Integrated approach using core analysis and wireline measurement to estimate rock mechanical properties of the Zubair Reservoir, Southern Iraq

2018 ◽  
Vol 166 ◽  
pp. 406-419 ◽  
Author(s):  
Ahmed K. Abbas ◽  
Ralph E. Flori ◽  
Mortadha Alsaba ◽  
Haider Dahm ◽  
Ethar H.K. Alkamil
Keyword(s):  
Mechanical Properties ◽  
Integrated Approach ◽  
Core Analysis ◽  
Rock Mechanical Properties ◽  
Southern Iraq

scholarly journals An Integrated Approach to Convert Lignocellulosic and Wool Residues into Balanced Fertilisers

Energies ◽  
2021 ◽  
Vol 14 (2) ◽  
pp. 497
Author(s):  
Filippo Marchelli ◽  
Giorgio Rovero ◽  
Massimo Curti ◽  
Elisabetta Arato ◽  
Barbara Bosio ◽  
...  
Keyword(s):  
Mechanical Properties ◽  
Renewable Energy ◽  
Circular Economy ◽  
Integrated Approach ◽  
Lignocellulosic Residues ◽  
Biomass Waste ◽  
Slow Pyrolysis ◽  
C And N ◽  
Water Hydrolysis ◽  
Conversion Technologies

Valorising biomass waste and producing renewable energy or materials is the aim of several conversion technologies. In this work, we consider two residues from different production chains: lignocellulosic residues from agriculture and wool residues from sheep husbandry. These materials are produced in large quantities, and their disposal is often costly and challenging for farmers. For their valorisation, we focus on slow pyrolysis for the former and water hydrolysis for the latter, concisely presenting the main literature related to these two processes. Pyrolysis produces the C-rich biochar, suitable for soil amending. Hydrolysis produces a N-rich fertiliser. We demonstrate how these two processes could be fruitfully integrated, as their products can be flexibly mixed to produce fertilisers. This solution would allow the achievement of balanced and tuneable ratios between C and N and the enhancement of the mechanical properties. We propose scenarios for this combined valorisation and for its coupling with other industries. As a result, biomass waste would be returned to the field, following the principles of circular economy.

Integration of Chemofacies and Rock Mechanical Properties Using Machine Learning Algorithms: Implications for Geomechanics and Hydraulic Fracture Stimulations in Paleozoic Formations, Saudi Arabia

2021 ◽  
Author(s):  
Maaruf Hussain ◽  
Abduljamiu Amao ◽  
Khalid Al-Ramadan ◽  
Sunday Olatunji ◽  
Ardiansyah Negara
Keyword(s):  
Machine Learning ◽  
Mechanical Properties ◽  
Saudi Arabia ◽  
Spatial Distribution ◽  
Chemical Composition ◽  
Rock Strength ◽  
Machine Learning Algorithms ◽  
Unconventional Reservoirs ◽  
Geochemical Properties ◽  
Rock Mechanical Properties

Abstract The knowledge of rock mechanical properties is critical to reducing drilling risk and maximizing well and reservoir productivity. Rock chemical composition, their spatial distribution, and porosity significantly influenced these properties. However, low porosity characterized unconventional reservoirs as such, geochemical properties considerably control their mechanical behavior. In this study, we used chemostratigraphy as a correlation tool to separate strata in highly homogenous formations where other traditional stratigraphic methods failed. In addition, we integrated the chemofacies output and reduced Young's modulus to outline predictable associations between facies and mechanical properties. Thus, providing better understanding of lithofacies-controlled changes in rock strength that are useful inputs for geomechanical models and completions stimulations.

Exploring the diversity of elastic responses of crystalline cadmium(ii) coordination polymers: from elastic towards plastic and brittle responses

CrystEngComm ◽  
2021 ◽  
Author(s):  
Mateja Pisačić ◽  
Ivan Kodrin ◽  
Ivana Biljan ◽  
Marijana Đaković
Keyword(s):  
Mechanical Properties ◽  
Coordination Polymers ◽  
Integrated Approach ◽  
Elastic Responses ◽  
Theory And Experiment

Noticeable differences in mechanically induced elastic responses were observed for isostructural crystalline coordination polymers, and their mechanical properties were examined through a highly integrated approach, using both theory and experiment.

scholarly journals Approximate Dynamic Programming Based Control of Proppant Concentration in Hydraulic Fracturing

Mathematics ◽  
2018 ◽  
Vol 6 (8) ◽  
pp. 132 ◽  
Author(s):  
Harwinder Singh Sidhu ◽  
Prashanth Siddhamshetty ◽  
Joseph Kwon
Keyword(s):  
Mechanical Properties ◽  
Dynamic Programming ◽  
Hydraulic Fracturing ◽  
Young’S Modulus ◽  
Large Scale ◽  
Approximate Dynamic Programming ◽  
Young's Modulus ◽  
Computational Cost ◽  
Control Technique ◽  
Rock Mechanical Properties

