View in EDS

Submergence depth modeling of oil well reservoirs and applications.

Saved in:
Bibliographic Details
Title: Submergence depth modeling of oil well reservoirs and applications.
Authors: Liu, Tianshi1 (AUTHOR) liutianshi@xsyu.edu.cn, Zheng, Min1 (AUTHOR), Song, Xinai1 (AUTHOR), Wu, Ying1 (AUTHOR), Zhang, Rong1 (AUTHOR)
Source: Journal of Petroleum Science & Engineering. Jan2022:Part B, Vol. 208, pN.PAG-N.PAG. 1p.
Subjects: Petroleum reservoirs, Oil wells, Linear differential equations, Curve fitting, Numerical calculations, Percolation theory, Potential energy
Abstract: In oilfield production, it is important to be able to acquire the reservoir status of oil wells in real time, especially for low or ultra-low permeability oil wells. In this paper, based on the reservoir percolation characteristics of the oil layer and combined with the oil well permeability, liquid pressure and oil well pressure formulas, the non-homogeneous linear differential equation for oil well pressure is derived, based on which a submergence depth model of oil well reservoirs is established. The parameter merging is applied to reduce the parameter dimension of the submergence depth model; this approach substantially reduces the parameter dimension and application complexity and effectively improves the model application range. The model not only conforms to the reservoir percolation law of the oil layer but also applies to the balance laws of other substances with potential energy balancing ability. The application methods studied (namely, the extraction of the greatest common divisor, the weighted dichotomy and least-squares curve fitting) successively reduce the calculation error and expand the application scope. The least-squares curve fitting method causes the submergence depth error to reach the minimum of the 2-norm, and the number of iterations can be accurately assessed by the convergence speed of halving the numerical calculation error in every iteration. This method is suitable not only for the zero submergence depth case in the initial state but also for non-zero submergence depth cases. The experimental results show that the proposed submergence depth model for oil well reservoirs accurately reflects the change laws of submergence depth and time. Combined with the proposed application methods, the corresponding submergence depth can be obtained at any time point. The model and application methods provide strong support for formulating scientific oil production plans and implementing reasonable production methods for oil wells. • The submergence depth model of the oil well reservoir is established. • The model is feasible for substances with potential energy balance capabilities. • The dimension of parameters is reduced to improve the usability of the model. • The numerical calculation methods with controllable precision are proposed. [ABSTRACT FROM AUTHOR]
Copyright of Journal of Petroleum Science & Engineering is the property of Elsevier B.V. and its content may not be copied or emailed to multiple sites without the copyright holder's express written permission. Additionally, content may not be used with any artificial intelligence tools or machine learning technologies. However, users may print, download, or email articles for individual use. This abstract may be abridged. No warranty is given about the accuracy of the copy. Users should refer to the original published version of the material for the full abstract. (Copyright applies to all Abstracts.)
Database: Engineering Source
FullText Text:
  Availability: 0
Header DbId: egs
DbLabel: Engineering Source
An: 153870991
AccessLevel: 6
PubType: Academic Journal
PubTypeId: academicJournal
PreciseRelevancyScore: 0
IllustrationInfo
Items – Name: Title
  Label: Title
  Group: Ti
  Data: Submergence depth modeling of oil well reservoirs and applications.
– Name: Author
  Label: Authors
  Group: Au
  Data: <searchLink fieldCode="AR" term="%22Liu%2C+Tianshi%22">Liu, Tianshi</searchLink><relatesTo>1</relatesTo> (AUTHOR)<i> liutianshi@xsyu.edu.cn</i><br /><searchLink fieldCode="AR" term="%22Zheng%2C+Min%22">Zheng, Min</searchLink><relatesTo>1</relatesTo> (AUTHOR)<br /><searchLink fieldCode="AR" term="%22Song%2C+Xinai%22">Song, Xinai</searchLink><relatesTo>1</relatesTo> (AUTHOR)<br /><searchLink fieldCode="AR" term="%22Wu%2C+Ying%22">Wu, Ying</searchLink><relatesTo>1</relatesTo> (AUTHOR)<br /><searchLink fieldCode="AR" term="%22Zhang%2C+Rong%22">Zhang, Rong</searchLink><relatesTo>1</relatesTo> (AUTHOR)
– Name: TitleSource
  Label: Source
  Group: Src
  Data: <searchLink fieldCode="JN" term="%22Journal+of+Petroleum+Science+%26+Engineering%22">Journal of Petroleum Science & Engineering</searchLink>. Jan2022:Part B, Vol. 208, pN.PAG-N.PAG. 1p.
