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Method and System for Automated Data Mining of Well Service Job Data

IP.com Disclosure Number: IPCOM000239335D
Publication Date: 2014-Oct-30
Document File: 9 page(s) / 421K

Publishing Venue

The IP.com Prior Art Database

Abstract

The oil and gas industry demands a diverse set of mechanical and technological capabilities as it has voluminous data from seismic, drilling, completion and production. A technical data mining application platform having built-in methodical tools will aid field engineers in retrieval of relevant information. Such an application, when combined with real time data collection and live notification capabilities, can help improve the operational productivity. Continuous surveillance and monitoring of the wells improves productivity. This application acts as an enabler for extracting relevant information in order to improve predictive models, make more reliable decisions, and ultimately, sustaining existing and creating new business opportunities.

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Method and System for Automated Data Mining of Well Service Job Data

2014-IP-095848

Walter A. Gaber & Pooja Nitin Khanapurkar

Abstract:

The oil and gas industry demands a diverse set of mechanical and technological capabilities as it has voluminous data from seismic, drilling, completion and production. 

A technical data mining application platform having built-in methodical tools will aid field engineers in retrieval of relevant information. Such an application, when combined with real time data collection and live notification capabilities, can help improve the operational productivity. Continuous surveillance and monitoring of the wells improves productivity.

This application acts as an enabler for extracting relevant information in order to improve predictive models, make more reliable decisions, and ultimately, sustaining existing and creating new business opportunities.

Introduction:

In today’s competitive industry, technical data mining and analysis is the key to create intelligent oil fields. However, there are major challenges associated with creation and consumption of data.

The starting point of data mining application is acquiring Real time job data (e.g. fracturing, well treatment, coiled tubing, etc.) using real-time data acquisition platform.  The data are contained in a proprietary binary format that is optimized for accumulating large amounts of real-time data, but does not lend itself to post-job secondary uses of that data. This data is processed, cleaned, mapped as

Real work of model-driven data mining has shown that our procedure is practical and potential for deeply analyzing data in the exploration and production of oil and gas.

Description:

A system as constituted in Fig [1] depicts a high level architectural overview of the automated data mining process.

Fig [1] High level architectural overview of the automated data mining process

 Below preface describes automated data mining processes and its purpose to be devised as:

1.       Acquire job files from all global job locations and all field engineers
Field engineers rely on the company’s engineering application suites in the execution of well site jobs for collecting real time Job execution data. The workflow utilizing these application suites includes the following:

·   Creation of the initial job configuration via:

      • Simple data entry
      • Data import for job design

·   Well site connection of data acquisition software to hardware sensors on the field equipment

·   Configuration of well site information (e.g. equipment assignments)

·   Job execution and monitoring

      • Monitor physical equipment data
      • Monitor down hole modelling calculations
      • Advance through discrete design stages
      • Record significant events
      • Produce plots and datasheets relevant to the job execution and attach to the job data
      • Create post-job report

·   Complete job and export to external data file

Thus, the resultant data files contain:

·         Definition of the job "design"

·         Raw equipment data

·         Derived (calculated) dat...