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Study On The Flow In The Well Head Of Offshore Oil Well

Posted on:2017-07-17Degree:MasterType:Thesis
Country:ChinaCandidate:N DingFull Text:PDF
GTID:2321330566957130Subject:Oil and gas field development project
Abstract/Summary:PDF Full Text Request
High cost and short development cycle are the two features of offshore oil and gas field development,and the nation's offshore oil strategy plays a very important role in its energy security.So the key point to the development is to improving the economic benefit throw improving the production and reducing the operation costs by optimize production para meters in existing facilities.This paper proposed an overall optimization method of the offshore oil and gas field cluster well group system based on the choke adjustment through the study of well interference problem under subcritical flow.Firstly,using the low cost and repetitive simulation experiments in the offshore oil and gas production experiment simulator to verify the existence of the wellhead interference phenomenon.Secondly,deduced the adjustment sensitivity function model of choke system that could determine choke diameter and explain the change law for tubing pressure and backpressure based on the choke flow model which established by Thomas k.Perkins.Thirdly,establish the multi-objective optimization model of offshore oil and gas fields cluster well group system,and choose the NSGA-? as the solving algorithms compared to other intelligent optimization algorithms.Finally,using the actual production data of offshore oil field to test the multi-objective optimization model of offshore oil and gas fields cluster well group system.According to the optimization results,there is a remarkable increase in the total oil production and system efficiency although the production of some oil well and the total production are reduced.So that proved this method can be applied to the optimization of development of offshore oil and gas field.
Keywords/Search Tags:offshore oil and gas fields, choke adjustment, multi-objective optimization, intelligent optimization algorithms, multi-objective evolutionary algorithm
PDF Full Text Request
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