坳陷湖盆大型浅水三角洲是目前中国陆上岩性油气藏规模储量增长的主体.通过对松辽盆地南部上白垩统保乾三角洲和现代鄱阳湖赣江三角洲解剖,重点探讨湖盆浅水三角洲形成的地质背景、沉积特征与生长模式.结果表面:①坳陷湖盆具有形成大型浅水三角洲的沉积背景,敞流型湖盆导致的湖平面频繁升降控制了浅水三角洲的纵横向发育规模.②松辽盆地南部上白垩统发育2种不同类型的三角洲,深湖型三角洲一般呈朵叶状,沉积亚相展布清晰,沉积微相以分流河道、河口坝和分流河道间为主;浅湖型三角洲一般呈鸟足状或树枝状,沉积亚相分异不明显,沉积微相以分流河道和分流河道间为主,河口坝不发育;③通过现代沉积遥感定量分析,刻画了鄱阳湖赣江中支三角洲近50年的发育特征和演化规律,揭示了分流河道从分散树枝状到闭合结网状的生长过程.④坳陷湖盆大型浅水三角洲是不断发育的多期朵叶体在平面上拼接而成的复合体,其中分流河道是最重要的储集砂体类型,在平面上呈结网状分布,控制了大面积岩性油气藏的分布与富集.

Effectively monitoring the location and land use of oil production facilities and production emissions in the oil region is of great significance to the HSE management of oilfields. In the study, we construct a location-based Petroleum Remote Sensing dataset (PetroRS dataset), which consist of 10 thousand labelled high-resolution images in two classes of oil production-related objects. After two distinct forms of data augmentation, the dataset is enlarged 9 times. We applied Faster R-CNN, a deep learning method, to the PetroRS dataset to set up a preliminary result as the baseline. On this basis, we use the model to train the augmented dataset and improve the model by optimized anchor based on scale and aspect-ratio statistics. The results show: (1) Faster R-CNN model could detect two classes of oil production-related object automatically and simultaneously with the accuracy of 76% and 32%, respectively; (2) The model training with augmented dataset gives better result, more than 5% accuracy increments, compared to the baseline; (3) The improved model with optimized anchor returns a better result, more than 10% accuracy increments, compared to the baseline. We believe deep learning could provide a new practical and applicable idea in terms of applying remote sensing technology in the petroleum industry.

Different application conditions applied for different models used in satellite-based terrestrial latent heat estimation. Therefore, great uncertainties exist in large-scale application of such methods. BMA fusion algorithm, which has combined three commonly used models (including Penman Monteith LE algorithm, Priestly-Taylor LE algorithm and Semi-empirical Penman LE algorithm), is then carried out in this study. It can effectively reduce the uncertainty and improve the accuracy of terrestrial latent heat estimation comparing with single algorithm itself after testing with 190 eddy covariance tower site data (Fluxnet site data). The error of mean square root (RMSE) has decreased by 5W/m(2) and the value of average correlation coefficient (R-2) has increased by 0.05 for most of observation points in this test. The fusion model has applied in China to carry out a monthly-based latent heat estimation and mapping for data achieved from 1989 to 2006. The estimation result, after analyzed quantitatively, returns sound precision and stability, which can make up the shortage of current latent heat products. Meanwhile, the spatial distribution analysis shows that: latent heat spatial distribution is the combined contribution of temperature, precipitation and vegetation together. The temporal distribution of latent heat has obvious seasonal characteristic, which is low in winter and high in summer. The latent heat value is declined by 0.07 W/m(2) per year for past 18 years.

Effectively monitoring the real-time position and status of oil facilities (mainly well-site) in oil field is very important for the safety production. Considering the low efficiency of traditional visual interpretation method and the high demands of preset feature for machine learning method, one of the object detection methods in Deep learning (YOLOv2) was introduced to recognize oil industry facilities automatically. After establishing the dataset of oil facility samples, 90 percent of samples are used for model training while 10 percent are for validating. Comparing with the results extracted by machine learning (Adaboost model based on Haar-like), YOLOv2 recognition results of oil facilities indicated that: Deep learning improve the recognition efficiency and accuracy of oil facilities. The accuracy can be as high as 92% while the error rate and omission rate can be maintained in a low level. At the same time, the constructed model was applied in an oilfield in eastern part of China, and the result shows that the model can identify most of the oilfield facilities correctly with only 4% omission rate, which is much lower comparing with manual interpretation. However, the 11% error rate, caused by insufficient sample types and sample quantities, is relatively high especially in city area.

