Font Size: a A A

Study Of Sedimentary Facies Of Gaotaizi Reservoir In The North Part Of Daqing Placantieline

Posted on:2003-07-03Degree:MasterType:Thesis
Country:ChinaCandidate:H J WenFull Text:PDF
GTID:2120360062486612Subject:Mineral prospecting and exploration
Abstract/Summary:PDF Full Text Request
On the basis of the integrated application of well logging , mud logging information and core analysis data, and using the method from the microcosm to the macrocosm analysis, this paper has studied the sedimentary characteristics of the sandstone oil bearing of the Gaotaizi reservoir in the north part of the Daqing placantieline, the program of automatic identification sedimentary microfacies with two different methods has been compiled.According to the abundance well logging ,mud logging and core analysis data , Gaotaizi reservoir has been classified into four sand group with the principle of cycle comparison and classified control .Based on the detailed study of lithologic character, sedimentary structure, paleontologic fossils, depositional sequence, rock association and logging data, the microfacies of the studied area are divided into such seven types: subaqueous distributary channel microfacies;river mouth bar microfacies; subaqueous interdistributary channel microfacies; subaqueous crevasse channel microfacies; subaqueous natural barrier microfacies; distal bar microfacies;delta front sheet sand microfacies.The characteristic of each sedimentary microfacies are described detailedly.Using digital logging data of logging curves to resume lithology section, based on single well sedimentary facies analysis of cored well, typical sedimentary microfacies and the corresponding electrofacies models are established. Each after extracting the essential factors of logging curves, each logging microfacies recognize model are set up to automatically identify sedimentary microfacies by the method of Bayes identification and neural networks technical. The program has been compiled by Visual Basic programming language, based on which the analysis of single well sedimentary microfacies and the study of the plane sedimentary facies are acomplished finally.
Keywords/Search Tags:sedimentary microfacies, neural networks, electrofacies model, automatic identification of sedimentary microfacies
PDF Full Text Request
Related items