Completing the Second Target: Finding Optimal Completion Practices for the Three Forks Formation in the Williston Basin Using Multivariate Statistical Analysis

Author(s):  
Brandon Lewis Williams ◽  
Brian Michael Weaver ◽  
Leen Weijers
2015 ◽  
Author(s):  
Brandon Williams ◽  
Brian Weaver ◽  
Leen Weijers

Abstract The Three Forks Formation in the Williston Basin has started to see a large increase in activity in the past six years. This is largely due to the shallower Bakken Formation transitioning into an infill development mode and operators looking at finding incremental reserves from the Three Forks Formation below. The objective of this paper is to evaluate the geological and completion variables of Three Forks horizontal wells in the North Dakota portion of the Williston Basin, and show which factors impact production performance using multivariate statistics. A financial evaluation of the completion factors will also be presented to show which variables have the biggest impact on production. A database of available completion and geological data has been assembled from the North Dakota Industrial Commission (NDIC) website. To date there are roughly 2,400 horizontal wells targeting the Three Forks Formation on the North Dakota side of the Williston Basin. Some of the variables collected include number of fracture stages, amount and type of proppant, total volume and type of frac fluid, lateral length, max treatment pressure and rate, API oil gravity, formation thickness (from formation tops) and production. The data was subjected to multivariate nonlinear statistical analysis. This type of analysis allows for simultaneously comparing multiple variables to one outcome variable. In this case study the outcome variable is 180-day production. Using multivariate analysis in the Three Forks Formation of the Williston Basin will aid in predicting production in different parts of the basin and finding which controllable completion variables have the most significant impact on production. The output can also aid in production forecasting based on changes to treatment designs.


2018 ◽  
Vol 52 (2) ◽  
pp. 15
Author(s):  
V. I. Radomskaya ◽  
D. V. Yusupov ◽  
L. М. Pavlova ◽  
А. G. Sеrgееvа ◽  
N. А. Bоrоdinа ◽  
...  

2017 ◽  
Vol 68 (4) ◽  
pp. 726-731
Author(s):  
Lenuta Maria Suta ◽  
Anca Tudor ◽  
Colette Roxana Sandulovici ◽  
Lavinia Stelea ◽  
Daniel Hadaruga ◽  
...  

In this paper, it was analysed the influence of formulation factors over obtaining oxicam hydrogels, using the statistical analysis. Data analysis and predictive modeling by multivariate regression offers a large number of possible explanatory/predictive variables. Therefore, variable selection and dimension reduction is a major task for multivariate statistical analysis, especially for multivariate regressions. The statistical analysis and computational data processing of responses obtained from different pharmaceutical formulations, via different experimental protocols, lead to the optimization of the formulation process. It was found that the most suitable pharmaceutical formulations based on oxicams with the possibility of rapid release contained cyclodextrin, in particular 2-hydroxypropyl-b-cyclodextrin.


Molecules ◽  
2021 ◽  
Vol 26 (14) ◽  
pp. 4146
Author(s):  
José Enrique Herbert-Pucheta ◽  
José Daniel Lozada-Ramírez ◽  
Ana E. Ortega-Regules ◽  
Luis Ricardo Hernández ◽  
Cecilia Anaya de Parrodi

The quality of foods has led researchers to use various analytical methods to determine the amounts of principal food constituents; some of them are the NMR techniques with a multivariate statistical analysis (NMR-MSA). The present work introduces a set of NMR-MSA novelties. First, the use of a double pulsed-field-gradient echo (DPFGE) experiment with a refocusing band-selective uniform response pure-phase selective pulse for the selective excitation of a 5–10-ppm range of wine samples reveals novel broad 1H resonances. Second, an NMR-MSA foodomics approach to discriminate between wine samples produced from the same Cabernet Sauvignon variety fermented with different yeast strains proposed for large-scale alcohol reductions. Third a comparative study between a nonsupervised Principal Component Analysis (PCA), supervised standard partial (PLS-DA), and sparse (sPLS-DA) least squares discriminant analysis, as well as orthogonal projections to a latent structures discriminant analysis (OPLS-DA), for obtaining holistic fingerprints. The MSA discriminated between different Cabernet Sauvignon fermentation schemes and juice varieties (apple, apricot, and orange) or juice authentications (puree, nectar, concentrated, and commercial juice fruit drinks). The new pulse sequence DPFGE demonstrated an enhanced sensitivity in the aromatic zone of wine samples, allowing a better application of different unsupervised and supervised multivariate statistical analysis approaches.


Foods ◽  
2021 ◽  
Vol 10 (6) ◽  
pp. 1377
Author(s):  
Song-Hui Soung ◽  
Sunmin Lee ◽  
Seung-Hwa Lee ◽  
Hae-Jin Kim ◽  
Na-Rae Lee ◽  
...  

Numerous varieties of doenjang are manufactured by many food companies using different ingredients and fermentation processes, and thus, the qualities such as taste and flavor are very different. Therefore, in this study, we compared many products, specifically, 19 traditional doenjang (TD) and 17 industrial doenjang (ID). Subsequently, we performed non-targeted metabolite profiling, and multivariate statistical analysis to discover distinct metabolites in two types of doenjang. Amino acids, organic acids, isoflavone aglycones, non-DDMP (2,3-dihydro-2,5-dihydroxy-6-methyl-4H-pyran-4- one) soyasaponins, hydroxyisoflavones, and biogenic amines were relatively abundant in TD. On the contrary, contents of dipeptides, lysophospholipids, isoflavone glucosides and DDMP-conjugated soyasaponin, precursors of the above-mentioned metabolites, were comparatively higher in ID. We also observed relatively higher antioxidant, protease, and β-glucosidase activities in TD. Our results may provide valuable information on doenjang to consumers and manufacturers, which can be used while selecting and developing new products.


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