پديد آورنده :
موسي خاني، مرتضي
عنوان :
تحمين پارامترهاي پتروفيزيكي ﴿نفوذپذيري و تخلخل﴾ مخازن تركدار با استفاده از داده هاي چاه نگاري به روشهاي هوشمند: ميدان گلشن
مقطع تحصيلي :
كارشناسي ارشد
گرايش تحصيلي :
اكتشاف معدن
محل تحصيل :
اصفهان: دانشگاه صنعتي اصفهان، دانشكده معدن
صفحه شمار :
ده،86ص.: مصور،جدول،نمودار
يادداشت :
ص.ع.به فارسي و انگليسي
استاد راهنما :
نادر فتحيان پور، حسن طباطبايي
استاد مشاور :
عليرضا باغبانان
توصيفگر ها :
شبكه ي عصبي وSVM , باز شدگي , تخمين تخلخل و شاخص شدت شكستگي
تاريخ نمايه سازي :
4/8/92
استاد داور :
احساني، طبايي
چكيده فارسي :
به فارسي و انگليسي: قابل رويت در نسخه ديجيتالي
چكيده انگليسي :
87Estimating petrophysical parameters Permeability Porosity from well logdata in a naturally fractured reservoir using intelligent methods Golshan field Morteza Mousakhani Mortezamousakhani@gmail com Date of Submission 2013 01 23 Department of Mining Engineering Isfahan University of Technology Isfahan 84156 83111 IranDegree M Sc Language FarsiSupervisor Nader Fathianpour Fathian @cc iut ac irSupervisor Saied Hassan Tabatabaei tabatabaei@cc iut ac ir AbstractReservoir characterization is considered as the main primary step in defining threedimensional distribution of petrophysical properties needed for any reservoir modeling andsimulation These parameters are normally estimated using both laboratory scale testscarried out on core samples and well log data Having more accurate and consistentpetrophysical parameters used for modeling reservoir properties is vital for oil industrymanagers and hence it is highly demanded to have as much agreement with underlyingactual subsurface geology as possible Due to having more complicated relationshipbetween porosity and permeability in fractured reservoirs the estimation of thesesparameters are more difficult and is still considered as challenging topic among upstreamresearchers The reservoir under study is considered as fractured reservoir having low permeability inmatrix part and highly permeable in crack paths The total porosity and permeability isaccounted for through addition of these two components normally called dual porositysystem Asmari formation as one of the main petroleum host in many Iranian south oilfields is an example of a formation with high effective porosity and permeability resultedfrom a naturally fractured network The prime objective of this study was to evaluate thefeasibility of using well log data as the predictor of estimating petrophysical parameters ofa fractured reservoir employing intelligent neural network and support vector regressiontechniques in Golshan gas field located 160 kms south east of Bushehr port In the firststep all required geological map and reports plus well log data and core sample resultswere obtained and put into a geodatabase ready for further processing Then the data werecorrected for any outlier and deviation followed by cross validating with correspondinggeological data The third step was to estimate formation water resistivity Rw andFracture Intensity Index FII using available well log data In the next step the predictorvariables were selected as the inputs for estimating porosity and permeability along wells In this study the available neural network and SVR codes in Matlab environment wasmodified to optimize the effective modeling parameters and improve their performances The most important part of this study was to identify and estimate petrophysicalparameters in fractured zones The estimated aperture permeability and porosity of cracksusing corrected well log data showed that the probability distribution of these parameters
استاد راهنما :
نادر فتحيان پور، حسن طباطبايي
استاد مشاور :
عليرضا باغبانان
استاد داور :
احساني، طبايي
