Markov chains and entropy tests in genetic-based lithofacies analysis of deep-water clastic depositional systems

Abstract

Abstract:The aim of this study was to examine the relationship between structural elements and the so-called genetic lithofacies in a clastic deep-water depositional system. Process-sedimentology has recently been gaining importance in the characterization of these systems. This way the recognized facies attributes can be associated with the depositional processes establishing the genetic lithofacies. In this paper this approach was presented through a case study of a Tertiary deep-water sequence of the Pannonian-basin. Of course it was necessary to interpret the stratigraphy of the sequences in terms of "general" sedimentology, focusing on the structural elements. For this purpose, well-logs and standard deep-water models were applied. The cyclicity of sedimentary sequences can be easily revealed by using Markov chains. Though Markov chain analysis has broad application in mainly fluvial depositional environments, its utilization is uncommon in deepwater systems. In this context genetic lithofacies was determined and analysed by embedded Markov chains. The randomness in the presence of a lithofacies within a cycle was estimated by entropy tests (entropy after depositional, before depositional, for the whole system). Subsequently the relationships between lithofacies were revealed and a depositional model (i.e. modal cycle) was produced with 90% confidence level of stationarity. The non-randomness of the latter was tested by chi-square test. The consequences coming from the comparison of "general" sequences (composed of architectural elements), the genetic-based sequences (showing the distributions of the genetic lithofacies) and the lithofacies relationships were discussed in details. This way main depositional channel has the best, channelized lobes have good potential hySzabolcs Borka: University of Szeged, Department of Geology and Paleontology 6722, Szeged, Egyetem utca 2-6., Hungary; Email: borka.szabolcs@gmail.com drocarbon reservoir attributes, with symmetric alternation of persistent fine-grained sandstone (Facies D) and muddy fine-grained sandstone with traction structures (Facies F).

Application and Comparison of Machine Learning Methods for Mud Shale Petrographic Identification

“…Different types of mud shale rocks can be effectively distinguished through classification based on the lithofacies of fine-grained sedimentary rocks. Mineral composi-tion, sedimentary structure, and organic matter abundance are the frequently employed classification indicators for the lithofacies of fine-grained sedimentary rocks [42][43][44][45][46]. For the crucial step of rock naming, this paper adheres to existing research findings and adopts a three-end-member petrological classification [47][48][49][50]; clay minerals, felsic minerals (landderived debris), and carbonate minerals (primarily dolomite) are considered as the three end members.…”

Cluster defined sedimentary elements of deep-water clastic depositional systems and their 3D spatial visualization using parametrization: a case study from the Pannonian-basin

“…The core analysis was presented by BORKA (2016). Accord ing to the core analysis, part of a typical mixed sandmud sub marine fan complex, with quasiinactive parts (zones of thin sand sheets and overbank), channelized lobes (persistent sandstones in them may denote distributary channels), and a main deposi tional channel were revealed.…”

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According to the paper by (GRUND & GEIGER;2011;BORKA, 2016) this study area was characterized as sequences represent ing a prodeltaic submarine fan (Fig. 1).

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A Special Issue: Geomathematics in practice: Case studies from earth- and environmental sciences – Proceedings of the Croatian-Hungarian Geomathematical Congress, Hungary 2015

“…The papers in this in this special issue of Open Geosciences were selected from within the framework of this conference with the hope of providing insights into-, and bridging the gap between mathematical and statistical practice among case studies from classical environmental applications of multivariate statistics [8,9] through the solution of reservoir geological problems [10][11][12][13][14], to the application of methods that are new to this field of science [15] along with many other aspects of geology and environmental sciences. The issue consists of two main parts, the first part deals with studies mainly concerning petrology, while the second is related to urban/classical environmental problems, handled using geostatistics.…”

“…deposits of slumps, sandy debris flows, turbidity currents etc). In the paper by Borka [14] this approach is presented through a case study of the Tercier deep-water sequence of the Pannonian-basin.…”