... the coupled effects of pore space and fluid saturation in the joint acoustic and electrical domains. The proposed inversion does not explicitly use a forward model, rather the correlation between the petrophysical properties and the resulting geophysical responses is inferred probabilistically from a training...

... then determined for different rock types. Experiments were performed multiple times for quality control and to test reproducibility. The measured binary diffusion coefficients without porous media show a very good agreement with the published literature data and available correlations based on the kinetic gas...

... siliciclastic-carbonate samples of the upper section of the Xiaganchaigou Formation are mainly formed by dolomite and clay minerals with low siliceous and calcite content. Porosity is relatively low (2.01−9.83%) and positively correlated with dolomite content, thus indicating that the dolomite intercrystalline...

... these four parameters (i.e., Corey exponents, true residual oil saturation, and gas endpoint relative permeability) were interpreted from simulations rather than from experiments. Based on our findings, a new correlation has been proposed to model the effect of temperature on two-phase gas/heavy oil relative...

... in Miocene carbonate layers as observed from integrated advanced log and core studies. Conventional petrophysical evaluation using constant petrophysical parameters ( a , m , n ) or linear correlation of cementation factor with porosity can lead to erroneous results in this scenario. A petrofacies-dependent...

... fracturing. We use the well logging measurements to correct the MS data in the vertical direction and then perform interpolation analysis to predict the spatial distribution of fractures. Moran’s index is a rational number that measures spatial correlation and has a value between −1 and 1. A positive...

...Yanrui Ning; Harrison Schumann; Ge Jin Summary In this study, we developed a data mining-based multivariate analysis (MVA) workflow to identify correlations in complex high-dimensional data sets of small size. The research was motivated by the integration analysis of geologic, geophysical...

... the polymer mechanical degradation at ultimate shear rates primarily observed near wellbores. Moreover, the fitting parameters used in the model were correlated to rock and polymer properties using machine learning technique, significantly reducing the need for time-consuming coreflooding tests for future...

... includes clustering, dimensionality reduction, correlation, in addition to novel interpretation methodologies that synthesize the results from reservoir simulation output, characterizing flow conditions. The insight was then used to build and select samples to train a VAE algorithm that reproduces...

... attributes were used to build a Bakken Shale capacity model. They found that the analyzed Bakken Shale capacity volume was strongly correlated with Bakken Shale production. Based on applying spatial statistics, ( Tian et al. 2017 ) conducted a quantitative analysis of the relative influences of various...

... convolutional network (GCN) is used to capture complicated spatial patterns between each well, and long short-term memory (LSTM) neural network is adopted to extract intricate temporal correlations from historical production data. To implement the proposed model more efficiently, two data preprocessing...

... our early studies on temperature dependence of NMR relaxation time to low-quality (LQ) carbonate formations. For more than 95% of the LQ samples investigated, NMR relaxation time shows a positive correlation with temperature. The correlation is similar to that observed in HQ carbonate rocks...

...Hesham Mokhtar Ali; Mahmoud Abu El Ela; Ahmed El-Banbi Summary The nonparametric transformation is a data-driven technique, which can be used to estimate optimal correlations between a dependent variable (response) and a set of independent parameters (predictors). This study introduces a systematic...

...-structure map showing the simulated area of 16 TH (top right). (c) Well correlation of the 16 TH Reservoir across the simulated area, with the cross-section location shown in red in the structural map above (bottom). The average porosity is 27% with a minimum of 17% and up to 38%. Oil gravity is 25...

... ratio upstream oil & gas correlation seven-spot model sweepable pv permeability spe reservoir evaluation dynamic lorenz coefficient lorenz coefficient equation of state waterflooding seven-spot pattern base dynamic lorenz coefficient workflow realization tracer test analysis...

... (FC) method, and time slice (TS) method. Moreover, we study the impact of a possible linear correlation (also linear C) between b and D i (comparable to field observations) on MC, FC, and TS type wells. We also study the effect of well count, and D min value, which is the 4th parameter introduced...

... a specific critical point within the constraints of the MCM definition. There are many analytical, numerical, correlational, and experimental methods available to estimate the minimum miscibility pressure (MMP) for MCM flow. The numerous available methods, some of which are quite inexpensive, have caused...

... 2020 2 7 2020 30 6 2020 23 9 2020 29 8 2020 12 11 2020 Copyright © 2020 Society of Petroleum Engineers upstream oil & gas correlation enhanced recovery fluid dynamics fine-grid simulation true residual oil saturation flow in porous media coarse-grid model...

... 2020 Copyright © 2020 Society of Petroleum Engineers production control machine learning reservoir characterization well logging hydraulic fracturing production monitoring drilling operation geomechanical facies correlation artificial intelligence complex reservoir upstream oil...

... in well resolution but fail when interpolating those facies further away from the 1D domain, because of the lack of correlation between FUs and spatial data. Seismic data can be used to detect large‐scale FUs and assist the interpolation of small‐scale FUs in 3D reservoir volume, thus producing more...