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Smart-GeoWells: Smart technologies for optimal design, drilling, completion and management of geothermal wells

Smart-GeoWells: Smart technologies for optimal design, drilling, completion and management of geothermal wells
智能地热井:用于地热井优化设计、钻探、完井和管理的智能技术
批准号:
EP/R005761/1
负责人:
Christopher Pain
金额:
$62.55万
依托单位:
依托单位国家:
英国
项目类别:
Research Grant
财政年份:
2017
资助国家:
英国
项目状态:
已结题
起止时间:
2017 至 --

项目摘要

项目成果

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中文摘要
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英文摘要
A novel product will be developed for designing, drilling, completing and managing well systems that incorporate many laterals with increased reservoir contact for geothermal industry. A hybrid drilling approach, based on conventional and jetting (water and supercritical-CO2) technologies, will be employed along with advanced numerical models to help optimise the deployment and management of the well system. The product targets the fast-growing geothermal industry, and can be readily re-applied to oil/gas production, with a particular focus on intermediate-deep geothermal resources. Objectives of this work include: (1) application of advanced well drilling and completion technologies for more efficient well system construction; (2) evaluation of new-generation numerical models for solving fluid flow and heat transfer problems in complex well-reservoir systems, (3) optimisation of well design and management for cost-effective production, and (4) deployment of the product to geothermal reservoirs for field trials. The novelty of this project comes from the unique combination of new drilling and completion technologies with novel computational methodologies for well management and production.China's current energy demands require innovative, cost-effective and environment-friendly solutions. We are proposing an innovative multi-lateral well system Smart-GeoWells to help meet these challenges. This will be used to develop cleaner, more affordable, localised (building, village, town, city) heating/hot water and electricity, harnessing almost limitless, sustainable and secure geothermal energy. In order to develop the new multi-lateral wells (with potentially hundreds of laterals), the proposed team (each member a world-leader in their fields) will apply their specialised knowledge in testing and exploiting the new well engineering solutions, hybrid drilling technologies, advanced numerical modelling and optimal well design and management methods. For the UK and China teams, this will be the first stepping stone towards long-term collaboration, aiming at optimal exploitation of geothermal resources and if successful will have a massive impact on the energy sector. However, the scope of the work is also immense and thus our initial product (that we aim to develop rapidly) will be focussed on geothermal hot water production, although the developed technology can serve as a longer term product for geothermal electricity generation as well as O&G production. The new multi-lateral drilling concepts of XLTL (project partner) together with the novel techniques in modelling multiphase fluid flows and heat transfer through these large number of laterals (similar to the fishbone structure), will lead to economic and efficient ways of drilling financially-competitive multi-lateral wells through: a) enhanced contact and connectivity with geothermal regions; b) minimisation of environmental damage i.e. pollution of groundwater sources/surrounding countryside and c) optimal control/management of the production wells. During the project, Sinopec will provide geothermal sites, test equipment and specialised engineers/technicans for field trials (the company's funding contribution amounts to 5 million RMB) with which the advanced drilling techniques will be examined and the prediction software will be validated. The developed Smart-GeoWells platform will be made available to the interested local and other companies/businesses, as well as public services, and will also benefit them through enhanced knowledge and technology transfer. The longer-term implications on the welfare of the local and other communities are immense, both directly through reduced pollution (water and air) and climate change impacts and, indirectly, through economic impacts.
期刊论文(10)
专著(0)
科研奖励(0)
会议论文
Dynamic adaptive mesh optimisation for immiscible viscous fingering
不混溶粘性指法的动态自适应网格优化
DOI: 10.1007/s10596-020-09938-5
发表时间: 2020
期刊: Computational Geosciences
影响因子: 2.5
作者: [Kampitsis A]
通讯作者: Kampitsis A
An efficient goal-based reduced order model approach for targeted adaptive observations
一种有效的基于目标的降阶模型方法,用于有针对性的自适应观测
DOI: 10.1002/fld.4265
发表时间: 2017
期刊: International Journal for Numerical Methods in Fluids
影响因子: 1.8
作者: [Fang F., Pain C. C., Navon Ionel M., Xiao D.]
通讯作者: Xiao D.
Modelling the reservoir-to-tubing pressure drop imposed by multiple autonomous inflow control devices installed in a single completion joint in a horizontal well
对安装在水平井单个完井接头中的多个自主流入控制装置施加的油藏至油管压降进行建模
DOI: 10.1016/j.petrol.2020.106991
发表时间: 2020
期刊: Journal of Petroleum Science and Engineering
影响因子: --
作者: [Lei Q]
通讯作者: Lei Q
DOI: --
发表时间: 2018-04
期刊: ArXiv
影响因子: --
作者: [C. Heaney;P. Salinas;F. Fang;C. Pain;Ionel M. Navon]
通讯作者: C. Heaney;P. Salinas;F. Fang;C. Pain;Ionel M. Navon
7
    Health assessment across biological length scales for personal pollution exposure and its mitigation (INHALE)
    • 批准号:
      EP/T003189/1
    • 项目类别:
      Research Grant
    • 资助金额:
      $356.0万
    • 财政年份:
      2019
    • 负责人:
      Christopher Pain
    • 依托单位:
    Investigation of the safe removal of fuel debris: multi-physics simulation
    • 批准号:
      EP/P013198/1
    • 项目类别:
      Research Grant
    • 资助金额:
      $64.22万
    • 财政年份:
      2016
    • 负责人:
      Christopher Pain
    • 依托单位:
    Reactor core-structure re-location modelling for severe nuclear accidents
    • 批准号:
      EP/M012794/1
    • 项目类别:
      Research Grant
    • 资助金额:
      $31.1万
    • 财政年份:
      2014
    • 负责人:
      Christopher Pain
    • 依托单位:
    MBase: The Molecular Basis of Advanced Nuclear Fuel Separations
    • 批准号:
      EP/I003002/1
    • 项目类别:
      Research Grant
    • 资助金额:
      $16.84万
    • 财政年份:
      2010
    • 负责人:
      Christopher Pain
    • 依托单位:
    海外基金