Use this URL to cite or link to this record in EThOS: http://ethos.bl.uk/OrderDetails.do?uin=uk.bl.ethos.445399
Title: A study of intelligent oil and gas fields' real time optimisation and its value quantification
Author: Aggrey, George Hayford
ISNI:       0000 0001 3399 3350
Awarding Body: Heriot-Watt University
Current Institution: Heriot-Watt University
Date of Award: 2007
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Abstract:
The thesis, "Intelligent Fields Added Value Quantification and Real Time Value Creation", covers the "added value" evaluation process and a novel extension of the use of real time pressure data of Intelligent Fields. Intelligent well completion technologies add value via real time optimisation and provide flexibility for future well control. The correct "value adding" evaluation must be developed to become part of the general optimisation process. Hence understanding the value added, which is dependent on the three main factors of additional cost, reliability and equipment functionality. is key to the success of Intelligent Well Technology (I WT). This thesis explores the added value quantification criteria and develops a widely applicable software for quantifying the value added by Intelligent Well Technology and Sensor applications. The work explores and compares the various valuation criteria and their applicability to "Added Value from IWT" whilst modelling the application in various reservoir environments. The importance of the future equipment functionality in the value creation definition is investigated and rigorously factored into the value assessment. Current modelling and optimisation techniques were employed to show the values associated with intelligent completions and with various permanent downhole sensors. Appropriate use of intelligent production information is necessary to effectively contribute to improve operational performance. To achieve this, data driven management techniques such as Artificial Neural Network (ANN) with Wavelets and Time Series were used for the analysis of real time data to create the necessary information. Alternatively, a model driven approach (unlike NN "black" box) which considers the underlying physics of fluid flow in the reservoir and realistically captures the wellborereservoir flow processes is used to show that real time downhole pressure can detect the time and source of water influx into a multi-zone horizontal or near horizontal completion thus permitting a more rapid response to water breakthrough.
Supervisor: Not available Sponsor: Not available
Qualification Name: Thesis (Ph.D.) Qualification Level: Doctoral
EThOS ID: uk.bl.ethos.445399  DOI: Not available
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