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Artificially intelligent and predictive modelling of geomechanical properties is performed by creating supervised machine learning data models utilizing artificial neural networks (ANN) and will predict geomechanical properties from basic and commonly used conventional well logs such as gamma ray, and bulk density. The predictive models were created by following the approach on a large volume of data acquired from 112 wells containing the Bakken Formation in North Dakota. The studied wells cover a large surface area of the formation containing the five main producing counties in North Dakota: Burke, Mountrail, McKenzie, Dunn, and Williams. Thus, with a large surface area being analyzed in this research, there is confidence with a high degree of certainty that an extensive representation of the Bakken Formation is modelled, by training neural networks to work on varying properties from the different counties containing the Bakken Formation in North Dakota. Shear wave velocity of 112 wells is also analyzed by regression methods and neural networks, and a new correlation is proposed for the Bakken Formation. The final goal of the research is to achieve supervised artificial neural network models that predict geomechanical properties of future wells with an accuracy of at least 90% for the Upper and Middle Bakken Formation. Thus, obtaining these logs by generating it from statistical and artificially intelligent methods shows a potential for significant improvements in performance, efficiency, and profitability for oil and gas operators.

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Shale formations present anisotropic characteristics in mechanical, acoustic, and flow properties due to their layering and pre-existing natural fractures. This anisotropic behavior can create a complex fracture network rather than the conventionally presumed planar fractures. Although incorporating anisotropic behavior is essential for optimizing the hydraulic fracturing design and analyzing the post-fracture data, there are limited studies addressing the anisotropic tensile behavior of organic-rich shale formations. The objective of this study is to explore the tensile strength and tensile fracture patterns in shales by conducting splitting tests on variety of shale formations. Core samples from the Eagle Ford shale in the oil window, its overlying Austin Chalk and the underlying Buda formation, Green River immature oil shale, Mancos shale, and Berea sandstone samples have been tested to investigate the effects of layering, natural fractures, total organic carbon (TOC), maturity and mineralogy on tensile behavior. Having different types of Green River shale, the impact of TOC on the tensile strength was obtained. The anisotropic tensile behavior of Mancos and Green River shales were studied systematically at various orientations between the applied force and the bedding direction providing key understanding on the fracture growth patterns at any direction. Finally, the tensile strength and fracture patterns for several Eagle Ford, Austin Chalk and Buda core samples with extensive natural fractures are discussed.

Intrinsic anisotropy due to layering as well as induced anisotropy due to fractures play critical role in fluid flow in organic-rich shales. In this paper, we characterize the impact of natural and induced fractures on permeability anisotropy utilizing various resolution CT-scans and present the effect of stress on the permeability of such fractured reservoirs. The effect of shale layering on fluid flow is also discussed.Wettability is another key factor in determining the fluid flow and recovery efficiency in shale reservoirs. We investigated the wettability of several shale samples from Eagle Ford, Mancos, Green River, Bakken and Niobrara shale plays. The effects of total organic carbon and maturity on contact angle in these shale formations are presented.

Although petroleum industry has obtained a good practice in unlocking the shale reservoirs, more comprehensive geomechanical experimental and modeling research is required to optimize the drilling, completion and hydraulic fracturing processes due to the significant heterogeneity and anisotropy of shale formations. Acoustic and mechanical properties strongly depend on several factors including the mineralogy, density and distribution of natural fractures, bedding plane orientation, total organic carbon (TOC), maturity and in-situ stress state and pore pressure which are significantly different in various shale reservoirs and even within a shale basin. The strong anisotropy of acoustic and mechanical properties has a major impact on the reservoir characterization and field development plan. In this paper, we present the results of an experimental study on several U.S. shale basins with different maturity including Eagle Ford, Green River and Mancos shales to provide more insight on the shale acoustic and mechanical properties. We discuss the effect of shale bedding plane orientation and emphasize on the impact of shale mineralogy and petrophysical characteristics on the acoustic and mechanical properties. The mineralogy and petrophysical properties of each shale sample have been examined. Using both ultrasonic and mechanical methods, dynamic and static Young Modulus and Poisson's Ratio have been obtained at different bedding plane angles. A relationship between dynamic and static moduli has been consequently developed to determine in situ static moduli directly from seismic or well log data obtained in the same field. IntroductionAs the global energy demand increases with limited undiscovered conventional reserves left, the developments of unconventional reservoirs have been increasing worldwide. Shale formations have various minerals and vary in their petrophysical and geochemical properties from the conventional reservoirs. Therefore, they introduce new challenges to the oil and gas industry on many development stages. These challenges need further laboratory and field research, and require a more integrated, multi-disciplinary approach to study their characteristics.An accurate evaluation of the formation mechanical properties along with other factors leads to a successful implementation of drilling, completion and hydraulic fracturing in shale reservoirs. Types of mineralogy, clay URTeC 2013

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Superhydrophobic surface is an enabling technology in numerous emerging and practical applications such as self-cleaning, anticorrosion, antifouling, anti-icing coatings, and oil–water separation. Here, we report a facile air-assisted electrospray approach to achieve a superhydrophobic surface by systematically studying spray conditions and the chemistry of a coating precursor solution consisting of silicon dioxide nanoparticles, polyacrylonitrile, and N,N-dimethylformamide. The wettability behavior of the surface was analyzed with contact angle measurement and correlated with surface structures. The superhydrophobic coating exhibits remarkable water and oil repellent characteristics, as well as good robustness against abrasion and harsh chemical conditions. This air-assisted electrospray technique has shown great control over the coating process and properties and thus can be potentially used for various advanced industrial applications for self-cleaning and anticorrosion surfaces.