Flooding a landscape: impact of Holocene transgression on coastal sedimentology and underwater archaeology in Kiladha Bay (Greece)

Franchthi Cave, bordering Kiladha Bay, in Greece, is a key archaeological site, due to its long occupation time, from?~?40,000 to?~?5000 year BP. To date, no clear evidence of Neolithic human dwellings in the cave was found, supporting the assumption that Neolithic people may have built a village where there is now Kiladha Bay. During the Neolithic period/Early Holocene, wide areas of the bay were indeed emerged above sea level. Bathymetric and seismic data identified a terrace incised by a valley in?~?1 to 2 m sediment depth. Eight sediment cores, up to 6.3-m-long, were retrieved and analysed using petrophysical, sedimentological, geochemical, and chronostratigraphic methods. The longest core extends into the exposure surface, consisting of a layer of carbonate rubble in a finer matrix, representing weathering processes. Dated organic remains place this unit at?~?8500 cal year BP. It is overlain by stiff silty mud representing an estuarine environment. This mud is capped by reduced sediments with roots marking an exposure surface. A shell-layer, dated to?~?6300 cal year BP, overlies this terrestrial sequence, reflecting the marine transgression. This layer occurs at 10.8 mbsl, 7.7 m deeper than the global sea level at that time, suggesting tectonic subsidence in the area. It is overlain by finer-grained marine carbonate-rich sediments. The top of the core shows traces of eutrophication, pebbles and marine shells, all likely a result of modern anthropogenic processes. These results are interpreted in the context of human occupation: the exposed surface contains pottery sherds, one dating to the Early to Middle Neolithic period, indicating that Neolithic people were present in this dynamic landscape interacting with a migrating coastline. Even if the artefacts are isolated, future investigations of the submerged landscape off Franchthi Cave might lead to the discovery of a Neolithic village, which eventually became buried under marine sediments.     

Geoscience Frontiers 2017 Annual Convention

正The 2017 Geoscience Frontiers Annual Convention was held in Beijing,China during October 19-21,2017 hosted by China University of Geosciences,Beijing(Fig.1).This convention assembled earth scientists from seven countries,including Australia(Dr.Christopher Spencer and Dr.Stijn Glorie),Korea(Dr.S.Kwon),India(Dr.Shaji Erath),Japan(Dr.Toshiaki Tsunogae and Dr.Masaki Yoshida),Russia(Dr.Inna Safonova),UK(Dr.Nick Roberts),China,and also     

The Fragmentation in a Protoplanetary Disk and the Properties of the Resultant Self-Gravitating Clumps

We study the fragmentation properties in the protoplanetary disk and properties of the resultant self-gravitating clumps using our newly constructed disk model. Our disk model includes the mass inflall term from a molecular cloud core and the photoevaporation winds effect. We adopt the conventional fragmentation criterion to judge whether a protoplanetary disk can fragment. In this work, we follow our previous work to investigate the properties of the resultant self-gravitating clumps. In our calculation, the initial masses of the resultant self-gravitating clumps lie in the range of tens of M_J to more than one hundred of M_J, where M_J is the Jupiter mass. These initial masses can seemingly account for the masses of extrasolar planets in magnitude. We also calculate the subsequent gas accretion of clumps in 1.27 × 10⁴ yr after the formation of self-gravitating clumps. We find that the subsequent gas accretion of self-gravitating clumps is very efficient, and the clump masses grow to hundreds of M_J and the physical radii R_c of clumps increase to about 10 AU. Additionally, we also calculate the orbital migration of clumps. We find that most clumps have short migration timescale to be accreted onto the protostar, and only a small fraction of clumps have long migration timescale (>10⁶ yr) to successfully become gas giant planets. These results are consistent with previous studies.     

Adjoint analysis of Buckley-Leverett and two-phase flow equations

This paper analyzes the adjoint equations and boundary conditions for porous media flow models, specifically the Buckley-Leverett equation, and the compressible two-phase flow equations in mass conservation form. An adjoint analysis of a general scalar hyperbolic conservation law whose primal solutions include a shock jump is initially presented, and the results are later specialized to the Buckley-Leverett equation. The non-convexity of the Buckley-Leverett flux function results in adjoint characteristics that are parallel to the shock front upstream of the shock and emerge from the shock front downstream of the shock. Thus, in contrast to the behavior of Burgers’ equation where the adjoint is continuous at a shock, the Buckley-Leverett adjoint, in general, contains a discontinuous jump across the shock. Discrete adjoint solutions from space-time discontinuous Galerkin finite element approximations of the Buckley-Leverett equation are shown to be consistent with the derived closed-form analytical solutions. Furthermore, a general result relating the adjoint equations for different (though equivalent) primal equations is used to relate the two-phase flow adjoints to the Buckley-Leverett adjoint. Adjoint solutions from space-time discontinuous Galerkin finite element approximations of the two-phase flow equations are observed to obey this relationship.     

High-dimensional geostatistical history matching

Hydrocarbon reservoir modelling and characterisation is a challenging subject within the oil and gas industry due to the lack of well data and the natural heterogeneities of the Earth’s subsurface. Integrating historical production data into the geo-modelling workflow, commonly designated by history matching, allows better reservoir characterisation and the possibility of predicting the reservoir behaviour. We present herein a geostatistical-based multi-objective history matching methodology. It starts with the generation of an initial ensemble of the subsurface petrophysical property of interest through stochastic sequential simulation. Each model is then ranked according the match between its dynamic response, after fluid flow simulation, and the observed available historical production data. This enables building regionalised Pareto fronts and the definition of a large ensemble of optimal subsurface Earth models that fit all the observed production data without compromising the exploration of the uncertainty space. The proposed geostatistical multi-objective history matching technique is successfully implemented in a benchmark synthetic reservoir dataset, the PUNQ-S3, where 12 objectives are targeted.