Hydraulic fracturing has played a crucial role in enhancing the extraction of oil and gas from deep underground sources. The two main objectives of hydraulic fracturing are to produce fractures with a desired fracture geometry and to achieve the target proppant concentration inside the fracture. Recently, some efforts have been made to accomplish these objectives by the model predictive control (MPC) theory based on the assumption that the rock mechanical properties such as the Young’s modulus are known and spatially homogenous. However, this approach may not be optimal if there is an uncertainty in the rock mechanical properties. Furthermore, the computational requirements associated with the MPC approach to calculate the control moves at each sampling time can be significantly high when the underlying process dynamics is described by a nonlinear large-scale system. To address these issues, the current work proposes an approximate dynamic programming (ADP) based approach for the closed-loop control of hydraulic fracturing to achieve the target proppant concentration at the end of pumping. ADP is a model-based control technique which combines a high-fidelity simulation and function approximator to alleviate the “curse-of-dimensionality” associated with the traditional dynamic programming (DP) approach. A series of simulations results is provided to demonstrate the performance of the ADP-based controller in achieving the target proppant concentration at the end of pumping at a fraction of the computational cost required by MPC while handling the uncertainty in the Young’s modulus of the rock formation.

Multi-Objective Build Orientation Optimization for Powder Bed Fusion by Laser

2017 ◽  
Vol 139 (11) ◽  
Author(s):  
Salah Eddine Brika ◽  
Yaoyao Fiona Zhao ◽  
Mathieu Brochu ◽  
Justin Mezzetta
Keyword(s):  
Mechanical Properties ◽  
Surface Roughness ◽  
Integrated Approach ◽  
Powder Bed Fusion ◽  
Powder Bed ◽  
Build Orientation ◽  
Multi Objective ◽  
Build Time ◽  
Process Factors ◽  
Experimental Data Analysis

This paper proposes an integrated approach to determine optimal build orientation for powder bed fusion by laser (PBF-L), by simultaneously optimizing mechanical properties, surface roughness, the amount of support structure (SUPP), and build time and cost. Experimental data analysis has been used to establish the objective functions for different mechanical properties and surface roughness. Geometry analysis of the part has been used to estimate the needed SUPP and thus evaluate the build time and cost. Normalized weights are assigned to different objectives depending on their relative importance allowing solving the multi-objective optimization problem using a genetic optimization algorithm. A study case is presented to demonstrate the capabilities of the developed system. The major achievements of this work are the consideration of multiple objectives and the establishment of objective function considering different load direction and heat treatments. A user-friendly graphical user interface was developed allowing to control different optimization process factors and providing different visualization and evaluation tools.

scholarly journals Properties of nickel-based superalloys of equiaxial crystallization

2021 ◽  
pp. 19-23
Author(s):  
O. Glotka ◽  
V. Olshanetskii
Keyword(s):  
Mechanical Properties ◽  
Chemical Composition ◽  
Regression Models ◽  
Computational Prediction ◽  
Integrated Approach ◽  
Experimental Data Processing ◽  
Predictive Regression ◽  
Heat Resistant ◽  
First Time ◽  
Thermodynamic Processes

Purpose. The aim of the work is to obtain predictive regression models, with the help of which, it is possible to adequately calculate the mechanical properties of nickel-based superalloys of equiaxial crystallization, without carrying out preliminary experiments. Research methods. To find regularities and calculate  the latest CALPHAD method was chosen, and modeling of thermodynamic processes of phase crystallization was performed. Results. As a result of experimental data processing, the ratio of alloying elements Kg¢ was proposed for the first time, which can be used to assess the mechanical properties, taking into account the complex effect of the main alloy components. The regularities of the influence of the composition on the properties of heat-resistant nickel alloys of equiaxial crystallization are established. The analysis of the received dependences in comparison with practical results is carried out. The relations well correlated with heat resistance, mismatch and strength of alloys are obtained. Scientific novelty. It is shown that for multicomponent nickel systems it is possible with a high probability to predict a mismatch, which significantly affects the strength characteristics of alloys of this class. The regularities of the influence of the chemical composition on the structure and properties of alloys are established. A promising and effective direction in solving the problem of predicting the main characteristics of heat-resistant materials based on nickel is shown Practical value. On the basis of an integrated approach for multicomponent heat-resistant nickel-based alloys, new regression models have been obtained that make it possible to adequately predict the properties of the chemical composition of the alloy, which made it possible to solve the problem of computational prediction of properties from the chemical composition of the alloy. This allows not only to design new nickel-based alloys, but also to optimize the composition of existing brands.

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