Quantitative 3D remote digital compositional and structural characterisation of outcrops

GSTDTAP

项目编号	NE/N017188/1
	Quantitative 3D remote digital compositional and structural characterisation of outcrops
	[unavailable]
主持机构	University of Hull
项目开始年	2016
	2016-07-01
项目结束日期	2017-04-30
资助机构	UK-NERC
项目类别	Research Grant
国家	英国
语种	英语
英文摘要	The construction of 3D sub-surface geospatial models of onshore basins is a vital aspect of hydrocarbon exploration and is critically dependant on the information derived from the analysis of geological outcrops and borehole cores. Current analysis techniques produce very limited datasets that do not fully capture the inherent 3D nature of these geological features which result in significant gaps in structural information with consequent severe effects on the accuracy of geological interpretation. A newly developed field portable imaging instrument (MicroFTS) has demonstrated the capability to remotely identify the key sedimentary lithologies accurately. This project will demonstrate the capability of the MicroFTS to significantly increase the volume, coverage, and level of detail, of structural and compositional information at sample-borehole-site and basin scales, at very low cost. Geological outcrops provide an important primary source of data for geologists and are extensively used within both academia and industry for teaching, training and research, and for the development of conceptual and predictive geological models. Accurate characterisation of lithology and mineralogy in rock volumes and the sedimentary architecture of a hydrocarbon basin is central to predicting the presence or quantifying the volumetrics of hydrocarbon resources. Seismic reflection data can image large-scale reservoir architectures but vertical and horizontal resolution is typically limited to tens of metres. Conversely, core and wireline logs can provide much higher resolution but wells are typically sparsely distributed, sampling only a very small percentage of the rock volume. Outcrops, however, offer direct observations of rock bodies and their geometries, architecture and lithological heterogeneities over scales ranging from less than 1 cm to several tens of kilometres. Conventional outcrop analysis techniques (e.g. sedimentary logs, surface geological maps and cross-sections provide invaluable information on geological systems, facilitating many contemporary structural and stratigraphical and syntheses. However, field data are typically collected by one- and two dimensional paper-based methods that do not fully capture the inherent 3D nature of geological features. Associated accuracy, precision and uncertainty are rarely defined, and it is often difficult to extract reliable quantitative information on the geometries and spatial heterogeneities of sedimentary rock bodies, data which are essential for 3D computer-based geostatistical reservoir modelling. However accessibility issues significantly limit the data acquired from such sites using traditional mapping methods. Geological exposures can also extend over 10s of square kilometres, resulting in a significantly under sampled and unrepresentative dataset. A more integrated approach to the analysis of the sedimentary architecture using a quantitative, digital- based characterisation of borehole cores and outcrops would enhance the accuracy of basin analysis. Although there have been significant advances in the accuracy of modelling the geometry of geological interfaces remotely using Terrestrial LiDAR Scanning (TLS), the definition of the rock volume itself has been restricted by severe limitations in the range and accuracy of the mineralogical and lithological information retrievable using photographs. While spectral reflectance based remote sensing methods have demonstrated some capabilities in resolving rock compositions the operational utility is severely restricted by the limited range and accuracy of minerals that can be detected and the effects of viewing configuration and illumination conditions. There is therefore an urgent requirement for a methodology that can remotely characterise the lithologies of interest to the oil and gas sector. Emission spectroscopy has a number of capabilities that can meet this requirement.
来源学科分类	Natural Environment Research
文献类型	项目
条目标识符	http://119.78.100.173/C666/handle/2XK7JSWQ/86259
专题	环境与发展全球科技态势
推荐引用方式 GB/T 7714	[unavailable].Quantitative 3D remote digital compositional and structural characterisation of outcrops.2016.