Abstract The paper presents a study of Lower Carboniferous (Visean) clastic sequence commonly called Bobrikovsky Formation, deposited in the Volga-Ural Petroleum Province, Orenburg Region. Our investigation included sedimentological description core samples from hydrocarbon wells and well log correlations. Facies were identified by patterns calibrated sedimentology. Formation is proposed to be ...

A pilot study of 13 wells in Means oil field of the Permian basin, West Texas, established porosity-permeability relationships for the Permian Queen, Grayburg and San Andres formations. The optimized workflow used borehole image and conventional log processing with calibration to core data. This approach allowed the quantification of porosity and perme-ability heterogeneity in vuggy carbonate f...

The objective of this study is to demonstrate the power of integrating rock physics theory, measurement and simulation to improve facies prediction in an unconventional limestone and shale reservoir. Reliable facies prediction is a challenge in unconventional reservoir characterization because of complex geological heterogeneities. Both deterministic and probabilistic approaches are commonly us...

The purpose of this study was to build small-scale genetic models of a reservoir by comparing the small and medium scale information derived from core analyses and well logs. The examined gas field is situated in the eastern part of the Pannonian Basin System. For the numerical solution several one (univariate) and multivariable (multivariate) statistical methods were used to describeone and mu...

[1] A high-resolution stratigraphic image of a flume-generated deposit was scaled up to sedimentary basin dimensions where a natural log hydraulic conductivity (ln(K)) was assigned to each pixel on the basis of gray scale and conductivity end-members. The synthetic ln(K) map has mean, variance, and frequency distributions that are comparable to a natural alluvial fan deposit. A geostatistical a...

Development of the Hugoton field model has required automated processing of large data volumes at several steps, including prediction of lithofacies from geophysical well logs in numerous wells based on a neural network trained on log-facies associations observed in cored wells, generation of geologic controlling variables (depositional environment indicator and relative position in cycle) from...

Knowledge of the distribution of permeability and porosity in a reservoir is necessary for the prediction of future oil production, estimation of the location of bypassed oil, and optimization of reservoir management. But while the volume of data that can potentially provide information on reservoir architecture and fluid distributions has increased enormously in the past decade, it is not yet ...

Aquifer systems are considered in which measurements of logpermeability (Y) at a 1E-2 m support scale are unimodally distributed as taken within the 1E0 to 1E1 m scale of individual sand and gravel (sg) lithofacies, are weakly multimodal at the 1E1 to 1E2 m scale of assemblages of these facies, and are strongly multimodal at the 1E3 m scale of complexes of sg facies assemblages juxtaposed with ...

While the well log-based lithology classi?cation has been extensively utilized in reservoir characterization, of carbonate sub-facies remains challenging due to subtle nuances conventional well-logs. The nuclear magnetic resonance (NMR) log provides extra information pore size and geometry features, improving differentiating sub-facies. Here we explore feasibility using ratio between NMR longit...