Resumes
Resumes
James Belaskie Phones & Addresses
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Stafford, TX
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Canutillo, TX
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4407 Plantation Creek Dr, Missouri City, TX 77459 (281) 499-2912
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Houston, TX
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Sugar Land, TX
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New York, NY
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Lafayette, LA
Work
Position:
Service Occupations
Education
Degree:
High school graduate or higher
Emails
Publications
Us Patents
Drilling Control
View pageUS Patent:
20230012511, Jan 19, 2023
Filed:
Dec 18, 2020
Appl. No.:
17/758034
Inventors:
- Sugar Land TX, US
James Belaskie - Houston TX, US
James Belaskie - Houston TX, US
International Classification:
E21B 47/12
E21B 47/04
E21B 44/00
E21B 47/04
E21B 44/00
Abstract:
A method can include receiving block position data of a rig prior to addition of a length of pipe to a drillstring, where the drillstring is disposed at least in part in a borehole and supported by the rig; receiving block position data of the rig after addition of the length of pipe to the drillstring; and controlling position of the drillstring with respect to time using the rig and at least a portion of the block position data for landing a drill bit of the drillstring on a bottom of the borehole.
Real-Time Well Construction Process Inference Through Probabilistic Data Fusion
View pageUS Patent:
20210285316, Sep 16, 2021
Filed:
Jun 27, 2018
Appl. No.:
16/605799
Inventors:
- Sugar Land TX, US
Sylvain Chambon - Katy TX, US
James P. Belaskie - Missouri City TX, US
Yingwei Yu - Katy TX, US
Mohammad Khairi Hamzah - Katy TX, US
Sylvain Chambon - Katy TX, US
James P. Belaskie - Missouri City TX, US
Yingwei Yu - Katy TX, US
Mohammad Khairi Hamzah - Katy TX, US
International Classification:
E21B 44/10
E21B 47/12
G06N 7/00
E21B 47/12
G06N 7/00
Abstract:
A method includes acquiring data during rig operations where the rig operations include operations that utilize a bit to drill rock and where the data include different types of data; analyzing the data utilizing a probabilistic mixture model for modes, a detection engine for trends and a network model for an inference based at least in part on at least one of a mode and a trend; and outputting information as to the inference where the inference characterizes a relationship between the bit and the rock
System And Method For Controlling Drilling Process
View pageUS Patent:
20150369031, Dec 24, 2015
Filed:
Feb 5, 2013
Appl. No.:
14/765857
Inventors:
- Sugar Land TX, US
James P. Belaskie - Missouri City TX, US
Jose Luis Sanchez Flores - Austin TX, US
Richard Harmer - Houston TX, US
James P. Belaskie - Missouri City TX, US
Jose Luis Sanchez Flores - Austin TX, US
Richard Harmer - Houston TX, US
International Classification:
E21B 44/04
E21B 4/02
G05B 13/04
E21B 7/06
E21B 4/02
G05B 13/04
E21B 7/06
Abstract:
Techniques for optimizing automated drilling processes are disclosed. Such techniques include modeling a formation and selecting a drilling trajectory in the formation. Measurements of rate of penetration (ROP), revolutions per minute (RPM), weight-on-bit (WOB) and torque-on-bit (TOB) of a drilling string at a position on the drilling trajectory in the formation are received. A functional relationship between depth of cut (DOC), WOB, and TOB for the modeled formation is determined. Operating constraints defining a safe operating envelope as a function of RPM and WOB along the selected drilling trajectory are determined, and an optimal RPM and WOB is determined based on operating constraints. A cost function of RPM and WOB is determined, and a path from current RPM and WOB to optimal RPM and WOB is determined based on the cost function.
System And Method For Online Automation
View pageUS Patent:
20140343694, Nov 20, 2014
Filed:
Aug 1, 2014
Appl. No.:
14/449407
Inventors:
- Sugar Land TX, US
Jonathan Dunlop - Cambridge, GB
James Belaskie - Stafford TX, US
Jonathan Dunlop - Cambridge, GB
James Belaskie - Stafford TX, US
International Classification:
G05B 13/04
E21B 41/00
E21B 41/00
US Classification:
700 30, 700275
Abstract:
A changepoint detector for modeling data received from at least one sensor in a process in the hydrocarbon industry. The data is segmented into a plurality of segments and for each segment a model is assigned and the data corresponding to the segment fit to that model. A plurality of segmentations are thus provided and these segmentations are evaluated and assigned weights indicative of the fit of the models of the segmentation to the underlying data. The segmentation models are further used to calculate a result that may be input to a process control program.