A New Facies Classification Scheme Using Gamma Ray and Bulk DensityLogs,With Multiple Practical Applications in North Kuwait Heavy Oil Fields

摘要

This paper presents a method for facies classification derived from cross plots of basic gamma ray andbulk density wireline log data.It has been specifically developed in-house for two North Kuwait heavy-oil fields,and has been calibrated against both field analogues and core sample measurements.This newfacies classification scheme has proven to be quick and cost effective,with multiple practical applicationsfor future field development and operation optimization.For two heavy oil fields in North Kuwait basic Gamma Ray and Bulk Density (GR-DENS) curve datafrom over 1300 wells were cross-plotted.The resulting relationship characteristics were used to delineateeight separate facies,which plot along a continuum from clean porous sands with little cement and clay,toless porous sands with increasing clay and cementation content,to carbonate and shale.The properties forthese facies were calibrated against data from core analyses and with outcrop analogues in North Kuwait.These facies were populated into static reservoir models using the Sequential Indicator Simulation (SIS)method,and petrophysical modeling was then conditioned to these facies.These resulting modeled facies,with their associated petrophysical properties,have been used in a wide variety of subsequent analyticalstudies.The eight facies which have been newly delineated by the GR-DENS classification scheme capture thetransitional nature of petrophysical properties for oil saturation,porosity and permeability.This has enabledseveral improvements for heavy-oil field development including: 1) better delineation of reservoir andbaffle zones;2) better calibration of oil saturation with core data;3) calibration of facies with 3D seismicamplitude response;4) better understanding of reservoir geomechanics and seal integrity assessment;5)greater confidence in the results of static and dynamic reservoir modeling;6) more effective decisionmaking in the WRFM process;and 7) alignment of the petrophysical and facies characterization approachbetween two separate heavy oil asset teams,which allows for direct comparisons between their data sets.Although more complex software exists for specialized facies classification,the GR-DENS workflow newlydeveloped for North Kuwait heavy oil has proven to be simple,rapid,accurate and cost effective.In summary a robust facies classification scheme was developed in-house which is appropriatelycustomized for two North Kuwait heavy oil fields.This methodology has enabled the creation of morerepresentative reservoir models,with resulting improvements in understanding for multiple aspects of bothfields.These improvements in turn will lead to better production forecasting and optimization as well asenhance future life of field planning.