Coupled ‘storm‐flood’ depositional model: Application to the Miocene–Modern Baram Delta Province,north‐west Borneo

The Miocene to Modern Baram Delta Province is a highly efficient source to sink system that has accumulated 9 to 12 km of coastal–deltaic to shelf sediments over the past 15 Myr. Facies analysis based on ca 1 km of total vertical outcrop stratigraphy, combined with subsurface geology and sedimentary processes in the present‐day Baram Delta Province, suggests a ‘storm‐flood’ depositional model comprising two distinct periods: (i) fair‐weather periods are dominated by alongshore sediment reworking and coastal sand accumulation; and (ii) monsoon‐driven storm periods are characterized by increased wave‐energy and offshore‐directed downwelling storm flow that occur simultaneously with peak fluvial discharge caused by storm precipitation (‘storm‐floods’). The modern equivalent environment has the following characteristics: (i) humid‐tropical monsoonal climate; (ii) narrow (ca <100 km) and steep (ca 1°), densely vegetated, coastal plain; (iii) deep tropical weathering of a mudstone‐dominated hinterland; (iv) multiple independent, small to moderate‐sized (10² to 10⁵ km²) drainage basins; (v) predominance of river‐mouth bypassing; and (vi) supply‐dominated shelf. The ancient, proximal part of this system (the onshore Belait Formation) is dominated by strongly cyclical sandier‐upward successions (metre to decametre‐scale) comprising (from bottom to top): (i) finely laminated mudstone with millimetre‐scale silty laminae; (ii) heterolithic sandstone–mudstone alternations (centimetre to metre‐scale); and (iii) sharp‐based, swaley cross‐stratified sandstone beds and bedsets (metre to decimetre‐scale). Gutter casts (decimetre to metre‐scale) are widespread, they are filled with swaley cross‐stratified sandstone and their long axes are oriented perpendicular to the palaeo‐shoreline. The gutter casts and other associated waning‐flow event beds suggest that erosion and deposition was controlled by high‐energy, offshore‐directed, oscillatory‐dominated, sediment‐laden combined flows within a shoreface to delta front setting. The presence of multiple river mouths and exceptionally high rates of accommodation creation (characteristic of the Neogene to Recent Baram Delta Province; up to 3000 m Ma⁻¹), in a ‘storm‐flood’‐dominated environment, resulted in a highly efficient and effective offshore‐directed sediment transport system.     

Conditioning generative adversarial networks on nonlinear data for subsurface flow model calibration and uncertainty quantification

Conditioning complex subsurface flow models on nonlinear data is complicated by the need to preserve the expected geological connectivity patterns to maintain solution plausibility. Generative adversarial networks (GANs) have recently been proposed as a promising approach for low-dimensional representation of complex high-dimensional images. The method has also been adopted for low-rank parameterization of complex geologic models to facilitate uncertainty quantification workflows. A difficulty in adopting these methods for subsurface flow modeling is the complexity associated with nonlinear flow data conditioning. While conditional GAN (CGAN) can condition simulated images on labels, application to subsurface problems requires efficient conditioning workflows for nonlinear data, which is far more complex. We present two approaches for generating flow-conditioned models with complex spatial patterns using GAN. The first method is through conditional GAN, whereby a production response label is used as an auxiliary input during the training stage of GAN. The production label is derived from clustering of the flow responses of the prior model realizations (i.e., training data). The underlying assumption of this approach is that GAN can learn the association between the spatial features corresponding to the production responses within each cluster. An alternative method is to use a subset of samples from the training data that are within a certain distance from the observed flow responses and use them as training data within GAN to generate new model realizations. In this case, GAN is not required to learn the nonlinear relation between production responses and spatial patterns. Instead, it is tasked to learn the patterns in the selected realizations that provide a close match to the observed data. The conditional low-dimensional parameterization for complex geologic models with diverse spatial features (i.e., when multiple geologic scenarios are plausible) performed by GAN allows for exploring the spatial variability in the conditional realizations, which can be critical for decision-making. We present and discuss the important properties of GAN for data conditioning using several examples with increasing complexity.

