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Stanley C Stephenson, 97Grapevine, TX

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Grapevine, TX   

Park Rapids, MN   

Becker, MN   

15528 300Th St, Sebeka, MN 56477   

Wayzata, MN   

Lubbock, TX   

Sheldon, IA   

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Publications & IP owners

Us Patents

Methods For Combining Well Test Analysis With Wavelet Analysis

US Patent:
6347283, Feb 12, 2002
Filed:
Jul 10, 2000
Appl. No.:
09/612746
Inventors:
Mohamed Soliman - Plano TX
Stanley V. Stephenson - Duncan OK
Assignee:
Halliburton Energy Services, Inc. - Dallas TX
International Classification:
G01V 318
US Classification:
702 6
Abstract:
The invention provides methods for combining well test analysis with wavelet analysis wherein the use of wavelet analysis with conventionally acquired well data provides verification of the well data. The methods include the steps of acquiring downhole data, converting the data to a first electronic signal, performing wavelet analysis of the first electronic signal to produce a second electronic signal, and using the second electronic signal to aid in the interpretation of the first electronic signal and/or to instigate corrective steps to ensure that the desired parameters of the well environment are accurately represented by the first electronic signal. Some or all of the steps may be performed in real-time.

Neural-Network Based Surrogate Model Construction Methods And Applications Thereof

US Patent:
8065244, Nov 22, 2011
Filed:
Mar 13, 2008
Appl. No.:
12/048045
Inventors:
Dingding Chen - Plano TX, US
Allan Zhong - Plano TX, US
Syed Hamid - Dallas TX, US
Stanley Stephenson - Duncan OK, US
Assignee:
Halliburton Energy Services, Inc. - Houston TX
International Classification:
G06E 1/00
G06E 3/00
G06F 15/18
G06G 7/00
G06N 3/02
US Classification:
706 15, 706 12, 706 13, 706 14, 706 16, 706 19
Abstract:
Various neural-network based surrogate model construction methods are disclosed herein, along with various applications of such models. Designed for use when only a sparse amount of data is available (a “sparse data condition”), some embodiments of the disclosed systems and methods: create a pool of neural networks trained on a first portion of a sparse data set; generate for each of various multi-objective functions a set of neural network ensembles that minimize the multi-objective function; select a local ensemble from each set of ensembles based on data not included in said first portion of said sparse data set; and combine a subset of the local ensembles to form a global ensemble. This approach enables usage of larger candidate pools, multi-stage validation, and a comprehensive performance measure that provides more robust predictions in the voids of parameter space.

Corrosion Resistant Fluid End For Well Service Pumps

US Patent:
2013016, Jun 27, 2013
Filed:
Dec 21, 2011
Appl. No.:
13/332452
Inventors:
Terry H. McCoy - Addison TX, US
David M. Stribling - Duncan OK, US
John Dexter Brunet - Duncan OK, US
Stanley V. Stephenson - Duncan OK, US
Timothy A. Freeney - Singapore, SG
Assignee:
Halliburton Energy Services, Inc. - Houston TX
International Classification:
E21B 43/26
F15D 1/00
US Classification:
1663081, 137 1501
Abstract:
The present invention relates to the use of corrosion resistant alloys in fluid ends to prolong the life of a well service pump. One embodiment of the present invention provides a method of providing a fluid end that has a corrosion resistant alloy having a fatigue limit greater than or equal to the tensile stress on the fluid end at maximum working pressure in the fluid end for an aqueous-based fluid; installing the fluid end in a well service pump; and pumping the aqueous-based fluid through the fluid end.

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