... fracture semivariance spe reservoir evaluation spline interpolation prediction spatial correlation correlation microearthquake resolution distribution method Effective shale gas production requires reservoir modification through volumetric fracturing technology, which generates complex...

... 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...

... 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...

... 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...

... 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...

...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...

... & simulation complex reservoir upstream oil & gas data mining bayesian inference neural network dca model reservoir characterization reservoir surveillance production forecasting reservoir simulation correlation bn-ode framework spe reservoir evaluation reservoir evaluation predictor...

... 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...

... model history matching oil-production rate spe annual technical conference spe reservoir evaluation spe reservoir evaluation & engineering upstream oil & gas reservoir simulation fluid dynamics correlation water-production rate measured data conditioning ensemble parameter...

... (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...

... in later sections for validation and testing of our proposed correlation. To test the effect of mobility ratio on dynamic Lorenz coefficient, the endpoint mobility ratios were varied from 1 to 1,000 in multiples of 10 (1, 10, 100, and 1,000). This was achieved by changing either the oil and/or water...

... 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...

.... upstream oil & gas correlation enhanced recovery fluid dynamics fine-grid simulation true residual oil saturation flow in porous media coarse-grid model experiment residual oil saturation fine-grid model pseudorelative-permeability curve viscosity ratio relative-permeability curve...

... 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...

... the same saturation‐function correlations as assumed in the analytical solution. Then, more‐general correlations are assumed when generating the synthetic data. This is to test the robustness of the analytical solution in producing functions similar to the “true” ones. Finally, we perform a waterflooding...

...Ishank Gupta; Chandra Rai; Deepak Devegowda; Carl Sondergeld Summary In this study we analyze the production data from 2,755 horizontal wells in the Haynesville Shale. Correlations were generated to predict 4-, 5-, 6-, and 7-year cumulative production from initial, 6-, 12-, and 24-month production...

.... The uncertainty also describes the correlation between estimates of mineral‐weight fractions, indicating which pairs of minerals cannot be independently estimated. Our Bayesian model also addresses the uncertainty propagated from the estimated linear operator and thus captures a possible mismatch of the model...