Quantitative Assessment of Sedimentary Provenance in Coastal Basins

Thesis Abstract

Coastal basins exhibit complex sedimentary records that reflect multi- sourced provenance, stratigraphic mixing, and dynamic sediment transport processes, yet quantitative attribution of sediment sources remains challenging due to diagenetic alteration, geochemical overlaps, and limited integration of multi-proxy data. This study aims to deliver a robust, quantitative assessment of sedimentary provenance in selected coastal basins to improve paleogeographic reconstructions and reservoir-quality predictions. The specific objectives are to (i) characterize mineralogical and geochemical signatures of sediments from suspected source regions, (ii) quantify relative source contributions using multivariate statistical and isotopic approaches, (iii) assess spatial and temporal variations in provenance through stratigraphic horizons and subsurface cores, and (iv) evaluate the sensitivity of provenance signals to diagenetic overprint and sedimentary sorting. The research adopts a mixed-methods design anchored in empirical field observations and laboratory analyses, integrating sedimentologic, mineralogical, geochemical, and isotopic datasets. The population comprises sediment samples from three coastal basins with quasi-continuous stratigraphic records spanning late Miocene to Holocene. A stratified random sampling scheme yields 120 surface samples and 60 borehole core intervals, ensuring representation of proximal and distal sources, channel belts, deltaic lobes, and shelf sediments. Data collection employs X-ray diffraction (XRD) for mineralogy, inductively coupled plasma mass spectrometry (ICP-MS) for major and trace element concentrations, laser ablation ICP-MS for in-situ trace element zoning, and Sr-Nd-Pb isotopic analyses to resolve crustal source lithologies. Elemental ratios (e.g., Zr/Ti, Th/Sc, La/Yb) and isotopic fingerprints are compiled with existing regional rock suites to construct a probabilistic provenance model. Validity and reliability are addressed through triplicate analyses, standard reference materials, and cross-validation with a curated regional geochemical library. Data analysis proceeds in three layers (i) exploratory multivariate techniques (principal component analysis, hierarchical cluster analysis) to identify distinct source assemblages; (ii) quantitative source apportionment using end-member mixing analysis (EMMA) and probabilistic isotopic mixing models; and (iii) temporal Bayesian updating to track provenance shifts through stratigraphic time steps. The study tests hypotheses that coastal basin sediments derive a dominant crustal component with measurable contributions from distant orogens, while also detecting secondary inputs from river basins with dendritic drainage patterns. Theoretical framing draws on processes-based provenance theory and tectono-kinematic basin analysis, with explicit use of the framework of end-member mixing models and isotopic discrimination as the core analytical lens. Expected findings include (a) distinct geochemical clusters corresponding to proximal nearshore vs. distal hinterland sources, (b) statistically significant contributions from particular lithologies (e.g., arc-derived granitoids vs. cratonic rocks) revealed by Sr-Nd-Pb isotope signatures, and (c) temporal shifts in provenance linked to known sea-level fluctuations and river avulsion events. The integration of mineralogical and isotopic data is anticipated to reduce non-uniqueness in source attribution and improve confidence intervals for source proportions. The study contributes to knowledge by providing a replicable, multi-proxy provenance framework tailored to coastal basins, enabling refined paleogeographic reconstructions, improved understanding of sediment routing, and better predictive power for reservoir characterization in siliciclastic systems. The conclusion emphasizes that combining EMMA with isotope-based discrimination yields more robust source apportionment than either approach alone, and that diagenetic considerations must be explicitly modeled to avoid overinterpretation of signal. Recommendations include extending the approach to additional coastal basins with varying tectonic settings, incorporating detrital zircon U-Pb dating to enhance source resolution, and applying the framework to hydrocarbon exploration models to improve stratigraphic correlation and reservoir quality assessment.