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The Evaluation Of Gas Characteristics Of Tight Sandstone And Productivity Prediction Of Sulige Gas Field

Posted on:2012-02-09Degree:MasterType:Thesis
Country:ChinaCandidate:J ZhangFull Text:PDF
GTID:2120330338493441Subject:Earth Exploration and Information Technology
Abstract/Summary:PDF Full Text Request
With the deepening exploration and development of Sulige field, the exploration is becoming difficult. In order to provide technical support to explore Sulige gas tight this paper study the sandstone reservoir evaluation, gas productivity prediction and evaluation of classification methods, and at the end of establishing an effective evaluation logging system.The Logging Evaluation of tight sandstone gas field exploration has been a difficult problem, Explanation of tight sandstone reservoir in domestic and foreign logging model parameters were used the traditional means. Tight sandstone gas buried deep, poor thing, this led to the gas resonations characteristics of the logging is not obvious. The evaluations of gas reservoirs can not be accurately reflect the reservoir characteristics.This paper first conducted a detailed study of the rock relationship and the response characteristics of the gas, extracted the sensitive parameters of gas reservoir, and then use a plot of methods, to study and evaluated Sulige A and B area. Those methods lay the foundation for capacity prediction of the gas reservoirsWith putting the core to the logging position, in this paper we used the method of "core-scale logging," established the log interpretation model which focused on using of airtight coring well result to adjust the Archie formula and the accuracy of S whas improved.In this paper we use many methods to determine the limitation of effective reservoir, and use the cross plot methods to determine the well logging boundaries of reservoir. According to the Geological, gas measurement, drilling, logging and other data to determine the effective thickness of the gas reservoir.Finally, distinguished the capacity of the gas well using multiple linear regression, and used probabilistic neural network method distinguished and study the reservoir.The actual date shows that the methods of this paper had a high compliance rate with the logging interpretation. So study of sandstone reservoirs in this paper has an important evaluation and significant application value.
Keywords/Search Tags:tight sandstone, gas assessment, reservoir boundaries, productivity prediction, neural network
PDF Full Text Request
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