Database technology for deep marine clastic characterisation: upscaling for impact

GSTDTAP

项目编号	NE/P01691X/1
	Database technology for deep marine clastic characterisation: upscaling for impact
	William McCaffrey
主持机构	University of Leeds
项目开始年	2017
	2017-02-01
项目结束日期	2018-01-31
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 geological characteristics of subsurface sedimentary rocks control the amount of oil, gas and/or water present within them (as hydrocarbon reservoirs or aquifers), and how such fluids will flow. Petroleum geologists build three-dimensional numerical models to assess the likely amount and flow rates of oil and gas and optimum well locations. These models ultimately determine whether hydrocarbon production is successful. (Hydrogeologists develop corresponding geological models to predict water yield or contaminant transport, in order to inform aquifer exploitation and clean-up; such models are also required to assess the feasibility of programmes of underground carbon capture and storage). When these models are built, geologists have available only limited direct subsurface data with which to constrain the type and geometry of subsurface geological bodies and thus their fluid-flow characteristics. To complement the sparse direct data, exposed outcrops of similar types of rocks, or modern sedimentary environments where comparable sediments are deposited, can be used as 'analogues' to hydrocarbon reservoirs or aquifers. These analogues provide proxy information regarding geological features that determine reservoir or aquifer heterogeneity. Within a reservoir or aquifer, these geological heterogeneities exert a primary control on well connectivity, flow rates, and behaviour to production or clean-up strategies, thereby dictating how much oil or gas is likely to be produced from a reservoir, or whether contaminants are successfully removed from the groundwater. Quantitative analogue data on these geological heterogeneities are required as input for constraining geological models of the subsurface. The derivation of this type of data from databases is an integral part of subsurface modelling workflows, but current approaches are inadequate because of the limited volume and quality of data stored in existing databases, and their current poor integration with existing modelling tools. The Leeds IP consists of three different relational databases that contain analogue data about types of rock volumes that constitute the building blocks of geological models of reservoirs or aquifers; each database relates to a particular geological setting. All data are stored in a format that allows quantitative output to be produced, in forms that can be fed into all the common numerical methods used to build models of subsurface heterogeneity. The technology of the IP surpasses similar databases in terms of data quality and format. The fact that a fuller characterisation of sedimentary heterogeneity is achieved by these databases enables the derivation of the output required by existing modelling algorithms: this makes the IP unique in its class. However, the current value of the combined IP is limited by the relative underdevelopment of the Deep Marine Clastic database, and its current inability to integrate fully with software platforms employed to generate and manage geological models of the subsurface, such as Schlumberger's Petrel. Thus, the up-scaling of this database and the development of an interface for the optimal integration of the Deep Marine Clastic database with Petrel are key requirements for making this IP marketable, and leveraging the full value of the integrated databases. Upon successful development, the IP will enable easy access and application of large volumes of high-quality data in the area of Deep Marine Clastics, in parallel with that from other environments. This technology will aid geologists and engineers in the hydrocarbon and water-management industries in the generation of geologically sensible reservoir and aquifer models. The project will be undertaken by Marco Patacci, currently a PDRA at Leeds, and supervised by Bill McCaffrey, who is a sedimentologist and director of the Turbidites Research Group, and Nigel Mountney (sedimentologist).
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/86551
专题	环境与发展全球科技态势
推荐引用方式 GB/T 7714	William McCaffrey.Database technology for deep marine clastic characterisation: upscaling for impact.2017.