesis, and permeability, porosity demonstrates that each influences the other, and in turn how understanding of reservoir properties is enhanced by integration of paleoenvironmental reconstruction, stratigraphy, mineralogy, and geostatistics.

Using geostatistical Bayesian Updating to integrate airborne radiometrics and soil geochemistry to improve mapping for mineral exploration

Mineral exploration programmes around the world use data from remote sensing, geophysics and direct sampling. On a regional scale, the combination of airborne geophysics and ground-based geochemical sampling can aid geological mapping and economic minerals exploration. The fact that airborne geophysical and traditional soil-sampling data are generated at different spatial resolutions means that they are not immediately comparable due to their different sampling density. Several geostatistical techniques, including indicator cokriging and collocated cokriging, can be used to integrate different types of data into a geostatistical model. With increasing numbers of variables the inference of the cross-covariance model required for cokriging can be demanding in terms of effort and computational time. In this paper a Gaussian-based Bayesian updating approach is applied to integrate airborne radiometric data and ground-sampled geochemical soil data to maximise information generated from the soil survey, to enable more accurate geological interpretation for the exploration and development of natural resources. The Bayesian updating technique decomposes the collocated estimate into a production of two models: prior and likelihood models. The prior model is built from primary information and the likelihood model is built from secondary information. The prior model is then updated with the likelihood model to build the final model. The approach allows multiple secondary variables to be simultaneously integrated into the mapping of the primary variable. The Bayesian updating approach is demonstrated using a case study from Northern Ireland where the history of mineral prospecting for precious and base metals dates from the 18th century. Vein-hosted, strata-bound and volcanogenic occurrences of mineralisation are found. The geostatistical technique was used to improve the resolution of soil geochemistry, collected one sample per 2 km2, by integrating more closely measured airborne geophysical data from the GSNI Tellus Survey, measured over a footprint of 65 x 200 m. The directly measured geochemistry data were considered as primary data in the Bayesian approach and the airborne radiometric data were used as secondary data. The approach produced more detailed updated maps and in particular maximized information on mapped estimates of zinc, copper and lead. Greater delineation of an elongated northwest/southeast trending zone in the updated maps strengthened the potential to investigate stratabound base metal deposits.

Organo-mineral complexation alters carbon and nitrogen cycling in stream microbial assemblages

Inland waters are of global biogeochemical importance receiving carbon inputs of ~ 4.8 Pg C y^-1. Of this 12 % is buried, 18 % transported to the oceans, and 70 % supports aquatic secondary production. However, the mechanisms that determine the fate of organic matter (OM) in these systems are poorly defined. One important aspect is the formation of organo-mineral complexes in aquatic systems and their potential as a route for OM transport and burial vs. their use potential as organic carbon (C) and nitrogen (N) sources. Organo-mineral particles form by sorption of dissolved OM to freshly eroded mineral surfaces and may contribute to ecosystem-scale particulate OM fluxes. We tested the availability of mineral-sorbed OM as a C & N source for streamwater microbial assemblages and streambed biofilms. Organo-mineral particles were constructed in vitro by sorption of ¹³C:¹⁵N-labelled amino acids to hydrated kaolin particles, and microbial degradation of these particles compared with equivalent doses of ¹³C:¹⁵N-labelled free amino acids. Experiments were conducted in 120 ml mesocosms over 7 days using biofilms and streamwater sampled from the Oberer Seebach stream (Austria), tracing assimilation and mineralization of ¹³C and ¹⁵N labels from mineral-sorbed and dissolved amino acids.Here we present data on the effects of organo-mineral sorption upon amino acid mineralization and its C:N stoichiometry. Organo-mineral sorption had a significant effect upon microbial activity, restricting C and N mineralization by both the biofilm and streamwater treatments. Distinct differences in community response were observed, with both dissolved and mineral-stabilized amino acids playing an enhanced role in the metabolism of the streamwater microbial community. Mineral-sorption of amino acids differentially affected C & N mineralization and reduced the C:N ratio of the dissolved amino acid pool. The present study demonstrates that organo-mineral complexes restrict microbial degradation of OM and may, consequently, alter the carbon and nitrogen cycling dynamics within aquatic ecosystems.

Compositional Data Analysis in Forensic Geoscience

Statistics are regularly used to make some form of comparison between trace evidence or deploy the exclusionary principle (Morgan and Bull, 2007) in forensic investigations. Trace evidence are routinely the results of particle size, chemical or modal analyses and as such constitute compositional data. The issue is that compositional data including percentages, parts per million etc. only carry relative information. This may be problematic where a comparison of percentages and other constraint/closed data is deemed a statistically valid and appropriate way to present trace evidence in a court of law. Notwithstanding an awareness of the existence of the constant sum problem since the seminal works of Pearson (1896) and Chayes (1960) and the introduction of the application of log-ratio techniques (Aitchison, 1986; Pawlowsky-Glahn and Egozcue, 2001; Pawlowsky-Glahn and Buccianti, 2011; Tolosana-Delgado and van den Boogaart, 2013) the problem that a constant sum destroys the potential independence of variances and covariances required for correlation regression analysis and empirical multivariate methods (principal component analysis, cluster analysis, discriminant analysis, canonical correlation) is all too often not acknowledged in the statistical treatment of trace evidence. Yet the need for a robust treatment of forensic trace evidence analyses is obvious. This research examines the issues and potential pitfalls for forensic investigators if the constant sum constraint is ignored in the analysis and presentation of forensic trace evidence. Forensic case studies involving particle size and mineral analyses as trace evidence are used to demonstrate the use of a compositional data approach using a centred log-ratio (clr) transformation and multivariate statistical analyses.

Do spectral gamma ray data really reflect humid-arid palaeoclimates? A test from the Palaeogene Interbasaltic weathered horizons at the Giant’s Causeway, N.Ireland

Since 1999, the rapid, inexpensive and non-destructive use of Th/K and Th/U ratios from spectral gamma ray measurements have been used as a proxy for changes in palaeo-hinterland weathering. This model is tested here by analysis of in situ palaeoweathering horizons where clay mineral contents are well-known. A residual palaeoweathered horizon of Palaeogene laterite (developed on basalt) has been logged at 14 locations across N. Ireland using spectral gamma ray detectors. The results are compared to published elemental and mineralogical data. While the model of K and U loss during the early stages of weathering to smectite and kaolinite is supported, the formation (during progressively more advanced weathering) of gibbsite and iron oxides has reversed the predicted pattern and caused U and Th retention in the weathering profile. The severity (duration, humidity) of weathering and palaeoweathering may be estimated using Th/K ratios as a proxy. The use of Th/U ratios is more problematic should detrital gibbsite (or similar clays) or iron oxides be detected. Mineralogical analysis is needed in order to evaluate the hosts for K, U and Th: nonetheless, the spectral gamma ray machine offers a real-time, inexpensive and effective tool for the preliminary or conjunctive assessment of degrees of weathering or palaeoweathering.