GB2379513A - Downhole sensing and flow control utilizing neural networks - Google Patents

Downhole sensing and flow control utilizing neural networks

Info

Publication number
GB2379513A
GB2379513A GB0230175A GB0230175A GB2379513A GB 2379513 A GB2379513 A GB 2379513A GB 0230175 A GB0230175 A GB 0230175A GB 0230175 A GB0230175 A GB 0230175A GB 2379513 A GB2379513 A GB 2379513A
Authority
GB
United Kingdom
Prior art keywords
sensor
flow control
neural networks
temporary
control utilizing
Prior art date
Legal status (The legal status is an assumption and is not a legal conclusion. Google has not performed a legal analysis and makes no representation as to the accuracy of the status listed.)
Granted
Application number
GB0230175A
Other versions
GB2379513B (en
GB0230175D0 (en
Inventor
Roger L Schultz
Jr Bruce H Storm
John Dennis
John M Richardson
Current Assignee (The listed assignees may be inaccurate. Google has not performed a legal analysis and makes no representation or warranty as to the accuracy of the list.)
Halliburton Energy Services Inc
Original Assignee
Halliburton Energy Services Inc
Priority date (The priority date is an assumption and is not a legal conclusion. Google has not performed a legal analysis and makes no representation as to the accuracy of the date listed.)
Filing date
Publication date
Application filed by Halliburton Energy Services Inc filed Critical Halliburton Energy Services Inc
Publication of GB0230175D0 publication Critical patent/GB0230175D0/en
Publication of GB2379513A publication Critical patent/GB2379513A/en
Application granted granted Critical
Publication of GB2379513B publication Critical patent/GB2379513B/en
Anticipated expiration legal-status Critical
Expired - Fee Related legal-status Critical Current

Links

Classifications

    • E—FIXED CONSTRUCTIONS
    • E21—EARTH DRILLING; MINING
    • E21B—EARTH DRILLING, e.g. DEEP DRILLING; OBTAINING OIL, GAS, WATER, SOLUBLE OR MELTABLE MATERIALS OR A SLURRY OF MINERALS FROM WELLS
    • E21B49/00—Testing the nature of borehole walls; Formation testing; Methods or apparatus for obtaining samples of soil or well fluids, specially adapted to earth drilling or wells
    • E21B49/008—Testing the nature of borehole walls; Formation testing; Methods or apparatus for obtaining samples of soil or well fluids, specially adapted to earth drilling or wells by injection test; by analysing pressure variations in an injection or production test, e.g. for estimating the skin factor
    • E—FIXED CONSTRUCTIONS
    • E21—EARTH DRILLING; MINING
    • E21B—EARTH DRILLING, e.g. DEEP DRILLING; OBTAINING OIL, GAS, WATER, SOLUBLE OR MELTABLE MATERIALS OR A SLURRY OF MINERALS FROM WELLS
    • E21B47/00—Survey of boreholes or wells
    • E—FIXED CONSTRUCTIONS
    • E21—EARTH DRILLING; MINING
    • E21B—EARTH DRILLING, e.g. DEEP DRILLING; OBTAINING OIL, GAS, WATER, SOLUBLE OR MELTABLE MATERIALS OR A SLURRY OF MINERALS FROM WELLS
    • E21B2200/00—Special features related to earth drilling for obtaining oil, gas or water
    • E21B2200/22—Fuzzy logic, artificial intelligence, neural networks or the like
    • E—FIXED CONSTRUCTIONS
    • E21—EARTH DRILLING; MINING
    • E21B—EARTH DRILLING, e.g. DEEP DRILLING; OBTAINING OIL, GAS, WATER, SOLUBLE OR MELTABLE MATERIALS OR A SLURRY OF MINERALS FROM WELLS
    • E21B47/00—Survey of boreholes or wells
    • E21B47/10—Locating fluid leaks, intrusions or movements

Abstract

Methods are provided for downhole sensing and flow control utilizing neural networks. In a described embodiment, a temporary sensor (DSn) is positioned downhole with a permanent sensor (SSn) at the surface. Outputs of the temporary and permanent sensor are recorded as training data sets. A neural network is trained using the training data sets. When the temporary sensor is no longer present or no longer operational in the well, the neural network is capable of determining the temporary sensor's output in response to the input to the neural network of the permanent sensor's output.
GB0230175A 2001-02-16 2001-02-16 Downhole sensing and flow control utilizing neural networks Expired - Fee Related GB2379513B (en)

