rdf-syntax-grammar
mods:
  schema location: http://www.loc.gov/mods/v3 http://www.loc.gov/standards/mods/v3/mods-3-2.xsd
  title info:
    title: Improved Upscaling & Well Placement Strategies for Tight Gas Reservoir Simulation and Management
  name:
    name part: Zhou, Yijie
    role:
      role term: creator
    role:
      role term: author.
  name:
    name part: King, Michael J. (Michael Joseph)
    role:
      role term: thesis advisor.
  name:
    name part: Texas A & M University
    role:
      role term: degree granting institution.
  type of resource: text
  genre: bibliography
  origin info:
    place:
      place term: txu
    date issued: 2013
    issuance: monographic
  language:
    language term: eng
  physical description:
    form: remote
    extent: 1 online resource.
  abstract: Tight gas reservoirs provide almost one quarter of the current U.S. domestic gas production, with significant projected increases in the next several decades in both the U.S. and abroad. These reservoirs constitute an important play type, with opportunities for improved reservoir simulation & management, such as simulation model design, well placement. Our work develops robust and efficient strategies for improved tight gas reservoir simulation and management. Reservoir simulation models are usually acquired by upscaling the detailed 3D geologic models. Earlier studies of flow simulation have developed layer-based coarse reservoir simulation models, from the more detailed 3D geologic models. However, the layer-based approach cannot capture the essential sand and flow. We introduce and utilize the diffusive time of flight to understand the pressure continuity within the fluvial sands, and develop novel adaptive reservoir simulation grids to preserve the continuity of the reservoir sands. Combined with the high resolution transmissibility based upscaling of flow properties, and well index based upscaling of the well connections, we can build accurate simulation models with at least one order magnitude simulation speed up, but the predicted recoveries are almost indistinguishable from those of the geologic models. General practice of well placement usually requires reservoir simulation to predict the dynamic reservoir response. Numerous well placement scenarios require many reservoir simulation runs, which may have significant CPU demands. We propose a novel simulation-free screening approach to generate a quality map, based on a combination of static and dynamic reservoir properties. The geologic uncertainty is taken into consideration through an uncertainty map form the spatial connectivity analysis and variograms. Combining the quality map and uncertainty map, good infill well locations and drilling sequence can be determined for improved reservoir management. We ap…
  note: by Yijie Zhou.
  note: "Major Subject: Petroleum Engineering."
  note: Includes vita.
  note: Doctor of Philosophy Texas A & M University 2013 http://hdl.handle.net/1969.1/151291
  note: Includes bibliographical references.
  note: Text (Dissertation)
  subject:
    topic: Major Petroleum Engineering
  subject:
    topic: Upgridding
  subject:
    topic: Upscaling
  subject:
    topic: Well Placement
  subject:
    topic: Pressure Approximation
  subject:
    topic: Tight Gas Reservoirs
  identifier: http://hdl.handle.net/1969.1/151291
  record info:
    record content source: TXA
    record creation date: 140303
    record change date: 20151206092215.0
    record identifier: in00003454928
    language of cataloging:
      language term: eng