     

Smooth particle hydrodynamics modelling of liquid-sediment system and coastal wave breaker

Ocean Dynamics - In this paper, a two-phase coastal liquid-sediment system and a wave breaker were numerically simulated using a particle-based smooth particle hydrodynamics (SPH). To verify the...     

Seismic response of a four-storey RC school building with masonry-infilled walls

This paper focuses on the evaluation of the effect of masonry-infilled walls on the seismic response of a four-storey RC school building. Numerical simulation is presented with respect to the building with and without masonry-infilled walls. The simulation employed force-based fibre elements for beams and columns, and a single equivalent diagonal strut to represent the masonry infill. The numerical model was verified through comparison with shake table test results. It was found that the presence of masonry-infilled walls has significant influence on the global response of the structure. Although the displacement of the structure with infilled wall is reduced in the in-plane direction, it was increased in both in-plane and out-of-plane directions when the infilled walls experienced loss in serviceability.     

A prediction model for wind speed ratios at pedestrian level with simplified urban canopies

The purpose of this study is to review and improve prediction models for wind speed ratios at pedestrian level with simplified urban canopies. We adopted an extensive database of velocity fields under various conditions for arrays consisting of cubes, slender or flattened rectangles, and rectangles with varying roughness heights. Conclusions are summarized as follows: first, a new geometric parameter is introduced as a function of the plan area index and the aspect ratio so as to express the increase in virtual density that causes wind speed reduction. Second, the estimated wind speed ratios in the range 0.05?<?z/h?<?0.3, where h is the building height, are consistent with those derived from the database to within an error of ±25%. Lastly, the effects of the spatial distribution of the flow were investigated by classifying the regions near building models into areas in front of, to the side of, or behind the building. The correlation coefficients between the wind speeds averaged over the entire region, and the front or side region values are larger than 0.8. In contrast, in areas where the influence of roughness elements is significant, such as behind a building, the wind speeds are weakly correlated.     

Mineralogical and geochemical characterization of listwaenite from the Semail Ophiolite, Oman

The late Cretaceous-lower Tertiary hydrothermal alteration of serpentinized peridotite in the Semail ophiolite has formed two distinct types of listwaenite. Type I is characterized by the presence of calcite (Type IA) or dolomite (Type IB)+fuchsite±spinel. Type II is dominated by silicate minerals (quartz, chlorite, fuchsite)±calcite+dolomite±magnetite±apatite±plagioclase. Most listwaenites occur as veins along thrust fault zones within the ophiolite mélange. High Cr and Ni contents, abundant occurrence of Cr-spinel within a matrix of red-brown ferruginous carbonates within a micro-vein network of goethite, and the relics of mesh texture indicate an ultramafic protolith. Type I and II listwaenites represent different stages of hydrothermal alteration. The mineralogical and chemical distinctions of both types are the response to the extent of the reactions between the protoliths and the solutions leading to different stages of metasomatic replacement. The hydrothermal fluids involved in the formation of Type I listwaenite were enriched in Ca, Mg, and CO₂, whereas Type II listwaenite bodies were formed from a hydrothermal fluid enriched in SiO₂. REE and trace elements in both listwaenite types were extracted in part from adjoining peridotite. No Au anomaly in the study areas has been detected.     

iGeoTrans – a novel iOS application for GPS positioning in geosciences

The iGeoTrans is an iOS application designed for navigation purposes for iPhone, iPad and iPod Touch. This application uses Global Positioning System (GPS), Assisted GPS system, GLONASS, Wi-Fi and Cellular Network for positioning. The iGeoTrans has included datum transformations and map projections that enable users to convert the collected data between different coordinate systems for almost all areas in the world. In addition, other features are also included such as distance, area measurements, and GPS results could be exported to the AutoCad dxf format for GIS softwares. The average horizontal and vertical root mean square errors (RMSEs) for the static test are around 4.11 and 3.51?m, respectively. The horizontal RMSE for the dynamic outdoor test is around 2.72?m. The iGeoTrans application can be used to support surveying, mapping and geosciences fieldworks for any area in the world.