Estimation of Hardgrove grindability index of Turkish coals by neural networks

In this research, different techniques for the estimation of coal HGI values are studied. Data from 163 sub-bituminous coals from Turkey are used by featuring I I coal parameters, which include proximate analysis, group maceral analysis and rank. Nonlinear regression and neural network techniques are used for predicting the HGI values for the specified coal parameters. Results indicate that a hybrid network which is a combination of 4 separate neural networks gave the most accurate HGI prediction and all of the neural network models, outperformed non-linear regression in the estimation process

Modeling and Experimental Study of Newtonian Fluid Flow in Annulus

A major concern in drilling operations is the proper determination of frictional pressure loss in order to select a mud pump and avoid any serious problems. In this study, a mechanistic model is proposed for predicting the frictional pressure losses of light drilling fluid, which can be used for concentric annuli. The experimental data that were available in the literature and conducted at the Middle East Technical University-Petroleum Engineering (METU-PETE) flow loop as well as computational fluid dynamics (CFD) software are used to verify the results from the proposed mechanistic model. The results showed that the proposed model can estimate frictional pressure losses within a +/- 10% error interval when compared with the experimental data. Additionally, the effect of the pipe eccentricity on frictional pressure loss and tangential velocity using CFD for laminar and turbulent flow is also examined. It has been observed that pipe eccentricity drastically increases the tangential velocity inside the annulus; especially, the flow regime is turbulent and frictional pressure loss decreases as the pipe eccentricity increases. [DOI: 10.1115/1.4002243

Friction factors for hydraulic calculations considering presence of cuttings and pipe rotation in horizontal/highly-inclined wellbores

Pressure loss calculations have a vital role for determining hydraulic horsepower requirements and to predict bottomhole treating pressure. One of the major concerns in developing hydraulic programs is to estimate the frictional pressure losses while cuttings are present in the annulus during pipe rotation. An experimental work has been carried out in a cuttings transport flow loop capable of operating at various inclinations. The pressure drop in the test section was recorded for variable flow rates, cuttings concentrations, pipe inclinations and rotation speeds. Existence of cuttings increase the pressure drop due to decrease in flow area inside the wellbore. As there are cuttings in the system, pipe rotation decreases the frictional pressure loss considerably in particular if the pipe is making an orbital motion in the eccentric annulus. Cuttings bed thickness defined as the ratio of cuttings bed area to the wellbore area is expressed in terms of dimensionless parameters obtained from dimensional analysis. Empirical expressions and charts for friction factor are proposed for low and high viscosity fluids in terms of combined Reynolds number and stationary cuttings bed thickness

Analysis of the influence of bubble size and texture on foam characterization

Foam is one of the most frequently-used lightened fluids in underbalanced drilling applications. However, the rheological characterization of foam remains a difficult and challenging task largely due to problems associated with problems associated with the accurate determination of rheological parameters. Foam flow tests were conducted using an experimental flow loop which consisted of a set of smooth pipes of various diameters. Foams generated from different surfactants and different generation techniques were characterized from the texture and bubble size point of view using digital image processing. This paper outlines the approach taken to relate the foam rheological parameters obtained from the flow loop tests with its bubble size and texture. © BHR Group 2005 Multiphase Production Technology 12

Support Vector Regression and Computational Fluid Dynamics Modeling of Newtonian and Non-Newtonian Fluids in Annulus With Pipe Rotation

The estimation of the pressure losses inside annulus during pipe rotation is one of the main concerns in various engineering professions. Pipe rotation is a considerable parameter affecting pressure losses in annulus during drilling. In this study, pressure losses of Newtonian and non-Newtonian fluids flowing through concentric horizontal annulus are predicted using computational fluid dynamics (CFD) and support vector regression (SVR). SVR and CFD results are compared with experimental data obtained from literature. The comparisons show that CFD model could predict frictional pressure gradient with an average absolute percent error less than 3.48% for Newtonian fluids and 19.5% for non-Newtonian fluids. SVR could predict frictional pressure gradient with an average absolute percent error less than 5.09% for Newtonian fluids and 5.98% for non-Newtonian fluids

Experimental Study of Single Taylor Bubble Rising in Stagnant and Downward Flowing Non-Newtonian Fluids in Inclined Pipes

An experimental investigation of single Taylor bubbles rising in stagnant and downward flowing non-Newtonian fluids was carried out in an 80 ft long inclined pipe (4°, 15°, 30°, 45° from vertical) of 6 in. inner diameter. Water and four concentrations of bentonite–water mixtures were applied as the liquid phase, with Reynolds numbers in the range 118 Re E0) ranging from 3212 to 3405 and apparent viscosity (μapp) ranging from 0.001 Pa∙s to 129 Pa∙s. The proposed correlation exhibits good performance for predicting drift velocity from both the present study (mean absolute relative difference is 0.0702) and a database of previous investigator’s results (mean absolute relative difference is 0.09614)

