Geology topics

Jan Harff

Publications and source records attributed to Jan Harff.

5 recordsLinked to original sources

USGS2011

Late quaternary climate variations reflected in Baltic Sea sediments

Late Pleistocene to Holocene climate change of the Atlantic and the northern European realm is reflected by the facies of sediments in the Baltic Sea. The sedimentary sequence have been subdivided into zones reflecting the main postglacial stages of the Baltic Sea basin development according to sediment echosounder profiling and investigating sediment cores from the central Baltic. The changes in the environment of Baltic Sea bottom water is displayed by sediment physical, geochemical, and microfossil proxies. These proxies mark the main shift in the sedimentary facies of the Baltic Basin at 8.14 cal. years BP, from a freshwater to a brackish/marine environment due to the Littorina transgression of marine water masses from the North Sea. The downhole physical facies variation from the Eastern Gotland can be correlated basinwide. Thickness maps of the freshwater and the brackish sediments ascribe the general change in the hydrographic circulation from a coast-to-basin to a basin-to-basin system along with the Littorina transgression. Variations in the salinity of the brackish Littorina Baltic Basin are attributed to changes in the North Atlantic Oscillation (NAO) ascribing the wind forces driving the inflow of marine water into the Baltic Basin. Time series analysis of facies variation reveals distinct periodicities of 900 and 1,500 years. These periods can be compared with data from North Atlantic marine sediments and Greenland ice cores identifying global climate change effects in Baltic Basin sediments.

Book chapter↗

USGS1999

Subdivision of Holocene Baltic sea sediments by their physical properties [Gliederung holozaner ostseesedimente nach physikalischen Eigenschaften]

The Holocene sediment sequence of a core taken within the centre of the Eastern Gotland Basin was subdivided into 12 lithostratigraphic units based on MSCL-data (sound velocity, wet bulk density, magnetic susceptibility) using a multivariate classification method. The lower 6 units embrace the sediments until the Litorina transgression, and the upper 6 units subdivide the brackish-marine Litorina- and post-Litorina sediments. The upper lithostratigraphic units reflect a change of anoxic (laminated) and oxic (non-laminated) sediments. By application of a numerical stratigraphic correlation method the zonation was extended laterally onto contiguous sediment cores within the central basin. Consequently the change of anoxic and oxic sediments can be used for a general lithostratigraphic subdivision of sediments of the Gotland Basin. A quantitative criterion based on the sediment-physical lithofacies is added to existing subdivisions of the Holocene in the Baltic Sea.

Petermanns Geographische Mitteilungen↗

USGS1998

Singularity and Nonnormality in the Classification of Compositional Data

Geologists may want to classify compositional data and express the classification as a map. Regionalized classification is a tool that can be used for this purpose, but it incorporates discriminant analysis, which requires the computation and inversion of a covariance matrix. Covariance matrices of compositional data always will be singular (noninvertible) because of the unit-sum constraint. Fortunately, discriminant analyses can be calculated using a pseudo-inverse of the singular covariance matrix; this is done automatically by some statistical packages such as SAS. Granulometric data from the Darss Sill region of the Baltic Sea is used to explore how the pseudo-inversion procedure influences discriminant analysis results, comparing the algorithm used by SAS to the more conventional Moore-Penrose algorithm. Logratio transforms have been recommended to overcome problems associated with analysis of compositional data, including singularity. A regionalized classification of the Darss Sill data after logratio transformation is different only slightly from one based on raw granulometric data, suggesting that closure problems do not influence severely regionalized classification of compositional data.

Mathematical Geology↗

USGS1992

Quantitative assessment of mineral resources with an application to petroleum geology

The probability of occurrence of natural resources, such as petroleum deposits, can be assessed by a combination of multivariate statistical and geostatistical techniques. The area of study is partitioned into regions that are as homogeneous as possible internally while simultaneously as distinct as possible. Fisher's discriminant criterion is used to select geological variables that best distinguish productive from nonproductive localities, based on a sample of previously drilled exploratory wells. On the basis of these geological variables, each wildcat well is assigned to the production class (dry or producer in the two-class case) for which the Mahalanobis' distance from the observation to the class centroid is a minimum. Universal kriging is used to interpolate values of the Mahalanobis' distances to all locations not yet drilled. The probability that an undrilled locality belongs to the productive class can be found, using the kriging estimation variances to assess the probability of misclassification. Finally, Bayes' relationship can be used to determine the probability that an undrilled location will be a discovery, regardless of the production class in which it is placed. The method is illustrated with a study of oil prospects in the Lansing/Kansas City interval of western Kansas, using geological variables derived from well logs. ?? 1992 Oxford University Press.

Nonrenewable Resources↗

USGS1990

Regionalization in geology by multivariate classification

The concept of multivariate classification of "geological objects" can be combined with the concept of regionalized variables to yield a procedure for typification of geological objects, such as rock units, well records, or samples. Numerical classification is followed by subdivision of the area of investigation, and culminates in a regionalization or mapping of the classification onto the plane. Regions are subdivisions of the map area which are spatially contiguous and relatively homogeneous in their geological properties. The probability of correct classification of each point within a region as being part of that region can be assessed in terms of Bayesian probability as a space-dependent function. The procedure is applied to subsurface data from western Kansas. The geologic properties used are quantitative variables, and relationships are expressed by Mahalanobis' distances. These functions could be replaced by other metrics if qualitative or binary data derived from geological descriptions or appraisals were included in the analysis. ?? 1990 International Association for Mathematical Geology.

Mathematical Geology↗