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Title: MSE based drilling optimization using neural network simulaton

Abstract

The method disclosed receives a data stream from an MWD system and determines the response of a specific energy (SE) relationship and a rate of penetration (ROP) relationship respectively to variables controllable by the operator, in order to enable operation at a lowest SE, or a highest Rate-of-Penetration (ROP) to SE ratio. The method utilizes artificial neural networks trained by MWD data to deduce a depth-of-cut and torque based on relationships manifesting between the various data points collected, and an SE equation and a predicted ROP is evaluated over a series of probable operating points. The method continuously gathers and analyzes MWD data during the drilling operation and allows an operator to manage the controllable parameters such that operation at the lowest SE or highest ROP or ROP to SE ratio can be achieved during the drilling operation.

Inventors:
Issue Date:
Research Org.:
US Department of Energy (USDOE), Washington DC (United States)
Sponsoring Org.:
USDOE
OSTI Identifier:
1525026
Patent Number(s):
10221671
Application Number:
14/799,753
Assignee:
U.S. Department of Energy (Washington, DC)
Patent Classifications (CPCs):
G - PHYSICS G06 - COMPUTING G06N - COMPUTER SYSTEMS BASED ON SPECIFIC COMPUTATIONAL MODELS
E - FIXED CONSTRUCTIONS E21 - EARTH DRILLING E21B - EARTH DRILLING, e.g. DEEP DRILLING
Resource Type:
Patent
Resource Relation:
Patent File Date: 2015-07-15
Country of Publication:
United States
Language:
English

Citation Formats

Zhang, Wu. MSE based drilling optimization using neural network simulaton. United States: N. p., 2019. Web.
Zhang, Wu. MSE based drilling optimization using neural network simulaton. United States.
Zhang, Wu. Tue . "MSE based drilling optimization using neural network simulaton". United States. https://www.osti.gov/servlets/purl/1525026.
@article{osti_1525026,
title = {MSE based drilling optimization using neural network simulaton},
author = {Zhang, Wu},
abstractNote = {The method disclosed receives a data stream from an MWD system and determines the response of a specific energy (SE) relationship and a rate of penetration (ROP) relationship respectively to variables controllable by the operator, in order to enable operation at a lowest SE, or a highest Rate-of-Penetration (ROP) to SE ratio. The method utilizes artificial neural networks trained by MWD data to deduce a depth-of-cut and torque based on relationships manifesting between the various data points collected, and an SE equation and a predicted ROP is evaluated over a series of probable operating points. The method continuously gathers and analyzes MWD data during the drilling operation and allows an operator to manage the controllable parameters such that operation at the lowest SE or highest ROP or ROP to SE ratio can be achieved during the drilling operation.},
doi = {},
journal = {},
number = ,
volume = ,
place = {United States},
year = {2019},
month = {3}
}

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Works referenced in this record:

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patent, April 2008


Methods for evaluating and improving drilling operations
patent, March 2006


Wellbore operations monitoring and control systems and methods
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