Palaeoenvironment and Its Control on the Formation of Miocene Marine Source Rocks in the Qiongdongnan Basin, Northern South China Sea

The main factors of the developmental environment of marine source rocks in continental margin basins have their specificality. This realization, in return, has led to the recognition that the developmental environment and pattern of marine source rocks, especially for the source rocks in continental margin basins, are still controversial or poorly understood. Through the analysis of the trace elements and maceral data, the developmental environment of Miocene marine source rocks in the Qiongdongnan Basin is reconstructed, and the developmental patterns of the Miocene marine source rocks are established. This paper attempts to reveal the hydrocarbon potential of the Miocene marine source rocks in different environment and speculate the quality of source rocks in bathyal region of the continental slope without exploratory well. Our results highlight the palaeoenvironment and its control on the formation of Miocene marine source rocks in the Qiongdongnan Basin of the northern South China Sea and speculate the hydrocarbon potential of the source rocks in the bathyal region. This study provides a window for better understanding the main factors influencing the marine source rocks in the continental margin basins, including productivity, preservation conditions, and the input of terrestrial organic matter

Thermal cracking of oil under water pressure up to 900 bar at high thermal maturities. 1. gas compositions and carbon isotopes

In this study, a C9+ fraction of saturate-rich Tertiary source rock-derived oil from the South China Sea basin was pyrolyzed in normal and supercritical water using a 25 mL vessel at a range of temperature from 350 to 425 °C for 24 h, to probe pressure effects up to 900 bar on gas yields and their stable carbon isotopic compositions during thermal cracking. Pressure generally retards oil cracking, as evidenced by reduced gas yields, but the trends depend upon the level of thermal evolution. In the early stages of cracking (350 and 373 °C, equivalent vitrinite reflectance of 1.3% R0), pressure still has a strong suppression effect from 200 to 470 bar, which then levels off or is reversed as the pressure is increased further to 750 and 900 bar. Interestingly, the stable carbon isotopic composition of the generated methane becomes enriched in 13C as the pressure increases from 200 to 900 bar. A maximum fractionation effect of ∼3‰ is observed over this pressure range. Due to pressure retardation, the isotopically heaviest methane signature does not coincide with the maximum gas yield, contrary to what might be expected. In contrast, pressure has little effect on ethane, propane, and butane carbon isotope ratios, which show a maximum variation of ∼1‰. The results suggest that the rates of methane-forming reactions affected by pressure control methane carbon isotope fractionation. Based on distinctive carbon isotope patterns of methane and wet gases from pressurized oil cracking, a conceptual model using “natural gas plot” is constructed to identify pressure effect on in situ oil cracking providing other factors excluded. The transition in going from dry conditions to normal and supercritical water does not have a significant effect on oil-cracking reactions as evidenced by gold bag hydrous and anhydrous pyrolysis results at the same temperatures as used in the pressure vessel

An Automatic Morphological Attribute Building Extraction Approach for Satellite High Spatial Resolution Imagery

A new morphological attribute building index (MABI) and shadow index (MASI) are proposed here for automatically extracting building features from very high-resolution (VHR) remote sensing satellite images. By investigating the associated attributes in morphological attribute filters (AFs), the proposed method establishes a relationship between AFs and the characteristics of buildings/shadows in VHR images (e.g., high local contrast, internal homogeneity, shape, and size). In the pre-processing step of the proposed work, attribute filtering was conducted on the original VHR spectral reflectance data to obtain the input, which has a high homogeneity, and to suppress elongated objects (potential non-buildings). Then, the MABI and MASI were calculated by taking the obtained input as a base image. The dark buildings were considered separately in the MABI to reduce the omission of the dark roofs. To better detect buildings from the MABI feature image, an object-oriented analysis and building-shadow concurrence relationships were utilized to further filter out non-building land covers, such as roads and bare ground, that are confused for buildings. Three VHR datasets from two satellite sensors, i.e., Worldview-2 and QuickBird, were tested to determine the detection performance. In view of both the visual inspection and quantitative assessment, the results of the proposed work are superior to recent automatic building index and supervised binary classification approach results

