View in EDS

Real-Time Diagnostics of Gas Lift Systems Using Intelligent Agents: A Case Study.

Saved in:
Bibliographic Details
Title: Real-Time Diagnostics of Gas Lift Systems Using Intelligent Agents: A Case Study.
Authors: Stephenson, G.1, Molotkov, R.2, De Guzman, N.3, Lafferty, L.4
Source: SPE Production & Operations. Feb2010, Vol. 25 Issue 1, p111-123. 13p. 12 Diagrams, 6 Graphs.
Subjects: Gas well drilling, Gas wells, Oil well gas lift, Production methods in oil fields, Oil well artificial lift, Gas lift pumps
Abstract: This paper describes a new method to continuously monitor and diagnose the condition of wells producing through continuous gas lift. The paper describes the application of this system in a mature onshore gas lift field in the western United States and the results obtained. A central problem related to the operation of gas lift wells is the ability to identify underperforming wells and to address the underlying issues appropriately and in a timely manner. This problem is compounded by the trend toward leaner operations and relative scarcity of application-specific domain knowledge. The purpose of this method is to address these issues by leveraging real-time data, gas lift domain expertise, and proven steady-state analysis techniques in a desktop software application. This system performs four key functions: Monitoring the wells' condition by collecting data, assessing the meaning of these data, recommending actions for correcting problems and responding to threats, and explaining recommendations. The performance of the system has met initial expectations and has provided additional unforeseen benefits. This paper cites specific cases that compare agent predictions to expert diagnoses and quantify the benefits of taking the recommended actions. What was found was that while the correct diagnoses of well performance issues was beneficial, the real benefit was in allowing production engineers to analyze a greater number of wells in far less time. To that end, the paper will discuss the role of this system as it relates to the overall production management workflow. The success of this project has demonstrated that intelligent agents can effectively perform functions historically performed by a handful of experts. The paper will discuss key system-design features that enable this level of functionality as well as other potential areas in which the technology can be extended in the future. [ABSTRACT FROM AUTHOR]
Copyright of SPE Production & Operations is the property of Society of Petroleum Engineers, Inc. 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: 48502421
AccessLevel: 6
PubType: Academic Journal
PubTypeId: academicJournal
PreciseRelevancyScore: 0
IllustrationInfo
Items – Name: Title
  Label: Title
  Group: Ti
  Data: Real-Time Diagnostics of Gas Lift Systems Using Intelligent Agents: A Case Study.
– Name: Author
  Label: Authors
  Group: Au
  Data: <searchLink fieldCode="AR" term="%22Stephenson%2C+G%2E%22">Stephenson, G.</searchLink><relatesTo>1</relatesTo><br /><searchLink fieldCode="AR" term="%22Molotkov%2C+R%2E%22">Molotkov, R.</searchLink><relatesTo>2</relatesTo><br /><searchLink fieldCode="AR" term="%22De+Guzman%2C+N%2E%22">De Guzman, N.</searchLink><relatesTo>3</relatesTo><br /><searchLink fieldCode="AR" term="%22Lafferty%2C+L%2E%22">Lafferty, L.</searchLink><relatesTo>4</relatesTo>
– Name: TitleSource
  Label: Source
  Group: Src
  Data: <searchLink fieldCode="JN" term="%22SPE+Production+%26+Operations%22">SPE Production & Operations</searchLink>. Feb2010, Vol. 25 Issue 1, p111-123. 13p. 12 Diagrams, 6 Graphs.
– Name: Subject
  Label: Subjects
  Group: Su
  Data: <searchLink fieldCode="DE" term="%22Gas+well+drilling%22">Gas well drilling</searchLink><br /><searchLink fieldCode="DE" term="%22Gas+wells%22">Gas wells</searchLink><br /><searchLink fieldCode="DE" term="%22Oil+well+gas+lift%22">Oil well gas lift</searchLink><br /><searchLink fieldCode="DE" term="%22Production+methods+in+oil+fields%22">Production methods in oil fields</searchLink><br /><searchLink fieldCode="DE" term="%22Oil+well+artificial+lift%22">Oil well artificial lift</searchLink><br /><searchLink fieldCode="DE" term="%22Gas+lift+pumps%22">Gas lift pumps</searchLink>
– Name: Abstract
  Label: Abstract
  Group: Ab
  Data: This paper describes a new method to continuously monitor and diagnose the condition of wells producing through continuous gas lift. The paper describes the application of this system in a mature onshore gas lift field in the western United States and the results obtained. A central problem related to the operation of gas lift wells is the ability to identify underperforming wells and to address the underlying issues appropriately and in a timely manner. This problem is compounded by the trend toward leaner operations and relative scarcity of application-specific domain knowledge. The purpose of this method is to address these issues by leveraging real-time data, gas lift domain expertise, and proven steady-state analysis techniques in a desktop software application. This system performs four key functions: Monitoring the wells' condition by collecting data, assessing the meaning of these data, recommending actions for correcting problems and responding to threats, and explaining recommendations. The performance of the system has met initial expectations and has provided additional unforeseen benefits. This paper cites specific cases that compare agent predictions to expert diagnoses and quantify the benefits of taking the recommended actions. What was found was that while the correct diagnoses of well performance issues was beneficial, the real benefit was in allowing production engineers to analyze a greater number of wells in far less time. To that end, the paper will discuss the role of this system as it relates to the overall production management workflow. The success of this project has demonstrated that intelligent agents can effectively perform functions historically performed by a handful of experts. The paper will discuss key system-design features that enable this level of functionality as well as other potential areas in which the technology can be extended in the future. [ABSTRACT FROM AUTHOR]
– Name: AbstractSuppliedCopyright
  Label:
  Group: Ab
  Data: <i>Copyright of SPE Production & Operations is the property of Society of Petroleum Engineers, Inc. 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=48502421
RecordInfo BibRecord:
  BibEntity:
    Identifiers:
      – Type: doi
        Value: 10.2118/124926-PA
    Languages:
      – Code: eng
        Text: English
    PhysicalDescription:
      Pagination:
        PageCount: 13
        StartPage: 111
    Subjects:
      – SubjectFull: Gas well drilling
        Type: general
      – SubjectFull: Gas wells
        Type: general
      – SubjectFull: Oil well gas lift
        Type: general
      – SubjectFull: Production methods in oil fields
        Type: general
      – SubjectFull: Oil well artificial lift
        Type: general
      – SubjectFull: Gas lift pumps
        Type: general
    Titles:
      – TitleFull: Real-Time Diagnostics of Gas Lift Systems Using Intelligent Agents: A Case Study.
        Type: main
  BibRelationships:
    HasContributorRelationships:
      – PersonEntity:
          Name:
            NameFull: Stephenson, G.
      – PersonEntity:
          Name:
            NameFull: Molotkov, R.
      – PersonEntity:
          Name:
            NameFull: De Guzman, N.
      – PersonEntity:
          Name:
            NameFull: Lafferty, L.
    IsPartOfRelationships:
      – BibEntity:
          Dates:
            – D: 01
              M: 02
              Text: Feb2010
              Type: published
              Y: 2010
          Identifiers:
            – Type: issn-print
              Value: 19301855
          Numbering:
            – Type: volume
              Value: 25
            – Type: issue
              Value: 1
          Titles:
            – TitleFull: SPE Production & Operations
              Type: main
ResultId 1