戈壁荒漠区生态环境脆弱,工业化进程中的环境风险高,及时获取工业化进程中基础环境要素演变有助于监控潜在的环境风险.以克拉玛依油区为例,通过遥感获取更大区域的植被和陆表水分布时序特征,分析工业化进程中区域环境要素时空变化特征及其对周边区域环境的影响.利用1977-2016年Landsat和MSS数据,基于NDVI和湿度反演陆表植被和水域覆盖,通过回归分析和复现率获取植被和陆表水分布的时序特征,结合区域内月平均陆表温度和降水信息,分析环境要素时空演变趋势.结果表明:城镇工业区植被覆盖总体改善,存在局部的植被覆盖退化区;研究区内大区域植被覆盖呈明显持续改善,陆表水分布环境稳定,区域环境要素的时空演变表现出不同的阶段性特征;区域环境要素时空演变的空间分布格局体现与人类活动的高相关性,人类活动是区域内环境要素改变的重要影响因素.城镇工业化进程中局部的环境要素退化难以避免,合理规划人类活动,可以促进大区域环境与工业化进程的协调发展,遥感技术可以监测工业化进程与区域环境演变的相关性.

This paper presents a study of revealing the environmental elements change during the process of local industrialization based on remote sensing technique in the western part of China. Spatio-temporal evolution of vegetation cover derived from NDVI and land surface water distribution was analyzed by time-series analysis of MSS and Landsat data from 1977 to 2011. Results show that remote sensing provide a way for monitoring the influence of local industrialization on regional environment elements in gobi region.

In this paper, an approach for oil contaminated wastewater recognition is presented. By analyzing the relationship between thermal and multispectral characteristics of clean water and oil contaminated wastewater. The Oil Contaminated Wastewater Index (OCWI) was then developed to extract the oil contaminated wastewater. Results show that remote sensing can be of great help in tracking the oil contaminated wastewater with visible high hydrocarbon concentration in gobi area.

In order to enhance accuracy of hydrocarbon reservoir prediction in shallow water lacustrine deltaic depositional system,we put forward a new and more comprehensive depositional model based on the deposits of the Ganjiang River Delta in Poyang Lake.Using cores,sketch logs,trenches and laboratory analyses,we described these deposits.Several basic attributes have been recognized for shallow water delta,including:(1 )The sand body is comprised of architectural elements including channel bars and levee in both of upper and lower delta plains,and longitude bars,transverse bars in river moth areas,especially unit bars in bar head areas.(2)Normal grading is absent in channel fill sediment in straight channel reach.(3)Facies se-quence of floodplain sediment is mainly composed of interbedded mud-sand deposited in flood stage on top, typical with lacustrine mud overlain by reverse-grading upward distributary mouth bars at lower part.(4)The delta formation process is mainly influenced by the climate cycles or flooding events.At low-flow stages mud is deposited in delta front.At high stages,older sediment is reworked,and the interbedded sand-mud is deposi-ted in delta plain.This depositional model quality represents the evolution process of shallow water lacustrine delta,and it would help to identify reservoir sweet spot in subsurface extensive sand body of these kinds of depositional systems.

This paper proposes a method to perform management and access to multi-temporal images in 3D petroleum remote sensing application.It combines data organization directory structure with image tile storage.It can effectively classifying data management and visit to satisfy different applications,flexible data extension and contrast analysis based on the multi-temporal and multi-sensors images.

In the application of remote sensing to petroleum exploration, multi-temporal images are very commonly used. How to manage effectively the massive multi -temporal images to satisfy diverse applications is an urgent problem to be solved. The authors firstly employ separate - management mode for two - set data in three -dimensional GIS. Based on the fundamental image data of three-dimensional GIS, the authors present a practical data storage model of multi-temporal images suitable to solving complicated data features,which is characterized by multi-application, multi -district or event, multi -data resource, multi -temporal in providing RS Information service for oil application. This research is verified by developing a multi -temporal images data management system to provide remote sensing multi-temporal images information service.

Establishing the remote sensing algorithm of retrieving the absorption coefficient of seawater petroleum substances is an efficient way to improve the accuracy of retrieving a seawater petroleum concentration using a remote sensing technology. A remote sensing reflectance is a basic physical parameter in water color remote sensing. Apply it to directly retrieve the absorption coefficient of seawater petroleum substances is of potential advantage. The absorption coefficient of waters containing petroleum [ACWCP, a o （λ）], consists of the absorption coefficient of pure water [ACPW, a w （λ）], plankton [ACP, a ph （λ）], colored scraps [ACCS, a d,g （λ）], and petroleum substance [ACPS, a oil （λ）]. Among those, ACCS consists of the absorption coefficient of nonalgal particle [ACNP, a d （λ）] and colored dissolved organic matter [ACCDOM, a g （λ）]. For waters containing petroleum, the retrieved ACCS using the existing method is a combination absorption coefficient of ACNP,ACCDOM and ACPA [CAC, a d,g,oil （λ）]. Therefore, the principle question is how to extract ACPS from CAC.Through the analysis of the three proportion tests conducted between the year of 2013 and 2015 and the corresponding remote sensing data, an algorithm of retrieving the absorption coefficient of petroleum substances is proposed based on remote sensing reflectance. First of all, ACPS and CAC are retrieved from the reflectance using the quasi-analytical algorithm（QAA）, with some parameter modified. Secondly, given the fact that the backscatter coefficient [BC, b bp （555）] of total particles at 555 nm can be obtained completely from the reflectance, the relation between BC and ACNP in petroleum contaminated water can be established. As a result, ACNP can be calculated. Then, combining the remote sensing retrieving algorithm of a g （440）, the method of achieving the spectral slope of the absorption coefficient can be established, from which ACCDOM,can be calculated. Finally, ACPS can be computed as the residual. The accuracy of ACPS based on this algorithm is 86% compared with the in situ measurements.

