Conventional Imtrltiple regression for permeability estimation from well logs requires a functional relationship to be presumed. Due to the inexact nature of the relationship between petrophysical variables, it is not always possible to identify the underlying functional form between dependent and independent variables in advance. When large variations in metrological properties arc exhibited, ...

the permeability is a main property of oil reservoirs that shows the ability of rocks in the conduct of fluids such as oil, water and gas through the pore spaces of reservoir. the determination of the permeability is a crucial task in reserve estimation, production and development of oil reservoirs. due to this, an accurate estimate of such important reservoir rock parameter should not be made ...

nowadays, by complication of production mechanisms from reservoirs and depletion of most of the reservoirs in iran, secondary production has become more important. regarding the nature of iranian reservoirs and carbonate inherencies and diagenetic and tectonic effects on these reservoirs, we see heterogeneities in them which cause uncertainty in predictions and performance of these reservoirs. ...

A field's hydrocarbon evaluation takes into account the productivity of reservoir bearing unit. It basically includes a thorough examination geological interpretation petrophysical parameter indices deduced from well logs. This study uses MHI and proven integrated methodologies including logs analysis, computing, to evaluate Sapele-field with objective establishing its fluid types saturations. ...

A stochastic Bayesian approach for combining well logs and geophysical surveys for enhancing subsurface characterization is presented. The main challenge we face is in creating the bridge to link between ambiguously related geophysical surveys and well data. The second challenge is imposed by the disparity between the scale of the geophysical survey and the scale of the well logs. Our approach ...

The power of Machine Learning is demonstrated for automatic interpretation well logs and determining reservoir properties volume shale, porosity, water saturation respectively tight clastic sequences. Random Forest algorithms are reputed their efficiency as they belong to a class called ensemble methods, which traditionally seen weak learners, but can be transformed into strong performers promi...

Advanced and Integrated Petrophysical Characterization for CO2 Storage: Application to the Ketzin Site — Reservoir simulations and monitoring of CO2 storage require specific petrophysical data. We show a workflow that can be applied to saline aquifers and caprocks in order to provide the minimum data set for realistic estimations of storage potential and perform pertinent simulations of CO2 inj...

Well logs are principal sources of subsurface geological information. They provide significant information on mineralogical composition, texture, sedimentary structures and petrophysical properties such as porosity and permeability. By compiling data from various well logs, one can discriminate sedimentary units with comparable log characteristics. Sedimentary units with similar fluid flow and ...