Applications Claiming Priority (1)

Application Number Priority Date Filing Date Title
PCT/US2001/005123 WO2002066791A1 (en) 2001-02-16 2001-02-16 Downhole sensing and flow control utilizing neural networks

Publications (3)

Publication Number Publication Date
GB0230175D0 GB0230175D0 (en) 2003-02-05
GB2379513A true GB2379513A (en) 2003-03-12
GB2379513B GB2379513B (en) 2005-06-29

Family

ID=21742345

Family Applications (1)

Application Number Title Priority Date Filing Date
GB0230175A Expired - Fee Related GB2379513B (en) 2001-02-16 2001-02-16 Downhole sensing and flow control utilizing neural networks

Country Status (2)

Country Link
GB (1) GB2379513B (en)
WO (1) WO2002066791A1 (en)

Families Citing this family (1)

* Cited by examiner, † Cited by third party
Publication number Priority date Publication date Assignee Title
US10495778B2 (en) 2015-11-19 2019-12-03 Halliburton Energy Services, Inc. System and methods for cross-tool optical fluid model validation and real-time application

Citations (7)

* Cited by examiner, † Cited by third party
Publication number Priority date Publication date Assignee Title
WO1998024010A1 (en) * 1996-11-27 1998-06-04 Siemens Aktiengesellschaft Method for neural modelling the forms of dependency of a technical system upon parameters
US5828981A (en) * 1995-05-11 1998-10-27 Texaco Inc. Generating pore types and synthetic capillary pressure curves from wireline logs using neural networks
EP0877309A1 (en) * 1997-05-07 1998-11-11 Ford Global Technologies, Inc. Virtual vehicle sensors based on neural networks trained using data generated by simulation models
EP0881357A2 (en) * 1997-05-06 1998-12-02 Halliburton Energy Services, Inc. Method for controlling the development of an oil or gas reservoir
US6041856A (en) * 1998-01-29 2000-03-28 Patton Enterprises, Inc. Real-time pump optimization system
US6044325A (en) * 1998-03-17 2000-03-28 Western Atlas International, Inc. Conductivity anisotropy estimation method for inversion processing of measurements made by a transverse electromagnetic induction logging instrument
WO2000031654A2 (en) * 1998-11-19 2000-06-02 Intelligent Inspection Corporation Apparatus and method of well management

Patent Citations (7)

* Cited by examiner, † Cited by third party
Publication number Priority date Publication date Assignee Title
US5828981A (en) * 1995-05-11 1998-10-27 Texaco Inc. Generating pore types and synthetic capillary pressure curves from wireline logs using neural networks
WO1998024010A1 (en) * 1996-11-27 1998-06-04 Siemens Aktiengesellschaft Method for neural modelling the forms of dependency of a technical system upon parameters
EP0881357A2 (en) * 1997-05-06 1998-12-02 Halliburton Energy Services, Inc. Method for controlling the development of an oil or gas reservoir
EP0877309A1 (en) * 1997-05-07 1998-11-11 Ford Global Technologies, Inc. Virtual vehicle sensors based on neural networks trained using data generated by simulation models
US6041856A (en) * 1998-01-29 2000-03-28 Patton Enterprises, Inc. Real-time pump optimization system
US6044325A (en) * 1998-03-17 2000-03-28 Western Atlas International, Inc. Conductivity anisotropy estimation method for inversion processing of measurements made by a transverse electromagnetic induction logging instrument
WO2000031654A2 (en) * 1998-11-19 2000-06-02 Intelligent Inspection Corporation Apparatus and method of well management

Non-Patent Citations (2)

* Cited by examiner, † Cited by third party
Title
A Murray et al, Society of Petroleum Engineers, No.56904, 7-9 Sept 1999, pages 1-8. *
D. Dashevskiy et al, Society of Petroleum engineers, No.56442, 3-6 October 1999 pages 1-8. *

Also Published As

Publication number Publication date
GB2379513B (en) 2005-06-29
GB0230175D0 (en) 2003-02-05
WO2002066791A8 (en) 2003-11-13
WO2002066791A1 (en) 2002-08-29

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Legal Events

Date Code Title Description
PCNP Patent ceased through non-payment of renewal fee

Effective date: 20120216