It is of great importance for petroleum exploration to study the sedimentary features and the growth pattern of shoal water deltas in lake basins. Taking spatio-temporal remote sensing images as the principal data source, combined with field sedimentation survey, a quantitative research on the modern deposition of Ganjiang delta in the Poyang Lake Basin is described in this paper. Using 76 multi-temporal and multi-type remote sensing images acquired from 1973 to 2015, combined with field sedimentation survey, remote sensing interpretation analysis was conducted on the sedimentary facies of the Ganjiang delta. It is found that that the current Poyang Lake mainly consists of three types of sand body deposits including deltaic deposit, overflow channel deposit, and aeolian deposit, and the distribution of sand bodies was affected by the above three types of depositions jointly. The mid-branch channels of the Ganjiang delta increased on an exponential growth rhythm. The main growth pattern of the Ganjiang delta is dendritic and reticular, and the distributary channel mostly arborizes at lake inlet and was reworked to be reticulatus at late stage.

Numerical simulation model of H2 S gas diffusion is used to analyse affected range of toxic gas,which is released in the well-blowout accidents during the exploration of high-sulfur oilfield in the complex mountain regions.It is necessary to integrate the model with 3D environmental emergency system in order to learn diffusion trend of the toxic gas along the terrain. To solve technical difficulties in system integration,this paper firstly analyses the features of dataset of the gas model,such as data structure,distribution of effective concentration value with time and space.In this research octree compression is used to improve the efficiency of data access.At the same time,the ground data of gas diffusion model is extracted and cut into temporal and spatial chips in order to display its four-dimensional characteristics.

With the neural network method, this paper used geochemical exploration and geoelectric as well as remote sensing data to evaluate hydrocarbon-bearing characteristics of Liandaowan area, with satisfactory result obtained. The trained result was further analyzed, and thus important factors were selected. The evaluation effects based on different types of factors were compared. The results are of guiding significance in factor optimization.

The 2.5m resolution data of SPOT5 can be used to produce image maps in large scale. The geometric correction is the key point, especially on the loessial area in northern Shanxi province, because of the rough landform with sharp relief and hundreds of dongas. The orthorectification has to be used. The intrinsical difference between physical model of orthorectification and normal polynomial algorithm is discussed theoretically and practically. Result images corrected by different methods are checked carefully. The accuracy of orthorectified image can be 3~5 times better than that of normal rectified method.

Long distance oil-gas pipeline construction is complex. GIS technology is applied to this field and provides a high-tech method for construction operation and management. The digital pipeline is the main feature of the 21st Century's oil-gas pipelines. The new oil-gas pipeline construction in China has the aim of high standards, good quality, advanced technology and best efficiency and GIS technology gives a powerful tool to accomplish this target. GIS and remote sensing technologies are used on route selection of the West-East Nature Gas Transportation Cross Continent Pipeline. The remote sensing images and revising maps of 1:50000, based on new SPOT images, produced from a GIS system are offered to the planning department of the pipeline and used for in situ investigation which obtain wonderful results

藏南特提斯域内伸展运动和伸展作用非常普遍,根据构造变形分析和伸展不整合、沉积岩相、古地理再造及岩相对比方法,对藏南海西期以来的伸展构造进行了较为系统的厘定,确定了海西期、印支期、早燕山期的主动伸展运动和晚燕山期和喜山期的被动伸展作用,并对这些运动特征进行了探讨.

晚三叠世及侏罗纪是特提斯大洋形成和扩张的时期.藏南聂拉木地区的相应地层中普遍存在裂陷盆地沉积及众多的伸展不整合.根据这些不整合面之上的"超越下伏地层不正常的化石混积事件",判断早侏罗世赫唐早期和中侏罗世巴通期裂陷幅度分别为大于1 600 m和大于800 m.作者根据这些不整合面以及遵循地层命名的"优先法则",对各个组的地层划分与名称进行了厘定.