– Name: Subject
  Label: Subjects
  Group: Su
  Data: <searchLink fieldCode="DE" term="%22Petroleum+reservoirs%22">Petroleum reservoirs</searchLink><br /><searchLink fieldCode="DE" term="%22Oil+wells%22">Oil wells</searchLink><br /><searchLink fieldCode="DE" term="%22Linear+differential+equations%22">Linear differential equations</searchLink><br /><searchLink fieldCode="DE" term="%22Curve+fitting%22">Curve fitting</searchLink><br /><searchLink fieldCode="DE" term="%22Numerical+calculations%22">Numerical calculations</searchLink><br /><searchLink fieldCode="DE" term="%22Percolation+theory%22">Percolation theory</searchLink><br /><searchLink fieldCode="DE" term="%22Potential+energy%22">Potential energy</searchLink>
– Name: Abstract
  Label: Abstract
  Group: Ab
  Data: In oilfield production, it is important to be able to acquire the reservoir status of oil wells in real time, especially for low or ultra-low permeability oil wells. In this paper, based on the reservoir percolation characteristics of the oil layer and combined with the oil well permeability, liquid pressure and oil well pressure formulas, the non-homogeneous linear differential equation for oil well pressure is derived, based on which a submergence depth model of oil well reservoirs is established. The parameter merging is applied to reduce the parameter dimension of the submergence depth model; this approach substantially reduces the parameter dimension and application complexity and effectively improves the model application range. The model not only conforms to the reservoir percolation law of the oil layer but also applies to the balance laws of other substances with potential energy balancing ability. The application methods studied (namely, the extraction of the greatest common divisor, the weighted dichotomy and least-squares curve fitting) successively reduce the calculation error and expand the application scope. The least-squares curve fitting method causes the submergence depth error to reach the minimum of the 2-norm, and the number of iterations can be accurately assessed by the convergence speed of halving the numerical calculation error in every iteration. This method is suitable not only for the zero submergence depth case in the initial state but also for non-zero submergence depth cases. The experimental results show that the proposed submergence depth model for oil well reservoirs accurately reflects the change laws of submergence depth and time. Combined with the proposed application methods, the corresponding submergence depth can be obtained at any time point. The model and application methods provide strong support for formulating scientific oil production plans and implementing reasonable production methods for oil wells. • The submergence depth model of the oil well reservoir is established. • The model is feasible for substances with potential energy balance capabilities. • The dimension of parameters is reduced to improve the usability of the model. • The numerical calculation methods with controllable precision are proposed. [ABSTRACT FROM AUTHOR]
– Name: AbstractSuppliedCopyright
  Label:
  Group: Ab
  Data: <i>Copyright of Journal of Petroleum Science & Engineering is the property of Elsevier B.V. and its content may not be copied or emailed to multiple sites without the copyright holder's express written permission. Additionally, content may not be used with any artificial intelligence tools or machine learning technologies. However, users may print, download, or email articles for individual use. This abstract may be abridged. No warranty is given about the accuracy of the copy. Users should refer to the original published version of the material for the full abstract.</i> (Copyright applies to all Abstracts.)
PLink https://search.ebscohost.com/login.aspx?direct=true&site=eds-live&db=egs&AN=153870991
RecordInfo BibRecord:
  BibEntity:
    Identifiers:
      – Type: doi
        Value: 10.1016/j.petrol.2021.109234
    Languages:
      – Code: eng
        Text: English
    PhysicalDescription:
      Pagination:
        PageCount: 1
        StartPage: N.PAG
    Subjects:
      – SubjectFull: Petroleum reservoirs
        Type: general
      – SubjectFull: Oil wells
        Type: general
      – SubjectFull: Linear differential equations
        Type: general
      – SubjectFull: Curve fitting
        Type: general
      – SubjectFull: Numerical calculations
        Type: general
      – SubjectFull: Percolation theory
        Type: general
      – SubjectFull: Potential energy
        Type: general
    Titles:
      – TitleFull: Submergence depth modeling of oil well reservoirs and applications.
        Type: main
  BibRelationships:
    HasContributorRelationships:
      – PersonEntity:
          Name:
            NameFull: Liu, Tianshi
      – PersonEntity:
          Name:
            NameFull: Zheng, Min
      – PersonEntity:
          Name:
            NameFull: Song, Xinai
      – PersonEntity:
          Name:
            NameFull: Wu, Ying
      – PersonEntity:
          Name:
            NameFull: Zhang, Rong
    IsPartOfRelationships:
      – BibEntity:
          Dates:
            – D: 15
              M: 01
              Text: Jan2022:Part B
              Type: published
              Y: 2022
          Identifiers:
            – Type: issn-print
              Value: 09204105
          Numbering:
            – Type: volume
              Value: 208
          Titles:
            – TitleFull: Journal of Petroleum Science & Engineering
              Type: main
ResultId 1