Invention Grant
- Patent Title: Big data point and vector model
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Application No.: US15755829Application Date: 2015-11-03
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Publication No.: US10775531B2Publication Date: 2020-09-15
- Inventor: Harold Grayson Walters , Ronald Glen Dusterhoft , Jeffrey Marc Yarus
- Applicant: Halliburton Energy Services, Inc.
- Applicant Address: US TX Houston
- Assignee: Halliburton Energy Services, Inc.
- Current Assignee: Halliburton Energy Services, Inc.
- Current Assignee Address: US TX Houston
- Agency: Baker Botts L.L.P.
- Agent John W. Wustenberg
- International Application: PCT/US2015/058748 WO 20151103
- International Announcement: WO2017/058267 WO 20170406
- Main IPC: G01V1/40
- IPC: G01V1/40 ; G01V99/00 ; E21B43/00 ; E21B47/00 ; E21B47/024 ; E21B49/00 ; E21B49/08 ; G06F30/20

Abstract:
Systems and methods for generating and storing measurements in point and vector format for a plurality of formations of reservoirs. In one embodiment, the methods comprise generating a set of measurements corresponding to a plurality of formations, reservoirs, or wellbores; determining physical locations for the set of measurements, wherein the physical locations are represented in a point and vector representation; associating the vector representations with the determined physical locations, wherein the vector representations comprise at least a magnitude and a direction derived from the measurement; wherein the magnitude and direction tracks the physical location in space and time; manipulating the set of measurements such that a change in physical location is updated in the vector representation; generating a repository of vector representations accessible to determine an optimal completion design for a set of parameters for a subterranean formation.
Public/Granted literature
- US20180329113A1 BIG DATA POINT AND VECTOR MODEL Public/Granted day:2018-11-15
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