Xiaohua Shen

Detection of hydrocarbon bearing sand through remote sensing techniques in the western slope zone of Songliao basin, China

To detect oil‐bearing sand in the western slope zone of Songliao Basin, China, a Landsat‐7 Enhanced Thematic Mapper Plus (ETM+) image was used to identify anomalous areas caused by hydrocarbon leakage. Enhancement of the image involved three techniques including Principal Component Analysis (PCA), band ratioing and False Colour Composition (FCC). In this paper, experimental work gives a detailed PCA description of different band combinations. The best four principal components (PCs)—1345‐PC3 (the third PC image of the PCA on band 1, 3, 4, 5), 1357‐PC3, 2357‐PC3 and 3457‐ PC4—were selected for FCC combined with band ratio layers. Based on the tonal characteristics of the existing bores and the basin boundary, differentiation of target areas in the four FCC images was achieved. Results indicated that anomalies are expressed as a halo in fuscous tone and located in the basin margin with an area of 70∼100 km2. Examination of the Ce/La ratio showed that the tonal anomalies are evidently associated with a reducing environment.

A region-growing approach for automatic outcrop fracture extraction from a three-dimensional point cloud

Conventional manual surveys of rock mass fractures usually require large amounts of time and labor; yet, they provide a relatively small set of data that cannot be considered representative of the study region. Terrestrial laser scanners are increasingly used for fracture surveys because they can efficiently acquire large area, high-resolution, three-dimensional (3D) point clouds from outcrops. However, extracting fractures and other planar surfaces from 3D outcrop point clouds is still a challenging task. No method has been reported that can be used to automatically extract the full extent of every individual fracture from a 3D outcrop point cloud. In this study, we propose a method using a region-growing approach to address this problem; the method also estimates the orientation of each fracture. In this method, criteria based on the local surface normal and curvature of the point cloud are used to initiate and control the growth of the fracture region. In tests using outcrop point cloud data, the proposed method identified and extracted the full extent of individual fractures with high accuracy. Compared with manually acquired field survey data, our method obtained better-quality fracture data, thereby demonstrating the high potential utility of the proposed method. HighlightsA region-growing-based method for automatic outcrop fracture extraction is proposed.The growth of the fracture region is based on the local surface normal and curvature.Compared with manual field survey, the proposed method obtained better-quality data.

Cloud Detection Method Based on Spectral Area Ratios in MODIS Data

Abstract A variety of clouds are present in almost all moderate-resolution imaging spectroradiometer (MODIS) images. To extract accurate information from MODIS data, a key preprocessing step is to detect the cloudy pixels. This article proposes a new algorithm to distinguish between cloudy and cloud-free pixels in MODIS images. This algorithm is based on the differences in the spectral areas between clouds and other surface features. It uses as many as 24 of the 36 MODIS spectral bands to obtain the integrated spectral information. The method has been illustrated by an example of 76 MODIS images recorded from 2011 to 2013. The results show that the algorithm is capable of correctly identifying most of the cloud-contaminated pixels except for some thin cloud pixels. We compared the new method with the MODIS Cloud Mask algorithm and found that the new algorithm performs better than the MODIS MOD35 Cloud Mask in some situation, such as coastal area, sun glint, and data with invalid values.

Identification of fracture development period and stress field analysis based on fracture fabrics in tectonic superposition areas

As a direct consequence of multiple periods of stress applied on areas with tectonic superposition, the multiple-periods fractures have complex abutting relationships, and the field study of fractures is usually restricted by outcrop conditions, such as section direction. Therefore, previous studies of superposed stress fields based on fractures have been generally performed in areas with proper observation conditions and clear abutting relationships. In contrast, in many other areas, the identification of fracture development period based on field observation is often infeasible. Compared to abutting relationships, fracture fabrics obtained from field measurement are not affected by the restriction of outcrops and consequently are more representative of the fractures. According to the analysis of fracture fabrics and fracture features, this paper has separated and extracted the superposed fracture sets and identified the fracture development period in the area without available abutting relationships. Taking the southern segment of the Longmen Mountain thrust belt as an example, fractures of two development periods are identified and timed in the tectonic superposition area between two adjacent fold belts. The analysis of stress direction in each period suggests that the structural boundaries, consisting of such pre-existing structures as faults and anticlines, could have induced directional rotation in the subsequent stress. An equivalent result was achieved using a finite element simulation of the stress field. Based on the stress analysis of the field sites and the stress field simulation, the stress variation in the tectonic superposition area is well modeled.