A Novel Change Detection Method for Natural Disaster Detection and Segmentation from Video Sequence

Change detection (CD) is critical for natural disaster detection, monitoring and evaluation. Video satellites, new types of satellites being launched recently, are able to record the motion change during natural disasters. This raises a new problem for traditional CD methods, as they can only detect areas with highly changed radiometric and geometric information. Optical flow-based methods are able to detect the pixel-based motion tracking at fast speed; however, they are difficult to determine an optimal threshold for separating the changed from the unchanged part for CD problems. To overcome the above problems, this paper proposed a novel automatic change detection framework: OFATS (optical flow-based adaptive thresholding segmentation). Combining the characteristics of optical flow data, a new objective function based on the ratio of maximum between-class variance and minimum within-class variance has been constructed and two key steps are motion detection based on optical flow estimation using deep learning (DL) method and changed area segmentation based on an adaptive threshold selection. Experiments are carried out using two groups of video sequences, which demonstrated that the proposed method is able to achieve high accuracy with F1 value of 0.98 and 0.94, respectively

Biomarker compositions and geochemical significance of crude oils of Baiyun Sag, Pearl River Mouth Basin

Crude oils from the Baiyun Sag of Pearl River Mouth Basin have high abundance of diagnostic biomarkers including novel C15 sesquiterpene, special configurated tricyclic sesquiterpenes and tetracyclic sesquiterpenes (X, Y, Z and X1, Y1, Z1), and bicadinanes, which indicate the contributions from terrestrial higher plants to the organic matters. These oils are also rich in oleanane, which is a diagnostic biomarker for angiosperm organic matter. Based on the analysis of 13 crude oils from the Baiyun Sag, the compositions and geochemical significance of typical biomarkers were revealed. Results indicate that C24-des-oleanane (Y1) and C27 tetracyclic (Z1) may share a similar biological origin. Novel C15 sesquiterpene, C24-des-oleanane and C27 tetracyclic, and bicadinanes may be derived from different higher plants according to the molecular structure and abundance correlation analysis of the related compounds. In addition, the biomarker compositions of crude oils from different regions are significantly varied, which will benefit the oil group classification in the Baiyun Sag. The distribution of novel C15 sesquiterpene and bicadinanes was influenced by sedimentary environment, and may be more enriched in oxidized environment. The distribution patterns of C24-des-oleanane, C27 tetracyclic and oleanane are principally affected by biogenic input, but are less influenced by sedimentary environment fluctuation. The relatively high abundance of C24-des-oleanane, C27 tetracyclic and oleanane in the crude oil in the northeastern and eastern Baiyun area reflects that the Dongsha Uplift and the Yunli Low Uplift may be an important source of terrigenous organic matter in this area

A New Method for Continuous Monitoring of Black and Odorous Water Body Using Evaluation Parameters: A Case Study in Baoding

Water is an important factor in human survival and development. With the acceleration of urbanization, the problem of black and odorous water bodies has become increasingly prominent. It not only affects the living environment of residents in the city, but also threatens their diet and water quality. Therefore, the accurate monitoring and management of urban black and odorous water bodies is particularly important. At present, when researching water quality issues, the methods of fixed-point sampling and laboratory analysis are relatively mature, but the time and labor costs are relatively high. However, empirical models using spectral characteristics and different water quality parameters often lack universal applicability. In addition, a large number of studies on black and odorous water bodies are qualitative studies of water body types, and there are few spatially continuous quantitative analyses. Quantitative research on black and odorous waters is needed to identify the risk of health and environmental problems, as well as providing more accurate guidance on mitigation and treatment methods. In order to achieve this, a universal continuous black and odorous water index (CBOWI) is proposed that can classify waters based on evaluated parameters as well as quantitatively determine the degree of pollution and trends. The model of CBOWI is obtained by partial least squares machine learning through the parameters of the national black and odorous water classification standard. The fitting accuracy and monitoring accuracy of the model are 0.971 and 0.738, respectively. This method provides a new means to monitor black and odorous waters that can also help to improve decision-making and management