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Research On Anti-water Lock Techniques In H-168 Block Of Songliao Basin

Posted on:2014-10-01Degree:MasterType:Thesis
Country:ChinaCandidate:J B XieFull Text:PDF
GTID:2321330473967797Subject:Oil-Gas Well Engineering
Abstract/Summary:PDF Full Text Request
H-168 block is one of the tight oil development demonstration area in 2012,The geological structure is very complex,it is medium-low porosity,ultra-low permeability reservoirs,due to the capillary force and Jamin effect,the oil flow will be separated by the mud filtrate,causing strong water blocking damage.Evaluate H168 block reservoir damage,carry out the sane measures to control water blocking damage,formulate reasonable reservoir protection is a major technical problems.We analyze the pore characteristics of the tight reservoirs scientifically and accurately evaluate the block reservoir damage mechanism,promote low-damage drilling fluid system research and formulate reasonable measures to tight oil reservoir protection,to create the conditions for oilfield exploitation.Based on the H-168 block reservoir properties and formation fluid characteristics determine the major damage in reservoir is water blocking,using the indoor experiment studied the water blocking damage mechanism,determine the main affecting factors and evaluate the extent of the damage.Using quantum neural network predicted reservoir water lock damage,the accuracy rate was significantly higher than the traditional BP neural network and gray correlation.provide a theoretical basis for on-site construction of intelligent development.preferred waterproof lock agent for H-168 block of water blocking damage,optimized the field drilling fluid system.And proposed targeted waterproof lock technical countermeasures,The application results show that the optimized drilling fluid system is a better compatibility and waterproof locking effect,which is a low-invasive,low-damage drilling fluid system,reached purposes to the reservoir protection.
Keywords/Search Tags:Low permeability reservoir, Water blocking damage, Prediction, Quantum neural network, Anti-water lock agent, Drilling fluid
PDF Full Text Request
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