MODELING OF NEWTONIAN FLUIDS IN ANNULAR GEOMETRIES WITH INNER PIPE ROTATION

Flow in annular geometries, i.e., flow through the gap between two cylindrical pipes, occurs in many different engineering professions, such as petroleum engineering, chemical engineering, mechanical engineering, food engineering, etc. Analysis of the flow characteristics through annular geometries is more challenging when compared with circular pipes, not only due to the uneven stress distribution on the walls but also due to secondary flows and tangential velocity components, especially when the inner pipe is rotated. In this paper, a mathematical model for predicting flow characteristics of Newtonian fluids in concentric horizontal annulus with drill pipe rotation is proposed. A numerical solution including pipe rotation is developed for calculating frictional pressure loss in concentric annuli for laminar and turbulent regimes. Navier-Stokes equations for turbulent conditions are numerically solved using the finite differences technique to obtain velocity profiles and frictional pressure losses. To verify the proposed model, estimated frictional pressure losses are compared with experimental data which were available in the literature and gathered at Middle East Technical University, Petroleum & Natural Gas Engineering Flow Loop (METU-PETE Flow Loop) as well as Computational Fluid Dynamics (CFD) software. The proposed model predicts frictional pressure losses with an error less than + 10 % in most cases, more accurately than the CFD software models depending on the flow conditions. Also, pipe rotation effects on frictional pressure loss and tangential velocity is investigated using CFD simulations for concentric and fully eccentric annulus. It has been observed that pipe rotation has no noticeable effects on frictional pressure loss for concentric annuli, but it significantly increases frictional pressure losses in an eccentric annulus, especially at low flow rates. For concentric annulus, pipe rotation improves the tangential velocity component, which does not depend on axial velocity. It is also noticed that, as the pipe rotation and axial velocity are increased, tangential velocity drastically increases for an eccentric annulus. The proposed model and the critical analysis conducted on velocity components and stress distributions make it possible to understand the concept of hydro transport and hole cleaning in field applications

Predicting the pressure losses while the drillstring is buckled and rotating using artificial intelligence methods

The prediction of equivalent circulating density in realistic conditions is complex due to many parameters in effect. Drillstring configuration and motion can play a significant role on the pressure profile in the annulus. Eccentricity, rotation and axial position of the drillstring can cause distinct pressure losses. If an accurate prediction is desired, these effects need to be accounted for. In this study, the pressure losses of Yield Power Law fluids with various drillstring rotation speeds and configurations are analyzed. These configurations include eccentricity and various buckling configurations and rotation speeds of the drillstring. Neural networks are used to predict the pressure losses and the results are compared with the experimental results and existing models from the literature. The input to the neural networks is optimized by comparing using direct measurements and using dimensionless parameters derived from the measurements. The comparison shows that using direct measurements as input yield better results instead of using dimensionless parameters, considering the experimental data used in this study. The results of this study showed that using neural networks to predict the pressure losses in complex geometries and motion showed a better precision compared to the existing models from the literature. The results analysis show that predicting with neural networks can yield as low as 5% absolute average percent error while predicting using existing models can yield as high as 115% absolute average percent error. Using neural networks shows a strong potential to accurately predict the pressure losses especially considering complex fluids and geometries

Pressure drop estimation in horizontal annuli for liquid-gas 2 phase flow: Comparison of mechanistic models and computational intelligence techniques

Frictional pressure loss calculations and estimating the performance of cuttings transport during underbalanced drilling operations are more difficult due to the characteristics of multi-phase fluid flow inside the wellbore. In directional or horizontal wellbores, such calculations are becoming more complicated due to the inclined wellbore sections, since gravitational force components are required to be considered properly. Even though there are numerous studies performed on pressure drop estimation for multiphase flow in inclined pipes, not as many studies have been conducted for multiphase flow in annular geometries with eccentricity. In this study, the frictional pressure losses are examined thoroughly for liquid-gas multiphase flow in horizontal eccentric annulus. Pressure drop measurements for different liquid and gas flow rates are recorded. Using the experimental data, a mechanistic model based on the modification of Lockhart and Martinelli [18] is developed. Additionally, 4 different computational intelligence techniques (nearest neighbor, regression trees, multilayer perceptron and Support Vector Machines - SVM) are modeled and developed for pressure drop estimation. The results indicate that both mechanistic model and computational intelligence techniques estimated the frictional pressure losses successfully for the given flow conditions, when compared with the experimental results. It is also noted that the computational intelligence techniques performed slightly better than the mechanistic model. (C) 2014 Elsevier Ltd. All rights reserved