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Research On Wellbore Instability And Drilling Fluid Technology Of Haituozi Area

Posted on:2011-03-27Degree:MasterType:Thesis
Country:ChinaCandidate:Y H WangFull Text:PDF
GTID:2121360305478247Subject:Oil-Gas Well Engineering
Abstract/Summary:PDF Full Text Request
Though the basic reasons of wellbore instability have been profoundly understood, due to differences in geological characteristic and formation condition and so on, detailed analysis of each oilfield should be carried out. some problems have been encountered, such as borehole shrinkage, loss, sidewall collapse and blocks falling off during exploration and exploitation of Haituozi area in Jilin Oilfield. In view of this situation, the physical-chemical properties and orientation of rock samples of Haituozi area are analyzed systematically by X-ray diffraction, spectrophotometry, cuttings roller recovery measuring and expansion rate measuring. The conclusion is got by systematical analyses that the mud shale of Nenjiang formation belongs to the type of strong expansion, medium to weak dispersity and medium to weak orientation, Yaojia formation, Qingshankou formation and Quantou formation belong to the type of medium to weak expansion, medium to weak dispersity and good orientation. Considering the time taken in experiments and large workload and so on, artificial neural network has been introduced into evaluation, evaluation model has been instructed. The accuracy and credibility of the model has been proved. On the basis of evaluating physical-chemical properties and orientation of shale, the paper discusses the wellbore instability reason of ground in this area. According to the reason, the impermeable drilling fluid suitable to the formation penetration of Haituozi area is developed on the basis of laboratory experiments. The results of field test show that this kind of drilling fluid can control the wellbore instability of this area and decrease the occurring of borehole complexities substantially.
Keywords/Search Tags:wellbore instability, Haituozi area, shale, neural network, drilling fluid
PDF Full Text Request
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